Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan (LCEP) - Up-dated Final Report Energy Mix and Renewable Resource Assessment 12th December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de Table of Contents Page 1. Introduction 4 2. Background 6 3. Approach and Methodology 7 4. Load and Supply Characteristics 8 4.1 Load Characteristics and Demand Projections 8 4.2 Supply Projections – Baseline of Conventional Power 9 5. Areas for the LCEP 12 6. Conditions, Constrains and Inputs into LCEP 15 6.1 The LCEP Model 15 6.1.1 The LCEP Target Function 16 6.1.2 Basis Years 17 6.1.3 Solution Variables 17 6.1.4 Capacity Credit 18 6.1.5 Brief Notes on Modelling Approach 19 6.2 Inputs to the model 19 6.2.1 Demand Growth 19 6.2.2 Existing and Pipeline Projects (Conventional) 19 6.2.3 RE Technology Configurations and Sites 19 6.2.4 RE Technology Costs and Values over Time 20 6.2.5 Exogenous Assumptions – Fuel Price 23 6.2.6 Technology Configurations and Costs for New Conventional 23 6.3 Side constraints 24 6.3.1 Satisfaction of Demand 25 6.3.2 Satisfaction of Peak Load Plus Reserve Capacity 25 6.3.3 Minimum Load Of Conventional Power Plants 25 6.3.4 Short Term and Long Term and Maximum RE Capacity 25 6.3.5 Year of Commissioning for New Conventional and Renewable Configurations 27 7. Scenarios 28 8. Sensitivities 31 9. Results of Scenario and Sensitivities 32 9.1 Scenario 4 (Sc4), No RE 32 9.2 Scenario 2 (Sc2), Unlimited RE 32 9.3 Scenario 3c (Sc3c), Reference Case 33 9.4 Sensitivities 35 9.5 Summary of Results 39 10. LCEP Follow-up 42 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx Table of Contents Page List of Annexes Annex I - Solar and Wind Resource Annex II - Grid Connection Aspects Annex III - Potential Areas and Sites Annex IV – Information Collected Annex V – Performance of Conventional Plants Annex VI – Cost of Capital Assumptions List of Tables Table 4-1: Power plants for LCEP model – Worst case (Source: Task A) Table 4-2: Power plants for LCEP model – Best case (Source: Task A) Table 5-1: Technology configuration for LCEP Table 6-1: Main performance, cost and technical values for the RE technology configurations Table 6-2: Projection of LNG prices until 2030 (Source : Task B) Table 6-3: Summary of fuel cost projections for the LCEP Table 6-4: CAPEX and OPEX estimations for new non-RE power plants (Source) Table 6-5: Short-term capacity restrictions for the LCEP areas in MW Table 7-1: Summary of scenarios Table 8-1: Summary of sensitivities Table 9-1: Summary of scenario results Table 9-2: Summary of sensitivity results List of Figures Figure 4-1: Exemplary daily profiles of monthly average load curves (MW) Figure 4-2: Scenarios for electricity consumption until 2030 (Task A) Figure 4-3: Scenarios of GECOL’s generation and T&D (Task A) Figure 5-1: Preselected areas for the LCEP Figure 6-1: LCEP Model Figure 6-2: Long-term expansion limits of RE capacity for the LCEP Figure 9-1: Scenario 4, reflecting unlimited RE implementation of 12.35 GW until 2030 Figure 9-2: Newly installed capacity for the Reference Case Figure 9-3: Reference case: Produced energy until 2030 Figure 9-4: Cost comparison showing savings in Sc3c (reference) in compared to Sc4 (No RE) Figure 9-5: Sensitivity 1, no constrain for wind power Figure 9-6: Sensitivity 1, no constrain for wind power, produced energy until 2030 Figure 9-7: Sensitivity 2, WACC for CSP lowered to 4%, Figure 9-8: Sensitivity 2, WACC for CSP lowered to 4%, produced energy until 2030 Figure 9-9: Sensitivity 3, Fuel price variation Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx Abbreviations CAPEX Capital Expenditures CCGT Combined Cycle Gas Turbine CRS/CR Central Receiver System CSP Concentrating Solar Power DNI Direct Normal Irradiation DSG Direct Steam Generation ENTSO European Network of Transmission System Operators ESS Energy Storage System FLH Full Load Hours GECOL General Electric Company of Libya GHI Global Horizontal Irradiation GI Global Irradiation GT Gas Turbine HFO Heavy Fuel Oil HRSG Heat Recovery Steam Generator HTF Heat Transfer Fluid IDC Interest During Construction IEC International Electro-chemical Commission IGBT Insulated Gate Bipolar Transistor IPP Independent Power Producer IRR Internal Rate of Return ISCC Integrated Solar Combined Cycle ITRPV International Technology Roadmap for Photovoltaic LCEP Least Cost Expansion Plan LCoE Levelized Cost of Electricity LDS Long-Duration Energy Storage LFO Light Fuel Oil LID Light Induced Degradation LLJ Low Level Jet LVRT Low Voltage Ride Through OPEX Operational Expenditures PID Potential Induced Degradation PPA Power Purchase Agreement PSP Private Sector Participation PT Parabolic Trough PV Photovoltaics RE Renewable Energies REAOL Renewable Energy Authority of Libya SCGT Simple Cycle Gas Turbine SM Solar Multiple STATCOM Static Compensators SPREL Strategic Plan for Renewable Energies in Libya TES Thermal Energy Storage TMY Typical Meteorological Year TSC Thyristor Switched Capacitors WACC Weighted Average Capital Cost WB World Bank WTG Wind Turbine Generator Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -4- 1. Introduction The Least Cost Expansion Plan (the LCEP) analysis is the first step towards the preparation of a Stra- tegic Plan for Renewable Energies in Libya (the SPREL). This report describes the methods, assump- tions, processes, inputs and outcomes undertaken and found by the Consultant in order to optimize a mix of Renewable Energies (RE) for Libya until 2030 as part of Task D, Strategic Plan for Renewable Energy Development, mandated by the World Bank. In the present situation Libya power generation park is not sufficient to cover peak demand for differ- ent reasons including the lack of resources/fuel, missing spare parts, maintenance or damaged infra- structure. However, the conventional power projects, either contracted or under development, which have been put on hold due to the current political situation could, if implemented, cover the demand in the future. In principle, renewable energies (RE) do not have to step in to close supply gaps but eco- nomic perspective, energy security and long-term perspective are at least three important arguments for renewables to be considered in the future energy strategy of Libya. The LCEP will perform a first assessment of the economic perspective of implementing RE. The optimization of the LCEP can only be performed in a time and resource efficient manner when agreement, not only on the optimization method but also on the inputs, has been achieved among the parties involved. The methods, inputs and scenarios described in this report have been thoroughly discussed with the WB, GECOL and REAOL. This report compiles all relevant information on the LCEP optimization model structure, its inputs, the scenarios proposed to analyse sensitivities of the LCEP and the results of the LCEP optimization. Since the market offers many solar and wind technology combinations, the Consultant assessed tech- nical alternatives in a two-step approach. In a first step, the Consultant performed a high level qualita- tive analyses based on market and maturity of the technologies aiming to narrow down the many solar and wind technologies to those most competitive for Private Sector Participation (PSP) during imple- mentation of the LCEP. In a second step, the Consultant assessed local related aspects such as re- source, load & supply profile and grid connection. The result of this second step will be in the form of a set of the most suitable technology alternatives according to both their competitiveness in PSP acqui- sition and their suitability for the Libyan conditions. In order to have a clear picture of the RE potential in Libya the Consultant has used sites and technol- ogy configurations which are only representative in order to be able to model different RE options un- der different meteorological conditions. Simultaneously with these processes, the Consultant analysed the role of the RE in Libya and prelimi- nary concluded, together with the stakeholders, on the scenarios to be part of the optimization pro- cess. Ultimately, both the reference case and the set of scenarios were thoroughly discussed and agreed amongst the stakeholders. The set of scenarios shall represent important questions that could be raised by decision makers. An integral part of the Consultant’s analyses is the LCEP model that has been designed for the scope of this particular assignment. The Consultant has dedicated a whole section to give an overview of its formulation and its approach, as well as the inputs, assumptions and side constraints defined for the optimization and the scenarios. A number of different scenarios were simulated, varying divers input data and constrains. The results of these different scenarios are herein presented alongside with the Consultant’s conclusions and re c- Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -5- ommendations. Constrains were implemented to identify the most realistic scenario as the reference case. Conclusions and recommendations are discussed with the stakeholders in order to define the fi- nal LCEP mix which will be used for the Strategic Plan Renewable Energies for Libya (SPREL). Finally the Consultant will recommend next steps to be taken by the stakeholders to maintain, update and adjust the LCEP to the changing market and technology conditions of RE. The Consultant’s analyses are partially based on the results of tasks performed by other consultants in parallel under assignment of the World Bank. Wherever the Consultant here refers to Task A, the Consultant is referring to results shared by other consultants working in parallel. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -6- 2. Background The Least Cost Expansion Plan (the LCEP) analysis is the first step towards the preparation of a Stra- tegic Plan for Renewable Energies in Libya (the SPREL). This LCEP model specification contains the main inputs, assumptions, scenarios and sensitivities used by the Consultant to optimize the electricity generation mix for Libya until 2030 – and explore the role of Renewable Energies (RE) in the country – as a part of Task D, Strategic Plan for Renewable Energy Development, mandated by the World Bank. Based on the data provided by Task A Libya has in principle sufficient oil and gas conventional power plants to match the current peak demand. However, the technical availability of this installed capacity is considerable reduced for different reasons including issues with fuel transport, missing spare parts and maintenance or damaged infrastructure. Although, further conventional capacity is currently under development (see section 4.2), there are at least three important arguments for renewables to be con- sidered:  First, there is the economic perspective. The efficiency of old conventional power plants is typi- cally low and they use fuels that could otherwise be exported. This opens a window of opportunity for RE as fuel saver as long as the costs of RE are lower than the (short-term) marginal cost of conventional plants. As Libya possess very favourable renewable energy resources, a competitive scenario is likely. This allows bringing further saving due to private sector participation (PSP) on the generation site combined with PPA contracting to allow competitive pricing schemes.  Second, there is the issue of energy security and grid stability. As most conventional power plants are located along the coast of Libya in particular remote locations in the centre and south (where solar resource conditions are most favourable), RE could be used to balance the grid and to in- crease energy security.  Third, there is the long-term perspective. Given the abundance of renewable energy resources, the increasing opportunity costs of conventional power plants and the need for efficient electricity pricing schemes, increasing the share of renewable in the power plant fleet is politically and eco- nomically strongly recommended. Typically, in order to determine the share of RE in any given grid goals in terms of the RE share, either of the total energy produced or the total peak capacity installed, in percentage are set. The Consultant will follow a different approach for this assignment following the economic rational of opportunity costs and competitive pricing. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -7- 3. Approach and Methodology The steps below provide a brief high-level description of the overall methodology applied to determine the least cost RE mix for Libya until 2030. The intention of this section is to present an overview of previous analyses undertaken by the Consultant to define the set of inputs and assumptions within this note. These analyses will be elaborated in detail in the Energy Mix and Renewable Resource As- sessment Report part of this assignment.  Review of the role of RE in Libya: A descriptive review of the current status of RE in Libya and the potential advantages of their implementation in a future generation mix;  High level qualitative analysis of the solar and wind alternatives : The result of this second step are a set of the most suitable technology alternatives according to both their competitiveness in PSP acquisition and their suitability for the Libyan conditions;  Appraisal of wind and solar resource: Review of the overall wind and solar resource based on satellite data and cross check with existing ground data for a determination of the most suitable ar- eas for implementation of solar and wind projects;  Appraisal of load and supply characteristics: The daily, weekly and seasonal load behaviour was characterized alongside with projection for the conventional power supply in Libya (existing and planned);  Grid connection alternatives: Review of existing transmission system expansion studies as well as preliminary identification of potential connection points close to areas and sites suitable for wind and solar power implementation;  Site restrictions and environmental aspects: A desktop review of potential site restrictions based on existing freeware digital mapping in order to identify potential major obstacles and availa- bility of suitable land for RE developments;  Technology configurations: Definition of configurations of solar and wind facilities which better reflect the current and future market conditions and which are highly competitive within a PSP pro- curement process. These configurations are only exemplary at this stage and not fixed for future project developments or procurement processes;  Set of areas and configurations for the LCEP optimization: Definition of a reasonable set of sites and technology configurations for preparation of performance indicators and incorporation in the LCEP model. This set of areas and configurations is only exemplary and serves the goal of in- corporating a representative picture of the performance of RE facilities in Libya; and  LCEP optimization: Set up the LCEP model together with the necessary assumptions, inputs, side constraints, scenarios and sensitivities. Run the LCEP optimization, scenarios, sensitivities and analysis of results. The methods, inputs and scenarios applied have been thoroughly discussed with WB, GECOL and REAOL in different sessions. The Consultant’s analyses are partially based on the results of tasks performed by other consultants in parallel under assignment of the World Bank. Wherever the Consultant here refers to either Task A or Task B, the Consultant is referring to results shared by other consultants working in parallel. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -8- 4. Load and Supply Characteristics There are many aspects important for integrating RE into an existing network, however in order to capture the order of magnitude and profiles of the demand that shall be satisfied by RE and for the purposes of the LCEP, the following aspects relating to load and supply were considered:  Hourly seasonal daily, weekly and annual load in Libya;  Baseline of conventional power plants existing and planned; and  Capacity factors and supply profiles of RE at different representative locations as they depend strongly on the location i.e. resources change substantially with changes thereof. 4.1 Load Characteristics and Demand Projections Figure 4-1 shows the seasonal load behaviour for the year of 2016. Load peaks not only occur in summer from 20 to 22 hours but also in winter (January) at 18 hours. An important fact is that these peaks occur at times with no daylight in both seasons, thus initially not beneficiating solar technologies without energy storage, but potentially offering a good match with wind power supply curves. 5500 5000 4500 January February 4000 Demand in MW July September 3500 3000 2500 2000 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Time in h Figure 4-1: Exemplary daily profiles of monthly average load curves (MW) Hourly load values for the complete year of 2016 were provided in electronic format by GECOL. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx -9- 1 Demand growth projections have been prepared under Task A . The demand growth has been pro- jected by Task A consultants until 2030 across two scenarios – Scenario-A representing lower de- mand growth in a case where political instability continues, and Scenario-B representing higher de- mand growth in a case where political stability allows rapid development of mega-projects leading to greater demand for electricity (see Figure 4-2). The Consultants have based and harmonized assumptions of demand on the results of the Task-A projections. Estimation of growth in hourly demand for the LCEP is based on the actual hourly load values provided by GECOL for the year of 2016 adjusted to the yearly aggregate demand assessed in Task A. Figure 4-2: Scenarios for electricity consumption until 2030 (Task A) 4.2 Supply Projections – Baseline of Conventional Power In order to optimize the LCEP it is necessary to feed the model with the current and projected compo- sition and performance of the conventional power fleet. Task A has defined this composition and per- formance in two different scenarios i.e. the worst and the best case as shown in Figure 4-3. While the best case assumes a scenario of quick recuperation of performance of conventional power plants, the worst case assumes a rather moderate one. 1 PWC, Simplified gas consumption estimate, World Bank, May 2017 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 10 - Scenario name Under construction and Variable Existing plants Planned plants (2017- contracted plants 2030) • Each year: 4 units overdue from 1 past years + all overhauls of newly Worst due units Overhauls/ • Cleared by 2024 major • Each year: 15 units overdue from Not applicable Not applicable maintenance past years + all overhauls of newly Best due units • Cleared by 2020 2 • Resolved by 2024 Worst • None considered after Not included Fuel No constraints on fuel supply constraints considered • Resolved by 2020 No constraints on fuel supply Best • None considered after considered 3 Worst • 0% for steam turbines Not included • 0% for steam turbines • 12% to 20% for single cycle and Derating • 12% to 20% for single cycle and combined cycle gas turbines factor combined cycle gas turbines depending on historical derating and • 0% for steam turbines depending on geographical location Best location • 12% to 20% for gas turbines depending on geographic location Figure 4-3: Scenarios of GECOL’s generation and T&D (Task A) It is reasonable to assume that if RE can be deployed substantially in Libya from 2022 also the recu- peration of availability and capacity of the conventional power would be feasible. The base case of the LCEP assumes the best case of Task A. One additional scenario will deal with Task A’s worst case (see section 7). Table 4-1 and Table 4-2 set out the complete baselines of conventional power plants as integrated in the LCEP. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 11 - Table 4-1: Power plants for LCEP model – Worst case (Source: Task A) WORST case 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 10243 10832 10153 11555 13058 13615 13835 14185 14185 14101 13401 12801 12801 12801 12801 Existing Various Small / rented 543 513 100 100 100 100 100 100 100 100 100 100 100 100 100 Steam Khoms 480 480 480 480 480 480 Derna 130 130 Tobruk 130 130 Misurata Steel 504 504 84 84 84 84 84 84 84 Gulf 350 350 350 350 350 350 350 350 350 350 350 350 350 350 350 Tripoli West 370 370 240 240 240 Benghazi North 80 80 Gas Tripoli South 500 594 594 594 594 594 594 594 594 594 94 94 94 94 94 Zwetina 770 770 770 770 770 770 770 770 770 770 570 570 570 570 570 Khoms 1 600 600 600 600 600 600 600 600 600 600 600 Western Mountain 936 936 936 936 936 936 936 936 936 936 936 936 936 936 936 Sarir 855 855 855 855 855 855 855 855 855 855 855 855 855 855 855 Khoms 2 (Fast Track) 0 525 525 525 525 525 525 525 525 525 525 525 525 525 525 CC Zawia 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 Benghazi North 1 915 915 915 915 915 915 915 915 915 915 915 915 915 915 915 Misurata 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820 Benghazi North 2 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820 Under contr. Steam Gulf 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 / contracted Tripoli West 167 668 1018 1718 2068 2068 2068 2068 2068 2068 2068 2068 Tripoli East 127 254 254 254 254 254 254 254 254 254 254 Gas Ubari 624 624 624 624 624 624 624 624 624 624 624 624 624 Misurata 320 640 640 640 640 640 640 640 640 640 640 Tobruk 185 740 740 740 740 740 740 740 740 740 740 740 Proposed Steam Tripoli East Tobruk 2 Derna 2 Benghazi West Gas Sabha Tripoli South 2 CC Misurata Mellitah Zweitina 2 Tobruk Aboukammash Table 4-2: Power plants for LCEP model – Best case (Source: Task A) 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 10243 10832 10641 12043 13546 14103 15658 18263 19463 20903 21728 22378 24028 24578 23586 Existing Various Small / rented 543 513 160 160 160 160 160 160 160 100 100 100 100 100 100 Steam Khoms 480 480 480 480 480 480 480 480 480 480 480 480 480 480 Derna 130 130 130 130 130 130 130 130 130 130 130 130 130 130 Tobruk 130 130 130 130 130 130 130 130 130 130 130 130 130 130 Misurata Steel 504 504 252 252 252 252 252 252 252 252 252 252 252 252 Gulf 350 350 350 350 350 350 350 350 350 350 350 350 350 350 350 Tripoli West 370 370 240 240 240 Benghazi North 80 80 Gas Tripoli South 500 594 594 594 594 594 594 594 594 594 94 94 94 94 94 Zwetina 770 770 770 770 770 770 770 770 770 770 570 570 570 570 570 Khoms 1 600 600 600 600 600 600 600 600 600 600 600 Western Mountain 936 936 936 936 936 936 936 936 936 936 936 936 936 936 936 Sarir 855 855 855 855 855 855 855 855 855 855 855 855 855 855 855 Khoms 2 (Fast Track) 0 525 525 525 525 525 525 525 525 525 525 525 525 525 525 CC Zawia 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 Benghazi North 1 915 915 915 915 915 915 915 915 915 915 915 915 915 915 915 Misurata 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820 Benghazi North 2 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820 Under contr. Steam Gulf 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 / contracted Tripoli West 167 668 1018 1718 2068 2068 2068 2068 2068 2068 2068 2068 Tripoli East 127 254 254 254 254 254 254 254 254 254 254 Gas Ubari 624 624 624 624 624 624 624 624 624 624 624 624 624 Misurata 320 640 640 640 640 640 640 640 640 640 640 Tobruk 185 740 740 740 740 740 740 740 740 740 740 740 Proposed Steam Tripoli East 700 1400 1400 1400 1400 1400 1400 1400 Tobruk 2 700 700 700 700 700 700 Derna 2 700 700 700 700 700 700 700 700 Benghazi West 700 1400 1400 1400 1400 Gas Sabha 855 855 855 855 855 855 855 855 855 Tripoli South 2 855 855 855 855 855 855 855 855 CC Misurata 500 750 750 750 750 750 750 Mellitah 550 1100 1650 1650 1650 Zweitina 2 550 825 825 825 825 825 Tobruk 550 825 825 Aboukammash 550 825 825 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 12 - 5. Areas for the LCEP For the purpose of obtaining a representative picture of the potential of RE in Libya the Consultant has identified representative areas for installation of RE facilities as shown in Figure 5-1. This section pre- sents an overview on how these areas were defined and the exemplary sites considered therein. NOTE: Sites and technology configurations performed by the Consultant within this analysis are only representative in order to model the RE potential in different regions in Libya and in no case substitute proper site selection and feasibility studies. Technologies and sites part of an international tender pro- cess shall be defined with specific studies in order to obtain the best value for money for each case. