DEMAND-SIDE ENERGY EFFICIENCY OPPORTUNITIES IN BANGLADESH Ijaz Hossain Ashok Sarkar Sheoli Pargal Demand-Side Energy Efficiency Opportunities in Bangladesh Ijaz Hossain, Ashok Sarkar and Sheoli Pargal1 2017 1 Ijaz Hossain (corresponding author) is Professor in the Chemical Engineering Department at the Bangladesh University of Engineering and Technology, Ashok Sarkar and Sheoli Pargal are respectively Senior Energy Specialist and Lead Economist in the Global Practice for Energy and Extractives at the World Bank. The team gratefully acknowledges useful conversations and valuable inputs provided by Mr. Md. Helal Uddin, Chairman, and Mr. Siddiqui Zobair, Member (Energy Efficiency & Conservation), of the Sustainable and Renewable Energy Development Authority in Dhaka, Bangladesh. Helpful comments and suggestions to improve the paper were also received from Jonathan Sinton, Ivan Jacques and Lia Sieghart of the World Bank. Financial support from Australian Aid is gratefully acknowledged. i Abstract Enhancement of energy efficiency (EE) can help bridge the gap between supply and demand for energy. This paper assesses the energy efficiency and conservation (EE&C) potential of sixteen EE end-use technologies and subsectors (for both primary energy (oil, gas and coal) and electricity) in Bangladesh vis a vis “business-as-usual”. Further, it prioritizes among them on the bases of their potential for generating energy savings, their costs, and the benefits of deployment on a large scale. The end-use EE improvement technologies/measures analyzed range from lights, fans, and refrigerators to motors, boilers, and chillers. Sectors covered include garments, textile dyeing and weaving, steel and cement. They were chosen for analysis because they represent the most promising prospective candidates for demand side energy efficiency improvement in the country. The analysis indicates that a total of 400 PJ can be saved in the year 2030 when the projected total primary energy requirement is likely to be approximately 2800 PJ, i.e., a savings of 14.3% of the total primary energy requirement in 2030 can be achieved by implementing EE measures alone. A back-of-the- envelope calculation of the relative cost effectiveness of the different options analyzed provides a measure of the costs and benefits of these EE options. Despite domestic electricity and gas prices being fairly low in comparison with international market prices, the cost of saved energy for most options is either low or negative: in other words, these EE investments have a favorable rate of return and should be a key part of energy sector development in Bangladesh. Higher electricity or gas prices would increase the cost-effectiveness of all options because the monetized value of energy saved would be higher. ii Table of Contents Abstract ................................................................................................................................................... ii Acronyms and Abbreviations ................................................................................................................. iv Preface .................................................................................................................................................... 6 I. Introduction .................................................................................................................................... 7 II. Methodology .................................................................................................................................. 8 III. Energy Use in Bangladesh ............................................................................................................... 9 IV. Energy Efficiency Strategy in Bangladesh ..................................................................................... 10 V. Energy Efficiency Opportunities and Implementation ................................................................. 12 A. Generic End-use Technologies (Motors/Drives, Boilers, Chillers, Cogeneration, and Lighting) .............. 15 B. Policies, Incentives, and Other Supporting Mechanisms ........................................................................ 19 C. Promotion through minimum energy performance standards and EE labeling and building EE codes .. 20 VI. Analysis of Energy Efficiency Options ........................................................................................... 24 VII. Short-, Medium-, and Long-Term Options.................................................................................... 29 VIII. Cost Implications of Energy Efficiency Options ............................................................................ 32 IX. Scale Up Potential of Energy Efficiency Options ........................................................................... 38 X. Consolidated Ranking of Energy Efficiency Options ..................................................................... 39 XI. Barriers and Implementation........................................................................................................ 40 Annex 1: Assumptions used for the Baseline and EE Scenarios ........................................................... 44 Annex 2: Growth Rates of Energy Consuming Devices/Processes ....................................................... 47 Appendix A: Energy Efficient Lighting ................................................................................................... 49 Appendix B: Efficiency Improvement of Fans in Residential Sector ..................................................... 53 Appendix C: Replacement of Inefficient Refrigerators ......................................................................... 57 Appendix D: Replacement of Inefficient ACs ........................................................................................ 61 Appendix E: Improvement of EE of Electrical Motors........................................................................... 65 Appendix F: EE Improvement of Boilers ............................................................................................... 70 Appendix G: Efficiency Improvement through Cogeneration............................................................... 75 Appendix H: Improvement of EE of Chillers.......................................................................................... 79 Appendix I: Efficiency of Improvement of RMG Industries .................................................................. 82 Appendix J: Efficiency of Improvement of Textile Dyeing .................................................................... 86 Appendix K: Efficiency Improvement of Steel Making Furnaces .......................................................... 90 Appendix L: Efficiency Improvement of Steel RRMs ............................................................................. 94 Appendix M: Efficiency of Improvement of Clinker Grinding ............................................................... 98 Appendix N: Efficiency Improvement of Cold Storage Facilities......................................................... 102 Appendix O: Efficiency Improvement of Urea Fertilizer Plants .......................................................... 106 Appendix P: Efficiency Improvement of Textile Weaving ................................................................... 110 iii Acronyms and Abbreviations AC Air Conditioner ADB Asian Development Bank ASD Adjustable Speed Drive BAU Business-as-Usual BEMA Bangladesh Energy Managers Association BPDB Bangladesh Power Development Board BRESL Barrier Removal to the Cost-Effective Development and Implementation of Energy Standards and Labeling BSTI Bangladesh Standards and Testing Institution BUET Bangladesh University of Engineering and Technology CCGT Combined Cycle Gas Turbine CDM Clean Development Mechanism CFL Compact Fluorescent Lamp CFT Cubic Feet CHP Combined Heat and Power CII Confederation of Indian Industry COP Coefficient of Performance CP Cleaner Production CPP Captive Power Plant DSM Demand Side Management EA Energy Auditor EE Energy Efficiency EE&C Energy Efficiency and Conservation EM Energy Manager EMS Energy Management System ESCO Energy Service Company GDP Gross Domestic Product GHG Greenhouse Gas GIZ German Agency for International Cooperation (Deutsche Gesellschaft für Internationale Zusammenarbeit) IFC International Finance Corporation IMC Intelligent Motor Controller ISO International Standards Organization JICA Japan International Cooperation Agency LED Light-Emitting Diode LNG Liquefied Natural Gas M&V Measurement and Verification MCF Thousand Cubic Feet MEPS Minimum Energy Performance Standards MMCF Million Cubic Feet MPEMR Ministry of Power, Energy, and Mineral Resources NDC Nationally Determined Contribution NG Natural Gas OEM Original Equipment Manufacturer PSMP Power System Master Plan RMG Ready Made Garment RRM Rerolling Mill SEC Specific Energy Consumption SME Small and Medium Enterprise iv SNC Second National Communication SREDA Sustainable and Renewable Energy Development Authority T&D Transmission and Distribution TCF Trillion cubic feet TGTDCL Titas Gas Transmission and Distribution Company Limited TOE Tonne of Oil Equivalent UNDP United Nations Development Programme UNFCCC United Nations Framework Convention on Climate Change USAID U.S. Agency for International Development VFD Variable Frequency Drive VRM Vertical Roller Mill VSD Variable Speed Drive v Preface This paper is part of a broad program of economic analytical work being carried out by the World Bank on the energy sector in Bangladesh. The objective of the paper is to present a systematic assessment of the energy efficiency (EE) improvement potential of selected demand-side measures across various sectors. The work builds upon the existing body of data and information available, while prioritizing by sectors or end-use measures (based on total potential savings or potential savings/unit of investment in EE) in relation to the government's action agenda on EE. The paper analyzes in detail the selected set of high-priority EE measures for their scale-up potential, estimated costs and likely impacts. 6 I. Introduction Despite efforts at increasing energy access, per capita energy consumption in Bangladesh remains low. The shortage of primary energy coupled with a low level of investment in the energy sector, especially in upgrading old power plants and electricity transmission and distribution (T&D) network, implies that energy supply will remain a big challenge. The reserves of natural gas (NG), which was responsible for 68 percent of the generated electricity2 in FY2014, are down to 14 Trillion cubic feet (Tcf), whereas annual production is close to 1 Tcf.3 Government annual investment in the electricity network has been around US$1 billion, whereas the requirement is at least double that to meet the targets laid out in Power Sector Master Plans. As Bangladesh’s economy continues to grow, along with rising population and increased urbanization, the electricity sector, in particular, is facing difficulty in ramping up production and keeping costs down and is having to meet demand growth using expensive oil-fired generators. In FY2014, nearly 20 percent of electricity was generated using diesel and furnace oil. Economic growth and social development will suffer if adequate and reliable energy supply at an affordable price cannot be ensured in the future. This is well recognized in the Sustainable Development Goals (SDGs) that were adopted by world leaders at an historic United Nations Summit in 2015: SDG 7 aims to “ensure access to affordable, reliable, sustainable and modern energy for all.” It explicitly targets universal access to energy, increased energy efficiency (EE), and expanded use of renewables, objectives that are considered central to achieving both the 2030 Agenda for Sustainable Development and the Paris Agreement on Climate Change.4 In a supply-constrained scenario such as exists in Bangladesh today, EE improvement across the supply and demand chain is a critical energy development option that can play an important role in a sustainable future energy roadmap for Bangladesh. Similarly, it could help Bangladesh meet its global commitments through its Nationally Determined Contributions (NDCs) for climate change mitigation. In addition to contributing to energy savings, and greenhouse gas (GHG) emission avoidance, EE can contribute to increased access to energy, reduced fuel poverty, energy supply security, and reliability; increase competitiveness; support job creation; contribute to economic growth; and reduce subsidy burden on the government – all components of the sustainable development agenda. Although there is an enormous potential for EE improvements across all sectors in Bangladesh— both supply and demand side—there remains barriers to large-scale EE adoption, and market transformation, particularly across various demand-side sectors, remains weak. The focus of this document is on the demand-side EE opportunities for both primary energy (oil, gas, and coal) and electricity. The momentum for formulation of new EE policies and regulations, their implementation, and impact evaluation has picked up with the emergence of the Sustainable and Renewable Energy Development Authority(SREDA). SREDA has been established as a nodal organization for EE and renewable energy under the Power Division of the Ministry of Power, Energy, and Mineral Resources (MPEMR) and empowered through the SREDA Act of December 2012. This report is intended to lay out estimates of EE scale up potential and impacts for selected measures across various demand-side sectors, which are realistic, achievable, and consistent with the national-level EE goals and targets laid out by the government. The purpose is to analyze the 2 Bangladesh Power Development Board (BPDB) Annual Report, 2014, www.bpdb.bd. 3 Petrobangla website, www.petrobangla.bd. 4 See: https://www.un.org/sustainabledevelopment/energy/. 