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 13 - Figure 5-1: Preselected areas for the LCEP In order to be able to estimate key performance indicators of representative solar and wind configura- tions at potential areas in Libya the Consultant has: a. Performed a high level qualitative analysis of the solar and wind alternatives in order to config- ure a set of representative technology alternatives and technology configurations which will al- low for simulation and estimation of key performance indicators, as well as cost indicators, to be entered into the LCEP such as energy yield, supply profiles, efficiency, capacity factors, CAPEX and OPEX (see Table 6-1); Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 14 - b. Appraised the Libyan wind and solar resource identifying within the areas selected the regions with suitable wind and solar resource. This appraisal included the existing studies and available ground measurement data; c. Preliminarily reviewed grid connection alternatives based on existing transmission system ex- pansion studies and potential connection points close to areas and sites suitable for wind and solar power implementation. Distances to substations were roughly estimated in order to add CAPEX for transmission connection (see section 6.2.4); d. Assumed that water availability will not be considered a major issue since CSP plants will be equipped with dry cooling systems; e. Verified area availability for the different technology configuration. Whereas the area available at some sites is suitable for PV, CSP and wind configurations other areas are only suitable for one or two technologies. For the case of solar technologies larger areas were considered for CSP due to the storage capability and hence the larger solar field. In general, areas considered for the LCEP shall be large enough to reduce issues related to exclusion due to environmental aspects (e.g. natural reserves) or land use (e.g. areas reserved for oil activities); f. Verified site restrictions and environmental aspects by means of a desktop review of potential site restrictions based on existing freeware digital mapping aiming to identify potential major ob- stacles and availability of suitable land for RE developments; and 2 g. Prepared a set of representative sites and technology configurations (see Annex III, Table 3-1) to be implemented in the LCEP model in the form of performance and cost data of solar and wind options in Libya. This data was calculated by means of simulation of technology configura- tions at the sites selected. Table 5-1: Technology configuration for LCEP RE Technology Alternative Technology Configuration PV  Crystalline / Thin film (CdTe)  50 and 100 MW ac fix mounted and  Fixed mounted / One axis tracked 1-axis tracked with p-Si modules  Central and string inverter configurations depend- and central inverter; ing on the size  One configuration crystalline fixed  Li-Ion Long-duration Energy Storage (3 hours) mounted of 50 MWac and 3 hours for the site in Sebah for comparison purposes Wind  Upwind / 3 blades rotors / horizontal axis  50 MW wind park; 2 MW turbines,  Onshore 90 m hub height, 90 m diameter;  Hub heights: 80 – 120 m  100 MW wind park; 3.5 MW tur-  Rotor diameters: 90 – 136 m bines; 110/120 m hub height; ap-  Site classification II and III prox. 120 m diameter.  Direct drive / gearbox  Double Feed Induction Generator (DFIG) / Fully rated converter type (Type 3 and Type 4) CSP  Parabolic trough with thermal oil as HTF and mol-  100 MWgross PT and Molten Salt ten salt TES tower with TES of 7 to 10 FLH  Central Receiver Systems with molten salt as HTF (techno-economic optimization of and TES SM and TES capacity);  Air cooled condenser system  100 MWgross PT and molten salt tower with TES of 13 to 15 FLH (base load configuration) 2 Sites defined within this assignment are only exemplary to appraise presentative performance data of RE in different areas of Libya. This assignment does not intend to select sites for any type of investment or feasibility thereof. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 15 - RE Technology Alternative Technology Configuration Battery  Li-Ion battery of Long-Duration energy Storage  Li-Ion modules of 10 MW and 7 hours In addition to this and following GECOL recommendation that a share of RE facilities may be installed preferably more in the south of the overall transmission and distribution grid (e.g. in the southern cen- tres of the two main North-south branches of the grid), representatives areas for the south i.e. Thala and Jagboub were incorporated in the LCEP in agreement with GECOL and REAOL. 6. Conditions, Constrains and Inputs into LCEP This section presents the description of the LCEP model and the inputs, assumptions and constraints part of the optimization process. It is not the intention to describe herein the detail of the formulation and the code used for the MATLAB tool as this will require a separate dedicated document which is not the purpose of this assignment. 6.1 The LCEP Model The Consultant’s LCEP model is an energy system model which allows the determination and the d e- velopment of electricity supply systems based on a least cost optimization approach. The model ap- proach is applicable to various supply systems with different background conditions. Therefore the model is able to consider renewables as well as conventional power plants. The determination of the least cost electricity supply systems is significantly dependent on the available input parameter to the model. Mainly the model needs information on:  Existing or planned installed capacities of supply systems;  Technical and economic characteristics of electricity generating configurations;  Hourly time series of renewable power generation (in spatial resolution); and  Electricity demand (in temporal resolution). Figure 6-1: LCEP Model Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 16 - The Consultant’s LCEP model is programmed in a modular structure, in which each supply technolo- gy/unit is represented by an independent module which is characterized by technical and economic specifications. The optimization relies on a perfect foresight modelling approach. The LCEP model is implemented in the software MATLAB, using a mixed-integer linear optimization approach and has been developed for the conditions of the scope of this particular assignment. The model has been tested for different cases within this assignment to check the validity of its results. A full validation of the model can only be done by running the same data with a similar model and com- paring the results. If necessary, such task is to be implemented by a third party under a separate as- signment. Due to the consideration of fluctuating behaviour renewable configurations, it is necessary to consider a high temporal resolution for the analysis of operation of suppliers in the LCEP model. The optimiza- tion of the Libyan generation system relies on an hourly basis of 8,760 hours per year. Although, the model can cover that time span and resolution, depending on the complexity of the power system, the expansion horizon is subdivided into optimization horizons of 6-8 years. Parts of the results are stored for the final solution and some of them are used for the next optimization horizon. 6.1.1 The LCEP Target Function The LCEP will be based on the minimization of CAPEX and OPEX of the solar and wind mix for Libya by means of a target function that includes these parameters together with performance data of each technology configuration such as capacity and energy production. In parallel, the target function mini- mizes the costs of stock and planned conventional power plants, but the overall focus is still on the op- timization of the solar and wind mix for Libya. The target function is defined as: 2030 8760 = ∑ [, ∙ (, + ,, ) + ∑ ,, ∙ (,,, )] =2017 =1 1 , = (, + ) ∗ ∙ −2017 1 + 1 1 ,,, = ∙ (,, + ,,, +2,, ) ∙ −2017 , 1 + Where: Fmin : Total cost of RE mix to be minimized [USD] Pinst,pp,a : Annual gross installed capacity reduced by the technical availability per plant [MW gross-a] Epp,a : Annual gross energy production per plant [MWhgross-a] ,, = ,, ∙ (1 − , ) , : Annual expenditures related to the power plant capacity [USD/MW gross] Investtotal,pp : Capital expenditures including cost of financing per plant [USD/MW gross] Transmissionpp,: Fixed expenditures for additional grid connection [USD/km] (see section 6.2.4) OPEXfix,pp,a : Annual fixed operational expenditures per plant [USD/MW gross-a] OPEXvar,pp,a,t : Aggregated variable operational expenditures per plant [USD/MWh-a] FuelCostpp,a,t : Fuel costs per plant [USD/MWh-a] OMvar,pp,a,t : Variable operation expenditures per plant [USD/MWh-a] CO2pp,a,t : Cost for CO2 emissions per plant [USD/MWh-a] Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 17 - : Depreciation time [a]; , : The thermal efficiency describes the conversion of thermal energy into electrical energy of the respective plant. [%/100] , : Annual degradation of the respective plant [%/100] : Discount rate [%/100] 1 ∙(1+ ) : Annuity factor [ ] = a (1+ ) −1 : Interest rate [%/100] 6.1.2 Basis Years In order to have a common basis for simulation of different technology configurations at different sites the Consultant will prepare for a number of selected sites a Typical Meteorological Year (TMY) for Global Horizontal Irradiation (GHI) and Direct Normal Irradiation (DNI), as well as wind speed and wind direction. These basis years will allow for the estimation of the annual electricity production (Epp,a) and levelised cost of electricity for each technology configuration at a defined site. 6.1.3 Solution Variables 6.1.3.1 Annual Gross Installed Capacity (Pinst,pp,a) Is the gross installed capacity in MW of each conventional plant, as well as each solar and wind tech- nology configuration (each plant) which will be installed per year e.g. the MW peak installed of a PV plant. This capacity is reduced by the given technical availability. 6.1.3.2 Hourly Net Electricity Production (Epp,a,t) The amount of energy produced gives the basis for estimating the revenues of selling electricity by the plant. For the purpose of this study the annual electricity production serves as the basis for estimating the variable operation expenses and indeed for estimation of the total electricity produced by the mix of RE. Epp,a,t is given in an hourly basis for the different sites (different basis years) and for each technology configuration and describes which power plant/RE-configuration contribute to cover the demand in the particular hour of the particular year of the expansion horizon. The maximum values for this solution variable are based on the power plant capacity reduced by the thermal efficiency and on hourly supply profiles for the renewable energy configurations. In the latter case the annual degradation of the tech- nology output is considered (if necessary). This energy is a net value after discounting the auxiliaries’ consumption the auxiliary consumption va l- ues will be given as a percentage of the gross electricity production for each plant. 6.1.3.3 Levelised Cost of Electricity (LCoE) The standard method of estimation of electricity cost could be used, the Levelised Cost of Electrictiy (LCoE). If necessary, the LCoE could be estimated for each new plant separately and an average LCoE could be calculated for each technology. The following (simplified) formula will be used: Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 18 - , + ,, ∑ =0 (1 + ) = , ∑ =0 (1 + ) Where: LCoEpp : Total LCoE per plant in USD/MWh; CAPEXpp,a : Capital expenses in the year t for the corresponding plant in USD; OPEXtotal,pp,a : Operation expenses in the year t in USD; OPEXtotal = + Epp,a : Annual gross energy production per plant [MWhgross-a] : Discount rate [%/100] : Life time of the system [a] 6.1.4 Capacity Credit3 The capacity credit expresses the ‘firm’ capacity of renewable power supply technologies as a fraction of total installed capacity of the particular power supply technology. As an example, wind turbines with an installed capacity of 10 GW and a capacity credit of 20 % have a ‘firm’ capacity of 2 GW. This means a reduction of 2 GW of other plants that has to cover the demand, compared to a situation with no wind capacity. Due to the point that the capacity credit is a function of the installed capacity, the relative capacity credit reduces with increasing penetration levels of the particular supply technology in the system. This does not mean that less conventional capacity can be replaced, but rather that e.g. a new wind plant added to a system with high wind power penetration levels will substitute less than the first wind plants in the system. The model is sensitive to capacity credit, for instance, in the case of Libya the capacity credit of PV- systems is lower than the capacity credit of wind and CSP systems since there is no sun at the mo- ment of peak load. Therefore, it is likely that the model finds a least cost optimization solution without PV-systems. This effect is mainly caused because PV-systems are only partly able to provide ‘firm’ capacity during the hours of high demand. The capacity credit is included in the model in the side constraint, which secures the covering of the yearly peak load see section 6.3.2. The capacity credit will be calculated in the following manner: 1. Calculation of the ‘firm’ capacity of stock power plants required to cover the demand . Convolu- tion of probability distributions representing the technical availability of each stock power plant. 2. Calculation of the ‘firm’ capacity of stock power plants required to cover the demand + particular RE-configuration. Convolution of probability distribution of ‘firm’ capacity of all stock power plants with probability density function of RE-feed-in. 3. Difference between (1) and (2) represents the ‘firm’ capacity of the particular RE -configuration The capacity credit is recalculated according to the stock power plants in different years of expansion horizon. To better assess the effects of the capacity credit for different technologies within the Libyan grid, the Consultant will perform different optimizations in the form of scenarios for common discussion. 3 Planning for the renewable future: Long-term modelling and tools to expand variable renewable power in emerging econo- mies. Abu Dhabi, 2017. – ISBN 978–92–95111–06–6 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 19 - 6.1.5 Brief Notes on Modelling Approach It is important to always consider that the focus of the LCEP model is to find the least cost mix of RE. The following notes summarize general aspects of the modelling approach defined during the process:  In order to consider the effect of conventional power, the Consultant integrates standard conven- tional power plants (i.e. a CCGT and a SCGT due to its peaker capabilities), which will be part of the optimization process together with the RE. The standard conventional power plants perfor- mances and cost indicators will follow suit to the assumptions made for plants under construction in the baseline determined for the LCEP. These additional conventional power plants, if necessary by the LCEP, will be available from 2021. Before this period, all possible occurring gaps in the electric- ity supply are covered by modelled electricity imports. The Consultant considers that after 2021 electricity imports from Tunis or Egypt shall not be cheaper than local produced electricity in the same conditions and thus no imports from 2021 are considered;  The model will perform an estimation of CO2 reduction and fuel savings in the results;  The modelling takes into consideration the existing and committed conventional power plants in the base scenario;  Conversion of SCGTs to CCGTs are usually only recommended when the plants were designed for a later conversion as they need further requirements such as cooling systems and further addition- al land. This could be implemented if GECOL provides the set of data for such conversions;  The Consultant understands the need of competition between all feasible conventional technolo- gies in a model. The technologies selected (i.e. SCGT and CCGT) with natural gas as fuel reflect the most likely decision according to the conditions of Libya since, according to internal discussions with the stakeholders, it is very unlikely that Libya will decide to install nuclear or coal power plants within the horizon of this LCEP; and  Reserves are chiefly given by the existing pipeline of projects and the capacity credit of RE is inte- grated in the model to consider if further reserves are required. In the model, a reserve capacity of 20% of the yearly peak load is considered to secure sufficient capacity in the system even if a sig- nificant capacity is disconnected. A detailed analysis of reserves needed for balancing energy is not considered at this preliminary stage of analysis. 6.2 Inputs to the model 6.2.1 Demand Growth Refer to section 4.1 for details on the demand growth. 6.2.2 Existing and Pipeline Projects (Conventional) Details on the existing line of pipeline projects are described in section 4.2. 6.2.3 RE Technology Configurations and Sites Details on technology configurations are described within the related report "Least Cost Expansion Plan Report; Technology Review" and sites are described in the annexes. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 20 - 6.2.4 RE Technology Costs and Values over Time For each technology configuration the Consultant will estimate the fixed costs (CAPEX and OPEX fix) and variable cost (OPEXvar) as total values in USD/MW inst and USD/MWh respectively to be entered into the model. CAPEX Economies of scale, when necessary, will be considered within the direct CAPEX by reducing its spe- cific cost according to the Consultant’s database. For instance in the case of a CSP plant the specific cost of the different plant’s systems will be reduced proportional to the size of the plant. CAPEX or capital expenses are costs that mainly occur during the project construction and are used to buy fixed assets e.g. a power plant. Using the annuity method, the investment costs are distributed over the lifetime of a power unit. Table 6-1 shows indicative CAPEX for the different configurations. Special attention was given to the case of CSP CAPEX due to the substantial price reduction experi- enced this year of 2017. The CSP CAPEX assumed by the Consultant as depicted in Table 6-1 in- cludes the total investment cost including development, EPC and start-up costs. This price was as- sumed to be similar to the level of the last auction in Dubai this year of 2017. Two further sensitivities for more optimistic price reductions for CSP were analysed to evaluate their effect in the LCEP mix composition. An estimated cost of transmission line has been added in accordance to estimated distances to sub- 4 stations in the form of a single circuit overhead line of 230 kV estimated to 600,000 USD/km . OPEX Operation expenses, OPEX, are ongoing costs for running the plant including staff salaries, admin- istration, land lease (if applicable), insurances, service fees, cars and consumption of media such as water among others. Operation expenses are divided into fixed (OPEXfix,pp,a) and variable (OPEXvar,pp,a). For PV and wind operation expenses are chiefly fixed expenses whereas for CSP the variable part of the operation ex- penses is more relevant as they consume water and fossil fuels in function of the electricity produced i.e. the capacity factor. While fixed operation expenses can be estimated as a function of the installed capacity, variable operation expenses can be estimated as a function of the electricity produced. Table 6-1 summarizes CAPEX and OPEX with the corresponding factors necessary for estimation of total values for the different configurations to be used in the LCEP model. Availability Annual availability (avpp,a) is a function of the reliability and the maintainability of the plant and hence of the quality of the equipment and the O&M strategy respectively. These values will be given as a per- centage for each technology configuration representing the plant outage hours either planned or forced varying from year to year to reflect major events such as overhauls. Energy production shall be annually reduced in accordance with this percentage. 4 Capital Costs for Transmission and Substations, Updated recommendations for WECC Transmission Expansion Planning, Prepared for Western Electricity Coordinating Council, Black & Veatch, February 2014 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 21 - Degradation Equipment wears out over time affecting and reducing its efficiency. Efficiency shall be adjusted at a certain percentage every year. Since this percentage is applied annually to the plant’s efficiency it is important to apply this directly to the plant’s remaining efficiency and not a s a percentage of the ener- gy production. For the purpose of this study, the degradation ( Degpp,a) will be also given as an annual percentage for each technology configuration bearing in mind that overhauls may partially recover the efficiency re- ductions in major equipment such as steam turbines. An annual degradation of 0.5% will be assumed for PV and CSP. Potential of cost reduction Each technology alternative selected has its own potential of cost reduction that depends on many factors such as technological innovation, expansion of the industry, more competitors and volume of production. For the purpose of this study, the Consultant will estimate a percentage of cost reduction for each technology configuration in order to cover this effect over the period of analysis. It is important to note that the factors affecting this figure cannot be foreseen with high degrees of cer- tainty as they depend on many political and framework aspects which may change over time. The es- timations made for this study are based on existing market researches however the Consultant will try to keep its views as conservative as possible. According to IRENA’s report the potential reduction of the costs of installed capacity of onshore wind is about 12% from 2014 to 2025 (see technology assessment report). This potential of cost reduction 5 will be applied linearly to the LCEP . 6 For the case of PV and CSP IRENA projections for cost reduction potential for 2025 could be around 65% and 37% for PV and CSP respectively. For the purposes of this analysis and considering the re- cent substantial cost reductions for solar technologies between 2016 and 2017 the Consultant as- sumes a potential of cost reduction of 20% until 2025 for both PV and CSP CAPEX in the LCEP and linearly until 2030. 5 The Power to Change, Solar and Wind Cost Reduction Potential 2025, IRENA, June 2016 6 The Power to Change, Solar and Wind Cost Reduction Potential 2025, IRENA, June 2016 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 22 - Table 6-1: Main performance, cost and technical values for the RE technology configurations Item Factors PV1 PV2 PV3 PV4 CSP1 CSP2 CSP3 CSP4 WIND1 WIND2 BTT1 1 1 2 2 PV (fix) PV (fix) PV (1ax) PV (1ax) CSP PTC CSP CRS CSP PTC CSP CRS Wind Wind Battery 50 MWAC 100 MWAC 50 MWAC 100 MWAC 100 MWgross 100 MWgross 100 MWgross 100 MWgross 50 100 standalone 60 MWp 120 MWp 60 MWp 120 MWp SM3/TES7 SM3/TES10 SM4/TES13 SM4/TES15 MWgross MWgross 10 MW 7 Hours CAPEX Indirect & direct CAPEXtotal,pp,a (Total M USD 1.0 0.97 1.1 1.07 4.46 5.07 6.05 6.53 1.67 1.63 3.27 Investment Costs) /MWp,gross CAPEXtotal,pp,a (Total M USD 60.29 116.38 66.26 128.07 445.75 507.27 605.19 652.7 83.45 162.97 32.67 Investment Costs) OPEXfix O&M incl. staff sala- USD/ ries, administrations, MW p/gross/ 14 300 13 000 17 600 16 000 43 000 46 050 43 000 46 050 29 900 29 235 29 848 land lease etc. a OPEXvar Auxiliaries consump- USD / - - - - 3.50 2.70 3.50 2.70 - - - tion (e.g. fossil fuels) MWh OPEXtotal,pp,a T USD/a 858 1 560 1 056 1 920 5 592 5 868 6 047 6 329 1 495 2 923 298 Availability Availability % 99 99 99 99 98 98 98 98 96 96 100 Degradation Degradation %/a 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 - - 2 Potential of cost reductionfor CAPEX Until 2025 % 20 20 20 20 20 20 20 20 12 12 30 From 2025 to 2030 % Linear Linear Linear Linear Linear Linear Linear Linear Linear linear 30 1 With medium to large thermal energy storage (7 to 10 FLH) as set out for PTC and CRS 2 With base load storage capacity similar to the last Dubai design Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 23 - 6.2.5 Exogenous Assumptions – Fuel Price For natural gas: Task B has provided the Consultant with the projection of LNG price (including mole- cule, liquefaction and shipping) shown in Table 6-2. Task B also clarified that the price was projected based on EIAs forecast and estimated as ~12% Brent (similar to Egypt and Pakistan contracts) and that these values do not include the repayment of new infrastructure (i.e. regasification terminal / ex- pansion or new pipelines). Table 6-2: Projection of LNG prices until 2030 (Source : Task B) Year 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 USD/MBtu 6.0 7.6 8.4 9.0 9.4 9.7 9.9 10.0 10.3 10.6 10.8 10.9 11.0 11.3 For Heavy Fuel Oil/Light Fuel Oil: As crude oil derivatives are highly correlated with the crude oil prices it is assumed that crude oil growth rate projections could be applied for both product catego- 7 ries . According to recent World Bank estimates crude oil prices are assumed to increase from 55 8 $/bbl (2017) to 80 $/bbl (2030) in nominal US dollars . This would correspond to an annual (linear) growth of 2.9 %. 9 Table 6-3: Summary of fuel cost projections for the LCEP Fuel Costs Price develop- LHV Fuel Type 3 3 [LD/m ] ment [MWh/m ] LFO 550 +2.9 10,77 HFO 421 +2.9 10,99 Based on the data on conventional power plants as provided by Task A the Consultant estimated the approximate share of fuel costs in the total OPEX of conventional power plants. For this share, the Consultant applied the price increase projections for fuels and for the remaining non-fuel share the dollar inflation rate. 6.2.6 Technology Configurations and Costs for New Conventional The Consultant has made preliminary assumptions for estimation of CAPEX and OPEX for conven- tional power in the Libyan system. These assumptions could be updated with the baseline of conven- tional generation to be provided by TASK A and further information from GECOL if available. Estimation of OPEX for non-RE will follow a similar structure as for RE by separating fixes and varia- bles OPEX. While fixed OPEX can be based in historic data of GECOL power plants, variable OPEX is, for conventional fossil-fired power plants, a sensitive aspect due to volatility of fuel prices. For fixed and variable OPEX of non-RE, and their price development over the period of the LCEP, the Consultant based his assumptions on a similar project carried out almost simultaneously for the World 7 Seeking Alpha (2015): https://seekingalpha.com/article/2918546-how-correlated-are-crude-oil-prices-to-finished-petroleum- products 8 World Bank Commodities Price Forecast (2017): http://pubdocs.worldbank.org/en/926111485188873241/CMO-January-2017- Forecasts.pdf 9 Other sources are: Price Development: Vuorinen, Asko; Planning of optimal power systems. s.L. Ekoenergo Oy, 2009 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 24 - 10 Bank in Jordan . For the variable OPEX costs, the Consultant applies the prices described in section 6.2.5. Values over time for conventional power are based on information provided by GECOL on efficiency and availability of the plants. Different to RE, substantial technology breakthroughs of generation of gas and steam power leading to considerable changes on availability and technology cost are not foreseen in the horizon of the LCEP. Degradation will be considered based on typical figures unless further information is provided by GECOL. Information on major overhauls, if provided, can be included as such overhauls bring about efficiency recoveries of the turbines. Estimations for new non-RE plants were assumed according to Table 6-4. The Consultant could in- corporate costs of major overhauls and repairs if information on the amount and time is provided. The new conventional plants are added (if needed) to the supply portfolio in multiple of a 500 MW unit. 11 Table 6-4: CAPEX and OPEX estimations for new non-RE power plants (Source ) CAPEX Price de- OPEX fix Price de- Technical Effi- Technology [$/MW] velopment [$/MW] velopment availability ciency 12 (2017) [%/a] (2017) [%/a] [%] [%] GT 800.000 0 5.690 0 88 37 CCGT 950.000 0 7.851 0 88 49 For the conventional plants, the base case will assume gas as preferred fuel from 2022. Meaning that until 2021 the LCEP will use the current fuel mix (i.e. gas, HFO and LFO) as applicable according to Task A and from 2022 the use of gas will be preferred. The model will usually decide for gas unless the plant can only burn HFO or LFO. 6.3 Side constraints Further to the assumptions so far described, the optimization process will need the implementation of side constraints relevant to a more realistic utilization and implementation of both conventional and re- newable energies. These side constraints are implemented as upper and lower bounds of the solution variables, inequations and equations. Side constraints 6.3.1 and 6.3.2 form the backbone of the model approach. 10 Possible roles of concentrating solar power in Jordan’s future electric power system ; Draft Final Report, October 2, 2017; The World Bank, Ernst & Young, Castalia and Fraunhofer ISE 11 Kehlhofer, Rolf, et al. Combined-Cycle Gas & Steam Turbine Power Plants. 3rd Edition. Tulsa : PennWell, 2009. pp. 24-26. ISBN 978-1-59370-168-0. - International Renewable Energy Agency (IRENA). Renewable Energy Technologies: Cost Analysis - Concentrating Solar Power. Bonn : IRENA, 2012. - National Renewable Energy Laboratory (NREL). Cost Report: Cost and Performance Data for Power Generation Techniques. s.l. : Black & Veatch, 2012 12 Possible roles of concentrating solar power in Jordan’s future electric power system ; Draft Final Report, October 2, 2017; The World Bank, Ernst & Young, Castalia and Fraunhofer ISE Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 25 - 6.3.1 Satisfaction of Demand The demand in every time step during the different years of the expansion horizon has to be covered by the available power of the different supply systems (or imports/exports). The number of time steps within one year is dependent on the temporal resolution chosen for the optimization (here 8,760 h). This constraint is mathematically implemented as an equation and is applied in all scenarios. ,, = ∑ ,, (+/ ) =1 ,, : Electricity demand for every time step t and for every year a of the optimization horizon; refer to section 4.1 for details on the demand profile and growth : Number of power plants / : Electricity exchanges of a region/country with a neighbouring region/country 6.3.2 Satisfaction of Peak Load Plus Reserve Capacity To secure a high security of supply, the peak demand plus additional requested reserve capacities need to be covered by the technical available capacities of the generation system. Due to the fluctuat- ing supply-depend behaviour of renewable energies, their technical availability is integrated as capaci- ty credit (refer to section 6.1.4). This constraint is mathematically implemented as an inequation and is applied in all scenarios. ∑ −,, ≤ −(, + , ) =1 ,, = ,, ∙ , , : Availability of the power plant , : Peak load in every year a of the optimization horizon , : reserve capacity to secure a sufficient security of supply 6.3.3 Minimum Load Of Conventional Power Plants A minimum load for the combined cycles and steam power plants of 23% will be set to reflect this technical constraint in the optimization. This constraint is implemented through limiting the lower bounds of the solution variable ‘hourly net electricity production’ and is applied in all scenarios. 6.3.4 Short Term and Long Term and Maximum RE Capacity Capacity limits are integrated in the model since:  In the short-term a moderate growth of renewable energy capacity is expected as the country is building its learning curve and establishing the necessary framework for RE implementation; and  In the long-term (until 2030 for the purpose of this assignment) an unlimited growth of renewable energy capacity is deemed as not realistic. RE will be implemented in two steps, i.e. short and long-term, as described below. While the short- 13 term considers capacity restrictions in order to give an indication of the sites which could be as- sessed for the installation of the first RE projects in Libya during the first years, the long-term does not consider constraints in capacity as the idea is to give an overall idea of the potential until 2030 for in- 13 Sites in the context of this study are to be considered exemplary and are only an indication of potential locations to be further assessed and its feasibility determined. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 26 - stallation of RE. It is necessary to perform updates of the LCEP beneficiating from the lessons learned of the first RE projects  Short-term (from 2019 to 2021): Within this short–term, capacity constraints chiefly due to available area will be roughly estimated in order to restrict the model to reasonable capacities within the are- as. This constraint will only be applied to PV and wind configurations since only these configura- tions are allowed by the model to be implemented within this short-term period as described in sec- tion 6.3.5. The estimated restrictions are described in Table 6-5.  Long-term (from 2021): Additional to the wind and PV configurations this term will include CSP con- figurations as they could be implemented within this timeframe. Rather than in specific locations, this period considers areas for installation as depicted in the first column of Table 6-5. It is im- portant to note that for the long-term, locations are to be determined in detail and further analyses are necessary for their development and potential implementation. The applied long-term expan- sion limits in MW of installed renewable capacity within the different years of the expansion horizon is shown in Figure 6-2. The solver is allowed to deviate from these limits in a range of ~2.5%. This value was chosen by the consultant to keep the RE capacity expansion in a realistic level. Table 6-5: Short-term capacity restrictions for the LCEP areas in MW Short-term capacity restrictions [MW] Area City/town Max. Tripoli Aziziya 200 Tripoli Misallatha 400 Tripoli Misurata 200 Tripoli Assaba 200 Tripoli Zliten 200 Tripoli Jadu 200 Bengazhi Derna 100 Bengazhi Al Maqron 200 Bengazhi Al Tamimi 100 Bengazhi Shahat 50 Sebah Sebah 500 Sebah Edri 100 Ghadamis Ghadamis 50 Brega Brega 100 Hun Hun 100 Ghat Thala 200 Jagboub Jagboub 100 Jagboub Kufra1 100 Jagboub Kufra2 100 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 27 - Figure 6-2: Long-term expansion limits of RE capacity for the LCEP Due to area restrictions for implementation of wind power in the areas selected sensitivities on the wind capacity restriction have been incorporated (see section 8). 6.3.5 Year of Commissioning for New Conventional and Renewable Configu- rations Since at least more than two years are needed for the development and implementation of a power project, all renewable and conventional configurations that are not part of the stock portfolio or part of the planned power plants will not be integrated in the supply profile before 2019. In order to reflect the different levels of complexity of project development and construction durations associated to each technology the following side constraints were implemented:  PV configurations could be in commercial operation from 2019; and  Wind/CCGT/GT/CSP configurations could be in commercial operation from 2021 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 28 - 7. Scenarios Scenarios are a main component of the LCEP analysis as they will allow the stakeholders to see changes in the LCEP mix with changes in main inputs to the optimization. In order to define the LCEP base case the Consultant will vary the share of RE, the combination of RE technologies and the utili- zation factor of the conventional plants. The LCEP base case will feature the final mix of configurations/sites, the capacity credit values and the baseline of conventional power plants. Table 7-1 summarizes the simulated and analysed scenarios. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 29 - Table 7-1: Summary of scenarios Existing and contracted power Limited implementation of RE Wind limitation of 1 GW Gas price assumption (short and long-term) Question answered Standalone battery Name of Scenario No of Model Run Demand growth Option of RE WACC CSP plants How does the power plant fleet oper- Low demand Best case Medium pre-scenario status quo ates without new conventional or growth (Case A of No - - - No of Task A (gas=Opportunity cost) new RE capacity? task A) Low demand What is the least-cost expansion Best case Medium Sc 4 No RE growth (Case A of No - - - No without RE ? of Task A (gas=Opportunity cost) task A) What is the least cost expansion with Low demand No shortterm Best case Medium Sc 2 Base case no short and no long term constraint growth (Case A of Yes and no long- No 4% No of Task A (gas=Opportunity cost) on RE implementation? task A) term What is the least cost expansion with Low demand Constraints on RE Best case Yes (short Medium Sc 1 no long term constraint on RE im- growth (Case A of Yes No 4% No implementation of Task A term) (gas=Opportunity cost) plementation? task A) What is the least cost expansion with Low demand Yes (short Sc 3a - WACC Constraints on RE Best case Medium short and long-term constraint on RE growth (Case A of Yes term and No 4% No 4% implementation of Task A (gas=Opportunity cost) implementation? task A) long term) What is the least cost expansion with Low demand Yes (short Sc 3a - WACC Constraints on RE Best case Medium short and long-term constraints on growth (Case A of Yes term and No 6% No 6% implementation of Task A (gas=Opportunity cost) RE implementation? task A) long term) What is the least cost expansion with Low demand Yes (short Constraints on RE short and long-term constraints on Best case Yes Medium Sc 3b growth (Case A of Yes term and 4% No implementation RE implementation and wind capaci- of Task A (1GW) (gas=Opportunity cost) task A) long term) ty limitation? What is the least cost expansion with Low demand Yes (short Constraints on RE short and long-term constraints on Best case Yes Medium Sc 3c growth (Case A of Yes term and 6% No implementation RE implementation and wind capaci- of Task A (1GW) (gas=Opportunity cost) task A) long term) ty limitation? What is the least cost expansion with Low demand Yes (short Constraints on RE short and long-term constraints on Best case Yes Medium Sc 3d growth (Case A of Yes term and 8% No implementation RE implementation and wind capaci- of Task A (1GW) (gas=Opportunity cost) task A) long term) ty limitation? Slow recovery of What would be the RE mix with slow Low demand Yes (short suspended units, recovery of suspended units, availa- Worst case Yes Medium Sc 5 growth (Case A of Yes term and 4% No availability, efficien- bility, efficiency and technical loss- of Task A (1GW) (gas=Opportunity cost) task A) long term) cy and technical es? Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 30 - Existing and contracted power Limited implementation of RE Wind limitation of 1 GW Gas price assumption (short and long-term) Question answered Standalone battery Name of Scenario No of Model Run Demand growth Option of RE WACC CSP plants losses? Slow recovery of What would be the RE mix with slow suspended units, Low demand Yes (short recovery of suspended units, availa- Worst case Yes Medium Sc 5 availability, efficien- growth (Case A of Yes term and 6% No bility, efficiency and technical loss- of Task A (1GW) (gas=Opportunity cost) cy and technical task A) long term) es? losses? Best case of Task A re- Cancellation of What would be the RE mix if the Low demand Yes (short moving the Yes Medium Sc 6 committed conven- committed power plants were can- growth (Case A of Yes term and 4% No committed (1GW) (gas=Opportunity cost) tional power plants celled? task A) long term) conventional power plants Best case of Task A re- Cancellation of What would be the RE mix if the Low demand Yes (short moving the Yes Medium Sc 6 committed conven- committed power plants were can- growth (Case A of Yes term and 6% No committed (1GW) (gas=Opportunity cost) tional power plants celled? task A) long term) conventional power plants What would be the RE mix if load in- High demand Yes (short High demand Best case Yes Medium Sc 7 creases faster due to High demand growth (Case B of Yes term and 4% No growth of Task A (1GW) (gas=Opportunity cost) growth? task A) long term) What would be the RE mix if load in- High demand Yes (short High demand Best case Yes Medium Sc 7 creases faster due to High demand growth (Case B of Yes term and 6% No growth of Task A (1GW) (gas=Opportunity cost) growth? task A) long term) Low demand Yes (short What is the least cost expansion high Best case Yes Sc 8 High fuel price growth (Case A of Yes term and 4% High (gas=+20 %) No fuel prices? of Task A (1GW) task A) long term) Low demand Yes (short What is the least cost expansion high Best case Yes Sc 8 High fuel price growth (Case A of Yes term and 6% High (gas=+20 %) No fuel prices? of Task A (1GW) task A) long term) Low demand Yes (short What is the least cost expansion low Best case Yes Sc 9 Low fuel price growth (Case A of Yes term and 4% Low (gas=-20 %) No fuel prices? of Task A (1GW) task A) long term) Low demand Yes (short What is the least cost expansion low Best case Yes Sc 9 Low fuel price growth (Case A of Yes term and 6% Low (gas=-20 %) No fuel prices? of Task A (1GW) task A) long term) Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 31 - 8. Sensitivities Further to the scenarios, the LCEP considers also sensitivities for the base case scenario. Table 8-1: Summary of sensitivities Sensitivity Assumptions 5% reduction of elec- Medium attenuation Effects of GHI attenuation of tricity production PV sites in the south on the electricity production* 10% reduction of elec- High attenuation tricity production CAPEX increase of PV sites in the south due to more com- Moderate CAPEX increase 4% increase in CAPEX plex transport and mobiliza- tion, as well as to cover sup- ply of reactive capacity. Ap- High CAPEX increase 8% increase in CAPEX plied only once to the CAPEX * Optimistic CAPEX reduction Base case -10% Consideration of optimistic CAPEX reduction of CSP Very optimistic CAPEX re- Base case -20% duction Strong Maximum 0.5 GW Limit of total installed wind capacity in the LCEP Moderate Maximum 2 GW Variations in Weighted Aver- Higher risk margin Base case +2% age Capital Cost (WACC) for CSP** Lower risk margin Base case -2% * PV sites in the south consist of those sites located in the Sebah, Ghadamis, Brega, Hun, Ghat and Jaboub. It is expected that sites in the south will be more affected by attenuation of GHI due to sand and sand storms, subsequently reducing the expected energy produc- tion. Also this sensitivity covers for CAPEX increase associated to remote locations and additional equipment needed to provide reactive capacity ** WACC sensitivities are intended to reflect the effects of the evolution of the Libyan polit- ical situation in terms of political instability and subsequently risk levels. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 32 - 9. Results of Scenario and Sensitivities The analysis of the results let to a selection of scenarios demonstrating the main outcome of the exer- cise. This chapter 9 will guide thru the development of the reference case finally defined as the most realistic case to mirror the system and its expansion until 2030 from today's point of view. Results of a system expansion following this scenario (reference case) are displayed and discussed. Sensitivities and their impact in case of simulating these scenarios as well as the reasons for not de- fining them as "reference case" are displayed. 9.1 Scenario 4 (Sc4), No RE Generally, the first scenario analysed for this selection is the scenario which does not consider any re- newables to be part of the energy supply system until 2030 (Sc4 in Table 7-1 and in Table 9-1). This scenario reflects the situation that only new conventional CCGT plants will be installed, no renewables will be implemented until 2030. Under this scenario, the additional conventional power to be installed will be 3.5 GW, mainly commissioned in 2021. As the new power plants are somewhat more efficient than the existing once, this scenario allows for a reduction of the specific costs over the whole optimi- zation horizon of 1%, compared to the case that no additional installations will be executed. An approach denying RE installations into the power generation system until 2030 would signify that no considerable cost savings on fuel by cheaper renewables is realised in Libya. Also, Lib- ya would be de-coupled by the global development towards a strong, competitive renewable upscaling. 9.2 Scenario 2 (Sc2), Unlimited RE A second scenario considered the implementation of RE power generators without restrictions (Sc 2 in Table 7-1 and in Table 9-1). It reflects an unlimited growth of renewable energy projects. Consequent- ly, no new conventional capacity is installed and 12.35 GW of renewable energy technologies will be added until 2030. This scenario demonstrates the highest cost savings, summing up to a reduction of the specific costs over the whole optimization horizon of 16%. Figure 9-1 displays the time line of installations. No conventional power generators will be installed: As early as possible (restricted installation for PV from 2019 and for wind from 2012 on, see chapter 6.3.5), PV as well as wind projects will be implemented, whereas PV can start from 2019 and wind from 2021. Once wind projects can be implemented (due to the constrains only from 2012), only wind projects will be implemented further on. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 33 - Figure 9-1: Scenario 4, reflecting unlimited RE implementation of 12.35 GW until 2030 The model results in a high deployment of RE projects and could be appreciated from that point of view. Anyhow, many constraints would need to be removed, e.g. of regulatory nature, capaci- ty building, development, financing and implementation, etc. All these administrative and tech- nical constrains would realistically require much more time and other efforts to be considered as realistic. The amount of RE projects to be implemented until 2030 needs to be restricted to re- flect a realistic scenario as a reference case. 9.3 Scenario 3c (Sc3c), Reference Case The reference case is reflected in Sc3c (please refer to Table 7-1 and Table 9-1). This scenario re- flects the "learnings" from the two scenarios mentioned above. The scenario 3c includes the needs for renewables, but limits its implementation to 5 GW until 2030. This is the most realistic scenario, allow for a saving in costs of about 6%. Here, the installation of renewable power generators is restricted maximum 5 GW total RE installations into Libya's system until 2030. Additionally, 3 GW of new con- ventional power plants (CCGT) will be installed. Further on, the installation of wind power projects in Libya is limited to 1 GW until 2030. Reason is, that it should be avoided to install too much wind power in one area of the country. This shall avoid challenges in grid extension and, as a very important issue, the installation of wind power projects which are all depending on same wind conditions as they would be projected to be installed in the North where very good wind conditions prevail. The reference case allows for a specific WACC for CSP at 6% (other RE technologies are at 8%). CSP technology shall help to stabilize the system and as storage systems are combined, make power generation from solar happen even at night. The reduced WACC reflects that CSP as a promising technology might receive more (financial) support than the other renewable technologies. The costs for the gas used in the conventional power plants follow a medium gas price scenario ap- proach. The result of the installation of new power plants is shown in Figure 9-2. Again, in 2019 only PV pro- jects will be realized as this is the only technology being possible to install before 2021. In 2021 a huge amount of CCGT plants and wind plants will be starting their operation. Due to the fact that a specific WACC for CSP is considered, in 2027 the first CSP project will go alive. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 34 - Figure 9-2: Newly installed capacity for the Reference Case To identify the energy supply by different devices, Figure 9-3 shows the energy demand as a black line ion top of the bars. The bars display the annual produced energy until 2030, from 2021 always ful- filling the demand. The diagram differs between the different technologies. Looking into 2029 where the share of renewables is the highest, it can be understood that the renewable share is less than 25%. So, a "challenging" impact onto the gird is not to be expected. Figure 9-3: Reference case: Produced energy until 2030 For this case, the Consultant analysed the economic savings of this Sc3c in comparison to the men- tioned Sc4 (scenario without RE). Figure 9-4 shows the results over the years. In this figure, the sav- ings with regard to CAPEX and OPEX as well as to fuel costs are displayed. For the two different cat- egories, both, the annual value and the NPV are shown. Considering the NPV bars, they are annually beneath the 200 Mio USD level, but in case not considering the discount rate, values go up and for fuel savings in 2030 more than 1,000 Mio USD are displayed! Over the complete time line until 2030 fuel cost savings reach 6,421 / 1,615 Mio USD, CAPEX/ OPEX savings are with 3,644 / 946 Mio USD (where in both cases the latter figure represents the NPV). Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 35 - Wrapping up the information from this comparison: Even with a realistic (and as such constrained sce- nario) huge savings will be reached! Figure 9-4: Cost comparison showing savings in Sc3c (reference) in compared to Sc4 (No RE) The reference case reflects a realistic scenario for the development of RE power plants in the Libyan grid system until 2030. Albeit a number of restrictions, the case shows that even with a reasonable growth of RE in the system a proper share of energy can be delivered into the grid at the end of the time interval, being between 20 and 25% annually. This amount of renewable share will not challenge grid systems. A detailed analyses shows that there will be considerable amounts of saving in comparison to the Sc4, No RE. E.g., fuel savings are summing up to more than 6,400 Mio USD, resulting in a NPV of more than 1,600 Mio USD! 9.4 Sensitivities There are constrains within the reference case for which sensitivities have been analysed. These fur- ther analyses are summarized:  Sensitivity 1: The reference case considers a limitation of wind power to 1 GW. What happens in case this constrain will be removed?  Sensitivity 2: The WACC for CSP is defined to be 6%. In case the WACC can be reduced to 4%, how does the system look like, then?  Sensitivity 3: The gas price scenario where the reference case is based on is a moderate scenario. What will be the impact on the LECP analysis in case the gas price will be either increased ot r lowered? Sensitivity 1 To understand the impact of the limitation of maximum 1 GW of wind power to be installed, a scenario removing this limitation but keeping all other conditions of the reference case, has been executed (Sc3a - WACC 6%, please refer to Table 7-1 and Table 9-1). Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 36 - The results of this scenario shows that the wind power would sum up to 4,1 GW., please see Figure 9-5. All these power plants would be installed in the coastal area and this means that a huge share of the capacity is depending on the same resource and same meteorological conditions. This might cause in-balances in the grid system. In general, with regard to the investment, wind power will not re- place CCGTs but solar (both PV and CSP). Figure 9-5: Sensitivity 1, no constrain for wind power Analysing the energy delivered into the system in an annual resolution (Figure 9-6), it becomes quite clear that solar technologies would be replaced by wind power. No significant higher share of renewa- bles in the grid would be reached compared to the reference case. Anyhow, the specific costs will be reduced by 1% compared to the reference case. Figure 9-6: Sensitivity 1, no constrain for wind power, produced energy until 2030 With this sensitivity 1 the specific costs can be lowered by 1% additionally. Having in mind -The big disadvantage of having installed a very high share of the renewable technologies in coastal areas and considering the resulting impact from wind conditions in the area; Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 37 - -The fact that currently most conventional generation systems are locaterd in the north of the country; -That installation of a proper share of RE generators in the south of the country; -The high local grid penetration; this scenario will not be considered to show a realistic case. Sensitivity 2 Sensitivity 2 (Sc 3b in Table 7-1 and in Table 9-1) shall reflect the effect of lowering the WACC for CSP projects to 4%. Generally, such a scenario makes sense to simulate as it can be useful to sup- port promising technologies to come to the market and often development banks show specific pro- grams for this including concessional loans. Actually, the simulation based on a 4% WACC for CSP shows a huge impact on the capacity of CSP plants to be installed under LCEP conditions. This scenario shows that 3,1 GW of CSP would be in- stalled until 2030. The total amount of RE capacity will then be 4,8 GW. The installed power remains same, and the reductions of specific cost are in the same range as for the reference scenario. Figure 9-7: Sensitivity 2, WACC for CSP lowered to 4%, With regard to the energy delivered, the graph (Figure 9-8) shows an increased amount of RE energy in the system. In 2029, the share is about 6% higher than in the reference case. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 38 - Figure 9-8: Sensitivity 2, WACC for CSP lowered to 4%, produced energy until 2030 Despite the positive effect to increase the RE share to almost 30% in 2029 and 2030, this case shows the most important "adjusting screw" to increase the capacity of CSP projects. With a WACC of 8% no CSP is considered by the solver, at 6% a reasonable share (0,4 GW until 2030) to support this technology is reached and with 4% the system focuses with (too) high shares on CSP. Consultant's view in this case is, that development banks are not going to soft loan so much CSP technology (3,1 GW in this case) in one country. It might be useful to apply such scenario only for a few plants (more than in the reference case) but this sensitivity 2 leads to results which cannot be called "realistic". Sensitivity 3 It is understandable that one says that the results are applicable only under the mentioned moderate gas price scenario. So, this sensitivity 3 analyses the impact of changing gas price into both direction, into increased price scenario and decreased price scenario. The "High Fuel Price scenario (Sc8 in Ta- ble 7-1 and in Table 9-1) considers an increase of the price of 20% whereas the Low Fuel Price sce- nario (Sc8 in Table 7-1 and in Table 9-1 foresees a decrease by 20%). Both scenarios are displayed in one chart together with the reference case (please refer to Figure 9-9). Each scenario is reflected in one bar. The different colors within the bars refer to different technologies. Depending on the scenario, the conventional installations remain almost similar, only slight differences occur. Within the RE technolo- gy mix, there is a big impact, and while PV installations remain almost similar, CSP and wind are changing. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 39 - Figure 9-9: Sensitivity 3, Fuel price variation The most important outcome from this sensitivity is that the share of RE technology installations is not sensitive against the fuel price! This means from economic point of view installing renew- ables is in all three fuel price scenarios the right way forward. On the other hand the sensitivity 3 shows that, depending on the fuel price development, it makes sense to re-run such LCEP model whenever forecast for fuel prices changes. 9.5 Summary of Results The results of the scenarios are summarized in Table 9-1 and a summary sensitivity analyses are dis- played in Table 9-2. Table 9-1 includes all described and analysed scenarios. Sc4 and Sc2 are highlighted yellow. These scenarios are described in the beginning of this chapter 9, in 9.1 and 9.2. The reference case de- scribed in chapter 9.3, is highlighted green, whereas the two sensitivity scenarios 1 and 2 are high- lighted light green. The scenarios forming the basis for sensitivity 3 are highlighted grey. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 40 - Table 9-1: Summary of scenario results optimization horizon compared to the 'status RE electricity share Addition to installed capacity [MW] Total CAPEX for all new configurations over Deviation in specific costs ((sum of CAPEX, (energy based [MWh]) (2030 includes the capacity installed Limited implementation of RE (short and OPEX Fix & OPEX Var (NPV))/ produced [%] until 2025) average utilization rates [%] Existing and contracted power plants electricty [USD/MWh]) over the whole Gas saving [Mio m3 in 2025/2030] Imported energy until 2030 [TWh] quo or 'reference scenario' [%] Total OPEX Fix until 2030 CO2 saving [Mio t CO2 in Wind limitation of 1 GW Gas price assumption Fuel costs until 2030 Question answered Standalone battery the whole life time Name of Scenario No of Model Run [mio USD (NPV)] [mio USD (NPV)] [mio USD (NPV)] Demand growth Conventional Option of RE stock CCGT WACC CSP long-term) new CCGT 2025/2030] Total RE Wind 2020 2025 2030 CSP GT PV ST How does the power plant fleet operates 2025 0 0 0 0 0 2025 0,0 0,0 Best case Low demand growth Medium pre-scenario status quo without new conventional or new RE No - - - No 0 1.300 17.000 0% 0% 0% 63 80% 14% 20% of Task A (Case A of task A) (gas=Opportunity cost) capacity? 2030 0 0 0 0 0 2030 0,0 0,0 2025 3.500 0 0 0 0 2025 0,0 0,0 What is the least-cost expansion Best case Low demand growth Medium Sc 4 No RE No - - - No 800 1.400 16.400 -1% 0% 0% 0% 55 76% 73% 4% 20% without RE ? of Task A (Case A of task A) (gas=Opportunity cost) 2030 3.500 0 0 0 0 2030 0,0 0,0 Definition of a reference case What is the least cost expansion with No shortterm 2025 0 5.850 4.700 0 10.550 2025 2,8 6,3 Best case Low demand growth Medium Sc 2 Base case no short and no long term constraint on Yes and no No 4% No 6.200 2.000 10.200 -16% 28% 53% 52% 45 42% 3% 20% of Task A (Case A of task A) (gas=Opportunity cost) RE implementation? longterm 2030 0 7.650 4.700 0 12.350 2030 3,3 7,3 What is the least cost expansion with No shortterm 2025 0 5.850 4.700 0 10.550 2025 2,8 6,3 Best case Low demand growth Medium Sc 2 Base case no short and no long term constraint on Yes and no No 6% No 6.200 2.000 10.200 -16% 28% 53% 52% 45 42% 3% 20% of Task A (Case A of task A) (gas=Opportunity cost) RE implementation? longterm 2030 0 7.700 4.700 0 12.400 2030 3,3 7,3 What is the least cost expansion with 2025 2.000 7.200 2.650 100 9.950 2025 2,9 6,4 Constraints on RE Best case Low demand growth Yes (short Medium Sc 1 no long term constraint on RE Yes No 4% No 5.200 1.900 11.400 -12% 11% 53% 52% 49 41% 28% 3% 20% implementation of Task A (Case A of task A) term) (gas=Opportunity cost) implementation? 2030 2.000 8.500 3.750 300 12.550 2030 3,4 7,4 What is the least cost expansion with 2025 3.000 2.050 750 200 3.000 2025 1,1 2,4 Sc 3a - WACC Constraints on RE Best case Low demand growth Yes (short term Medium short and long-term constraint on RE Yes No 4% No 2.700 1.500 14.300 -7% 5% 20% 28% 55 64% 54% 3% 20% 4% implementation of Task A (Case A of task A) and long term) (gas=Opportunity cost) implementation? 2030 3.000 4.000 750 200 4.950 2030 1,8 4,0 What is the least cost expansion with 2025 3.000 2.250 750 0 3.000 2025 1,1 2,3 Sc 3a - WACC Constraints on RE Best case Low demand growth Yes (short term Medium short and long-term constraints on RE Yes No 6% No 2.600 1.500 14.400 -7% 5% 20% 27% 55 65% 55% 3% 20% 6% implementation of Task A (Case A of task A) and long term) (gas=Opportunity cost) implementation? 2030 3.000 4.100 750 0 4.850 2030 1,8 3,9 What is the least cost expansion with 2025 3.000 600 750 1.600 2.950 2025 1,3 2,8 Constraints on RE short and long-term constraints on RE Best case Low demand growth Yes (short term Yes Medium Sc 3b Yes 4% No 4.000 1.600 14.000 -6% 5% 23% 33% 55 62% 51% 3% 20% implementation implementation and wind capacity of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 850 850 3.100 4.800 2030 2,1 4,6 limitation? What is the least cost expansion with 2025 3.000 600 2.350 0 2.950 2025 0,8 1,8 Constraints on RE short and long-term constraints on RE Best case Low demand growth Yes (short term Yes Medium Sc 3c Yes 6% No 2.500 1.500 14.800 -6% 5% 15% 22% 55 68% 59% 3% 20% implementation implementation and wind capacity of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 850 3.350 400 4.600 2030 1,4 3,1 limitation? What is the least cost expansion with 2025 2.500 550 2.350 0 2.900 2025 0,8 1,8 Constraints on RE short and long-term constraints on RE Best case Low demand growth Yes (short term Yes Medium Sc 3d Yes 8% No 2.000 1.500 14.900 -6% 5% 15% 20% 55 69% 63% 4% 20% implementation implementation and wind capacity of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 2.500 800 3.700 0 4.500 2030 1,3 2,8 limitation? Scenarios Slow recovery of What would be the RE mix with slow 2025 3.500 600 800 1.600 3.000 2025 1,3 2,8 suspended units, recovery of suspended units, Worst case Low demand growth Yes (short term Yes Medium Sc 5 Yes 4% No 4.500 1.400 12.200 0% 8% 24% 35% 102 42% 88% 1% 20% availability, efficiency availability, efficiency and technical of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 4.500 950 800 3.100 4.850 2030 2,2 4,9 and technical losses? losses? Slow recovery of What would be the RE mix with slow 2025 4.000 600 2.350 0 2.950 2025 0,8 1,8 suspended units, recovery of suspended units, Worst case Low demand growth Yes (short term Yes Medium Sc 5 Yes 6% No 3.900 1.300 12.700 0% 9% 16% 30% 109 44% 93% 1% 20% availability, efficiency availability, efficiency and technical of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 4.000 950 2.500 1.600 5.050 2030 1,9 4,1 and technical losses? losses? Cancellation of Best case of What would be the RE mix if the 2025 2.500 450 800 1.600 2.850 2025 1,2 2,7 committed Task A Low demand growth Yes (short term Yes Medium Sc 6 committed power plants were Yes 4% No 4.100 1.400 13.800 -2% 5% 23% 36% 57 49% 90% 6% 20% conventional power removing the (Case A of task A) and long term) (1GW) (gas=Opportunity cost) cancelled? 2030 3.000 1.000 800 3.100 4.900 2030 2,2 4,9 plants committed Cancellation of Best case of What would be the RE mix if the 2025 3.000 600 1.950 0 2.550 2025 0,7 1,6 committed Task A Low demand growth Yes (short term Yes Medium Sc 6 committed power plants were Yes 6% No 3.900 1.300 14.400 -3% 5% 13% 30% 57 49% 94% 6% 20% conventional power removing the (Case A of task A) and long term) (1GW) (gas=Opportunity cost) cancelled? 2030 3.500 900 2.300 1.800 5.000 2030 1,9 4,2 plants committed What would be the RE mix if load High demand 2025 3.500 500 800 1.600 2.900 2025 1,2 2,7 Best case Yes (short term Yes Medium Sc 7 High demand growth increases faster due to High demand growth (Case B of Yes 4% No 4.100 1.600 16.300 -7% 5% 18% 24% 56 76% 77% 4% 20% of Task A and long term) (1GW) (gas=Opportunity cost) growth? task A) 2030 3.500 850 850 3.000 4.700 2030 2,1 4,7 What would be the RE mix if load High demand 2025 3.500 500 2.150 0 2.650 2025 0,8 1,7 Best case Yes (short term Yes Medium Sc 7 High demand growth increases faster due to High demand growth (Case B of Yes 6% No 3.100 1.500 17.100 -7% 5% 11% 17% 56 78% 81% 5% 20% of Task A and long term) (1GW) (gas=Opportunity cost) growth? task A) 2030 4.000 900 3.100 700 4.700 2030 1,6 3,4 2025 3.000 600 700 1.700 3.000 2025 1,3 2,9 What is the least cost expansion high Best case Low demand growth Yes (short term Yes Sc 8 High fuel price Yes 4% High (gas=+20 %) No 4.200 1.600 16.700 15% 5% 24% 35% 53 64% 51% 3% 21% fuel prices? of Task A (Case A of task A) and long term) (1GW) 2030 3.000 850 700 3.400 4.950 2030 2,2 4,9 2025 3.500 600 2.000 300 2.900 2025 0,9 2,0 What is the least cost expansion high Best case Low demand growth Yes (short term Yes Sc 8 High fuel price Yes 0,06 High (gas=+20 %) No 4.100 1.500 17.300 16% 5% 17% 31% 53 68% 53% 3% 21% fuel prices? of Task A (Case A of task A) and long term) (1GW) 2030 3.500 950 2.100 2.000 5.050 2030 2,0 4,3 2025 2.500 600 2.350 0 2.950 2025 0,8 1,8 What is the least cost expansion low Best case Low demand growth Yes (short term Yes Sc 9 Low fuel price Yes 4% Low (gas=-20 %) No 2.700 1.500 12.000 -16% 5% 15% 24% 52 67% 61% 4% 20% fuel prices? of Task A (Case A of task A) and long term) (1GW) 2030 2.500 900 2.900 900 4.700 2030 1,6 3,4 2025 2.500 600 2.350 0 2.950 2025 0,8 1,8 What is the least cost expansion low Best case Low demand growth Yes (short term Yes Sc 9 Low fuel price Yes 6% Low (gas=-20 %) No 2.100 1.500 12.100 -16% 5% 15% 20% 52 68% 63% 4% 20% fuel prices? of Task A (Case A of task A) and long term) (1GW) 2030 2.500 900 3.800 0 4.700 2030 1,3 2,8 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 41 - Table 9-2: Summary of sensitivity results optimization horizon compared to the 'status RE electricity share Addition to installed capacity [MW] Total CAPEX for all new configurations over Deviation in specific costs ((sum of CAPEX, (energy based [MWh]) (2030 includes the capacity installed Limited implementation of RE (short and OPEX Fix & OPEX Var (NPV))/ produced [%] until 2025) average utilization rates [%] Existing and contracted power plants electricty [USD/MWh]) over the whole Gas saving [Mio m3 in 2025/2030] Imported energy until 2030 [TWh] quo or 'reference scenario' [%] Total OPEX Fix until 2030 CO2 saving [Mio t CO2 in Wind limitation of 1 GW Gas price assumption Fuel costs until 2030 Question answered Standalone battery the whole life time Name of Scenario No of Model Run [mio USD (NPV)] [mio USD (NPV)] [mio USD (NPV)] Demand growth Conventional Option of RE stock CCGT WACC CSP long-term) new CCGT 2025/2030] Total RE Wind 2020 2025 2030 CSP GT PV ST Sensitivities Effects of GHI 2025 3.000 600 800 1.600 3.000 2025 1,3 2,8 attenuation of Best case Low demand growth Yes (short term Yes Medium GHI South -5% Yes 4% No 4.000 1.600 14.000 0% 5% 24% 33% 55 62% 51% 3% 20% PV sites in the south of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 1.000 950 3.000 4.950 2030 2,1 4,7 on the Effects of GHI 2025 3.000 400 2.350 0 2.750 2025 0,7 1,6 attenuation of Best case Low demand growth Yes (short term Yes Medium GHI South -5% Yes 6% No 2.600 1.500 14.800 0% 5% 14% 22% 55 68% 60% 3% 20% PV sites in the south of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 900 3.400 400 4.700 2030 1,4 3,1 on the Effects of GHI 2025 3.000 600 900 1.200 2.700 2025 1,1 2,4 attenuation of Best case Low demand growth Yes (short term Yes Medium GHI South -10% Yes 4% No 4.000 1.600 14.100 0% 5% 20% 33% 55 62% 53% 3% 20% PV sites in the south of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 950 1.000 3.000 4.950 2030 2,1 4,7 on the Effects of GHI 2025 3.000 600 2.300 0 2.900 2025 0,8 1,8 attenuation of Best case Low demand growth Yes (short term Yes Medium GHI South -10% Yes 6% No 2.600 1.500 14.800 0% 5% 15% 22% 55 68% 60% 3% 20% PV sites in the south of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 1.000 3.350 400 4.750 2030 1,4 3,1 on the CAPEX increase of 2025 3.000 600 800 1.600 3.000 2025 1,3 2,8 CAPEX South PV sites in the south Best case Low demand growth Yes (short term Yes Medium Yes 4% No 3.900 1.600 14.000 0% 5% 24% 32% 55 62% 51% 3% 20% +4% due to more complex of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 750 850 3.100 4.700 2030 2,1 4,6 transport and CAPEX increase of 2025 3.000 500 2.350 0 2.850 2025 0,8 1,7 CAPEX South PV sites in the south Best case Low demand growth Yes (short term Yes Medium Yes 6% No 2.900 1.500 14.800 0% 5% 14% 25% 55 68% 59% 3% 20% +4% due to more complex of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 1.000 3.400 700 5.100 2030 1,6 3,5 transport and CAPEX increase of 2025 3.000 600 900 1.500 3.000 2025 1,3 2,8 CAPEX South PV sites in the south Best case Low demand growth Yes (short term Yes Medium Yes 4% No 3.900 1.600 14.100 0% 5% 23% 33% 55 63% 52% 3% 20% +8% due to more complex of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 950 950 2.900 4.800 2030 2,1 4,6 transport and CAPEX increase of 2025 3.000 600 2.350 400 3.350 2025 0,8 1,8 CAPEX South PV sites in the south Best case Low demand growth Yes (short term Yes Medium Yes 6% No 2.600 1.500 14.800 0% 5% 15% 22% 55 68% 60% 3% 20% +8% due to more complex of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) 2030 3.000 900 3.400 400 4.700 2030 1,4 3,1 transport and CSP - Optimistic Consideration of 2025 3.000 500 700 1.700 2.900 2025 1,3 2,8 Best case Low demand growth Yes (short term Yes Medium CAPEX optimistic CAPEX Yes 4% No 3.800 1.600 14.000 -1% 5% 23% 35% 55 61% 51% 3% 20% of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) reduction reduction of CSP 2030 3.000 950 800 3.300 5.050 2030 2,2 4,9 CSP - Optimistic Consideration of 2025 3.000 550 2.000 400 2.950 2025 0,9 2,1 Best case Low demand growth Yes (short term Yes Medium CAPEX optimistic CAPEX Yes 6% No 3.400 1.500 14.600 0% 5% 17% 28% 55 65% 56% 3% 20% of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) reduction reduction of CSP 2030 3.000 950 2.200 1.600 4.750 2030 1,8 3,9 CSP - Very Consideration of 2025 2.500 600 700 1.700 3.000 2025 1,3 2,9 optimistic Best case Low demand growth Yes (short term Yes Medium optimistic CAPEX Yes 4% No 3.400 1.600 14.000 -1% 5% 24% 33% 55 62% 54% 3% 20% CAPEX of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) reduction of CSP 2030 2.500 800 700 3.200 4.700 2030 2,1 4,7 reduction CSP - Very Consideration of 2025 3.000 600 800 1.600 3.000 2025 1,3 2,8 optimistic Best case Low demand growth Yes (short term Yes Medium optimistic CAPEX Yes 6% No 4.000 1.600 14.000 0% 5% 24% 33% 55 62% 52% 3% 20% CAPEX of Task A (Case A of task A) and long term) (1GW) (gas=Opportunity cost) reduction of CSP 2030 3.000 1.000 850 3.000 4.850 2030 2,1 4,7 reduction Limit of total installed 2025 3.000 300 900 1.800 3.000 2025 1,3 2,9 Best case Low demand growth Yes (short term Yes Medium Wind 0,5 GW wind capacity in the Yes 4% No 4.200 1.600 14.000 0% 5% 24% 34% 55 61% 51% 3% 20% of Task A (Case A of task A) and long term) (0,5GW) (gas=Opportunity cost) LCEP - strong 2030 3.000 500 950 3.500 4.950 2030 2,2 4,8 Limit of total installed 2025 2.500 300 2.650 0 2.950 2025 0,8 1,7 Best case Low demand growth Yes (short term Yes Medium Wind 0,5 GW wind capacity in the Yes 6% No 2.200 1.500 14.900 0% 5% 15% 20% 55 69% 64% 4% 20% of Task A (Case A of task A) and long term) (0,5GW) (gas=Opportunity cost) LCEP - strong 2030 2.500 500 4.000 200 4.700 2030 1,3 2,9 Limit of total installed 2025 3.000 950 750 1.000 2.700 2025 1,1 2,4 Best case Low demand growth Yes (short term Yes Medium Wind 2 GW wind capacity in the Yes 4% No 3.500 1.600 14.200 0% 5% 20% 31% 55 64% 53% 3% 20% of Task A (Case A of task A) and long term) (0,5GW) (gas=Opportunity cost) LCEP - moderate 2030 3.000 1.850 800 2.100 4.750 2030 2,0 4,4 Limit of total installed 2025 3.000 1.250 1.750 0 3.000 2025 0,9 2,0 Best case Low demand growth Yes (short term Yes Medium Wind 2 GW wind capacity in the Yes 6% No 2.900 1.500 14.600 0% 5% 17% 27% 55 67% 58% 3% 20% of Task A (Case A of task A) and long term) (0,5GW) (gas=Opportunity cost) LCEP - moderate 2030 3.000 1.850 2.850 500 5.200 2030 1,7 3,7 Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx - 42 - 10. LCEP Follow-up The Consultant recommends the following actions for a successful implementation of the LCEP:  The LCEP is a dynamic tool, which needs to be constantly updated according to changes of the lo- cal electricity system, electricity market, technology development and technology breakthroughs;  Constrains used to identify a realistic set-up and to identify the reference case need to be scruti- nized permanently to up-date or adapt them whenever the situation occurs.  Also, whenever new results for more detailed meteorological resource analysis or more detailed basic information for site selection are available, a re-run of the LCEP might bring new results.  