7 technical potential of the various EE measures, and prioritize among them on the basis of the opportunity for energy savings, costs, and benefits of deployment on a large scale.5 Using information from existing studies/reports, including the government’s EE Action Plan (2013) and Energy Efficiency and Conservation (EE&C) Master Plan (2015), a set of sixteen high-priority end- use EE improvement technologies/measures6 have been identified and their large-scale potential, associated costs and impacts assessed in this report. By projecting energy demand in the ‘business-as-usual’(BAU) scenario for each of the selected EE options, an attempt has been made to estimate the reduction in energy demand as a result of implementing these specific measures. Sections VI through X of this report summarize the total potential energy savings, costs and benefits of implementing these measures, projected through 2030. Details of the analysis carried out are provided in the appendixes. The barriers to implementing these EE demand side measures and how the potential application of EE technologies across various sectors can be promoted are presented in the last section (XI). II. Methodology The options chosen for the analysis represent the most prospective candidates for demand-side EE improvement. The selection of end-use options (appliances, equipment, processes, and so on) and corresponding EE improvement measures was based on the following broad-based criteria: • The energy consumption of the baseline end-use must represent at least 1 percent of the total energy consumption. • Potential of EE improvements must exist for this end-use, that is, the existing baseline technology is fairly inefficient for the particular end-use. • Reasonable amount of data and information exists to permit analysis of the energy savings potential. The following methodological steps were applied in the analysis of the energy savings potential of different EE options: • For the selected end-use options, data and information on the number of units and energy consumption in the base year were collected from secondary sources. • Data and information on the historical growth of the option were collected. • Data and information on the future growth of the options up to 2030 were gathered and/or projected. • A set of EE improvement technologies for each option was collected from literature. • The efficiency information of the EE improvement technologies was gathered. • A baseline energy consumption in the ‘BAU’ scenario is constructed using the information gathered from industry associations, the baseline assumptions used in the Second National Communication (SNC) and the SREDA Energy Efficiency and Conservation (EE&C) Master Plan. In some cases, expert judgment had to be used because no other data or information was available. 5 The paper does not intend to get into the implementation approaches pertaining to each of these measures. This has been covered in the EE Master Plan of SREDA and also in other reports, including a report prepared by the World Bank in 2016. 6 Lights, Fans, Refrigerators, Air-conditioners, Motors, Boilers, Cogeneration, Chillers, RMG, Textile Dyeing, Steel Melting Furnace, Steel Re-rolling Mill, Cement, Cold Storage/Ice Plants, Fertilizer (urea), and Textile Weaving. 8 • An EE improvement in the ‘efficiency’ scenario is established using the improved efficiencies and an assumed penetration rate. • For the penetration rate or the diffusion rate of the efficient technologies, expert judgment was used. • The difference between the energy/electricity consumptions in the ‘BAU’ and ‘efficiency’ scenarios thus establishes the energy savings potential in a particular year. A total of sixteen (16) identified EE improvement technologies/measures for different end-uses were analyzed.7 Each of these measures is described in detail along with total potential, costs and benefits, and projections through 2030 in the appendixes. III. Energy Use in Bangladesh The primary energy and electricity consumption by the different sectors for the financial year8 2013–14 is shown in tables 1 and 2, respectively. Table 1.Primary energy consumption in 2013–14 in million GJ Natural Gas Oil Coal Total Grid power 335 65 30 430 Captive power 128 — — 128 Industry (includes fertilizer) 196 6 100 302 Domestic 90 14 — 104 Commercial 9 — — 9 Transport 39 103 — 142 Agriculture — 42 — 42 Total 797 230 130 1,157 Note: Compiled by author using data from BPDB and Petrobangla. Coal data are expert judgment. Table 2.Electricity consumption by different sectors in 2013–14 in GWh Consumption GWh (%) Domestic 18,265 50.40 Industrial 12,293 34.00 Commercial 3,313 9.15 Agriculture 1,713 4.73 Others 628 1.73 Total 36,211 100.00 Note: This is billed consumption. Distribution losses computed from supplied minus these figures. The breakdown of distribution loss into technical and nontechnical is not known. To fully calculate total energy consumption by end-use sectors, it is necessary to distribute the primary energy consumed for power generation into the various sectors in proportion to their electricity consumption. Thus, 558 million GJ of primary energy supplied for electricity generation is required for final energy consumption of 36,211 GWh of electricity at the consumer level, and then 0.0154million GJ is required to deliver 1 GWh of electricity to consumers for final use. This also translates into a supply-side efficiency of only 23 percent and means that a total of 77 percent of the 7 Lights, Fans, Refrigerators, Air-conditioners, Motors, Boilers, Cogeneration, Chillers, RMG, Textile Dyeing, Steel Melting Furnace, Steel Re-rolling Mill, Cement, Cold Storage/Ice Plants, Fertilizer (urea), and Textile Weaving. 8 The financial year is from July 1 to June 30. 9 primary energy is lost in generation (conversion from primary fuels into electricity), transmission, and distribution of electricity. Supply-side EE improvement actions (such as high-efficiency generation, repowering, combined cycle generation, and reduction of T&D losses) can help bring down these losses. The total energy consumed has been computed and shown in Table 3. Table 3. Total primary energy consumption by sectors in 2013–14 (in million GJ) Total Primary Electricity Primary Energy Needed Primary Energy Share of Energy Consumed (GWh) to Produce Electricity for Other Uses Total (%) Consumed Domestic 18,265 282 104 386 33.3 Industrial 12,293 189 302 491 42.4 Commercial 3,313 51 9 60 5.2 Transport — — 142 142 12.3 Agriculture 1,713 26 42 68 5.9 Others 628 10 — 10 0.9 Total 36,211 558 599 1,157 100 IV. Energy Efficiency Strategy in Bangladesh Bangladesh has been a late starter in the area of energy conservation and EE. Even though high energy inefficiencies exist across all sectors, including on the supply side, not much had been done in terms of setting up a framework for pursuing EE programs until recently, with the establishment of SREDA. In 2014, SREDA was set up through an act of Parliament, the SREDA Act. To assist in SREDA's functioning and to implement its programs, rules and regulations have been framed. Before SREDA was set up, the issue of EE was pursued in a limited manner, mainly through support from various bilateral and multilateral agencies. In most cases, the focus was on GHG mitigation and development of clean development mechanism (CDM) projects to tap into the global carbon finance markets. The following five studies performed in the last ten years are relevant: (a) World Bank-German Agency for International Cooperation (Deutsche Gesellschaft für Internationale Zusammenarbeit, GIZ) EE Road Map (2009) (b) Second National Communication (SNC) (2011) (c) 2050 Calculator (U.K. Department of Energy and Climate Change) (2013) (d) Asian Development Bank's (ADB) EE Bankable Projects (2011) (e) SREDA-Japan International Cooperation Agency (JICA) EE&C Master Plan (May, 2016) The SREDA EE&C Master Plan, prepared by JICA, is the most recent comprehensive report and contains data and information that are directly relevant to the present study. A few relevant figures that are referenced in this master plan are reproduced below. This study has attempted to determine the EE&C potential of various EE end-use technologies and subsectors compared to a BAU scenario. The BAU scenario has been taken from the SNC of the Bangladesh Government. The BAU scenario is essentially an energy consumption scenario that is projected as if no EE&C measures are undertaken. The ‘efficiency’ scenario on the other hand considers measures, such as light-emitting diode (LED) bulbs in place of incandescent bulbs for lighting or efficient refrigerators in place of the existing standard refrigerators. The ‘efficiency’ scenario is one where realistically achievable measures have been considered. Figure 1 for 2030 shows a daily load curve for a typical day (May 30) and the breakdown by contribution of various sectors and end-uses. The potential of EE&C actions for modifying the daily load curve (by either load shifting or load clipping) has also been estimated and is shown in Figure 1. 10 Figure 1. Load curve in 2030 for BAU and EE scenarios (Source: SREDA EE&C Master Plan) Figure 2 shows the projected electricity demand in a BAU scenario through 2030 as well as the EE&C improvement potential for various sectors and end-uses. As can be seen from this analysis, energy efficient air-conditioning and lighting shows the greatest potential. This is because of the rapid increase in household electrification and the large reduction possible from LED lighting as well as the rapid increase in the cooling load due to increasing prosperity of households and the tendency of air- conditioning all shopping centers. Figure 2. Electricity demand of devices for BAU and EEscenarios (Source: SREDA EE&C Master Plan) Figure 3 and Figure 4 show, respectively, the electricity demand growth through 2030 in buildings and industry sector, and the EE&C potential in these two sectors are projected to be 11 percent of the electricity demand and 21 percent of the primary energy demand, respectively. 11 Figure 3. Projection of electricity demand reduction potential in the building sector (Source: SREDA EE&C Master Plan) Figure 4: Energy reduction potential in the industrial sector (Source: SREDA EE&C Master Plan) (1000 TOE) 6 sub sectors = 47% of total 422, 3% 1,641, 12% 357, 3% Chemical fertilizer Steel making & re-rolling Cement grinding 7,232, 53% 3,727, 27% Textile & garment Cold storage Chemical Other Industrial total: 13.7 million TOE 60, 0% 309, 2% Source: Compiled by JICA Project Team based on the current gas and electricity consumption data V. Energy Efficiency Opportunities and Implementation (PETROBANGLA, distribution companies) Six Large Energy-consuming Industrial Sub Sectors As shown in Table 3, industry and domestic sectors dominate overall energy use in Bangladesh, totaling nearly 75 percent of the national primary energy consumption. If only electricity consumption is considered, then their share is even higher. The industry sector in Bangladesh, including large- and small/medium-scale industries ranging from fertilizer to brickmaking to textiles, offers large potential for EE improvements. Specific industry- focused pilot projects include brick kiln’s moving to the more efficient Hoffman kiln process, lighting efficiency improvements in the textile industry, and so on. Some development partners, including the International Finance Corporation (IFC) and the U.S. Agency for International Development (USAID), have worked with private industry to mainstream the concepts of energy auditing and energy service companies (ESCOs). However, significant untapped potential remains, as do implementation gaps on both the policy and the investment sides. A total of 113 energy-intensive industries have been identified as ‘designated’ consumers under the SREDA Act. However, there is no national-level program to implement EE improvements across these industries; full-scale energy audit reports are available only for a limited number of industries; and there is practically no ESCO-based EE implementation. Moreover, there is limited in-house capacity to implement recommendations from energy audits in most of these industries. 