After preparation of the Strategic Plan for Renewable Energy of Libya (the SPRE) based on out- comes of the LCEP, an investment plan shall be refined and agreed upon;  Implementation of geospatial intelligence for the LCEP, which shall be used for coordination and monitoring the implementation of the LCEP. Such system shall allow stakeholders to access vital information of the LCEP, its infrastructure and each RE facility in real time;  Implementation of state-of-the-art measurement campaigns for the preferred wind and solar sites identified in the LCEP;  Preparation of a master plan for implementation of the required infrastructure necessary for the LCEP alongside with an investment plan;  Preparation of at least basic power system studies to verify the suitability of connection points and transmission lines for the LCEP;  Preparation of an administrative structure at REAOL in charge of administration of the LCEP in- cluding project management, as well as asset & facility management;  Prepare policies and guidelines in order to streamline the participation of the private sector with re- gard to permitting, land securing and grid connection (this will be also addressed as part of the SPREL included in this assignment); and  Preparation of a strategy for allocation of land to be centralized in the geospatial intelligence. Libya SPREL – LCEP Final Report LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan Report Annex I – Solar and Wind Resource 12 December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de Table of Contents Page 1. Solar and Wind Resource 1 1.1 Solar Resource 1 1.1.1 Global Horizontal Irradiance (GHI) - PV 2 1.1.2 Direct Normal Irradiance (DNI) - CSP 2 1.2 Wind Resource 5 1.2.1 Wind Resource – Local Distribution 6 1.2.2 Available Ground Measurements in Libya 8 List of Tables Table 1-1: Sites pre-selected for solar plants Table 1-2: Summary of wind data review Table 1-3: Summary of pre-selected sites according to solar and wind resource List of Figures Figure 1-1: Satellite view (left) and topography (right) of Libya, source: Solar-Med-Atlas Figure 1-2: GHI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas (right) Figure 1-3: DNI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas (right) Figure 1-4: Locations selected for solar power plants incl. solar met stations Figure 1-5: Wind energy density at 100m above ground level - DTU Global Wind Atlas Figure 1-6: Average annual wind speed at 100 m above ground level – DTU Global Wind Atlas Figure 1-7: Wind energy density in Libya, North-western coast - DTU Global Wind Atlas Figure 1-8: Wind energy density in Libya, North-eastern coast - DTU Global Wind Atlas Figure 1-9: Wind energy density in Libya - DTU Global Wind Atlas Figure 1-10: Wind profile illustration of low level jets - Source: NREL Figure 1-11: Locations with available ground wind data Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx Abbreviations CAPEX Capital Expenditures CCGT Combined Cycle Gas Turbine CRS/CR Central Receiver System CSP Concentrating Solar Power DNI Direct Normal Irradiation DSG Direct Steam Generation ENTSO European Network of Transmission System Operators ESS Energy Storage System FLH Full Load Hours GECOL General Electric Company of Libya GHI Global Horizontal Irradiation GI Global Irradiation GT Gas Turbine HFO Heavy Fuel Oil HRSG Heat Recovery Steam Generator HTF Heat Transfer Fluid IDC Interest During Construction IEC International Electro-chemical Commission IGBT Insulated Gate Bipolar Transistor IPP Independent Power Producer IRR Internal Rate of Return ISCC Integrated Solar Combined Cycle ITRPV International Technology Roadmap for Photovoltaic LCEP Least Cost Expansion Plan LCoE Levelized Cost of Electricity LDS Long-Duration Energy Storage LFO Light Fuel Oil LID Light Induced Degradation LLJ Low Level Jet LVRT Low Voltage Ride Through OPEX Operational Expenditures PID Potential Induced Degradation PPA Power Purchase Agreement PSP Private Sector Participation PT Parabolic Trough PV Photovoltaics RE Renewable Energies REAOL Renewable Energy Authority of Libya SCA Solar Collector Arrangement SCGT Simple Cycle Gas Turbine SM Solar Multiple STATCOM Static Compensators SPREL Strategic Plan for Renewable Energies in Libya TES Thermal Energy Storage TMY Typical Meteorological Year TSC Thyristor Switched Capacitors WACC Weighted Average Capital Cost WB World Bank WTG Wind Turbine Generator Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -1- 1. Solar and Wind Resource Based on the information made available and the Consultant databases the Consultant reviewed the overall solar and wind resources available in the country and identified the most suitable areas, and when possible sites, of the country for implementation of PV, wind or CSP projects. The main activities include:  Review of available satellite wind and solar data for the complete country;  Determination of the sites where measurement campaigns have been carried out;  Determination of the sites with ground meteorological data;  Appraisal of the completeness, quality and plausibility of the meteorological data provided; and  Determination of the extent to which the meteorological data provided can be used (e.g. for LCEP, for feasibility study or bankability). 1.1 Solar Resource Libya has a high potential of solar energy for both, PV-technology and CSP-technology due to the very favourable conditions of global and direct solar radiation for almost the whole country. The annual av- erage of sunshine hours reaches around 3,200 hours. Libya is fourth in size among the countries of Africa and seventeenth among the countries of the world. The Mediterranean coast and the Sahara Desert are the country's most prominent natural fea- tures. As can be seen in Figure 1-1, Libya is dominated by arid and warm desert. There are several highlands but no true mountain ranges except in the largely empty southern desert near the Chadian border. In general, intensity of GHI and in special DNI is strongly related to the ground elevation that can be seen by comparison of the topography map in Figure 1-1 with the GHI/DNI maps in Figure 1-2 and Figure 1-3. Figure 1-1: Satellite view (left) and topography (right) of Libya, source: Solar-Med-Atlas Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -2- 1.1.1 Global Horizontal Irradiance (GHI) - PV The distribution of the long-term annual GHI sums is quite homogeneous in Libya and can reach up to 2 around 2,500 kWh/m for the Tibesti Massif in the South that rises to over 2,200 metres. However, this region is very hard accessible and an almost total empty desert countryside, thus not the first option for solar energy. 2 2 The most part of Libya reaches annual GHI sum between 2,100 kWh/m and 2,300 kWh/m as can be seen in Figure 1-2, which shows the GHI maps from two different sources: the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas (right). Since the Solar-Med-Atlas just covers the Medi- terranean region the used colour code reaches from around 1400 kWh/m2 up to around 2600 kWh/m2. Thus, the GHI of the Solar-Med-Atlas is visualized with a higher resolution in compari- son to the World Bank’s ESMAP Global Solar Atlas, which covers nearly the complete planet using a colour code reaching from around 600 kWh/m2 up to around 2700 kWh/m2. Therefore, the correlation of GHI to the ground elevation could be better seen in the Solar-Med-Atlas. In general, almost the whole country reaches long-term annual GHI sums, which are more than suita- ble for solar energy applications with PV-technology. Higher GHI values occur in the centre, South, Southeast and West (yellow, orange and red colour shades in Solar-Med-Atlas, Figure 1-2). Lower 2 GHI values of around 2,000 kWh/m appear in the North and in Northeast (green colour shades in So- lar-Med-Atlas, Figure 1-2). In the coastline, it is partly below, especially in the eastern and southern part of the Gulf of Sirte. Only the Solar-Med-Atlas shows for very small areas long-term annual GHI 2 sums below 1,900 kWh/m indicated by the blue colour shades. Figure 1-2: GHI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar At- las (right) 1.1.2 Direct Normal Irradiance (DNI) - CSP In comparison to the GHI distribution the distribution of the long-term annual DNI sums is naturally more heterogeneous in Libya, as can be seen in Figure 1-3, which shows the DNI maps from the So- lar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas (right). The highest values up to 2 around 3,000 kWh/m can also be found for the Tibesti Massif in the South. However, this region is very hard accessible and an almost total empty desert countryside, thus no option for solar energy. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -3- 2 In a big part of the country the long-term annual DNI sums, lying between 2,200 kWh/m and 2,500 2 kWh/m , are suitable for solar energy applications with CSP-technology. Similar to the GHI distribu- tion, higher DNI values occur in the centre, South, Southeast and West (yellow, orange and red colour 2 2 shades in Solar-Med-Atlas, Figure 1-3). Lower DNI values of around 2,000 kWh/m to 2,200 kWh/m appear in the North, Northeast and Southwest (green colour shades in Solar-Med-Atlas, Figure 1-3). In the coastline it is partly below, especially in the eastern and southern part of the Gulf of Sirte. Only 2 the Solar-Med-Atlas shows for very small areas long-term annual DNI sums below 1,900 kWh/m indi- cated by the blue colour shades. Figure 1-3: DNI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar At- las (right) 1.1.2.1 Available ground solar measurements in Libya The climatological long-term annual average solar irradiance is usually the most crucial information for site selection and project implementation. Solar resource assessments aim to get long-term averages of the GHI for PV projects or DNI for CSP projects. These data typically represent the long-term annu- al average P50 (i.e. with a probability of exceedance of 50% in all cases and is presented on a data set called Typical Meteorological Year (TMY), which shall closely represent P50 values. One of the main aims of a solar resource assessment is to prepare a TMY data set, which should also include auxiliary meteorological parameters like ambient temperature, humidity, and wind speed and wind direction. This TMY is the base for site-specific engineering and yield estimation. Having suffi- cient and proper ground measurements allows for more accurate long-term averages and hence more accurate TMYs. According to the information made available to the Consultant and direct requests of the stakeholders the following locations are pre-selected for studying the solar resource potential available in Libya: Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -4- Table 1-1: Sites pre-selected for solar plants Site Remarks Jadu (Bir al-Ganam) GHI and DNI ground measurements available Ghadamis GHI and DNI ground measurements available Edri GHI ground measurements available Thala GHI ground measurements available Sebah GHI and DNI report available; no ground measurements available Shahat GHI Report available; no ground measurements available Hun GHI Report available; no ground measurements available Brega Suggested by Consultant; only satellite data Zliten Suggested by REAOL; only satellite data Jagboub Suggested by GECOL; only satellite data Kufra1 Suggested by GECOL; only satellite data Kufra2 Suggested by GECOL; only satellite data According to Table 1-1 although many resource campaigns for solar ground measurements were commissioned the bulk of the ground data is missing and cannot be retrieved. The best sets for solar data are at Bir Al-Gahnam, Ghadamis, Edri and Thala, however only Bir Al-Gahnam and Ghadamis with DNI data. Although for some of the remaining sites there are solar resource assessment reports the ground data is missing and thus only satellite data could be used for the simulations. Brega, Zliten, Jagboub, Kufra1 and Kufra2 were added to the analyses either by the Consultant or by suggestion of the stakeholders. Data to be used at these sites is also satellite data. The locations at the coastal areas are characterized by significant lower long-term averages for GHI and DNI in comparison to the other locations. This is especially critical for DNI, which strongly de- pends on aerosols and water vapour present in higher quantities in the atmosphere of coastal areas. Therefore these areas will not be considered for solar application as part of the LCEP. The conclusions are as follows.  For the locations where ground measurements of GHI and DNI are available the uncertainty of the corresponding long-term best estimates could be significantly reduced by considering these on-site measurements.  For following locations ground measurements are already available to us: – Ghadamis; – Bir Al-Ghanam; – Edri; and – Thala  For following locations ground measurements exist but data sets are missing: – Hun; – Sebah; and – Shahat. Table 1-3 presents a summary of the pre-selected sites for verification of the solar resource after per- forming a review of the solar data provided and, when relevant, gives an overview of the long-term es- timate of GHI and DNI for the considered locations. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -5- Figure 1-4 shows the locations for solar power plants considered for the LCEP including those with available ground data and those with only satellite. Ground data will be used for reducing uncertainties in these areas. It is important to note again that DNI ground data is only available at Bir Al-Gahnam and Ghadamis and that satellite derived DNI carries along much higher uncertainties than satellite derived GHI. Figure 1-4: Locations selected for solar power plants incl. solar met stations 1.2 Wind Resource 1 Libya has very good potential for onshore wind. In terms of wind energy density , Libya is predicted to have higher onshore wind resource than northern countries where wind power is widely spread, such as Germany and Spain. In addition, the wind resource is similar to other countries in the region where wind power is experiencing rapid development, such as Egypt and Jordan. 1 Wind energy density is the average power available per square meter of swept area of a turbine. It is a far more reliable indi- cator than the average annual wind speed, as it takes into account the wind distribution, the temperature, humidity and pressure of the wind. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -6- Figure 1-5: Wind energy density at 100m above ground level - DTU Global Wind Atlas Figure 1-6: Average annual wind speed at 100 m above ground level – DTU Global Wind Atlas 1.2.1 Wind Resource – Local Distribution Along the northern coast, the wind resource is high. Around the cities of Misurata, Sirte, and Tripoli, the wind resource ranges between 400-450 W/m2. The plateau south of Alaluas, and the coastal area to the west and south-east of Misurata show interesting potential. While sea areas seem darker, the wind potential is equal or higher than in the coast. This effect is due to the background sea colour in the map, which makes those areas appear slightly darker. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -7- Figure 1-7: Wind energy density in Libya, North-western coast - DTU Global Wind Atlas In the north-eastern coast, the woodland areas of Jebel Akhdar (al-Jabal al-Akhdar) show reduced 2 wind resource (250-300 W/m ). However, the plateau to the south shows very good wind resource 2 (450-500 W/m ). Figure 1-8: Wind energy density in Libya, North-eastern coast - DTU Global Wind Atlas In the mainland, the most promising areas are the Nafusah Plateau and the Murzuq plateau. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -8- Figure 1-9: Wind energy density in Libya - DTU Global Wind Atlas 1.2.2 Available Ground Measurements in Libya A wind measurement campaign can be carried out for several purposes, such as climate research, wind atlas elaboration, and/or wind farm development. Depending on the case, different standards and methodologies are to be applied to obtain the required data. For the purposes of the LCEP wind data provided has been surveyed taking as a reference the MEASNET guidelines, the gold standard for wind measurement campaigns for wind farm development. When developing a wind farm, the wind measurement campaign and wind resource assessment are the most important aspects since they are the basis to calculate the energy production of the wind farm and the revenues that the wind farm will produce. A proper and state-of-the-art measurement campaign and resource assessment will yield lower uncertainties in the energy yield. A bankable wind resource assessment is one in which high quality verifiable data is available to quan- tify the uncertainty in wind resource at the planned wind project location. The key to this assessment is the data obtained by the wind measurement campaign. The gold standard for wind measurement campaigns are the MEASNET guidelines, based on IEC, ISO, and IEA standards. Full compliance with MEASNET standards is required for a high quality, bankable wind resource assessment. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx -9- The complete list of MEASNET requirements can be found online at: http://www.measnet.com/wp-content/uploads/2016/05/Measnet_SiteAssessment_V2.0.pdf Since it is a 56-page document, and freely available online, it is considered too lengthy to be included in the present document. However, the following requirements are key to justify the analysis of the wind data for the purposes of the LCEP:  The height of the primary wind speed measurement level shall be at least 2/3 of the planned hub height (Section 6.4, third paragraph);  In case of changes of sensors, complete documentation of performed work, changes in equipment and resulting changes of calibration values (Annex A, “Measurement history” bullet point); and  For mast measurements: Unambiguous assignment of the data channels to the sensors (Annex A, “Measurement data” bullet point). Wind data was provided by REAOL for 28 measurement sites. Only 6 sites out of the 28 were provid- ed with a wind measurement report:  Dernah,  Azizyah,  Assaba,  Gotria / Goterria,  Misallatah, and  Tarhuna. For estimating the production at these sites, the data can be regarded as acceptable. The Consultant has interpreted the data files based on previous experiences; the signals have been identified (wind speed, wind direction, temperature, pressure, humidity) but information regarding their height and lo- cation on the mast is missing. However, combined with virtual met-mast data from NASA (MERRA 2 database), the production of wind farms can be modelled with a reasonable level of accuracy (uncer- tainty levels above 20% are considered acceptable for the LCEP purpose). It is important to highlight that the available reports are not bankable wind resource assessment ac- cording to MEASNET guidelines. Therefore, a bankable feasibility study cannot be performed with the current data. Where no measurement report has been provided, no further analysis could be performed with suffi- cient certainty (22 out of 28 sites). The signals in the measurement data files are not by themselves sufficient. In addition, the files themselves do not have information regarding the met mast position neither identification of the mast configuration was possible. It is necessary to clarify the sensors and height of installation, the logger channel to which they are connected and sensors’ model, amongst others, as this cannot be deducted out of the information provided. The data currently available is not suited for utility-scale wind power development involving debt fi- nancing. The available reports are not bankable according to MEASNET guidelines, due to a number of deficiencies (see Table 1-2). Worth highlighting is that the maximum measurement height (40 m) is not compatible with today’s state of the art utility scale wind turbine s (minimum of 80 m hub height). For the development of future wind farms, the Consultant recommends performing new wind meas- urement campaigns compliant with MEASNET guidelines in their latest version, or equivalent stand- ards. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 10 - The maximum height of the analysed data (available) is 40 m, which does not allow identifying if Low Level Jets (LLJs) are common at the sites. A LLJ is a phenomenon starting usually at dusk. When the ground has cooled down, the turbulent, well-mixed, boundary layer comes to rest after the turbulence production by solar irradiation and thermal mixing vanishes. In practice, it causes increased wind speed at high heights at night, and thus increased production for wind turbines. The height to the maximum wind speed in a LLJ is typically 200 m; however, this is greatly dependent on the local conditions. The LLJ region of interest for wind power production ranges from 40 to 260 m. WTGs with an upper tip height below 40 m receive negligible impact from LLJs. Figure 1-10: Wind profile illustration of low level jets - Source: NREL The wind measurement data and reports analysed are summarized in Table 1-2 below. The conclusions are as follows:  In 22 of the 28 measurement sites, the wind resource assessment reports and logs are missing. The raw data cannot be interpreted without these reports hindering further analyses.  For the six sites that have wind resource assessment reports: – For Dernah site (MTorres report # EE20100222) ♦ The uncertainties have not been analysed; ♦ Measurement documentation is severely incomplete; and ♦ Site assessment is incomplete. – For the rest of the sites (ambio reports) Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 11 - ♦ The received reports are severely incomplete, according to the MEASNET guidelines; ♦ Measurement documentation is severely incomplete; ♦ Measurement data is incomplete; ♦ Site assessment is incomplete; and ♦ The logger channel assignment is not defined. – The maximum measurement height of all of the above is 40 m above ground level. This does not allow to identify LLJs, and thus can lead to underestimations of the wind energy yield. None of the wind measurement campaigns can be termed bankable according to the MEASNET guidelines with the current information. Therefore, it is not possible to base a bankable feasibility study on this data. Table 1-2 shows a summary of the wind measurement systems in Libya with the main data and out- comes of data review. Figure 1-11 show the location of those wind masts with suitable wind data for further analyses. Although, as mentioned previously in this section, ground data is not bankable, the data available on those areas features indicates optimum wind resource and proper infrastructure for installation of a wind park. Figure 1-11: Locations with available ground wind data Alternatively, areas close to Brega and Hun could be considered for installation of wind power. Other locations in the south e.g. Sebah, although with still good wind resource will be badly affected by abrasion and curtailment of wind energy due to high temperatures and thus are not recommended for the first years of the LCEP. For the reasons above the sites considered for wind development in the LCEP are:  Aziziya;  Misallatha;  Misurata;  Assaba;  Derna;  Al Maqron; and  Brega. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 12 - Table 1-2: Summary of wind data review Annual av- erage wind Is the report Measure- Max height Area Site Lat (N) Long (E) speed at Report MEASNET ment data Other (m) 2 max height compliant? available? (m/s) 31.26348 20.83294 40 No No Yes Coastal Area Al Maqrun 5 Sensor information provided in a separate email Additional information: P.E.A & Wind Farm Report. Datalogger channel assignation Wind Farm Report 32.710684 22.753885 40 7.96 Yes No Yes does not match the data in measurement file - An interpretation has been made, but we cannot ensure its Coastal Area Dernah accuracy. 32.10320 15.17400 40 No No Yes Coastal Area Misurata / Misrata 2 9 Sensor information is missing – Data cannot be interpreted 16.33507 31.92155 40 No No Yes Coastal Area Sirt 3 Sensor information is missing – Data cannot be interpreted 32.41550 20.55581 40 No No Yes Coastal Area Tolmeita /Tolmetha 6 Sensor information is missing – Data cannot be interpreted Arabic region Azia / Aziziya 32.33106 13.051861 40 7.35 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100% Arabic region Assaba / Asba / Sabha 32.12213 12.87776 40 6.35 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100% Arabic region Goterria / Gtri / Gotria 32.03832 13.07304 40 5.56 Yes No No No data, only final report, no data on channel configuration Arabic region Misalatah 32.611444 13.859514 40 6.68 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100% Arabic region Tarhuna / Tarh 32.43515 13.56144 40 7.14 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100% South East Abugrin - ‫اب وزري ق‬ 25.40762 22.11013 60 No No Yes No data on channel configuration - Logger data cannot be interpreted 100% South East Al Sarir - ‫ال سري ر‬ 27.15984 21.39861 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Lijkhira- ‫اجخرة‬ 29.18981 21.41264 60 No No Yes Sensor information is missing – Data cannot be interpreted Al Tariq al Sahrawi - 30.24108 20.32382 60 No No Yes South East ‫ال صحراوي ال طري ق‬ Sensor information is missing – Data cannot be interpreted South East Al Kafara - ‫ال ك فرة‬ 24.3174 23.17545 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Tazerbo - ‫ت ازرب و‬ 26.1695 21.55348 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Marwa - ‫مراوة‬ 32.26509 21.27329 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Gagboob 29.46731 24.22072 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Ghkra 24.3174 23.17545 60 No No Yes Sensor information is missing – Data cannot be interpreted South East Argeba 26.34456 13.3358 60 No No Yes Sensor information is missing – Data cannot be interpreted South West Bongeam 23.253 15.24479 60 No No Yes Sensor information is missing – Data cannot be interpreted South West Qatron / Gatroon 24.51101 14.34186 60 No No Yes Sensor information is missing – Data cannot be interpreted South West Gath 25.02261 10.10264 60 No No Yes Sensor information is missing – Data cannot be interpreted 15.53089 Hoon 29.07311 60 No No Yes South West 3 Sensor information is missing – Data cannot be interpreted South West Schwerf 29.59368 14.14007 60 No No Yes Sensor information is missing – Data cannot be interpreted 14.26200 Sabha 26.48333 60 No No Yes South West 9 Sensor information is missing – Data cannot be interpreted Tragen / Traghan/ 25.57552 14.30349 60 No No Yes South West Taraghin Sensor information is missing – Data cannot be interpreted South West Abugrin - ‫اب وزري ق‬ 25.40762 22.11013 60 No No Yes Sensor information is missing – Data cannot be interpreted 2 According to the wind resource assessment report Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 13 - It is important to note that Al Maqrun configuration of the anemometers in the tower was provided via email by REAOL during the preparation of the LCEP. Furthermore, Brega site was suggested by REAOL. In general, and to reduce the complexity of the LCEP model the Consultant will, if necessary, select representative areas for wind farms at the sites selected i.e. for sites nearby with similar wind potential according to satellite data one site could be considered representative of the area. Table 1-3 summarizes the locations selected and the corresponding measurement coordinates for the resource analyses to be used for the site selection and the later simulations of the technology configu- rations part of the LCEP. Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 14 - Table 1-3: Summary of pre-selected sites according to solar and wind resource Meteorologi- cal station Area City/town Coordinates Name Coordinates Distance (km) Type Mast height Wind Wind GHI1 GHI DNI1 DNI (Latitude, longitude) (Latitude, longitude) (m) speed Ground data kWh/m2/ Ground da- kWh/m2/ Ground (m/s) y ta y data Tripoli Aziziya 32°19'52"N; 13° 3'7"E Aziziya 32°19'51.82"N; 13° 3'6.70"E 0 WIND 40 7,35 Report/data wo 1986 2028 sensor Tripoli Misal- 32°38'59"N; 13°53'27"E Misal- 32°36'41.20"N; 13°51'34.25"E 0 WIND 40 6,68 Report/data wo 1956 1993 latha latha sensor Tripoli Misurata 32°28'7"N; 14°48'47"E Misurata 32° 6'11.53"N; 15°10'26.43"E 60 WIND 40 Data wo sensor 1925 1850 Tripoli Assaba 32° 7'20"N; 12°52'40"E Assaba 32° 7'19.67"N; 12°52'39.94"E 0 WIND 40 6,35 Report/data wo sensor Tripoli Zliten 32°12'37"N; 14°30'1"E satellite data GHI Satellite Tripoli Jadu 32° 5'55"N; 12° 4'47"E Bir al 32° 21' 3.19" N; 12° 39' 21.39" E 60 GHI/DNI 1987 Data 2023 Data Gahnam Bengazhi Derna 32°42'37"N; 22°45'14"E Derna 32°42'38.46"N; 22°45'13.99"E 0 WIND 40 8 Report/data 1917 1821 Bengazhi Al 31°15'48"N; 20°49'59"E Al 31°15'48.55"N; 20°49'58.58"E 0 WIND 40 Data Maqron Maqron Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E satellite data GHI 2004 Satellite 1999 Bengazhi Shahat 32°48'37"N; 21°44'16"E Shahat 32°45'36.00"N; 21°53'24.00"E 15 GHI Report Sebah Sebah 26°47'20"N; 14°25'16"E Sebah 26°47'19.65"N; 14°25'16.22"E 4 GHI/DNI 60 Data wo sensor 2248 Report 2259 Report Sebah Edri 27°29'19"N; 13°10'50"E Argiba 26°34'50.28"N; 13°34'25.56"E 100 GHI Data Ghad- Ghadamis 30° 5'35"N; 9°36'17"E Ghadamis 30°10'4.80"N; 9°45'21.60"E 17 GHI/DNI 2127 Da- 2162 Data amis ta/Report Brega Brega 30°23'37"N; 18°41'56"E satellite data _WIND Satellite Hun Hun 29° 8'34"N; 15°51'34"E Hun 29° 9'15.69"N; 16° 0'17.60"E 15 GHI 60 Data wo sensor 2157 Report 2212 Ghat Thala 25°24'37"N; 10°21'34"E Ghat 24°57'51.53"N; 10°10'32.72"E 52 GHI 60 Data wo sensor Data Jagboub Jagboub 29°44'28"N; 24°30'0"E satellite data GHI Satellite Jagboub Kufra1 27°38'53"N; 21°42'47"E satellite data GHI Satellite Jagboub Kufra2 26°56'49"N; 22° 9'3"E satellite data GHI Satellite Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx - 15 - Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan Report Annex II – Grid Connection Aspects 12 December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de Table of Contents Page 1. Grid Support Overview 3 1.1.1 PV 3 1.1.2 Wind 4 1.1.3 CSP 5 1.1.4 General Notes on Grid Support with RE 6 2. Grid Connection Alternatives 8 2.1 Transmission System Network Studies 9 2.2 Connection Points for Sites Suggested by Stakeholders 12 2.3 Conclusions on Grid Connection Alternatives 12 List of Tables Table 1-1: Stability criteria according to ENTSO – Levels according to Consultant Table 2-1: Summary of identified connection points – Transmission system network studies Table 2-2: Substations identified for sites suggested by stakeholders List of Figures Figure 2-1: Georeferenced Libyan grid as provided by GECOL Figure 2-2: Potential connection points for RE facilities in Libya acc. to transmission studies Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx Abbreviations CAPEX Capital Expenditures CCGT Combined Cycle Gas Turbine CRS/CR Central Receiver System CSP Concentrating Solar Power DNI Direct Normal Irradiation DSG Direct Steam Generation ENTSO European Network of Transmission System Operators ESS Energy Storage System FLH Full Load Hours GECOL General Electric Company of Libya GHI Global Horizontal Irradiation GI Global Irradiation GT Gas Turbine HFO Heavy Fuel Oil HRSG Heat Recovery Steam Generator HTF Heat Transfer Fluid IDC Interest During Construction IEC International Electro-chemical Commission IGBT Insulated Gate Bipolar Transistor IPP Independent Power Producer IRR Internal Rate of Return ISCC Integrated Solar Combined Cycle ITRPV International Technology Roadmap for Photovoltaic LCEP Least Cost Expansion Plan LCoE Levelized Cost of Electricity LDS Long-Duration Energy Storage LFO Light Fuel Oil LID Light Induced Degradation LLJ Low Level Jet LVRT Low Voltage Ride Through OPEX Operational Expenditures PID Potential Induced Degradation PPA Power Purchase Agreement PSP Private Sector Participation PT Parabolic Trough PV Photovoltaics RE Renewable Energies REAOL Renewable Energy Authority of Libya SCA Solar Collector Arrangement SCGT Simple Cycle Gas Turbine SM Solar Multiple STATCOM Static Compensators SPREL Strategic Plan for Renewable Energies in Libya TES Thermal Energy Storage TMY Typical Meteorological Year TSC Thyristor Switched Capacitors WACC Weighted Average Capital Cost WB World Bank WTG Wind Turbine Generator Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -3- 1. Grid Support Overview This section is an overview of solar and wind alternatives and its grid connection aspects relevant to grid support. Further, this section focuses on probable impact of penetration of renewable sources by different technologies on the Libyan electric grid in terms of system performance, technical challenges and opportunities for achieving higher levels of reliability and efficiency in the grid performance. Note: The content of this section deals with qualitative characteristics of grid support in order to high- light how RE nowadays could provide grid support in a general manner. This assignment, and for ex- tension, this section does not deal with analyses of power networks. Due to its complexity, such anal- yses if required shall be part of a separate assignment or shall be carried out during the implementa- tion of the LCEP. 1.1.1 PV One of the key components of PV systems is the inverter. DC (Direct Current) output from PV system is changed into AC (Alternating Current) by the inverters. The performance of the inverter is especially important for grid connected PV plants since it directly influences whether the PV power plant can meet the requirements of the grid operation. Nowadays, most of the inverters have LVRT capability (Low Voltage Ride Through) and flexible active and reactive power control capabilities. However, since there is no rotating component, PV systems cannot supply inertia support to the power system /grid. As also mentioned by GECOL PV can support voltage control when located at the end of long trans- mission lines. Inverters are smart enough to help solar power plant to get along with the grid. In addition, to convert- ing DC to AC they also enable monitoring, decision making and control functions. Due to this feature, the PV system currently brings more support to existing networks. Further, most larger inverters con- trolling its own output, they provide reactive power support to the grid as and when needed. This in- deed improves grid stability. The basic grid support functions are mentioned as below:  Active Power Curtailment: The adjustment of active power in various response time frames assists in balancing the generation and load, thereby improving power system reliability. When solar pro- duces too much (as established by grid operators), the inverter increases PV voltage to reduce the power output of the array.  Reactive power control: When voltage and current are not in-phase, you get reactive power that moves back and forth in the grid. This power can help grid operators regulate voltage on a timeframe of hours or days. Through SCADA systems, utilities can tell the inverter how much reac- tive power should get into the grid.  Power factor control: Inverters can set the ratio of reactive power to active power, on a cycle to cy- cle of the AC line, which help maintain voltage.  Voltage ride-through: The Inverter can help maintain solar plant operation through periods of lower grid voltage to avoid disconnection, which may cause a chain reaction of other plants disconnecting due to the dip in voltage, known as cascading. This helps keep the grid stable.  Frequency ride-through: The inverter can help keep the solar plant from disconnecting from the grid during time of high or low variations in frequency, determined by regulatory requirements, therefore aiding grid stability.  Ramp-rate controls: The inverter can control the rate at which it transitions between different estab- lished power factor points. This ensures the plant output does not ramp up or down faster than a Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -4- specified limit. Energy storage technology can add or subtract power to or from the PV output to smooth out the high frequency components of the PV power. 1.1.2 Wind There are mainly four types of WTGs commercially in operation. Each type has some unique charac- teristics due to its features in the aspects of grid support.  Type 1 – Fixed speed Induction Generator: This type of WTG operates on fixed speed, thus their output fluctuates as wind speed varies. To alleviate this problem, stall control system is needed. Because induction generators absorb a lot of reactive power when generating active power, type 1 WTG requires reactive power compensators. This type of WTGs has no reactive power control ca- pability. The devices like TSCs (Thyristor switched capacitors), STATCOMs (Static Compensators) are needed in the system to provide reactive power control. There is high risk involved of dynamic voltage collapse with WTG of type 1. Therefore, in the voltage dip scenario, this type of WTG need to disconnect from operation.  Type 2: Induction Generator with Variable Rotor Resistance: This type of WTG allows speed varia- tion of 10%, which improves power quality and reduces mechanical loading of turbine components. This type of WTG equips with induction generator and it requires compensators for reactive power compensation. However, there is no reactive power capability available in this type of generators; therefore TSCs and STATCOM have to be added additionally. Further, it has limited LVRT , thus in case of voltage collapse mitigation measures can be taken by either providing fast increase of rotor resistance during faults or by increasing reactive power compensation devices in the system.  Type 3 Double Fed Induction Generator: This type of WTG combines the advantages of previous two types design with advance power electronics (type 1 and type 2). The rotor of this WTG is con- nected to the grid through a back to back insulated gate bipolar transistor (IGBT) that controls both magnitude and frequency of the rotor current. Further, it provides the advanced concept for varia- ble speed operation. The converter provides decoupled control of active and reactive power, ena- bling flexible voltage control without additional reactive power compensation, as well as fast voltage recovery and voltage ride through. In case of severe faults, crowbar protection may be needed. There is no reactive power control available when crowbar is connected.  Type 4 Generator with fully rated converter/ direct drive: In this type of WTG, the stator of the gen- erator is connected to the grid via full power back to back IGBT power converter, which means all the power output goes to the grid through the converter. The generator may be a synchronous generator with wound rotors or induction generator. The gear box may be drive-train type, half di- rect drive or direct drive (no gearbox). A type 4 WTG is completely decoupled from its grid, thus it can provide even wider range of speed variation as well as reactive power and voltage control ca- pability. In addition, its output can be modulated to zero, thereby limiting the short circuit contribu- tion to the grid. This type of WTG also provides reactive power at zero active power (STATCOM mode). The synchronous generators released their stored kinetic energy into the grid, reducing the initial rate of change of frequency and allowing slower governor actions to catch up and contribute frequency stabilization. Therefore, a performance similar to conventional generators can be achieved with wind power plant by utilizing a controlled inertial response. Early versions of the turbine generators (type 1) consisted of fixed-speed wind turbines with conven- tional induction generators. This type of machines is limited to operation in narrow wind-speed range. In addition, the conventional induction generator (type 2), which is directly connected to the grid, re- quired the reactive power support be provided (locally) to achieve desired voltage level. The highly ef- ficient, variable speed DFIG (Double Fed Induction Generator) (type 3) is designed to extract maxi- mum energy from the wind, and it puts out the electricity at a constant frequency irrespective of speed. Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -5- The generators with fully rated converters (type 4) which have synchronous generators and fully rated converters have a wide range of both real and reactive power for varying wind speeds. A WTG has flickers which will highly impact on the power quality of the system. Further, by looking the Libyan grid stability and reliability aspects, type 1, 2 and 3 WTGs may not be recommended. Type 4 WTG is the most recommended as it will support the behaviour of the Libyan electric grid. However, type 4 still might have a limited number of suppliers mostly for the climatic conditions of Libya and therefore due to market conditions at least type 3 and type 4 are to be considered for procurement and competition purposes. 1.1.3 CSP CSP technologies deliver electricity to the grid by means of a steam turbine and a conventional elec- trical generator. In general, CSP without storage features many grid advantages for the grid as con- ventional thermal power plants such as inertia, however with also many disadvantages including fluc- tuations and no possibility of operation through the night. In particular, the real advantage of CSP plants relies in its thermal storage capability for many hours and in capacities in the order of tens or even hundreds of megawatts. For the purpose of this assignment, only CSP with storage will be fur- ther analysed as it can be considered as the benchmark of solar and wind technologies in what refers to grid support. Utilizing the stored thermal energy to operate a conventional synchronous generator, they can also support power quality and provide ancillary service, including voltage support, frequency response, regulation and spinning reserves, as well as ramping services. When comparing CSP with thermal energy storage to alternative renewable technologies (including CSP without storage), there are several primary categories of additional benefits provided by thermal energy storage as listed below:  Energy – Hourly optimization of energy schedule; – Sub-hourly energy dispatch; and – Ramping reserves.  Ancillary Services (for secondary frequency control) – Regulation; – 10- minute spinning reserves; and – Operating reserves on greater than 10 minute time-frames synchronized generator.  Power quality and other ancillary services – Voltage Control; – Frequency response; and – Black-start.  Capacity – Generic MW shifted to meet evolving system needs; and – Operational attributes.  Integration and curtailment cost compared to solar PV and Wind – Reduced production forecast error and associated reserve requirements; – Reduced curtailment due to greater dispatch flexibility without production losses; and – Ramp mitigation. Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -6- 1.1.4 General Notes on Grid Support with RE Integrating RE in a power system shall, to the extent possible, not pose a conflict with a “robust, reli a- ble and stable” supply of electricity. Grid support of solar and wind technologies will be at this stage only qualitatively evaluated. Low penetration of renewable energies (i.e. low share of RE or single digit 1 percentages) will need to prioritize the following technical requirements :  Protection;  Power quality;  Power reduction during over-frequency;  Communication;  Adjustable reactive power; and  Constraining active power (active power management). 2 Increasing the penetration of RE to higher shares up to 20%, will require additionally :  LVRT including current contribution; and  Simulation models. Following IRENA’s recommendations for these shares the following generators will be recommended:  Synchronous machines;  PV converters;  Wind turbines with full converter (type 4); and  Wind turbines with DFIG (type 3) Depending on the progress and success of the implementation of the LCEP, it is recommended to re- visit the LCEP timely before of 2025 and perform network analyses for the additions of capacity until 2030. Alternatively, to IRENA’s guide and only for illustrative purposes, Table 1-1 shows stability criteria ac- cording to the European Network of Transmission System Operators (ENTSO). With the bars, the Consultant intends to show the level of support of solar and wind technologies to the grid (green posi- tive support, red negative support and white no support). Note that this is only indicative and reliable results can only be obtained with a proper network analysis. 1 Scaling up Variable Renewable Power: The Role of Grid Codes. IRENA 2016 2 Scaling up Variable Renewable Power: The Role of Grid Codes. IRENA 2016 Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -7- Table 1-1: Stability criteria according to ENTSO – Levels according to Consultant frequency regulation Island capability Power Quality Short Circuit Fluctuations Voltage and Black Start Inertia Night Day Technologies PV CSP (no storage) CSP (with storage) Wind (synchron machine) Wind (DG asynchron machine) Sta bi l i ty cri teri a (from ENTSO) - onl y i l l us tra ti ve - fi na l res ul t ca n be obta i ned onl y a fter network ca l cul a ti ons Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -8- 2. Grid Connection Alternatives This assignment focuses on grid connected solar and wind facilities and therefore it is of foremost im- portance to locate these facilities at suitable distances from potential connection points. Typically suit- able connection points are substations on the 66 or 30 kV level and under certain conditions at 220 kV level for the case of Libya. A reasonable proximity to the connection points will not only reduce trans- mission losses but will also maintain CAPEX at predictable levels as transmission lines are capital in- tensive and require complex permits and authorization processes. As indicated in section 1, this assignment, and for extension this section, does not deal with analyses of power networks. Due to its complexity, such analyses if required shall be part of a separate as- signment or shall be carried out during the implementation of the LCEP. It is a main assumption that potential connection points/substations shall be analysed in more detail in further steps of implementa- tion where decisions on either expansions or upgrades of these connection points shall be taken. For the LCEP the Consultant will focus on existing substations by identifying connection points:  Either existing or planned, defined in the transmission system network studies;  Mentioned in existing feasibility studies;  Close to sites with existing ground measurements; and  Suggested by the stakeholders. Figure 2-1 depicts a screenshot of the georeferenced Libyan grid as provided by GECOL to the Con- sultant. Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx -9- 3 Figure 2-1: Georeferenced Libyan grid as provided by GECOL The substations identified have been, to the extent possible, georeferenced, characterized and cross- checked with the latest information provided by GECOL and the existing feasibility studies. The areas proposed for the LCEP were presented and agreed with the stakeholders with no major objections to use the substations on those areas for further analyses. A deeper analysis of the grid connection is a task to be performed within the scope of a specific study for a specific plant. With regard to the location of potential RE power plants, GECOL generally stated that such power plants should be installed preferably more in the south of the overall transmission and distribution grid (e.g. in the southern centres of the two main North-south branches of the grid). Since the main con- ventional power plant fleet is located more in the northern coastal line, GECOL suggestion will help to balance the overall load flow, to avoid negative impact of short circuit issues and overall stabilize with this the system. 2.1 Transmission System Network Studies In an initial step, the Consultant has screened the existing transmission system network studies for po- tential substations near the representative sites defined for the LCEP analysis. Figure 2-2 sets out the location of the identified substations and Table 2-1 summarizes the current status of the following in- formation of each substation:  Name of substation in English language;  Voltage level;  Coordinates;  Available capacity of connection (MW); 3 Libyan networks georeferenced in GoogleEarth (.kmz file with substations), provided by GECOL, 2017 Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx - 10 -  Existing, under construction or planned; and  Year of installation. This information allows the Consultant to determine the areas for installation with better resolution, as well as the size of RE facilities and the distance of interconnection. Figure 2-2: Potential connection points for RE facilities in Libya acc. to transmission studies Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx - 11 - Table 2-1: Summary of identified connection points – Transmission system network studies Connection point - Substation Name Coordinates Check with GECOL Distance TFR Rating Capacity Year Voltage Planned load [MW] Av. geodata (Latitude, longitude) Name (Latitude, longitude) Info [km] [MVA] MW [kV] 2020 2025 2030 MW Gyrian (MISSING) ‫الهيره‬ 32°27'3.87"N; 13° 2'9.07"E ‫ف الهيره‬.‫ ك‬220/66/30/11 ‫محطة تحويل‬ 0 0 El Hira (MISSING) ‫ابوعرقوب‬ 32°25'15.03"N; 13°14'18.85"E ‫ ابوعرقوب‬220/30/11 ‫محطة تحويل‬ 0 0 Alzahara (Azahra) 32°40'45.10"N; 12°52'44.50"E ‫الزهراء‬ 32°40'46.86"N; 12°52'43.32"E ‫ف الزهراء‬.‫ ك‬220 ‫محطة تحويل‬ 40 126 101 1974 220/66/30 126 145 165 -64 Bir Huisa 32°31'26.30"N; 12°40'57.70"E PLANNED? 40 200 160 2015 220/30 26 30 34 126 Bir Alganam 32°21'6.00"N; 32°21'6.00"N ‫بئر الغنم‬ 32°21'3.19"N; 12°39'21.39"E ‫ف بئر الغنم‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 36 126 101 1981 220/30 144 165 188 -87 Mislata 32°35'28.68"N; 14° 4'14.93"E ‫القره بولي‬ 32°42'55.01"N; 13°47'9.22"E ‫ف القره بولي‬.‫ ك‬220/30/11 ‫محطة‬ 20 200 160 2015 220/30 63 73 83 77 Wadi Rabea (Ramil?) 32°31'51.50"N; 13°56'12.71"E PLANNED? 11 200 160 2015 220/30 97 112 127 33 Tarhona 32°23'52.90"N; 13°38'17.20"E ‫ ترهونة‬32°23'50.61"N; 13°38'15.89"E ‫ف ترهونة‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 31 63 50 1980 220/30 146 169 192 -142 Zlitan 32°27'13.31"N; 14°34'55.33"E ‫ حكمون‬32°26'14.80"N; 14°33'28.29"E ‫ف حكمون زليتن‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 21 126 101 1980 220/30 107 123 140 -39 Misurata South 32°14'16.97"N; 14°56'43.25"E ‫ طمينه‬32°14'59.64"N; 15° 7'27.03"E ‫ف طمينة‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 25 126 101 1983 220/30 22 25 28 73 Misurata Switching 32° 8'29.91"N; 15° 7'1.00"E PLANNED? 42 300 240 2015 220/30 116 134 153 87 Misurata Power (Steel 400?) 32°18'16.71"N; 15°11'22.56" ‫ مصراته المزدوجه‬32°19'48.09"N; 15°14'37.70"E ‫ف مصراته المزدوجة‬.‫ ك‬400/220/30 ‫محطة‬ 630 504 1988 220/30 650 650 650 -146 Misurata Power (Steel 400?) 32°18'16.71"N; 15°11'22.56" 32°19'50.65"N; 15°13'54.40"E ‫ف الحديد‬.‫ ك‬220 ‫محطة تحويل‬ 750 E 400/220 Tripoli West 220/30 32°49'24.00"N; 12°58'24.00"E PLANNED? 126 101 1980 220/30 106 123 140 -39 Tripoli West 400/220 32°49'24.00"N; 12°58'24.00"E ‫ غرب طرابلس‬32°49'22.81"N; 12°58'28.44"E ‫ف غرب طرابلس‬.