12 The SREDA EE&C Master Plan shows that energy consumption in the industrial sector is dominated by the following three subsectors (Figure 4): (a) Fertilizer production (b) Ready-made garments (RMG) for the export market (c) Textile (spinning, weaving, and dyeing) The fertilizer industry, which is very energy intensive, is dominated by large government-owned urea plants. There are 10 large fertilizer plants, only one of which is privately owned. The privately-owned industries operate at the international standard benchmark of 24 MCF of gas/ton of urea, whereas the average of the old public-sector plants is 45 MCF/ton of urea. A new urea plant will be commissioned very soon, which will have a specific energy consumption (SEC) of 25 MCF/ton of urea. EE improvement potential in these plants has been identified, but experts opine that replacing old plants with new ones is the correct way forward. Lack of investment funds is preventing the government from building new plants and shutting down the older ones, and new plants may not come on line for some time. Hence, one of the short- and medium-term options is to examine the feasibility of implementing EE (and some process) retrofits in the existing fertilizer plants. An in- house study performed nearly a decade ago on one of the old plants showed that US$32 million would be required to restore the plant to its design values. With regard to savings, this will not be optimum because the design values of old plants are much higher than those of the state-of-the-art plants. The payback period on these investments will be very high because the price of gas for fertilizer plants is around US$1/1,000cft. However, if an economic price of gas, which is at least three times higher, is used, the payback would be lucrative. The option analysis for EE in fertilizer plants is presented in appendix O. There are more than 5,000 Ready Made Garment (RMG) factories in Bangladesh. The RMG industry is a dispersed industry of small individual-sized factories, but, as a whole, this subsector consumes over 17 percent of total industrial energy as shown in Figure 4. Although the EE improvement potential in one factory is small and faces many barriers to implementation, bundling of several factories increases the bankability of such projects and chances of implementation. The bundling will require first to identify a cluster and convince as many mills as can be persuaded to participate. The next step will be to convince the participating mills to secure investment funds, either from own resources or from a commercial bank. The last step will be to fix a technology provider that will perform the retrofits and manage the entire project. It might be a good idea to first do a pilot to convince the mills about the viability of the EE retrofit. The option analysis for EE in RMG factories is presented in appendix I. The textile industry supplies cloth to the RMG industry and consists of spinning, weaving, and dyeing industries. Energy consumption of one textile factory is not very large compared to a steel rerolling mill (RRM) or a clinker grinding cement plant, and therefore, an EE program in the textile subsector will also have to bundle several factories to have a sizable project that could be financed and implemented. To achieve an implementable project, at least 15–20 textile mills have to be bundled. The option analysis for EE in the textile industry is presented in appendix J. In addition to the three main subsectors within the industry sector, the following energy-intensive industries were also considered for further analysis: (a) Steel production from scrap steel (b) Steel RRMs (c) Cement clinker grinding industries (d) Industries that use refrigeration technology (frozen foods, cold storage, and ice plants) 13 These four subsectors were chosen for analysis because the energy consumption of each is greater than 1 percent of the total energy consumption of the industry sector according to the recent survey conducted by JICA for the SREDA Master Plan. Table 4 gives the numbers of industries and energy consumption data for the four selected industrial subsectors. The option analyses for EE in these four energy-intensive industries are analyzed in appendixes K to N. Table 4.Energy consumption data of selected energy-intensive industries Energy Use % of Total Industrial Subsector Numbers Tonne of Oil Equivalent (TOE) Consumption Steel production from scrap 230 150 steel 4.7 Steel RRMs 250 276 Cement (basic and clinker 394 2.9 50 grinding) Food and cold storagea >300 71 0.5 Note: a. If ice plants are included, the consumption will exceed 1 percent. In addition to focusing on the investments and implementation of EE measures and retrofits in specific industries, particularly fertilizers, RMG, and textiles, there is a need for the industry sector EE strategy in Bangladesh to also focus on some generic low-hanging measures, also known as ‘horizontal’ measures and actions that can be implemented in the short term across these same and other industries, including small and medium enterprises (SMEs). These include the following: (a) Cross-cutting, generic end-use technologies such as motor drives and driven equipment (pumps, fans, compressors, and blower), boilers and steam systems, cogeneration, space cooling (fans and air conditioners [ACs]), and lighting (b) Energy management systems(EMS) These end-use technologies and EMS can be promoted through the following policy approaches: (a) Establishment of mandatory specific energy consumption targets (b) Minimum Energy Performance Standards (MEPS) for equipment (c) EE standards and labeling of equipment (d) EE procurement based on life-cycle costing (and not lowest first cost-based procurement) (e) Design and implementation of International Standards Organization (ISO) 50,0001 EMS (f) Building EE codes (new buildings only) (g) Utility-driven industrial Demand Side Management (DSM) programs As experience around the world indicates, MEPS and labeling policies coupled with awareness campaigns, financial incentives (such as EE rebates, tax and fiscal incentives, and so on), and capacity building of energy auditors (EAs) and managers, accredited measurement and verification (M&V) professionals, and ESCOs can help scale up EE investments. These policy approaches and supportive measures are applicable not only in the industry sector but also across other demand-side sectors. It is worth investing in the development of EE service providers that could provide technical design and implementation support to industry on generic EE projects. Also, training programs for shop floor personnel should be organized to build awareness and capacity to implement generic EE measures. Finally, it should be pointed out that a large portion of energy consumption in Bangladesh is in the SME sector, as shown in Figure 4. Although the SME sector has large EE savings potential, it does not have the technical awareness/capacity or the financial strength or access to funds to adopt EE measures/actions. In addition, it is very difficult to bring about changes in this industry category for the following reasons: 14 (a) The smaller industries often do not have legal status and are therefore unable to borrow funds from domestic financial institutions (b) ‘Here today gone tomorrow’ syndrome (c) Inability to afford expensive technologies (d) Not fully convinced about the benefits of making the higher initial investment for EE equipment and devices (e) Poor management practices (f) Inefficient maintenance systems and unavailability of spare parts (g) Antiquated technologies, generally locally designed and fabricated systems such as furnaces, ovens, and so on (h) Noneconomic sizes (i) Inefficient product and process designs (j) Scarcity of skilled labor However, an analysis of SMEs will reveal that their electricity consumption is dominated by the following three devices and equipment: (a) Motors and drives for pumps, compressors, and small machines (b) Lights and fans (c) ACs (medium industry category) Some of these EE measures and their opportunities and potential for scaling up their implementation across the demand-side EE domain are described in further detail in the following sections. A. Generic End-use Technologies (Motors/Drives, Boilers, Chillers, Cogeneration, and Lighting) Motors and Drives Industrial energy consumption, particularly in the SME sector, is dominated by motors/drives and boilers. According to an international EE manual,9nearly 75 percent of the electricity and 45 percent of the primary energy consumption10in industries is due to motors. If an EE program targets the deployment of EE motors/drives only, which could entail up to 50 percent of energy savings, almost a third of total industry energy consumption could be reduced. This, however, is only the technical (theoretical) potential and needs to be revised downward to reflect the economic potential. The actual realizable potential would be less if the several technical, management, and financial barriers to EE were to be factored in as explained earlier. The following aspects of motors in Bangladesh are important for further analysis and assessment of this opportunity: • More than 90 percent of motors are imported mainly from China and India. • The motors are coupled to the machines using very poor quality belts and drives. • Variable speed drives (VSDs) and intelligent motor controllers (IMCs) are not used. • Rewinding of burnt-out motors is common and not done properly. Motor efficiency varies between 88 percent and 94 percent, but high-efficiency motors are more expensive and such investments may entail long payback periods that prevent the end-users from 9 Consumers Energy, https://www.consumersenergy.com/eeprograms/BHome.aspx?id=4096 10 Clean Technica, http://cleantechnica.com/2011/06/16/electric-motors-consume-45-of-global-electricity- europe-responding-electric-motor-efficiency-infographic/ 15 making investments to switch to efficient motors. This situation will arise when the electricity price is low and the efficiency gains are 2–3 percent. Although high-efficiency/quality motors are available from Germany and Japan, these are much more expensive compared to the standard ones from China or India, resulting in a low uptake of high-efficiency motors, except when specific end-users consider other factors in their procurement decisions when reliability is the main issue. The World Bank-GIZ EE Roadmap (2010) also found that even if the motor may be energy efficient, the motor systems may not be. That is, power delivered to the machine by the motor could be lowered even below 70 percent due to faulty drives. The most commonly used drive is the V-belt, but V-belts often get worn out quickly, are not aligned properly, and are of low quality. Superior energy performance can be obtained by using synchronous belts. The use of VSDs and IMCs, which is common in most developed and many developing countries, is very low in Bangladesh. The principal reasons behind the low application and acceptance of variable frequency drives (VFDs), VSDs, and IMCs in Bangladesh are cost, unavailability, and lack of awareness. In India, for instance, the market for such retrofit devices in industrial electric motors developed as follows: • Large-scale awareness-building and sensitization programs by industry associations, namely, the Confederation of Indian Industry (CII), • Redesign of motor-driven equipment to include VSDs and so on by Original Equipment Manufacturers (OEMs) • Vendor-sponsored demonstration projects in industry followed by active marketing by vendors These resulted in the exponential growth of the market from a few million U.S. dollars in the early 2000s to over US$200 million/year today, making it among the fastest-growing EE measure and market in Indian industry. There are lessons here for SREDA and Bangladesh industry to emulate. Motors operate at a constant speed and deliver a fixed amount of power making the operation inefficient when the machine runs on part load, and to reduce the speed, mechanical methods with pulleys and gears are used. While the mechanical ones merely reduce speed, the electronic ones as in VSD systems can actually bring down the power delivered while reducing speed. IMCs are more sophisticated than VSDs and can change the power depending upon specific requirement. Rewinding of motors is widespread. A study at the Institute of Energy found that efficiencies can fall by as much as 10 percent. Rewinders do not follow standard procedures or use standard equipment, for example, insulation material, size and quality of wires, and manual rewinding of armature coils is common. They are not trained, and no certification of rewinders is available. Some large industries have their own rewinding facilities, which are marginally better than the usual small-time rewinders. The three options for reducing energy consumption of motors are analyzed in appendix E. Boilers Boilers are a common energy end-use equipment in industries. While motors are the predominant consumers of electricity in industries, boilers are the predominant consumers of primary energy. Depending on country, the primary energy may be NG, coal, wood, or even oil. Because of its high price, generally the use of oil is restricted and the predominant fuel is NG in case of Bangladesh. Apart from the use of gas in furnaces and kilns in some industries (steel rerolling, ceramic/glass, Portland cement, lime, bricks), all gas is used in boilers to raise steam. More than 80 percent of the industrial gas is burned in boilers. 16 Boiler efficiencies can be very high depending on manufacturing standards followed, configuration (once-through or condensate recycling), and operation. It has been found that most boilers in Bangladesh are operating in the region of 70 percent efficiency with some being as low as 65 percent. Information gathered from local manufacturers indicate that once-through boilers have an efficiency of 80 percent. Imported high-quality once-through boiler could have an efficiency of 85 percent. With condensate recycle boilers, the efficiencies could be more than 90 percent. However, in the case of condensate recycling boilers, the pumps for handing hot water are prone to damage and must be designed to prevent cavitation, and therefore, most boilers used in Bangladesh industry sector are once-through.11 Condensate reuse as boiler feedwater has been advocated as an EE option in several studies. Good combustion air control can easily deliver up to 10 percent efficiency improvement in boilers. Several studies (RoadMap, Titas Gas Transmission and Distribution Company Limited- TGTDCL, SREDA) have conclusively determined that burners and combustion control are the weak links in boiler efficiency. Adequate and well-maintained insulation, especially after 4–5 years, is an issue. Additionally, the pipes that carry steam from boilers are often not lagged properly and, in the worst case, are actually leaking. Efficient distribution and utilization of steam must be a key part of a plant industrial fuel efficiency program. The SREDA-JICA study found that most boiler operators are also unaware of the need for combustion air control. The boiler design of a gas-fired system must incorporate the following features to reflect high fuel efficiencies (85 percent and higher): (a) Combustion and draft control systems to minimize excess air operations (b) Scale-free boiler tubes due to effective water treatment (c) Economizers and air preheaters to recover waste heat from outgoing flue gases (d) Recycling of heat in feedwater through condensate recovery systems This option has been analyzed in the report in appendix F. Cogeneration Due to the unreliable electricity supply, most of the large industries in Bangladesh generate their own electricity (captive power) using NG and use the power from the national grid as a standby option. The installed capacity of captive power generation is more than 2,000 MW. Bangladesh is unique in having a large share of captive generation in industries. Considering the fact that the country has not been able to exceed 7,800 MW in peak generation, having 2,000 MW that is outside the national grid is fairly remarkable. Assuming an annual load factor of 60 percent, the 2,000 MW will generate approximately 10,500 GWh annually. Therefore, the demand of all the industries (12,300 GWh in the year 2013–14) that take electricity from the grid is comparable to electricity generated through captive generation. Several studies (IFC, Road Map, SREDA) have shown that the average generation efficiency of the captive gas engine generators is less than 35 percent. This has led many to argue that if this gas is available to the high-efficiency grid generators, which use combined cycle gas turbines (CCGTs) as baseload technology, efficiency as high as 55 percent could be obtained. Opposing this view captive generators have argued that the electricity generated is consumed at the industry and as a result there is no T&D losses, which for the national grid is more than 15 percent at present. 