‫ ك‬400/220 ‫محطة تحويل‬ 1400 U 400/220 Homs Power 32°31'25.73"N; 14°20'47.73"E ‫ كعام‬32°29'49.49"N; 14°25'9.10"E ‫ف كعام‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 126 101 1974 220/30 85 98 112 -11 Homs Power 32°31'25.73"N; 14°20'47.73"E ?? 1400 P 400/220 Zawia Power 32°47'15.20"N; 12°40'30.20"E 32°47'15.18"N; 12°40'27.64"E ‫ف الزاوية‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 300 240 2006 400/220 55 62 71 169 Zawia Power 32°47'15.20"N; 12°40'30.20"E 32°47'17.27"N; 12°40'16.71"E ‫ف الزاوية‬.‫ ك‬400/220 ‫محطة تحويل‬ 450 E 400/220 Milita 32°50'46.90"N; 12°15'16.75"E [empty lot?] 32°50'51.28"N; 12°13'44.07"E ‫ف مجمع مليته المقترحة‬.‫ ك‬220 ‫محطة‬ 200 160 2015 220/30 63 73 83 77 Milita 32°50'46.90"N; 12°15'16.75"E ‫ الجميل‬32°52'32.48"N; 12° 4'25.03"E ‫ف الجميل‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 1640 P 400/220 Abu Kamash 32° 1'34.10"N; 11°47'44.70"E ‫ شكشوك‬32° 2'6.12"N; 11°57'52.38"E ‫ف شكشوك‬.‫ ك‬220/66/11 ‫محطة تحويل‬ 126 101 1980 220/30 39 45 51 50 Abu Kamash 32° 1'34.10"N; 11°47'44.70"E ‫ شكشوك‬32° 2'6.12"N; 11°57'52.38"E ‫ف شكشوك‬.‫ ك‬220/66/11 ‫محطة تحويل‬ 820 P 400/220 Bengazhi North Old 32°11'13.70"N; 20° 8'59.10"E ‫شمال بنغازي‬ 32°11'10.45"N; 20° 8'53.15"E ‫ف شمال بنغازي القديمة‬.‫ ك‬220/30/11 ‫محطة‬ 83 66 1976 220/30 117 135 154 -88 Bengazhi North New+power 32°11'57.37"N; 20° 8'6.24"E ‫شمال بنغازي‬ 32°12'2.54"N; 20° 8'2.99"E ‫ف شمال بنغازي‬.‫ ك‬400/220 ‫محطة تحويل‬ 126 101 2005 220/30 115 132 150 -49 Bengazhi North New+power 32°11'57.37"N; 20° 8'6.24"E ‫شمال بنغازي‬ 32°12'6.14"N; 20° 8'8.47"E ‫ف شمال بنغازي‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 820 E 400/220 Bengazhi West (See Gwarsha old - CLOSE) ‫جنوب بنغازي‬ 32° 1'50.33"N; 20° 6'52.54"E ‫ف جنوب بنغازي‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 1400 P 400/220 Gwarsha old 32° 0'0.80"N; 20° 4'23.10"E ‫جنوب بنغازي‬ 32° 1'50.33"N; 20° 6'52.54"E ‫ف جنوب بنغازي‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 315 252 1984 220/66/30 291 295 381 -129 Derna 32°46'23.49"N; 22°34'31.02"E 32°36'17.65"N; 22°46'9.07"E ‫ف الفتائح‬.‫ ك‬66/11/ ‫محطة تحويل‬ 126 101 1976 220/30 97 112 127 -26 Derna Al-Meyna 32°45'32.18"N; 22°39'17.19"E ‫ درنه‬32°46'49.81"N; 22°35'12.16"E ‫ف درنة التوليد‬.‫ ك‬220/30/11 ‫محطة تحويل‬ 300 240 2015 220/30 88 100 114 126 Al Fatiyah (MISSING) PLANNED? 200 160 2015 220/30 49 56 64 96 Tamimi 32°20'0.75"N; 23° 3'19.88"E ‫التميمي‬ 32°26'56.32"N; 23° 3'39.18"E ‫ف التميمي‬.‫ ك‬220/66/11 ‫محطة‬ 15 126 101 1984 220/66 31 36 41 60 Beada North 32°47'9.02"N; 21°45'4.01"E ‫البيضاء‬ 32°46'41.08"N; 21°45'35.91"E ‫ف البيضاء‬.‫ ك‬220/30/11 ‫محطة‬ 13 250 200 2009 220/66 85 98 111 89 Sebha Airport 26°57'47.70"N; 14°26'21.20"E 18 ‫سبها كم‬ 26°53'11.66"N; 14°25'8.97"E ‫ف سبها كم‬.‫ ك‬220/66/11 ‫محطة تحويل‬ 20 126 101 2015 220/66 24 29 33 68 Sebha North 27° 2'42.60"N; 14°26'31.70"E 400 ‫سبها‬ 27° 2'23.98"N; 14°31'48.57"E ‫ف سبها‬.‫ ك‬400/220/66/11 ‫محطة تحويل‬ 30 250 200 2010 220/66 158 163 150 50 Sebha North 27° 2'42.60"N; 14°26'31.70"E ‫سبها الشمالية‬ 27° 2'43.03"N; 14°26'35.38"E ‫ف سبها الشمالية‬.‫ ك‬220 ‫محطة تحويل‬ Sebha North 27° 2'42.60"N; 14°26'31.70"E ‫سبها الغربية‬ 27° 2'28.88"N; 14°23'51.91"E ‫ف سبها الغربية‬.‫ ك‬220 ‫محطة تحويل‬ Ghadamis 30°10'4.80"N; 9°45'21.60"E ‫غدامس‬ 30° 8'57.23"N; 9°29'26.49"E ‫ف غدامس‬.‫ ك‬400/220 ‫محطة تحويل‬ 6 0 440/220/66 21 25 28 -28 Ghadamis 30°10'4.80"N; 9°45'21.60"E 30°10'13.76"N; 10° 0'40.78"E ‫محطة كهرباء‬ Brega 30°26'6.10"N; 19°42'25.30"E ‫اجدابيا‬ 30°55'24.60"N; 20°11'26.54"E ‫ف اجدابيا‬.‫ ك‬400/220 ‫محطة تحويل‬ 53 126 101 1984 220/30 93 106 121 -20 Ras Lanof 30°34'26.15"N; 18°25'6.34"E ‫راس النوف‬ 30°27'48.85"N; 18°32'46.92"E ‫ف راس النوف‬.‫ ك‬400/220/66 ‫محطة‬ 90 126 101 2006 220/66/306 63 73 83 18 Hoon 29° 8'50.18"N; 16° 0'59.66"E ‫هون‬ 29° 7'2.26"N; 15°53'28.96"E ‫ف هون‬.‫ ك‬220/66/11 ‫محطة تحويل‬ 1,5 189 151 1983 400/220/66 111 128 146 5 Thala 25°47'16.76"N; 10°33'18.82"E ‫العوينات‬ 25°47'16.76"N; 10°33'18.82"E ‫ف العوينات‬.‫ ك‬220/66/11 ‫محطة‬ Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx - 12 - 2.2 Connection Points for Sites Suggested by Stakeholders Further to those sites where measurement campaigns have been carried out, GECOL and REAOL suggested other sites for which the connection points (substations) have been preliminarily identified. Table 2-2 shows for the sites suggested by the stakeholders the connection points identified by the Consultant. Table 2-2: Substations identified for sites suggested by stakeholders Substations Area City/town Coordinates SS Name SS Name Coordinates Distance (Latitude, longitude) (arabic) (english) (Latitude, longitude) (km) Tripoli Zliten 32°12'37"N; 14°30'1"E ‫البرج‬ Zliten SS 32°12'38.00"N; 14°34'51.00"E 5 Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E ‫التميمي‬ Tamimi 32°26'56.32"N; 23° 3'39.18"E 3 Brega Brega 30°23'37"N; 18°41'56"E ‫راس النوف‬ Raz Lanof 30°27'48.85"N; 18°32'46.92"E 16 Jagboub Jagboub 29°44'28"N; 24°30'0"E Aljagboub 29°44'45.00"N; 21°17'58.00"E 300 Jagboub Kufra1 27°38'53"N; 21°42'47"E ‫السرير‬ 27°35'52.58"N; 21°36'48.66"E 7 Jagboub Kufra2 26°56'49"N; 22° 9'3"E ‫السرير‬ 26°54'33.47"N; 22° 5'53.83"E 10 ‫الجنوبي‬ 2.3 Conclusions on Grid Connection Alternatives The set of grid connection alternatives so far identified allows the Consultant to overlap the potential sites with the topology of the Libyan power network in order to better define the potential development of RE within the term of analysis of the LCEP i.e. until 2030. Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan Report Annex III –Potential Areas and Sites 12 December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de Table of Contents Page 1. Site restrictions 3 1.1 Environmental Restrictions 3 1.2 Adverse Climatic Conditions 3 1.3 Accessibility 4 1.4 Allocated Areas for Oil Field Exploitation or Exploration 4 1.5 Security and Integrity of Facilities 4 2. Environmental Aspects in Libya 5 3. Identification of Potential Areas and Sites 8 3.1 Areas for the LCEP 8 3.1.1 Tripoli Area 9 3.1.2 Bengazhi Area 10 3.1.3 Sebah Area 11 3.1.4 Ghadamis, Brega and Hun Areas 12 3.1.5 Thala and Jagboub Areas 14 3.2 Final Representative Sites for the LCEP 16 List of Tables Table 1-1: Some of the national parks and nature reserves in Libya Table 3-1: Final set of sites and technology configurations for the LCEP List of Figures Figure 3-1: Preselected areas for the LCEP Figure 3-2: Conventions used in the maps Figure 3-3: Tripoli area (Google Earth) Figure 3-4: Bengazhi area (Google Earth) Figure 3-5: Sebah area (Google Earth) Figure 3-6: Ghadamis area (Google Earth) Figure 3-7: Brega area (Google Earth) Figure 3-8: Hun area (Google Earth) Figure 3-9: Thala area (Google Earth) Figure 3-10: Jagboub area (Google Earth) Figure 3-11: Location of selected RE plants for LCEP Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx Abbreviations CAPEX Capital Expenditures CCGT Combined Cycle Gas Turbine CRS/CR Central Receiver System CSP Concentrating Solar Power DNI Direct Normal Irradiation DSG Direct Steam Generation ENTSO European Network of Transmission System Operators ESS Energy Storage System FLH Full Load Hours GECOL General Electric Company of Libya GHI Global Horizontal Irradiation GI Global Irradiation GT Gas Turbine HFO Heavy Fuel Oil HRSG Heat Recovery Steam Generator HTF Heat Transfer Fluid IDC Interest During Construction IEC International Electro-chemical Commission IGBT Insulated Gate Bipolar Transistor IPP Independent Power Producer IRR Internal Rate of Return ISCC Integrated Solar Combined Cycle ITRPV International Technology Roadmap for Photovoltaic LCEP Least Cost Expansion Plan LCoE Levelized Cost of Electricity LDS Long-Duration Energy Storage LFO Light Fuel Oil LID Light Induced Degradation LLJ Low Level Jet LVRT Low Voltage Ride Through OPEX Operational Expenditures PID Potential Induced Degradation PPA Power Purchase Agreement PSP Private Sector Participation PT Parabolic Trough PV Photovoltaics RE Renewable Energies REAOL Renewable Energy Authority of Libya SCA Solar Collector Arrangement SCGT Simple Cycle Gas Turbine SM Solar Multiple STATCOM Static Compensators SPREL Strategic Plan for Renewable Energies in Libya TES Thermal Energy Storage TMY Typical Meteorological Year TSC Thyristor Switched Capacitors WACC Weighted Average Capital Cost WB World Bank WTG Wind Turbine Generator Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -3- 1. Site restrictions The overview on site restrictions in Libya will enable the Consultant to identify those areas which are restricted to installation of RE generation facilities. Based on the information collected the Consultant will focus on environmental restrictions, exclusion areas for oil and gas exploration / exploitation, re- stricted accessibility for construction, adverse climatic conditions and security restrictions, as de- scribed below. 1.1 Environmental Restrictions National parks and nature reserves can be considered as restricted areas due to environmental and 1 conservation reasons. Table 1-1 lists the national parks and nature reserves in Libya . These areas will be excluded for a selection of potential sites for RE implementation. Table 1-1: Some of the national parks and nature reserves in Libya Protected area Date of creation Total area (Ha) Status El Kouf 1978 100,000 National Park Alhesha 1984 160,000 Nature reserve Algharabolli 1992 8,000 National Park Abughylan 1992 4,000 National Park Bir Ayad 1992 12,000 Nature reserve Surman 1992 4,000 National Park El Naggaza 1993 4,000 National Park Sabrata 1995 500 National Park Msalata 1998 1,800 Nature reserve Nalout 1998 200 Nature reserve Zulton 1998 1,000 Nature reserve 1.2 Adverse Climatic Conditions Adverse climatic conditions such extreme high temperatures and sand storms will affect negatively the implementation of RE. Although irradiance might be higher in areas with higher temperatures, some- times it is not worth the trade off as technologies might be affected by high temperatures and dust with the subsequent curtailment of electricity production. As an example normal WTGs usually will be stopped when temperatures exceed some 45°C. The highest values of DNI irradiance can be found for the Tibesti Massif in the South. However, this region is very hard accessible and an almost total empty desert countryside, thus no option for solar energy. 1 Bouras, Essam M. "National parks and reserves" (PDF). Head, of protected area & biodiversity section, Nature conservation Dept, Environment General Authority, Convention on Biological Diversity. Retrieved 26 March 2013 Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -4- The south area, the Sahara desert, is also well known for their adverse climatic conditions and little settlements and grid connection possibilities exist, thus this area will not be the focus for potential im- plementation of RE. 1.3 Accessibility Areas not accessible for transportation of large equipment will not be considered for further analyses. Although this is more relevant for CSP and WTGs the Consultant will initially exclude those areas for further analyses for all technologies and focus on areas with suitable access. 1.4 Allocated Areas for Oil Field Exploitation or Exploration The Consultant assumes that oil field areas cannot be considered for RE implementation. Further, the Consultant tried to the extent possible to identify the boundaries of those areas as well as other areas allocated for oil and gas exploration. 1.5 Security and Integrity of Facilities Due to the ongoing conflict it is necessary to identify together with other stakeholders the areas and technologies which are preferred for deployment of RE during the implementation of the LCEP. Amongst others, issues related to safe access to construction sites and sabotage/destruction of elec- tricity generation facilities were discussed with the stakeholders. It is important to highlight that WTGs and solar towers are an easier infrastructure target for sabotage or destruction if this is the case. In addition, CSP due to its nature of one single generator pose more risk of shortfall if damaged than wind and PV which are inherently scalable. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -5- 2. Environmental Aspects in Libya The following laws form the regulatory framework for environmental impacts assessment in Libya, with focus on renewable energy projects.  The Law No. 15 of 2003 on protection and improvement of the environment is the main EIA relat- 2 ed legislative framework in Libya. The law has 12 chapters and 79 articles. The law stipulates re- sponsibilities of the public authorities and the projects proponents towards preserving the environ- ment in the following fields: – General Provision (Articles 1 – 9); – Air Pollution (Articles 10 – 17); – Protection of Sea and Marine wealth (Articles 18 – 38); – Protection of Water Sources (Articles 39 – 47); – Protection of Foodstuffs (Articles 48 – 50); – Environmental Hygiene (Article 51); – Protection from Common Animal Diseases (Article 52); – Protection of Soil and Plants (Article 53 – 55); – Protection of Wildlife (Article 56 – 57); – Biological Safety (Article 58 – 63); – Penalties (Articles 64 – 76); and, – Final Provisions (Articles 77 – 79).  National Oil Corporation's Environmental Impact Assessment Guidelines The National Oil Corporation's Environmental Protection Department's "Environmental Impact As- sessment Guidelines for Seismic Operations" was published in 2006 and constitute the guidelines for conducting environmental impact assessments in Libya. The guide defines the following steps as be- ing required: – Scoping: defining the geographical area to be surveyed, ecosystems, land-use and an indica- tion of the area likely to be affected; – Assessment: identification of potential impacts, anticipation of their scale, duration and severity followed by recommendation of mitigation measures presented within an Environmental Man- agement Plan; – Key stakeholders consultation: usually discussions with the NOC and department of antiquities; and, – Follow up: ensuring that mitigation measures are being implemented, usually through inde- pendent audits and monitoring. On the other hand, The National Oil Corporation's has also set HSE guidelines. The National Oil Cor- 3 poration acts as ministry, regulatory agency, and state-owned company .  Law No. 426 establishing the Renewable Energy Authority of Libya 4 2 Law 15 (1371) ; 2003 on protection and improvement of environment 3 http://www.resourcegovernance.org/our-work/country/libya 4 http://www.iea.org/policiesandmeasures/pams/libya/name-24772-en.php Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -6- The Libyan government created the Renewable Energy Authority of Libya (REAOL) in 2007. The main goal of the REAOL is to implement proper policies so as to meet the governmental target of a 10% share of the total energy mix coming from renewable energy sources by 2020. The REAOL imple- ments renewable energies projects, encourages and supports related industries, proposes supporting legislation and regulations and evaluates Libyan renewable energy potentials to identify priority areas. REAOL also has the mandate to assess in developing regulatory and industry infrastructure, and as- sess and conducting renewables resources mapping.  Other relevant laws are – Law No (5) of 1969 on the organization and planning of towns and villages amended by law No. (3) of 2002; – Law No (38/39) of 1975, concerning municipalities organizing actions, defining in details con- cerned with environmental protection; – Law on the Protection of Agricultural Lands (No. 33 of 1970); – Law on Range and Forest Protection (No. 5 of 1982); – Decision no (81) for 1976: Model regulation to Regulate the Water and Drainage Utility at the Municipalities (28 April 1976); – Decision no (94) for 1976: Model Regulation Related to Public Cleanliness (16 May 1976); – Decision no (142) for 1976: Rules for Disposal of Waste Materials at the Municipalities (19 May 1976); – Law on Water Use (Law No. 3 of 1982); – Law on Protecting Animals and Trees (No. 15 of 1989); – Health Law No. 106 (1973) – Details aspects of environmental protection including water pollu- tion and sampling; – Labour Law (No. 58 of 1970); – General Peoples Council Decision No. 8 of 1974 – Protection and Security of Employees; and – Law on Industrial Security and Labour Safety (No. 93 of 1976).  International conventions signed by Libya – Convention on Preservation of Fauna and Flora in their Natural State (London , 1933); – African Convention on the Conservation of Nature and Natural Resources (Algeria , 1968 ); – Convention on Wetlands (Ramsar, 1971); – World Heritage Convention (Paris, 1972); – Convention on International Trade in Endangered Species of Fauna and Flora (CITES Wash- ington, 1973); – Convention for the Protection of the Mediterranean Sea against Pollution (Barcelona, 1976); – Convention on the Conservation of Migratory Species of Wild Animals (Bonn, 1979); – United Nations Convention on the Law of the Sea (UNCLOS) (Montegoby, 1982); – The Basel Convention on the Transboundary Movement of Hazardous Wastes and their Dis- posal (Basel, 1989); – Bamako Convention on the Ban of the Import Into Africa and the Control of Transboundary Movement and Management of Hazardous Wastes Within Africa (Mali,1991); Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -7- – Convention on Biological Diversity (Rio, 1992); – 16th November 1994. Libya has signed but not yet ratified the convention; – Cartagena Protocol on Biosafety to the convention on biological diversity (Montreal , 2000); – UN Framework Convention on Climate Change, Climate Change-Kyoto Protocol; – United Nations Paris Agreement on climate change (not yet ratified); – UN Convention on Combating Desertification; and – Vienna Convention for the protection of the Ozone Layer.  Final notes on environmental aspects Since, to the Consultant’s understanding and information received, Libya has no operational "large scale renewable energy projects" it is assumed that experience in dealing with environmental issues shall be learnt based on the experience of oil projects which usually have a strong impact on the envi- ronment. From a preliminary appraisal the Libyan environmental regulations are less restrictive than in the Eu- ropean Union and thus for preliminary assessments as this ongoing technology assessment, critical environmental restrictions will be identified in accordance with international environmental standards as such in the European Union. The more relevant issues affecting CSP solar towers and WTGs would be issues related to birds. Environmental impacts shall always be ultimately dealt with for specific projects. Environmental as- pects will be closer evaluated for the site selection and feasibility of the pilot PSP project in stage III of this assignment. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -8- 3. Identification of Potential Areas and Sites For the purposes of the LCEP the Consultant has so far performed a desktop appraisal of the solar re- source and potential connection points as they are the two most important aspects. Further to these aspects, the Consultant has also preliminarily performed a desktop appraisal of:  Land required by different technology configurations;  Environmental restrictions;  Topography;  Proximity to demand centres or areas with important demand growth;  Water availability; and  Access and transportation infrastructure for especial equipment including roads and railways. The objective is to screen the country for the most convenient areas for wind and/or solar implementa- tion within the term of the LCEP and according to the information available. Thus these aspects were not analysed in detail but only dealt with to the extent that allows the Consultant to identify whether major constraints exist leading to exclude an area or a technology configuration from the LCEP pro- cess. A detailed analysis can only be performed for specific projects. 3.1 Areas for the LCEP Based on the analyses performed in Annex II and Annex III the Consultant has identified main areas for installation of RE facilities as shown in Figure 3-3. This section presents an overview of these are- as, as well as other assumptions made in order to evaluate and rank them for preparation of the LCEP. Figure 3-1: Preselected areas for the LCEP Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx -9- The following assumptions were made by the Consultant in order to define the areas proposed for the LCEP:  Areas considered for the LCEP shall be large enough to reduce issues related to exclusion of are- as due to environmental aspects (e.g. natural reserves) or land use (e.g. areas reserved for oil ac- tivities);  Water availability will not be considered a major issue since CSP plants will be equipped with dry cooling systems;  GECOL recommendation that RE facilities may be installed preferably more in the south of the overall transmission and distribution grid (e.g. in the southern centres of the two main North-south branches of the grid); and  A major need of present and future demand is expected close to Tripoli. For the purposes of the LCEP the Consultant has selected areas for further analyses and ranking i.e. Tripoli, Bengazhi, Sebah, Ghadamis, Brega, Hun; Thala and Jagboub. An overview of these areas is presented in the sections below. Figure 3-2 sets out the conventions used throughout this section in order to easily identify objects herein. Wind Farm PV Plants PV/CSP Plants Wind mast Solar met station Substation Generator Area for RE 400 kV 220 kV 132 kV 66 kV Figure 3-2: Conventions used in the maps 3.1.1 Tripoli Area Although no feasibility study for RE has been performed within this area, the Tripoli area is the major consumer area in Libya also characterized for a good quantity of potential connection points and good infrastructure for transport due to the proximity to the north coast. In terms of resource the area offers:  Spots with very good wind resource and wind ground measurements at Aziziya, Assaba, Misalatah, Misurata, Gotteria and Tarhona. Although these measurements are not bankable (see Annex II) they may help reduce the uncertainty for energy yield estimations; and  Reduced solar irradiation in comparison with other areas in Libya with solar ground measurements of GHI and DNI at Bir Al-Gahnam. Identified potential sites for:  Wind are: Assaba, Aziziya, Misalata and Misurata; and  Solar are: Jadu for PV and CSP and Zliten only for PV. Security is not a high concern in this area according to the Consultant’s information. A preliminary snap shot of the Tripoli area is shown in Figure 3-3. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 10 - Figure 3-3: Tripoli area (Google Earth) 3.1.2 Bengazhi Area The Bengazhi area is located in the north-west part of the country in the proximities of the city of Ben- gazhi. Different to the Tripoli area, this area includes sites some hundred kilometres away from Ben- gazhi, the main consumption center, to the west such as Tamimi, Dernah, Al Maqron and Shahat. Although solar resource in this area is not the highest in Libya it is still very good resource for both PV and CSP deployments. Wind resource is very attractive in this area, chiefly in the plateau some kilo- metres to the south of the coastal line. Feasibility studies have been performed already in this area for wind, PV and CSP being the Dernah wind park development the most advanced of them all achieving delivery of components of the WTGs to the area. The Dernah wind project was put on hold due to security reasons in the area and accord- ing to recent information, its location is being modified. Although Dernah is still undergoing security is- sues these could be transitory and thus this situation will not negatively affect the location for the LCEP. It is important to clarify the status of interconnection between east and west of Libya since according to information received the transmission line could be disconnected due to serious damages of infra- structure near Bengazhi. This area is also a main demand centre of the country although considerably less demand is expected there in comparison to Tripoli area. Figure 3-4 shows a snapshot of the Bengazhi area. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 11 - Figure 3-4: Bengazhi area (Google Earth) 3.1.3 Sebah Area The Sebah area is located approximately 650 km south of Tripoli and encompasses the area nearby Sebah city, capital of the Sebah district. The area offers a very good solar resource and good wind re- source, alongside with good transport infrastructure and security conditions. Feasibility studies for both a PV and a CSP plants have been already performed in this area. GHI measurements have been tak- en in this area at Sebah and Argiba, unfortunately the data of the former location are missing. The site at Edri has been recommended by REAOL and GECOL since the area is available and al- ready secured by the Libyan government for solar power developments. Wanzreck substation has been confirmed by GECOL for connection of solar plants. Another attractive aspect of this area is the vicinity to an important consumption centre of the country and therefore the Consultant considers it as an integral area for the LCEP. Figure 3-5 shows a snapshot of the Sebah area. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 12 - Figure 3-5: Sebah area (Google Earth) 3.1.4 Ghadamis, Brega and Hun Areas Ghadamis. Brega and Hun areas offer good wind and solar resources together with sufficient potential for connecting RE facilities to the Libyan grid. Although not as important as the Tripoli, Bengazhi and Sebha areas the Consultant recommends the implementation of RE in these areas as part of the LCEP as they will help deploying solar and wind facilities close to remote consume centres. RE pro- jects in these areas will support the stability of the network and reduce transmission losses while ben- efiting from the infrastructure associated to the nearby settlements. Figure 3-6, Figure 3-7 and Figure 3-8 show snapshots of the Ghadamis, Brega and Hun areas respec- tively for reference. Ghadamis and Hun areas have solar measurement systems for GHI with available data. There is also available DNI data at Ghadamis. Although there are no measurements in Brega the Consultant recommends this area for wind power facilities due to the high wind resource and infrastructure in the area. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 13 - Figure 3-6: Ghadamis area (Google Earth) Figure 3-7: Brega area (Google Earth) Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 14 - Figure 3-8: Hun area (Google Earth) 3.1.5 Thala and Jagboub Areas The Thala and Jagboub areas offer a good solar resource together with sufficient potential for con- necting RE facilities to the Libyan grid. Different to the other areas these areas have been suggested by GECOL as they are of essential importance for electricity supply as they are in very remote areas. PV plants will be considered in these areas for the LCEP term since restrictions in accessibility and harsh climatic conditions will make CSP and wind developments difficult. Such issues are to be ad- dressed via a feasibility study for a concrete development. For the Jagboub area, three sites have been considered for simulation of the PV plants i.e. Jagboub, Kufra1 and Kufra2. There is no ground data available for the Jagboub area. The intention of these sites is to analyse how they will be incorporated in the LCEP mix. The Thala area has GHI ground measurement at Ghat site and a substation for connection of solar power at the Thala substation. Figure 3-9 and Figure 3-10 show snapshots of the Thala and Jagboub areas for reference. Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 15 - Figure 3-9: Thala area (Google Earth) Figure 3-10: Jagboub area (Google Earth) Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 16 - 3.2 Final Representative Sites for the LCEP The process and criteria applied so far allowed the Consultant to identify a set of sites and technology configuration representative for Libya which will be the base to perform the simulations and prepare the economic indicators for optimization of the LCEP mix of RE. The set of representative sites and technology configurations, including substations, met stations and short-term restrictions is shown in Table 3-1. Figure 3-11 shows the final proposed RE plants for the LCEP. It is also important to note that distances to substations were roughly estimated in order to add CAPEX for connection. Whereas some sites are suitable for the PV, CSP and wind others are pro- posed for only one or two technologies. Larger areas were checked for CSP due to the storage capa- bility and hence the larger solar field. Figure 3-11: Location of selected RE plants for LCEP Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 17 - Table 3-1: Final set of sites and technology configurations for the LCEP Capacity [MW] Meteorological station Substations Voltage Technology Configurations Area City/town Coordinates Min. Max. Name Coordinates Distance SS Name SS Name Coordinates Distance [kV] PV CSP WIND BATTERY (Latitude, longitude) (Latitude, longitude) (km) (arabic) (english) (Latitude, longitude) (km) Tripoli Aziziya 32°19'52"N; 13° 3'7"E 200 Aziziya 32°19'51.82"N; 13° 3'6.70"E 0 ‫ الهيره‬El Hira 32°27'3.87"N; 13° 2'9.07"E 13 220/66/30/11 WIND1;WIND2 Tripoli Misallatha 32°38'59"N; 13°53'27"E 400 Misallatha 32°36'41.20"N; 13°51'34.25"E 0 ‫القره بولي‬ 32°42'55.01"N; 13°47'9.22"E 12 220/30/11 WIND1;WIND2 Tripoli Misurata 32°28'7"N; 14°48'47"E 200 Misurata 32° 6'11.53"N; 15°10'26.43"E 60 ‫حكمون‬ 32°26'14.80"N; 14°33'28.29"E 11 220/30/11 WIND1;WIND2 Tripoli Assaba 32° 7'20"N; 12°52'40"E 50 200 Assaba 32° 7'19.67"N; 12°52'39.94"E 0 ‫الرابطه‬ 32°13'7.61"N; 12°53'54.82"E 10 220/30/11 WIND1;WIND2 Tripoli Zliten 32°12'37"N; 14°30'1"E 50 200 satellite data ‫ البرج‬Zliten SS 32°12'38.00"N; 14°34'51.00"E 5 30 PV1; PV2;PV3;PV4 Tripoli Jadu 32° 5'55"N; 12° 4'47"E 50 200 Bir al Gahnam 32° 21' 3.19" N; 12° 39' 21.39" E 60 ‫ شكشوك‬Shakshuk 32° 2'6.12"N; 11°57'52.38"E 13 220/66/11 PV1; PV2;PV3;PV4 CSP1;CSP2;CSP3;CSP4 Bengazhi Derna 32°42'37"N; 22°45'14"E 100 Derna 32°42'38.46"N; 22°45'13.99"E 0 ‫محطة تحويل‬ 32°36'17.65"N; 22°46'9.07"E 12 66/11 WIND1;WIND2 Bengazhi Al Maqron 31°15'48"N; 20°49'59"E 50 200 Al Maqron 31°15'48.55"N; 20°49'58.58"E 0 ‫اجدابيا‬ 31°27'2.50"N; 20° 9'30.90"E 64 400/220 WIND1;WIND2 Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E 100 100 satellite data ‫ التميمي‬Tamimi 32°26'56.32"N; 23° 3'39.18"E 3 220/66 CSP1;CSP2 BTT1 Bengazhi Shahat 32°48'37"N; 21°44'16"E 50 Shahat 32°45'36.00"N; 21°53'24.00"E 15 ‫ البيضاء‬Beada 32°46'41.08"N; 21°45'35.91"E 4 220/66 PV1; PV2;PV3;PV4 Sebah Sebah 26°47'20"N; 14°25'16"E 100 50 Sebah 26°47'19.65"N; 14°25'16.22"E 4 18 ‫ سبها كم‬Sebha 26°53'11.66"N; 14°25'8.97"E 13 220/66 PV1; PV2;PV3;PV5 CSP1;CSP2 Sebah Edri 27°29'19"N; 13°10'50"E 50 100 Argiba 26°34'50.28"N; 13°34'25.56"E 100 Wanzreck 27°29'20.60"N; 13°10'47.78"E 0.5 66/11 PV1; PV2;PV3;PV4 Ghadamis Ghadamis 30° 5'35"N; 9°36'17"E 50 50 Ghadamis 30°10'4.80"N; 9°45'21.60"E 17 ‫ غدامس‬Ghadamis 30° 8'57.23"N; 9°29'26.49"E 13 440/220 PV1; PV2;PV3;PV4 Brega Brega 30°23'37"N; 18°41'56"E 100 satellite data ‫ راس النوف‬Raz Lanof 30°27'48.85"N; 18°32'46.92"E 16 220/66/306 PV1; PV2;PV3;PV4 CSP1;CSP2 Hun Hun 29° 8'34"N; 15°51'34"E 50 100 Hun 29° 9'15.69"N; 16° 0'17.60"E 15 ‫ هون‬Hoon 29° 7'2.26"N; 15°53'28.96"E 4 220/66/11 PV1; PV2;PV3;PV4 CSP1;CSP2 Ghat Thala 25°24'37"N; 10°21'34"E 50 200 Ghat 24°57'51.53"N; 10°10'32.72"E 52 Thala 25°24'29.22"N; 10°21'25.88"E 0.5 400/220/66 PV1; PV2;PV3;PV4 Jagboub Jagboub 29°44'28"N; 24°30'0"E 50 100 satellite data Aljagboub 29°44'45.00"N; 21°17'58.00"E 300 66 PV1; PV2;PV3;PV4 Jagboub Kufra1 27°38'53"N; 21°42'47"E 50 100 satellite data ‫السرير‬ 27°35'52.58"N; 21°36'48.66"E 7 220/66/11 PV1; PV2;PV3;PV4 Jagboub Kufra2 26°56'49"N; 22° 9'3"E 50 100 satellite data ‫السرير الجنوبي‬ 26°54'33.47"N; 22° 5'53.83"E 10 220 PV1; PV2;PV3;PV4 750 2750 Technology configurations PV1 - 50 MWac; Fix CSP1 - 100 MW gross PTC with WIND1 - 50 MW wind park; 2 BTT1 - Li-IonBattery storage of mounted; p-Si modules; thermal oil as HTF; Air Cooled MW turbines, 90 m hub height, 10 MW and 7 hours central inverter Condenser; Molten salt two 90 m diameter tanks of 7 FLH and SM 3 PV2 - 100 MWac; Fix CSP2 - 100 MW CRS with WIND2 - 100 MW wind park; 3.5 mounted; p-Si modules; molten salt as HTF; Air Cooled MW turbines; 110/120 m hub central inverter Condenser; Molten salt two height; approx. 120 m diameter tanks of 10 FLH and SM 3 PV3 - 50 MWac; 1-axis CSP3 - 100 MW PTC with tracked; p-Si modules; thermal oil as HTF; Air Cooled central inverter Condenser; Molten salt two tanks of similar TES capacity of 13 FLH and SM of 4 PV4 - 100 MWac; 1-axis CSP4 - 100 MW CRS with tracked; p-Si modules; molten salt as HTF; Air Cooled central inverter Condenser; Molten salt two tanks of 15 FLH and SM of 4 Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx - 18 - Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan Report Annex IV – Information Collected 12th December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de -1- Table of Contents Page 1. Existing Studies and Information Collected 2 -2- 1. Existing Studies and Information Collected In order to identify these connection points and determine the inputs for the LCEP, GECOL and REAOL have provided the Consultant with the following information:  Consultancy for updating the transmission network expansion studies 2010 - 2030, 2020 - 2025 - 2030 Power System Studies Final Report, October 2010;  Feasibility Study Hun - 14MW PV Plant, REAoL & GIZ, Dr. Christian Bornhauser, Jan 2014;  Feasibility Study Sabha 40 MW PV, REAoL & GIZ, August 2013 (PRESENTATION);  Project Information Memorandum for a 5 and 10 MW PV Plants, EMPower Program Phase II, Lib- ya, June2010;  Different sets of solar and wind ground measurement data;  Wind resource analysis, Tender Dernah wind farm, mTorres, Wind energy division, October 2010;  Preliminary Environmental Assessment, Wind farm, City of Derna, ELARD for REAoL, Feb. 2014;  Preliminary Environmental Assessment, Solar PV Plant in the City of Hun, ELARD for REAoL, Feb. 2014;  Analysis of Wind Energy Conversion Systems in Two Selected Sites in Libya Using Levelized Cost of Electricity (LCOE), Paper of the University of Tripoli, 2016;  Renewable Energy and Energy Efficiency in Libya - Situation - Challenges and Prospects, REAoL, January 2015 (PRESENTATION);  Feasibility Study for a Solar Thermal Power Plant in Libya, 100 MW Booster Heater, Abengoa So- lar, October 2009 (CONFIDENTIAL);  Project Information Memorandum for a 50 MW CSP Plant, EMPower Program Phase II, Libya, June2010;  Google Earth georeferenced grid data including the complete network, generators and substations (My Places on google2017.kmz);  “‫ اإلن تاج مخطط‬5-3-2017.xlsx” provided by GECOL on 27 March 2017; th  MENA CSP KIP, in-depth technical assistance in Jordan (ITA Inception note MA 050317.docx);  PWC, Rapid assessment of the sector performance, World Bank, April 2017;  List and data of substations in the Libyan grid (partial);  Libyan networks georeferenced in GoogleEarth (.kmz file with substations);  PWC, Simplified gas consumption estimate, World Bank, May 2017; and  Daily generation reports of 2016, GECOL. Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan (LCEP) Annex V – Projected Performance of Conventional Plants 12th December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de -2- Table of Contents Page 1. TASK A’s Technical Availability and Thermal Efficiency of Conventional Power Plants 3 -3- 1. TASK A’s Technical Availability and Ther- mal Efficiency of Conventional Power Plants The following tables summarize the availability and thermal efficiency for worst and best case scenari- os used by TASK A for the estimation of fuel consumption. -4- WORST case Technical availability 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 8 7 10 11 14 16 15 16 17 16 16 15 15 15 15 Existing Various Small / rented 0% 4% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% Steam Khoms 91% 80% 80% 80% 80% 80% 0% 0% 0% 0% 0% 0% 0% 0% 0% Derna 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Tobruk 32% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Misurata Steel 0% 12% 71% 71% 71% 71% 71% 71% 71% 0% 0% 0% 0% 0% 0% Gulf 44% 0% 43% 43% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Tripoli West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Benghazi North 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Gas Tripoli South 90% 80% 82% 85% 85% 85% 85% 85% 85% 85% 88% 88% 88% 88% 88% Zwetina 39% 33% 33% 74% 79% 79% 85% 85% 85% 85% 85% 85% 85% 85% 85% Khoms 1 93% 82% 82% 87% 87% 87% 87% 87% 87% 87% 87% 0% 0% 0% 0% Western Mountain 89% 72% 72% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% Sarir 38% 22% 22% 22% 22% 53% 53% 53% 80% 80% 80% 80% 80% 80% 80% Khoms 2 (Fast Track) 0% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% CC Zawia 80% 68% 68% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Benghazi North 1 30% 38% 54% 59% 59% 59% 74% 88% 88% 88% 88% 88% 88% 88% 88% Misurata 92% 45% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Benghazi North 2 81% 69% 71% 85% 85% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Under contr. Steam Gulf 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% / contracted Tripoli West 0% 0% 0% 0% 44% 58% 66% 96% 96% 96% 96% 96% 96% 96% 96% Tripoli East 0% 0% 0% 0% 0% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88% Gas Ubari 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% Misurata 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88% Tobruk 0% 0% 0% 0% 66% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Proposed Steam Tripoli East 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Tobruk 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Derna 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Benghazi West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Gas Sabha 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Tripoli South 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% CC Misurata 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Mellitah 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Zweitina 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Tobruk 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Aboukammash 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% BEST case Technical availability 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 8 7 10 17 21 20 20 24 25 26 28 27 29 29 25 Existing Various Small / rented 0% 4% 53% 81% 91% 91% 91% 91% 91% 85% 85% 85% 85% 85% 85% Steam Khoms 91% 80% 80% 85% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0% Derna 1% 0% 0% 50% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0% Tobruk 32% 0% 0% 50% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0% Misurata Steel 0% 12% 24% 90% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0% Gulf 44% 0% 43% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Tripoli West 0% 0% 0% 100% 100% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Benghazi North 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Gas Tripoli South 90% 80% 85% 85% 85% 85% 85% 85% 85% 85% 88% 88% 88% 88% 88% Zwetina 39% 33% 33% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% Khoms 1 93% 82% 87% 87% 87% 87% 87% 87% 87% 87% 87% 0% 0% 0% 0% Western Mountain 89% 72% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% Sarir 38% 22% 44% 53% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% Khoms 2 (Fast Track) 0% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% CC Zawia 80% 68% 79% 79% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Benghazi North 1 30% 38% 74% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Misurata 92% 45% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Benghazi North 2 81% 69% 85% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Under contr. Steam Gulf 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% / contracted Tripoli West 0% 0% 0% 88% 88% 92% 87% 96% 96% 96% 96% 96% 96% 96% 96% Tripoli East 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88% Gas Ubari 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% Misurata 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88% Tobruk 0% 0% 0% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% Proposed Steam Tripoli East 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% Tobruk 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% Derna 2 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% Benghazi West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% Gas Sabha 0% 0% 0% 0% 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80% Tripoli South 2 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88% 88% 88% CC Misurata 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88% 88% Mellitah 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% Zweitina 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88% Tobruk 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% Aboukammash 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% -5- WORST case Thermal effciency - gas production 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 31% 30% 31% 30% 30% 30% 30% 29% 29% 29% 29% 29% 29% 29% 29% Existing Various Small / rented 10% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% Steam Khoms 20% 21% 21% 21% 21% 21% Derna Tobruk Misurata Steel 31% 31% 31% 31% 31% 31% 31% 31% 31% Gulf 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% Tripoli West 21% 21% 21% 21% 21% Benghazi North 21% 21% Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Zwetina 31% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% Khoms 1 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% Western Mountain 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Sarir Khoms 2 (Fast Track) 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% CC Zawia 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% Benghazi North 1 46% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% Misurata 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% Benghazi North 2 46% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Under contr. Steam Gulf 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% / contracted Tripoli West 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% Tripoli East 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% Gas Ubari 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Misurata 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Tobruk 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Proposed Steam Tripoli East Tobruk 2 Derna 2 Benghazi West Gas Sabha Tripoli South 2 CC Misurata Mellitah Zweitina 2 Tobruk Aboukammash BEST case Type of plant Power Station 31% 33% 33% 33% 33% 33% 33% 33% 34% 34% 35% 35% 36% 37% 37% Existing Various Small / rented 10% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% Steam Khoms 20% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% Derna Tobruk Misurata Steel 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Gulf 21% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Tripoli West 31% 31% 31% 31% 31% Benghazi North 31% 31% Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Zwetina 31% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% Khoms 1 29% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Western Mountain 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Sarir Khoms 2 (Fast Track) 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% CC Zawia 45% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% Benghazi North 1 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% Misurata 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% Benghazi North 2 46% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% Under contr. Steam Gulf 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% / contracted Tripoli West 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Tripoli East 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% Gas Ubari 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% Misurata 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% Tobruk 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% Proposed Steam Tripoli East 31% 31% 31% 31% 31% 31% 31% 31% Tobruk 2 31% 31% 31% 31% 31% 31% Derna 2 31% 31% 31% 31% 31% 31% 31% 31% Benghazi West 31% 31% 31% 31% 31% Gas Sabha 37% 37% 37% 37% 37% 37% 37% 37% 37% Tripoli South 2 37% 37% 37% 37% 37% 37% 37% 37% CC Misurata 49% 49% 49% 49% 49% 49% 49% Mellitah 49% 49% 49% 49% 49% Zweitina 2 49% 49% 49% 49% 49% 49% Tobruk 49% 49% 49% Aboukammash 49% 49% 49% -6- WORST case Thermal effciency - oil production 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 24% 28% 28% 28% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% Existing Various Small / rented 23% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% Steam Khoms 29% 29% 29% 29% 29% 29% Derna 19% 23% Tobruk 24% 17% Misurata Steel 20% 22% 22% 22% 22% 22% 22% 22% 22% Gulf 30% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% Tripoli West 24% 24% 24% 24% 24% Benghazi North 24% 24% Gas Tripoli South 28% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% Zwetina 24% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% Khoms 1 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Western Mountain 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Sarir 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% Khoms 2 (Fast Track) 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% CC Zawia 40% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% Benghazi North 1 31% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Misurata 32% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% Benghazi North 2 Under contr. Steam Gulf 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% / contracted Tripoli West 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% Tripoli East 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% Gas Ubari 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% Misurata 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% Tobruk 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% Proposed Steam Tripoli East Tobruk 2 Derna 2 Benghazi West Gas Sabha Tripoli South 2 CC Misurata Mellitah Zweitina 2 Tobruk Aboukammash BEST case Thermal effciency - oil production 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Type of plant Power Station 25% 31% 31% 31% 31% 31% 31% 31% 32% 32% 33% 33% 34% 35% 35% Existing Various Small / rented 23% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% Steam Khoms 29% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Derna 19% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% Tobruk 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% Misurata Steel 20% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% Gulf 30% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% Tripoli West 33% 33% 33% 33% 33% Benghazi North 33% 33% Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% Zwetina 24% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% Khoms 1 28% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Western Mountain 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% Sarir 27% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Khoms 2 (Fast Track) 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% CC Zawia 40% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% Benghazi North 1 31% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% Misurata 32% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% Benghazi North 2 Under contr. Steam Gulf 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% / contracted Tripoli West 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% Tripoli East 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% Gas Ubari 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Misurata 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Tobruk 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% Proposed Steam Tripoli East 33% 33% 33% 33% 33% 33% 33% 33% Tobruk 2 33% 33% 33% 33% 33% 33% Derna 2 33% 33% 33% 33% 33% 33% 33% 33% Benghazi West 33% 33% 33% 33% 33% Gas Sabha 30% 30% 30% 30% 30% 30% 30% 30% 30% Tripoli South 2 30% 30% 30% 30% 30% 30% 30% 30% CC Misurata 46% 46% 46% 46% 46% 46% 46% Mellitah 46% 46% 46% 46% 46% Zweitina 2 46% 46% 46% 46% 46% 46% Tobruk 46% 46% 46% Aboukammash 46% 46% 46% Libya - Supporting Electricity Sector Reform (P154606) Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development Least Cost Expansion Plan (LCEP) Annex VI – Cost of Capital Assumptions 12th December 2017 Client: The World Bank 1818 H Street, N.W. Washington, DC 20433 Consultant: GOPA-International Energy Consultants GmbH Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20 eMail: info@gopa-intec.de; www.gopa-intec.de Suntrace GmbH Grosse Elbstrasse 145c, 22767 Hamburg, Germany Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20 www.suntrace.de Table of Contents Page 1. Cost of Capital Assumptions 2 Libya SPREL – LCEP Report – Annex VI Cost of Capital Assumptions LBY2560_TaskD_ StageI_LCEP_Report_AnnexVI_CostCapitalAssumptions.docx -2- 1. Cost of Capital Assumptions For the estimation of total CAPEX and other economic estimations in this assignment, the Consultant made the assumptions set out below. Item Unit PV CSP Wind Leverage % 70 70 70 Interest Base Rate % 5 2 5 Discount rate % 15 15 15 WACC % 8 6 8 Depreciation time a 25 30 25 Construction time a 0.5 2 0.6 Table 1-1: Economic and financial assumptions for cost of capital According to discussions among the stakeholders carbon price will not play a role within this assign- ment. Libya SPREL – LCEP Report – Annex VI Cost of Capital Assumptions LBY2560_TaskD_ StageI_LCEP_Report_AnnexVI_CostCapitalAssumptions.docx