11 As per communication with local manufacturers. 17 While the reliance of industries on captive or in situ generation option is going to continue and its share is likely to expand in the future, it also provides an opportunity to make this approach more energy efficient through the adoption of cogeneration. In the World Bank-GIZ EE Road Map (2009) study, it was found that most captive generators are not utilizing the heat of the flue gas and the engine jacket cooling water. In the last five years, however, many industries have, on their own, installed cogeneration systems to capture this waste heat, especially for space cooling using absorption chillers. However, there still remains a considerable unutilized potential for heat recovery and cogeneration in this subsector. The theoretical potential of EE of cogeneration from captive gas engine generators is very high. There is nothing new or innovative about this technology, and chemical industries have been using this technology for over half a century. Several studies have been performed to evaluate this potential, and some projects have also been undertaken. Recently, a bundled CDM project on cogeneration has also been approved by the United Nations Framework Convention on Climate Change (UNFCCC). One of the main reasons for its lower rate of application in Bangladesh is that captive power generation capacity was deployed very quickly, mainly to address the electricity shortages and developers/vendors did not propose holistic solutions (with heat recovery). However, this subsector offers an enormous opportunity to improve EE through the following options: (a) Using waste heat (flue gas) to raise low-pressure steam in a waste heat boiler (b) Using flue gas to run absorption chillers for space cooling (c) Using the engine jacket cooling water as a hot water supply According to a reliable source,12 there are more than 600 absorption chillers installed in Bangladesh. Assuming 2 chillers per factory, more than 300 units are already practicing cogeneration. It is estimated that another 200 industries have waste heat boilers. That still leaves more than 1,000 industries that are not practicing cogeneration. Even if 50 percent of the remaining industries adopt cogeneration,13 the potential can be exploited in more than 500 industries. This potential has been analyzed in appendix G. Lighting Lighting is one of the largest load in the electricity system in Bangladesh. This is to be expected because more than 50 percent of the electricity is consumed by the residential sector, and the predominant load in rural households is lighting. In addition, lighting constitutes a significant portion of the commercial sector's load, and there is also lighting load in the industrial sector. The industrial sector of Bangladesh is dominated by the garment industry. There are thousands of lights, mainly fluorescent lamps, in one garment industry. The Bangladesh Government has achieved significant success through a compact fluorescent lamp (CFL) dissemination program, where nearly 10 million CFLs were given away free to consumers. The program achieved an exemplary performance by distributing the CFLs through the Rural Electrification Board's centers in one day. However, the program could not achieve the desired impact because the bulbs were of inferior quality, and many were returned. As a result of this popularization move and other private sector efforts, CFLs have been able to achieve significant penetration. In shops and offices, it is the device of choice, and residential users are also slowly opting for it. Appendix A analyzes the EE improvement potential in the lighting category up to 2030. A significant assumption in the modeling is the incandescent phaseout. The World Bank is working with the 12 EOS Textile Mills Ltd, personal communication with the owner of the factory. 13 Some may not have any use for steam or any space cooling needs, or they simply cannot be motivated. 18 government to bring it about in 5–6 years. If that is successful, then the rollout of CFLs and the more expensive LED lighting will gain significant momentum. Environmental Management System The Environmental Management System is an extremely powerful system to bring about cleaner production (CP) that includes energy and resource efficiency. That saving water and material resources also saves energy is a useful concept that CP proponents have established a long time back. SMEs, which cannot be directly targeted through EE programs, can be encouraged to adopt the system. The system through careful audit first identifies the areas that can be improved and then through a systematic application procedure moves forward to ultimately seeking a formal recognition such as the ISO certification. Energy and environmental audits, which are key to energy and resource efficiency improvements, need to be encouraged in every industry. SMEs do not have the financial means or the understanding to employ energy mangers. A well-structured program that assists SMEs in developing a simple Environmental Management System can go a long way in EE improvement. The sixteen options analyzed, the more important of which have been discussed in more detail above, are summarized below. OPTIONS Energy Consumption in Energy Efficiency Measures 2015 (million TOE) 1 Lights 0.875 LED and CFL lights 2 Fans 1.305 Efficient fans 3 Refrigerator 1.042 Efficient refrigerators 4 AC 0.583 AC with inverter technology 5 Motors 1.321 Synchronous Belt + VFD + Efficient Motors 6 Boilers 2.625 Air control + Insulation + Economizer 7 Cogeneration 2.933 Waste Heat Boiler; Absorption Chiller 8 Chillers 0.400 Efficient Chillers of COP greater than 5 9 RMG 0.770 Servo motors; Automation of aeration system; Heat recovery 10 Textile Dyeing 0.155 Cleaner Production 11 Steel Melting Furnace 0.614 Arc Furnace 12 Steel Re-rolling Mill 0.100 Burner + Air Control + Insulation + Waste heat recovery 13 Cement 0.263 Vertical Roller Mill 14 Cold Storage / Ice 0.063 High COP Chiller + Insulation Plants 15 Fertilizer (urea) 1.268 New plants 16 Textile Weaving 0.690 Air jet Looms Total 15.000 B. Policies, Incentives, and Other Supporting Mechanisms Even though EE&C makes eminent sense with regard to sustainable development, it is extremely difficult to promote without correct policies, incentives, and other supporting mechanisms. Following are some of the factors that hinder the promotion of EE: (a) Low prices of energy (b) Unavailability and a low level of awareness about the energy efficient technology (c) Lack of financial incentives for adoption of efficient technologies and penalty for continuing to use inefficient technologies 19 Although in most cases, EE measures are cost-effective on a lifecycle basis, if the energy savings cannot cover the incremental up-front cost of the improved technology in a reasonable time (payback period), the incentives to adopt those and make investment are not there. Therefore, low energy prices could be considered the biggest barrier to the promotion of EE, and subsidized energy tariffs lower the monetary value of energy savings. In recent years, the price of electricity has gone up to approximately US$0.08/kWh, which is favorable to many EE projects. The price of NG, however, has remained low. A recent increase has seen the price go up by 16 percent for industrial users, but the price compared to other countries remains very low. Table 5 gives a comparison of prices in several countries. For instance, the low price of gas at US$2/1,000 cft implies that industries will not be investing in boiler maintenance and waste heat utilization. Table 5. Comparison of electricity and gas prices in selected countries Industrial Gas Electricity (US$/kWh) (US$/1,000 cft) Bangladesh 0.05 to 0.09 3.0 India 0.001 to 0.18 (average 0.07) 4.2 Pakistan 0.02 to 0.151 5.7 Thailand 0.06 to 0.13 9.5 Malaysia 0.071 to 0.148 5.0 Indonesia 0.11 9 to 10 Source: https://en.wikipedia.org/wiki/Electricity_pricing Often knowledge and awareness of the benefits of energy efficient technologies is lacking, particularly in countries that do not have a good technology manufacturing base and if those EE technologies cannot be acquired easily. This acts as a significant barrier. In nearly all cases, programs are required to increase awareness, and policies are required to both set minimum energy performance standards of end-use appliances and equipment and provide incentives to address the barriers pertaining to the initial incremental cost of EE technologies, so that those can compete at par with the standard technologies. For EE market transformation, two actions promoted by the government and other stakeholders have proved very effective in many countries of the world. These are as follows: (a) MEPS and EE labeling and building EE codes (b) Energy Management Program These two aspects of promoting EE technologies are discussed in the following two sections. C. Promotion through minimum energy performance standards and EE labeling and building EE codes The Bangladesh Government through SREDA is initiating policies and initiatives such as MEPS and EE labeling schemes to promote energy efficient appliances and equipment. The STAR labeling program was initiated under the Barrier Removal to the Cost-Effective Development and Implementation of Energy Standards and Labeling(BRESL)14 project funded by the United Nations Development Programme (UNDP) in 2002, with Bangladesh Standards and Testing Institution (BSTI) as the key implementing institution. Under BRESL, MEPS have been set up for six appliances (CFLs, motors, refrigerators, electronic ballasts, fans, and ACs). Manufacturers and importers have been asked to apply for STAR rating for their products. After SREDA became operational and functional in 2014, this 14 http://breslbd.org/ 20 policy implementation activity has been brought under its purview. However, the responsibility of setting standards and labeling mechanism remains with BSTI. The standards and labeling programs in many countries have yielded good results, especially when they are backed by consumer awareness and proper monitoring and enforcement. The program in Bangladesh is in its infancy, but if this is strengthened, then impacts could be high. The areas that need strengthening are as follows: • Compliance: As in most developing countries, in nearly all areas of the economy, compliance has proved to be a challenge. To have an effective compliance system, competent personnel with an attractive salary structure and equipped with good testing facilities have to be developed. • Equipment testing facility: This is essential to properly assess the state of energy consumption of the existing technologies in the country. • Certification: Certified auditors and mangers are a key to a successful program. The SREDA study has shown that the following four appliances will have a significant share in the growth of the baseline energy demand up to 2030: (a) Lighting (incandescent lamps, although the share of efficient bulbs such as CFLs and LED bulbs is also increasing) (b) Fans (which will continue to be the most common cooling device in lower-income households) (c) Refrigerators (will increase in numbers as households move into the middle-class income category) (d) ACs (which will likely be limited to high-income households at least in the short term) Lighting and fan demand will keep on increasing and will remain a significant demand in the residential sector up to 2030. The LED option for lighting, which is over 60 percent more efficient than incandescent lamps and more efficient than even CFLs, is becoming more affordable and will need to be specially promoted to have a significant penetration in the Bangladeshi market by2030. These two EE options have been analyzed in appendixes A and B, respectively. The space cooling load in the country is increasing at a very fast rate leading to a proliferation of ACs in middle- and high-income households and central chillers in commercial and public buildings. The significance of this load can be appreciated from the seasonal variation. In the hottest days of the year, the peak demand is just under 8,000 MW, while in the coldest days the peak demand falls to around 5,000 MW. This clearly shows that much of the 3,000 MW increase during summer is associated with space cooling requirements. With refrigerators as well, which must be kept on at all times, the difference in ambient temperature leads to increasing and decreasing load, but not as much as in the case of ACs. With central chillers and ACs, it is the same except for the fact that in at least three months of the year from early November to late February (winter season), ACs are not in use. Industrial and commercial cooling, which often uses very large chillers, is also contributing to this load. There is a great need to pay serious attention to this increasing load and consider it be a potentially large EE option. The commercial, and to some extent, the industrial cooling is greatly dependent upon the building envelope. If that is designed following EE building codes, then air-conditioning load can be greatly reduced. For instance, using a glass facade in commercial building as a means of beautification is popular but it also causes higher energy consumption. The best solution is to totally avoid glass walls on the south and west sides of the building. If that is not possible, at least an effort should be made to use solar reflective glass for windows and facade. Good insulation, air leakage prevention, and 21 energy efficient lighting are other measures to lower the cooling load. Even though these are not directly connected to the cooling equipment but as demand-side management measures, these need to be considered for the new buildings and, in many cases, can yield greater reduction in energy consumption of the space cooling energy needs than pure technical efficiency improvement of the AC/chiller systems. Analysis of refrigerators and ACs is provided in appendixes C and D, respectively. Energy Management Program In the SREDA EE&C Master Plan, one of the three pillars of achieving EE, especially in industries, is the ‘Energy Management Program’. The salient features of the program are as follows: • All designated large energy consumers must have energy managers (EMs). • Bangladesh Energy Managers Association (BEMA) will be formed. • BEMA will be linked to SREDA. • SREDA will hold EM/EA training courses. • SREDA will also conduct EM/EA/M&V certification examination. • An ‘Energy Management Guidebook’ will be published. SREDA expects that through this program the culture of EE&C will get established first in large industries and then gradually in the medium and small industries. The Energy Management Program will be supplemented by mandatory audits and submission of those to SREDA. In the second phase of the intervention, industry-specific standards or benchmarks will be established. To establish the SEC for each of the energy-intensive designated consumers, SREDA will have to commission studies that will collect data and information on existing industries in a particular category. These data will then need to be analyzed to see what technologies are being employed. Through a process of comparison with international standards, the SEC can be established. Those performing below the benchmark will be first warned and later fined. In the worst case, shutdown for noncompliance can be considered. The industry-specific standards will be developed based on the reality on the ground. It cannot be expected that Bangladeshi industries will be able to perform as Japanese or German industries. On the other hand, allowing industries a totally unregulated regime of energy usage will lead to unbridled consumption, especially if energy prices are not made market based. Starting with a reasonably lax standard, progressive tightening of those standards over a number of years will allow industries to adjust as well as ensure good energy management. SREDA's Energy Management Program is shown Figure 5. 22 Figure 5. Energy Management Program OF SREDA Source: Energy Efficiency and Conservation Master Plan up to 2030, SREDA, 2015. Policies and programs to encourage setting up new industries with high efficiency By 2030 Bangladesh's energy demand will increase 3 to 5 times depending upon what gross domestic product (GDP) growth rates are assumed. In the most conservative scenario, it is expected to grow by 2.5 times. In the period between now and 2030, more than half of the existing stock of machinery, equipment, and devices will need to be changed. Therefore, EE programs to change existing stock is not likely to yield significant savings. Since more than 80 percent of the energy consuming technologies are going to be newly installed, it is better to concentrate on programs that will prevent inefficient technologies from being installed and promote the efficient technologies so that these are preferred. This will also be cost-effective because programs that work with existing stock have to deal with the cost of discarding inefficient technologies. The following two issues require attention to promote energy efficient technologies: • Control of import of energy inefficient products • Energy pricing Probably the single-most important factor in promoting energy efficiency is energy pricing. In recent years, the electricity prices have been enhanced, but the price of gas is being kept artificially low. As mentioned earlier, nearly all large or energy-intensive industries depend on captive generation using very low-priced gas. The following examples will illustrate the negative impact of low prices: • Gas is so cheap that it is not cost-effective to install waste heat boilers to raise steam. Thus, in most industries, NG is burned to produce steam though waste heat of the gas engine generators could be used for that purpose. • The savings from EE improvement in reduction in gas bill is so low that industrialists do not bother to tune their boilers or undertake other EE options. • Industries that have captive generators can produce their own electricity at less than Tk 2.5/kWh, while a similar industry that buys electricity from the grid has to pay Tk 7.5/kWh leading to unfair competition 23 Since 2005, the country has been experiencing electricity and gas shortages. In the last five years, using hurriedly built oil-fired power stations, the government has alleviated the electricity shortage but at the cost of increased electricity prices. Gas shortage and high electricity prices have actually forced many industries into conservation and EE improvement. Rather paradoxically, the energy intensity of the economy has actually improved. In the economic growth stage that Bangladesh is at now, the energy intensity should increase. VI. Analysis of Energy Efficiency Options In this report, sixteen demand-side EE improvement options have been analyzed to study the energy savings potential up to 2030. The reasons behind the selection of these EE improvement measures are provided in the previous section. In this section, the results are presented, analyzed and discussed. Annex 1 gives the summary of the assumptions used to construct the ‘BAU’ and ‘efficiency' scenarios, while annex 2 gives the assumed growth rates and the numbers of existing and replacement efficient devices/equipment of the different options. For most options, there is only one basic device, but for lights, motors, boilers, and chillers, there are more than one. The growth rates of the total number of units (inefficient plus efficient) of each option vary between 4 and 11 percent except for cogeneration, which experiences no growth between 2015 and 2030. These growth rates were taken from several sources15 but were modified using expert judgment to suit the needs of this study. Table 6 provides a snapshot of the analysis done in this work. The savings potential is given as baseline energy consumption in BAU scenarios minus energy consumption in efficiency scenarios. The efficiency scenario has been constructed assuming a certain penetration rate of the efficient device. Therefore, the energy savings do not indicate the maximum potential. The maximum potential shown in table 6as 'technical potential' is 100 percent penetration of the energy efficient device/process. The penetration or diffusion rate of the energy efficient device/process will depend on many factors. The SNC, the EE&C Master Plan of SREDA, and expert judgment have been employed to shape these assumptions. Table 7 shows the savings potential in 2030 in primary energy as well as final electricity consumption for end-use sectors. The conversion of GWh has been accomplished by assuming an average power generation efficiency of 40 percent and T&D loss of 10 percent in 2030. It is worth pointing out that the generation efficiency in 2015 was 33 percent and the T&D loss was 15 percent. Since the Bangladesh Government is investing heavily in power generation and T&D infrastructure, it seems reasonable to assume efficiency gains by 2030. The 16 options analyzed for EE improvement potential in the demand side indicate that a total of 370 PJ can be saved in the year 2030. The projected total primary energy requirement in 2030 is approximately 2800 PJ.16 The savings therefore amount to 13.2 percent of the total primary energy requirement. The avoided electricity generation capacity as a result of the electricity saving options amounts to 3,201 MW. This is a significant saving given the fact that only 16 EE measures were considered and the projected average electricity demand in 2030 according to the Power System Master Plan (PSMP), 2016 is less than 25,000 MW. Even if the projected peak demand according to the PSMP 2016 of 27,000 MW is considered, the savings amount to 12 percent. 15 SNC, Government of Bangladesh, 2005; EE&C Master Plan, SREDA, 2014; and Intended Nationally Determined Contributions (INDC), Ministry of Environment and Forests (MoEF), 2016. 16 This figure is slightly modified from that of the SNC and SREDA Master Plan 24 Table 7 also presents the percentage of total technical potential likely to be achieved. These values derive from the penetration rate. Thus, efficient lights are expected to constitute 77.4 percent of total lights in 2030. The penetration rates for different options vary between 49 percent and 100 percent. For most options, the penetration rate is between 70 percent and 90 percent. The potential of energy savings of each option compared to the other 15 options is better appreciated from Figure 6. As can be seen, the highest total energy savings potential is that of motors and boilers. This is to be expected because motors are cross-cutting technologies employed in all sectors, and boilers are the most common industrial equipment consuming primary energy. The other options having significant energy savings potential are the devices used in all sectors, but mainly in the residential sector, such as lights and fans. It is important to point out that for two very significant options, namely, cogeneration and fertilizer, the estimated energy savings potential in this study is limited to the infrastructure that exists in 2015. This is because of the government's decision to limit supply of gas to certain categories of customers. The government has decided to phase out captive generation in industries, a practice that was started when the national electricity grid was highly unreliable with long hours of load- shedding. Since the grid has become somewhat reliable and load shedding is greatly reduced, the government wants to divert gas supplied to low-efficiency captive generators to high-efficiency CCGT power plants. With regard to fertilizer, the government is committed to the production of urea fertilizer in the country rather than importing it. Since the government plans to build new plants having high efficiencies, the full technical potential of this option is restricted to the five existing ammonia-urea fertilizer plants. The EE option considered in the efficiency scenario, for the fertilizer industry, is to shut down the five old plants and construct 'new state-of-the-art ammonia-urea fertilizer plants'. The challenge in securing investment to build these giant plants (each costing over US$500 million) is considerable. Furthermore, the multilateral organizations, which were keen to fund these large plants, are now advocating private sector or public-private partnership funding for these. Between 1995 and 2015, no urea fertilizer plant was built. However, one 2,000 tons/day plant went into production in 2016. Another new plant having double the capacity, that is, 4,000 tons/day is being planned. This plant will replace two old plants—one of capacity 1,760 tons/day and one smaller one of 800 tons/day. Of the energy-intensive industries, the steel options are the most significant. The steel mills are not primary steel mills—these melt scrap steel to produce ingots. Therefore, the option here is replacing the inefficient induction furnace. Similarly, the cement mills merely grind imported clinker to produce cement. Inefficient ball mills are used in the grinding operation. These can be replaced by more efficient vertical roller mills (VRMs). The chiller option refers to vapor compression chillers running on electricity used in numerous industries for cooling. The cold storage option is merely a special case of chillers. Cold storages are warehouses for storing vegetables. Usually 300–500 kW chillers are used to keep these warehouses at the desired temperature. There are numerous ice plants and central air-conditioning units that employ chillers. The AC option for the residential sector is also a cooling option. The cooling load in the hot summer months is a significant load for the entire generation system of the country, and one study has estimated that more than 50 percent of the generation capacity need to be devoted to meet this load. 25 Table 6.Summary of analysis of EE improvement potential of different options in 2030 2030 2030 Savings 2030 (EE) Technical No. Option (BAU) (EE) (Maximum) Potential Remarks (a) (b) (a) − (b) (c) (a) − (c) Devices 1 Lights (GWh) 9,831 4,744 5,087 3,566 6,265 Fluorescent, CFL, LED 2 Fans (GWh) 15,072 10,895 4,177 10,341 4,731 Efficient fans 3 Refrigerator (GWh) 12,026 8,369 3,657 6,330 5,696 Efficient refrigerators 4 AC (GWh) 6,735 5,112 1,623 4,455 2,280 Split ACs with higher energy star rating Cross-cutting 5 Motors (GWh) 18,948 15,870 3,078 14,697 4,251 Synchronous belt + VFD + efficient motors 6 Boilers (TJ) 38,2684 336,962 45,721 321,478 61,206 Air control + insulation + economizer 7 Cogeneration (TJ) 113,480 95,364 18,116 66,669 46,811 Waste heat boiler, absorption chiller Efficient chillers of Coefficient of Performance 8 Chillers (GWh) 5,275 3,935 1,790 3,241 2,034 (COP) greater than 5 Industrial subsector Servo motors, automation of aeration system, 9 RMG (GWh) 5,020 3,621 1,399 3,262 1,758 heat recovery 10 Textile dyeing (GWh) 1,549 953 595 857 692 CP Steel: Induction furnace 11 Melting furnace (GWh) 6,156 4,375 1,781 3,803 2,353 Burner + air control + insulation + waste heat 12 RRM(TJ) 9,988 6,386 3,602 5,968 4,020 recovery 13 Cement (GWh) 2,638 2,153 485 2,012 626 VRM 26 2030 2030 Savings 2030 (EE) Technical No. Option (BAU) (EE) (Maximum) Potential Remarks (a) (b) (a) − (b) (c) (a) − (c) Cold storage/ice plants 14 629 409 220 317 312 High COP chiller + insulation (GWh) 15 Fertilizer (urea) (TJ) 114,910 71,450 43,450 71,460 43,450 New plants 16 Textile weaving (GWh) 4,502 2,563 1,939 2,273 2,229 Air-jet looms 27 Table 7.Savings of primary energy (TJ) and power requirement (MW) in 2030 Savings Percentage of the No. Name Savingsb (TJ) MW Savings (GWh or TJ)a Technical Potential Devices 1 Lights 5,087 GWh 50,870 581 81.2 2 Fans 4,177 GWh 41,770 477 88.3 3 Refrigerator 3,657 GWh 36,570 417 64.2 4 AC 1,623 GWh 16,230 185 71.2 Cross-cutting 5 Motors 3,078 GWh 30,780 351 72.4 6 Boilers 45,721 TJ 45,721 n.a. 74.7 7 Cogeneration 18,116 TJ 18,116 n.a. 38.7 8 Chillers 1,790 GWh 17,900 204 88.0 Industrial subsector 9 RMG 1,399 GWh 13,990 235 79.6 10 Textile dyeing 595 GWh 5,950 100 86.0 Steel: 11 Melting furnace 1,781 GWh 17,810 203 75.7 12 RRM 3,602 TJ 3,602 41 89.6 13 Cement 458 GWh 4,580 56 73.2 14 Cold storage/ice 220 GWh 2,200 25 70.5 plants 15 Fertilizer (urea) 43,450 TJ 43,450 n.a. 100.0 16 Textile weaving 1,939 GWh 19,390 326 87.0 Total (TJ) 368,929 3,201 Note: a. Taken from table 6. b. Those options in GWh have been converted to primary energy in TJ. To convert power generation efficiency has been taken as 40 percent and the T&D loss as 10 percent. In 2015, the generation efficiency was 33 percent and T&D loss was 15 percent. 28 Figure 6.Energy savings potential in 2030 of different options VII. Short-, Medium-, and Long-Term Options The savings potentials in 2020 (short term) and 2025 (medium term) are given in Table 8. The results are better appreciated from Figure 7 and Figure 8. The short-term options that have savings options of more than 8,000 TJ/year (calculated for 2020) are considered to be significant and can be targeted immediately. These energy savings options are the following: (a) Motors (b) Urea fertilizer plants (c) Boilers (d) Cogeneration (e) Lights The significant medium-term options are those that have energy savings potential of more than 15,000 TJ in 2025. These options should be targeted after the short-term options. The options in this category are the following: (a) Motors (b) Boilers (c) Urea fertilizer plants (d) Cogeneration (e) Lights (f) Fans 29 The significant long-term energy savings options are deemed to be those that have energy savings potential of more than 25,000 TJ/year as calculated in 2030. The options in this category are the following: (a) Boilers (b) Motors (c) Lights (d) Urea fertilizer plants (e) Fans (f) Refrigerators It should be noted that motors, boilers, and lights figure prominently across all the three categories. The reason behind this is that in this study more emphasis has been given on cross-cutting technologies. This approach ensures that all industries, small, medium, and large enterprises, are targeted. This approach, however, gives a misleading picture of many of the industrial subsectors' energy savings potentials. For example, in the RMG and textile sectors the potential even in 2030 is low. The options considered in the RMG and textile sectors are only the process improvements or those options that are not covered by generic or cross-cutting technologies. Since a large portion of the energy savings potential in the RMG and textile sectors will be lights, motors, boilers, chillers, and cogeneration, the actual potential will be more than double what is shown in Table 6 and Figures 6 to 8. If the total potential in the RMG was shown, then it would amount to double counting. A well-designed EE program will, of course, target all the 16 options, but when resources are limited, it is best to start with short-term options and then gradually move on to medium-term and long- term options. This can be considered to be a prioritization of implementation. The interesting thing about the options in different categories is that some of the options change places moving from 2020 to 2030 and some options move out of the top 5 ranking in 2030, while some options appear for the first time in the significant list. The most noteworthy disappearance is the captive power plant (CPP) waste heat cogeneration because the government has decided not to give any further new captive generation gas connections to industries. Therefore, this option is targeted immediately and with full attention in the 2020 option only. An option that acquires prominence in 2030 is refrigerators. The desire of every single household—urban or rural, rich or poor—in owning a refrigerator and a freezer is propelling this growth. This also adds to space cooling and associated load that the electricity grid has to cope with. As remarked earlier, the cooling load more than doubles from winter (December-January) to summer (March-April and August- September). This is the reason that in this study the demands for electricity by cooling devices and appliances—ACs, chillers, and cold/storages—have been given higher emphasis. As the economy grows and standard of living improves, the cooling load will increase. Table 8.Savings potential in 2020, 2025, and 2030 Savings (GWh or TJ) No. Name 2020 2025 2030 1 Lights 869 GWh 2,019 GWh 5,087 GWh 2 Fans 107 GWh 1,527 GWh 4,177 GWh 3 Refrigerator 129 GWh 1,241 GWh 3,657 GWh 4 AC 173 GWh 689 GWh 1,623 GWh 30 Savings (GWh or TJ) No. Name 2020 2025 2030 5 Motors 1,300 GWh 2,072 GWh 3,078 GWh 6 Boilers 16,950 TJ 29,343 TJ 45,721 TJ 7 Cogeneration 14,259 TJ 20,528 TJ 18,116 TJ 8 Chillers 535 GWh 1,069 GWh 1,790 GWh 9 RMG 467 GWh 946 GWh 1,399 GWh 10 Textile dyeing 116 GWh 307 GWh 595 GWh 11 Steel melting furnace 117 GWh 496 GWh 1,781 GWh 12 Steel RRM 263 TJ 1,258 TJ 3602 TJ 13 Cement 29 GWh 140 GWh 458 GWh 14 Cold storage/ice plants 13 GWh 57 GWh 220 GWh 15 Fertilizer (urea) 21,620 TJ 30,080 TJ 43,450 TJ 16 Textile weaving 512 GWh 1,223 GWh 1,939 GWh Figure 7. Energy savings potential in 2020 of different options 31 Figure 8. Energy savings potential in 2025 of different options VIII. Cost Implications of Energy Efficiency Options This section presents a back-of-the-envelope calculation of the relative cost-effectiveness of the 16 different options analyzed in this report. This was undertaken to provide a quick proxy for assessing the cost versus benefits of these EE options and has generated a ranking of the net cost per unit of energy saved (in US$/GJ) from implementing each EE option.17As it indicates the net cost to save one unit of energy, the value can be either positive or negative. A negative value associated with the cost of energy saved, as is common for most EE options, indicates that the initial investment in that EE option will be recovered through the monetary value of energy savings, during a certain payback period, and the monetary value of energy savings will continue to accrue over the remaining lifetime of that EE option, thereby actually yielding a profit. On the other hand, a positive cost-effectiveness implies that investment cost will not be recovered fully; that is, on a net basis, money will have to be spent to save energy. Assumptions To perform the calculation of US$/GJ, the following assumptions and data were used: (a) Discount factor = 10 percent (b) Price of electricity = US$0.10/kWh (c) Price of NG = US$2.4/GJ (d) Replacement of inefficient units is considered up to 2030, which is the end year of the study period. (e) Energy efficient units installed will yield energy savings benefit until the end ofservice life considered. For most options, useful life is 15 years. This implies that the calculations go 17 The literature on EE and GHG mitigation has traditionally used the concept of cost-effectiveness with units of US$/GJ saved or US$/ton of CO2 reduced, respectively. Cost-effectiveness in this report is represented by the cost of saved energy. The cost of saved energy associated with EE investment has nothing to do with net present value (NPV) of the investment, which is estimated with respect to the supply-side option that the EE option is displacing. 32 beyond the study period, that is, 2030. The savings from those efficient units installed in 2030 are accounted for up to 2045. (f) All prices have been kept fixed, that is, no escalation or inflation have been considered. (g) All efficiencies have been kept fixed. The discount factor chosen is the one generally applied by the World Bank for such calculations. The prices for electricity and gas chosen for this study require some discussion. Since electricity tariffs are different for different sectors, choosing one single value proved to be difficult. The problem is further aggravated by the fact that the tariffs for the residential sector are in slabs and over a wide range. The lowest tariff of US$0.05/kWh is paid by those consuming below 100 kWh, and the highest tariff paid for consumption above 500 kWh is US$0.125/kWh. Cost-effectiveness calculations are sensitive to the value used for tariff and give different results. Another issue is the type of consumer using the energy device/equipment under consideration. For example, lights are used by all types of consumers, while ACs are used by affluent consumers whose monthly consumption will certainly fall in a slab where they will be paying above US$0.08/kWh. In households where there are several ACs, a significant portion of the bill may have to be paid at US$0.125/kWh. Fans, like lights, are used by all consumers except probably those who are on the lifeline tariff. The number of fans in affluent households is, however, several times more than that in households whose monthly consumption is below 200 kWh. The use of refrigerators is also skewed toward the more middle- and high-income households. Therefore, the cost-effectiveness will greatly depend on the sector chosen to implement an EE project. For example, the electricity tariff for the commercial sector is a flat US$0.12/kWh. Thus, if an AC EE project is formulated for the commercial sector, its prognosis would be much better than one for the residential sector, where the tariff in all but the highest slab is lower than the flat rate commercial tariff. Similarly, cost-effectiveness of an EE option in the SME sector, where tariff is lower, will be far less favorable than in the large industries or the commercial sectors. A negative cost-effectiveness option may become positive if the electricity price is too low. To overcome these kinds of problems, studies generally use economic prices that are free from subsidies, cross-subsidies, or taxes. However, determining economic prices for a country where all kinds of price distortions exist is not a simple task. Therefore, a value that reflects the true cost of electricity and is also close to the tariff of several sectors was chosen, which is US$0.1/kWh. This tariff value is lower than the highest tariffs paid in the country but is considerably higher than that for most residential customers and the SMEs. In the specific context of Bangladesh, the electricity tariff used has another typical issue associated with it. In Bangladesh, several large industries (steel melting, cement, and textile options) generate their own electricity using NG. The cost of electricity in these industries is less than US$0.05/kWh compared to industries that have to buy electricity from the grid at US$0.10/kWh. Therefore, the monetary value of saved electricity for industries that generate their own electricity using cheap gas is much lower than those using grid electricity. With the price of NG, the problem was even greater because the public sector industries (power and fertilizer plants) pay only US$1.00/1,000 cft (or million Btu or GJ). Private sector industrial customers pay for gas a higher price of US$2.4/GJ and US$3.0/GJ for industrial heating use and captive power generation, respectively. These gas prices are much lower than those in most other countries. For example, in India, it is around US$5.0/GJ. All the gas EE options considered in this study are industrial options (boilers, steel RRM, cogeneration, and fertilizer). The cogeneration option displaces industrial gas through the production of steam using waste heat. The fertilizer option uses highly 33 subsidized gas, which could be used in other industries. Therefore, for this study, the industrial tariff of US$2.4/GJ was used to compare all options. Calculation Methodology The cost-effectiveness calculations over 2015–2030 use the projected numbers of the energy inefficient and energy efficient devices/equipment/processes shown in the graphs in appendixes A to Z. In each year, the investments for new energy efficient units are represented as positive cash flows, while the monetized energy savings, due to reduced electricity/gas consumption, are considered as negative cash flows.18The cost-effectiveness (or cost of saved energy) for each EE measure is the summation of these cash flows over 2015–2030, discounted to the present (2015). To bring the electricity EE options to the primary energy (GJ) terms, the average power plant efficiency and T&D losses in the year 2030 had to be assumed. The average power plant efficiency is assumed to improve from 33 percent in 2015 to 40 percent in 2030, while the T&D losses are assumed to improve from 15 percent to 10 percent during the same period. Cost-Effectiveness of EE Options Figure 9 shows cost-effectiveness of the various options to reduce energy consumption computed over 2015–2030. As can be seen, other than the four options, cogeneration, fertilizer, steel melting, and air-jet looms, all other EE options have a negative cost-effectiveness, implying that investments in EE measures will not only be recovered but will actually yield a return over the lifetime of the EE measure. But, even in the case of the four ‘positive’ cost-effectiveness options (cogeneration, fertilizer, steel melting, and air-jet looms),the cost of saving energy will be cheaper than the marginal supply cost of gas at US$3/million Btu. Sensitivity Analysis Choosing a higher electricity or gas price will make the cost-effectiveness of all the options even more attractive for investments because the monetized value of energy saved will be higher. The cost of saved energy for theair-jet loom option will become 'zero', at an electricity tariff of US$0.19/kWh. Such a high tariff for electricity cannot be justified in 2017, even though such values are not uncommon in European countries or some parts of the United States. In 2030, as a result of inflation and the fact that a large quantity of the primary energy for power generation will have to be imported, this high tariff value can become a reality in Bangladesh also. Since there is no possibility of the electricity or gas tariffs coming down, considering a lower tariff for the cost- effectiveness calculations need not be considered. The two positive cost-effectiveness options, cogeneration and fertilizer, at a 10 percent interest rate and with gas price being US$2.4/GJ, are financially nonviable projects. However, it is worth noting that the actual price of gas paid by the public-sector fertilizer industries is only US$0.9/GJ. If this artificially subsidized gas tariff is used for calculating the cost-effectiveness, then the cost- effectiveness becomes even more positive and reaches a value of 3.27 and the EE measure becomes nonviable. One reason why fertilizer is an expensive option is that the study considered replacing the old plant with an entirely new plant. If a retrofit option was considered for the fertilizer plant, then the cost-effectiveness (cost of saved energy) would have been lower and be more attractive. But it must be borne in mind that these large fertilizer plants are way past their useful life, and retrofits 18 Since initial investments in an EE option represent money going out (that has to be spent), the convention followed here is that it is considered positive cash flow. As a result, the energy saving accruing as a result of that investment, which is money coming in, is considered as negative. 34 and repairs have their limits. A sensitivity calculation showed that only at a very high gas price of US$11.2/GJ, the cost-effectiveness of the fertilizer option becomes zero. Similarly, the cogeneration option can be made 'zero' with a gas price of US$6.3/GJ. A lower interest rate (or discount rate) or higher price of energy/electricity will naturally favor EE projects yielding negative cost-effectiveness (or lower cost of saved energy). As NG starts to deplete in Bangladesh, and the country begins to add imported liquefied natural gas (LNG) to its gas supply mix, it is likely that a gas price scenario will continue with higher gas prices over the next two decades. It is estimated that when all domestic NG is depleted, the minimum price at which gas can be imported as LNG and supplied to consumers may be in the region of US$10/GJ or more. As can be seen, the current price of electricity and gas is fairly low when compared to international market prices. Despite this, the cost of saved energy for most options considered in the analysis is either low or negative, even with conservative assumptions of low energy prices. Therefore, it can be concluded that, in the Bangladesh context, the EE project investments will continue to be attractive as they entail a favorable rate of return. Therefore, policy makers should consider EE projects and programs should be implemented in a larger scale, as a part of the energy sector development roadmap in Bangladesh. The analysis in this study has used costs of EE technologies only. It has not considered the benefits of reduced GHG emissions and local air pollution in the cost-effectiveness calculations. To implement the EE options, however, appropriate programs and projects have to be designed that will address the implementation, institutional, financing, and delivery barriers. Moving from an EE technology to actually deliver energy savings through any implementation mechanism will therefore incur additional transaction costs, which can also be interpreted as the cost of addressing barriers. If implementation or transaction costs are added to the technology costs, the delivery costs of all the EE options will increase depending upon the specific implementation model and delivery mechanism that will be used. In this situation, even some of the negative cost-effectiveness options shown in the earlier analysis, especially those EE options that are at the margin, such as steel melting, refrigerator, boilers, and RRMs, may actually become positive cost-effectiveness options; that is, the cost of saved energy for these EE measures will be no longer negative but become positive. However, the transaction costs vary by the type of implementation mechanism or delivery model that is used. For instance, regulatory policy mechanisms will entail different implementation costs from utility DSM models, which will be different from implementation through ESCOs. Table 9 Cost of Saved Energy Total Potential Cost of Saved Energy(US$/GJ) (2015 to 2030) (PJ) Light −2.75 586 Chillers −2.59 261 Textile −2.40 89 Motors −2.36 416 Cold storage −1.86 20 Cement −1.58 77 AC −1.57 255 RMG −1.55 10 Fan −1.39 706 Refrigerator −1.0 609 Boilers −0.46 541 35 RRM −0.19 54 Steel melting 0.13 279 Cogeneration 1.38 243 Looms 2.24 304 Fertilizer 2.79 652 36 Figure 9.Cost-effectiveness of different EE options in 2030 37 IX. Scale Up Potential of Energy Efficiency Options Figure 10 shows the cost-effectiveness or cost of saved energy (US$/GJ) of an EE option versus the total energy savings potential (in PJ) of that EE option, for 2015–2030. As can be seen, some EE options have significant energy savings potential, while others have very little. Most noteworthy among the low-potential options are the RMG and textile options. This may appear counter intuitive because the RMG and textile subsectors are the two largest industrial subsectors. These two account for more than 80 percent of all industrial production. The reason behind this anomaly is that this study analyzed mainly generic and cross-cutting technologies/devices/equipment in all the sectors. This implies that a significant proportion of the EE improvement potential in industries such as RMG and textiles have already been accounted for because these industries all have lights, fans, boilers, motors, and/or chillers. Therefore, in these industries, only specialized equipment/devices and process improvement are considered. For example, in RMG industries, electronic ballast and servo motors for sewing machines have been considered. Similarly, in textile weaving, only replacement of rapier looms by efficient and high- productivity air-jet looms have been considered. In textile dyeing, only process improvement through CP has been considered. It must be emphasized that the potential of EE shown for these industries is partial and deals with the main process and excludes the opportunities from the cross- cutting technologies, which have been accounted for as separate EE options. Had all the options for EE improvement been considered, which mainly include motors, boilers, and chillers, the total potential for RMG and textile subsectors will significantly increase. Figure 10 can be used in prioritizing the actions based on a criterion that consolidates both parameters, that is, cost-effectiveness (cost of saved energy in US$/GJ saved) and the energy savings potential (in PJ).While the former parameter is a good indicator of the attractiveness of investment at the end-user consumer level (that is, industries, utility, or ESCOs), from the government policy maker’s perspective, the EE measures that also score high in the total volume of potential energy savings could be a better candidate for support. 38 Figure 10.Energy savings potential of different options X. Consolidated Ranking of Energy Efficiency Options From the data on cost-effectiveness (cost of saved energy) and energy savings potential, it is noted that while some EE options rank higher in the cost of saved energy (that is, have lower and even negative values), others have larger volume of potential energy savings. The 16 options analyzed in this study have been ranked in Table 10using both the parameters—cost-effectiveness (cost of saved energy in US$/GJ) and energy savings potential in PJ. A score of 0 to 10 has been assigned to these two parameters with 10 being good and 0 being bad. The summation of the two scores for cost and potential determined the consolidated rank. The option that received the highest consolidated score was ranked 1 (in last column of Table 10), while the option with the lowest score was ranked 16. As discussed in the next section, the implementation of EE projects and programs requires addressing many EE barriers. Moreover, these barriers may be different for different EE technologies and sectors, and the transaction costs of addressing these barriers will depend on a variety of factors such as what implementation mechanisms or delivery models are being used, the readiness of the sector with regard to regulations and technical capacity, awareness of EE among the consumers for a specific end-use or sector, and so on. The consolidated ranking shown in Table 10 can be improved further by including 'barriers' as a third parameter. Since determining the barriers and assigning scores is a complex task, the consolidated ranking of EE options in Table 10does not consider barriers; instead, the barriers are qualitatively assessed in the next section. 39 Table 10. Ranking of EE options Score on the Basis of Total Options Cost of Saved Total Energy Rank Score Energy Savings Potential Light 10 8 18 1 Fan 6 10 16 2 Motors 9 6 15 3 Chillers 10 4 14 4 Refrigerator 5 8 13 5 Boilers 4 7 11 6 AC 7 4 11 6 Textile 9 2 11 6 Fertilizer 0 9 9 9 Cement 7 1 8 10 Cold storage 8 0 8 10 Looms 1 5 6 12 Cogeneration 2 4 6 12 Steel melting 3 3 6 12 RMG 6 0 6 12 RRM 3 1 4 16 XI. Barriers and Implementation The principal barriers to investment and implementation of energy efficient technologies are as follows: (a) Lack of awareness regarding EE technologies and their benefits (b) First cost barrier—the high initial investment is a deterrent (c) High interest rates on commercial loans (d) Unfavorable taxes and duties on energy efficient technologies (e) Disruption of operation to perform the retrofit Table 11 lists the barriers to investment and large-scale implementation of the energy efficient technologies, considered in this study. The table also lists a few implementation strategies. These barriers need to be systematically removed to successfully implement an EE program. Usually it is not possible for the private sector to tackle all the barriers by themselves, and therefore, significant support is needed from the government. In Bangladesh, SREDA has been entrusted with this responsibility. SREDA is supposed to be a one-stop shop for renewables and EE, but SREDA has only been set up recently and has manpower limitations that prevent it from providing the support that will remove these barriers. In India, the Bureau of Energy Efficiency (BEE) has been promoting EE for over two decades and has been able to show real success in removing many barriers. Commercial lending institutions need to be sensitized and trained to lend to industries for EE projects. Without adequate awareness and funds at reasonable cost, EE programs cannot be promoted. At the end, however, there is no alternative to regulatory pressure. Implementation of EE programs and projects depends strongly on the type of intervention and the efficient technology in question. Thus, a 'fan' dissemination program will be very different from a 40 'fertilizer' retrofit project. The implementation strategies listed in Table 11 can be categorized into the following approaches: (a) Standardization (MEPS) and EE labeling programs (b) Utility-driven programs (c) Energy audit and energy management program (d) Incentives-based programs Implementation of EE projects are never easy. Not only are there many barriers that directly complicate implementation, but there are also many indirect barriers. The indirect barriers are to do with inertia of the owners and workers of industries. This is especially true for industries that are running smoothly and profitably. In such cases, the EE retrofit or changeover yields very little financial gain. Such is also the case when electricity and/or fuels are cheap or subsidized. The gain from an EE project is not enough to justify a disruption of operation. In fact, industries can lose money as a result of an EE retrofit. EE implementation programs must therefore be very carefully designed. It is often not sufficient to provide low-cost financing and demonstrate the benefits of energy efficient technologies. A well- structured regulatory regime enforced and managed by a competent agency is crucial for the success of an EE program. 41 Table 11.Barriers and Implementation of EE Options No. Name Barriers Implementation 1 Lights Unless costs of EE light bulbs come down significantly, A utility-driven program is best for implementation. EE light bulbs can poorer households would be reluctant to replace be distributed and a monthly charge can be added to the bill, or bulbs incandescent bulbs. Many users may not be aware of the EE can be given at subsidized prices in exchange for the bulbs being lighting options. replaced. 2 Fans The efficient model may not be available everywhere and Awareness campaign coupled with the STAR rating of fans. A utility- users may not be aware that EE models exist. driven program can also be designed. 3 Refrigerator The first cost barrier is significant in this option. Incentives for EE models and disincentives for inefficient model are the way forward. Importers and retailers of the EE model have to be targeted. 4 AC Awareness is the principal barrier. Initial investment is also Widespread demonstration of the benefits of the EE model is needed. a barrier. Disincentives for the inefficient model are important. 5 Motors Efficient motors are not only expensive but also difficult to Since most motors are imported, some sort of disincentives for procure. Moreover, there is a general lack of awareness inefficient motors and incentives for efficient ones at the customs duty regarding efficient motors. level can promote this option. 6 Boilers Most boilers are efficient when new. Lack of maintenance is SREDA in association with gas utilities can effectively enforce a generally the principal reason behind low boiler efficiency. program that will ensure efficiency improvement. 7 Cogeneration The low price of gas is the principal barrier. Lack of A combination of pressure from SREDA and technical support to complete information including the need to perform a full perform the energy audit and design the cogeneration system is audit is also a barrier. important for implementation. ESCOs can play a big role here. 8 Chillers Efficient chillers are generally much more expensive than Low-cost financing can be helpful in implementing this option through standard chillers. ESCOs. 9 RMG Awareness is the principal barrier. A combination of regulatory pressure and awareness building can be effective in bringing about efficient operation. An ESCO can be engaged to implement this option. 10 Textile dyeing There is a general lack of awareness regarding CP. The Setting up a CP center will address the awareness and information investment requirement for full CP implementation can also barrier. An ESCO can be used to implement this option. be significant. 11 Steel melting The high cost of the efficient furnace is the principal barrier. Low-cost financing is one way to convince industrialists to implement furnace this option. 12 Steel RRM The disruption in operation is the principal barrier. The low SREDA can assist in performing energy audits to ascertain the savings price of gas implies that the payback period will be long, and potential. Low-cost financing coupled with regulatory pressure can as a result industrialists are not fully convinced about the help in implementing the EE measures. savings due to the proposed retrofit. 42 No. Name Barriers Implementation 13 Cement The initial investment to replace the grinding mill for Low-cost financing along with motivational campaigns can implement existing industries and for new ones to purchase the more this option. efficient mill is the principal barrier. 14 Cold The high initial investment cost of the more efficient option Low-cost financing and demonstration projects can assist in storage/ice is the principal barrier. implementing this option. plants 15 Fertilizer The investment required to build new state-of-the-art urea These are public sector industries. These plants are being operated way (urea) fertilizer plants is the main barrier. beyond their useful lives. In most cases, efficiency improvement involves building new plants. The government has to find funds, and multilateral and bilateral organizations can be approached to fund these large plants. 16 Textile Awareness is the principal barrier. Initial investment is also Low-cost financing is one way to convince industrialists to implement weaving a barrier. this option. 43 Annex 1: Assumptions used for the Baseline and EE Scenarios No. Name Baseline Scenario Assumptions EE Scenario Assumptions 1 Lights A composite growth rate has been assumed based on GDP growth rate. • Growth rate of incandescent bulbs will be negative. • T8 bulbs will increase slowly at first and later start decreasing. T5 bulbs will steadily increase. • CFL will increase at a steady but slow growth rate. • LED will grow faster than any other lighting option because it is expected to be promoted through government programs. 2 Fans A composite growth rate has been assumed based on GDP growth rate. In • Growth rate of inefficient fans will decrease and eventually will 2015, 85% fans are the inefficient type. be negative. • Efficient fans will increase rapidly. 3 Refrigerator A composite growth rate has been assumed based on GDP growth rate. In • Growth rate of regular refrigerators will decrease. No growth of 2015, 90% refrigerators are inefficient (energy star rating less than 3). inefficient refrigerators after 5 years. • Efficient refrigerators will increase slowly, but after a few years, the rate of increase will accelerate. 4 AC A composite growth rate has been assumed based on GDP growth rate. In • Growth rate of inefficient window ACs will be zero. The 2015, 95% of ACs are the less efficient types (energy star rating 3 or less). inefficient split ACs will increase initially but the growth rate will decrease • Efficient ACs will increase slowly at first, but these will increase rapidly after a few years. 5 Motors The electricity consumption in the industrial sector in Bangladesh has a V-belt-driven motors will be phased out by 2030. The number of growth rate of 8%/year. The rate is therefore used for the growth in VSDs installed has been assumed to be 25% of the total. Efficient power consumption by the electric motors. The motor size distribution motors are expensive. Therefore, only 5% of the motors above was estimated from the growth rate of small, medium, and large 10HP are assumed to have been replaced by efficient motors. industries. Different growth rates have been assumed for different EE technologies. 6 Boilers Growth rate will be 15% for the first five years, which is in line with the An efficiency increment by 5 percent was assumed with proper growth of the RMG and textile sectors. The growth assumed to be 10% insulation of boilers. Controlling/reducing excess air is assumed to and 8%, respectively, for 2021–2025 and 2026–2030. increase the efficiency by 4 percent. It is assumed that the installation of economizers will increase the boiler efficiency by 4 percent. Recovery and reuse of condensate will further increase the efficiency by 4 percent. Only boilers with capacity more than 5 tons/hour were assumed to accommodate this technology. 44 No. Name Baseline Scenario Assumptions EE Scenario Assumptions Different growth rates for different EE technologies have been assumed. 7 Cogeneration The number of CPPs is not going to increase since there will be no NG The EE scenario assumes that maximum potential of energy saving allocation for new CPPs. Approximately 30% of the CPPs are doing by CPPs will be achieved by 2025. Not all the CPPs, approximately cogeneration. 35%, have potential as combined heat and power (CHP) and therefore operate as they are operating now. 8 Chillers The growth in the number of chillers is assumed to be 8 percent. It is assumed that the number of chillers with capacities less than 500 RT will decrease by 10% per year till 2020 and will decrease by 5% per year from 2021-2030. For larger capacity chillers the decrement rate is assumed to be 5% per year till 2030. 9 RMG In 2015, there are about 5,785 RMG industries in Bangladesh. Each By 2030, there will be 9,012 RMG factories in Bangladesh, and by factory produces1 million pieces of RMG (knit and woven) per month, and the end of 2030, 7,172 industries will adopt efficient technologies 0.0468 kWh is required to produce every piece. to improve their EE. By implementing efficient technologies, the RMG industries will be able to reduce power consumption from 46.8 kWh/1,000 pieces to 30 kWh/1,000 pieces. 10 Textile dyeing In 2015, there are about 270 dyeing-printing factories with a production In 2030, there will be about 646 textile dyeing factories. By 2030, capacity of 15 tons fabric/day/factory. The energy consumed to dye 1 kg about 86% of the textile dyeing industries will adopt CP options to of fabric using traditional dyeing technique is approximately 0.47 kWh. improve their EE. Adopting CP options by the textile dyeing industries will reduce the power consumption required to dye each kilogram of fabric from 0.47 kWh to 0.26 kWh. 11 Steel melting The number of steel melting unit is about 150 and this will increase at the In 2030, there will be about 359 melting units with average furnace annual growth rate of 6% during 2015–2030. Total production is production capacity of 20,000 tons/year. It is assumed that about estimated in 2015 to be approximately 3 million tons. The average energy 50% of steel melting units will be converted to arc finance (more used per ton of production in induction furnace is 212 kg oil energy efficient, 130 kg oil equivalent/ton of production) by 2030 equivalent/ton of production. either on their own volition or as a result of SREDA's regulatory pressure. 12 Steel RRM In 2015, there are approximately 250 steel RRMs with a production It is assumed that approximately 90% of steel RRMs (energy capacity of approximately 3.5 million tons. The annual growth rate inefficient and responsible for 50% of total production) will considered is 6%/year. implement the energy efficient process. 13 Cement There are 45 cement factories with annual production of about 2.8 million In 2030, there will be 108 units with average capacity of 622,000 tons. The annual growth rate is 6%. Currently most industries are using tons/year. The less efficient ball mill will be gradually replaced (50% less energy efficient (40 kWh/ton) ball mill for clinker grinding. by 2030) by a VRM (with energy consumption of 30 kWh/ton of production). 45 No. Name Baseline Scenario Assumptions EE Scenario Assumptions 14 Cold Storage / There are approximately 400 cold storage facilities with 5 million tons of In 2030, there will be approximately 720 cold storage units. By Ice Plants storage capacity. The electricity consumption levels are as high as 70–150 2030, 50% of the units will adopt the energy efficient process. The kWh/ton. The growth rate is assumed to be 4%/year. COP will increase from 3.5–4.5 to more than 5.5. 15 Fertilizer In 2015, there are 7 urea fertilizer plants producing 1.28 million tons of Replacing the old less efficient plants with new, more efficient (urea) urea/year and consume 53.07 million GJ NG. The average efficiency is plants with double capacity. In 2030, the 7 plants will produce 2.78 39.20 MCF NG/ton urea. million tons/year and will consume 71.45 million GJ NG. The average efficiency will be 24.37 MCF NG/ton. 16 Textile In 2015, the annual production of fabric was 4.3 billion meters. With a By gradually replacing rapier looms by air-jet looms, the weaving Weaving growth rate of 2.5%, this number will increase to 4.87 billion meters by sector of Bangladesh will reduce the power consumption. It is end of 2020. Considering 3% and 3.5% growth rates for 2021–2025 and projected that, by the end of 2030, about 65% looms will be energy 2026–2030, respectively, it is projected that the annual fabric production efficient air-jet looms; hence, the energy consumption will be will increase to 5.64 billion meters and 6.70 billion meters by end of 2025 about 2,564 GWh. and 2030, respectively. 46 Annex 2: Growth Rates of Energy Consuming Devices/Processes Growth Rate No. Name Type and Average Size of Unit Numbers (%) 2015 2030 1 Lights Incandescent (60 W) 15.1 million 2.1 million −12.3 Fluorescent T8 (60 W) 14 million 5.7 million −5.8 Fluorescent T5 (40 W) 3.5 million 18.2 million 11.6 CFL (15 W) 36.6 million 109 million 7.6 LED (7 W) 1.18 million 58.6 million 29.7 Total 70.4 million 194 million 7.0 2 Fans Regular (100 W) 38.4 million 12.4 million −7.2 Efficient (65 W) 6.77 million 112 million 20.6 Total 45.2 million 125 million 7.0 3 Refrigerators Regular 14 cft (300 W) 4.7 million 4.7 million 0 Efficient 14 cft (150 W) 0.52 million 9.8 million 21.6 Total 5.2 million 14.5 million 7.1 4 AC Regular 1.5 ton (2,000 W) 1.08 million 0.86 million −1.5 Efficient 1.5 ton (1,300W) 56,800 2.27 million 27.9 Total 1.14 million 3.13 million 6.8 5 Motors 1-5 hp 75766 2413 -20.5 5-15 hp 33147 225 -28.3 15+ hp 11049 75 -28.3 1-5 hp (with synchronous belt) 26518 322048 18.1 5-15 hp (with synchronous 5398 48601 15.8 belt) 3299 29700 15.8 15+ hp (with synchronous belt) 12596 113403 15.8 5-15 hp (with VFD) 2399 21600 15.8 15+ hp (with VFD) 300 2700 15.8 15+ hp (Premium + VFD) 170472 540764 8.0 Total 6 Boilers 1-5 ton/h 2686 27 -26.4 5-10 ton/h 601 6 -26.4 1-5 ton/h with proper 877 4990 12.3 insulation 168 697 9.9 5-10 ton/h with proper insulation 376 7484 22.1 1-5 ton/h with feed air controller 56 976 21.0 5-10 ton/h with feed air controller 56 1116 22.1 5-10 ton/h with economizer + blowdown heat recovery 4820 15264 8.0 Total 7 Cogeneration No cogeneration 1203 630 −4.2 Cogeneration 212 785 9.2 Total 1415 1415 0.0% 8 Chillers Less than 100 RT 104 37 -6.7 Greater than 100 RT but less 283 131 -5.0 than 500 RT Greater than 500 RT 235 109 -5.0 Less than 100 RT with chilled 21 357 20.9 water temperature control Greater than 100 RT but less 39 890 23.2 than 500 RT with VSD 47 Growth Rate No. Name Type and Average Size of Unit Numbers (%) 2015 2030 Greater than 500 RT with VSD 32 737 23.2 Total 713 2261 8.0 9 RMG Inefficient 4300 1367 -7.4 Efficient 1 5332 77.2 Total 4300 6699 3.0 10 Textile dyeing Without CP 270 90 7.1 With CP 1 556 52.4 Total 271 646 6.0 11 Steel melting Induction 147 85 −3.6 furnace Arc 3 274 35.1 Total 150 359 6.0 12 Steel RRM Inefficient RRM 220 55 −9.0 Insulated + waste heat 30 545 21.4 Total 250 600 6.0 13 Cement Ball Mill (40 kWh/ton) 42 22 −9.5 VRM (30 kWh/ton) 3 85 24.8 Total 45 107 6.0 14 Cold storage Cold Storage (200 kW) 400 293 −2.0 Efficient (140 kW) 1 666 54.3 Total 400 959 6.0 15 Fertilizer Inefficient Plants 5 1 10.2 (urea) Efficient Plants 1 7 13.9 Total 6 8 1.9 16 Textile Rapier loom 126,343 25,614 −10.2 weaving Air-jet loom 3,560 48,961 19.1 Total 129,903 74,575 −3.6 48 Appendix A: Energy Efficient Lighting A Name and Brief Description of the Option Household Efficient Lighting Incandescent bulbs and fluorescent lamps to be replaced by energy efficient bulbs (CFL and LED) B Present Situation Incandescent, CFL, fluorescent T8 and T5, and a small number of LED bulbs. Currently these are responsible for approximately 20 percent of household electricity consumption and 10 percent of the total electricity consumption.19 In 2013–14, the total household electricity consumption was 18,300 GWh.20 C Efficient Technology For the same lumen output, CFL and LED bulbs have power rating of 15 W and 7 W, respectively, compared to incandescent 60 W bulbs. D Number of Units or Output Number of bulbs of all types: 70.4 million21 Incandescent, fluorescent T8, fluorescent T5, CFL, and LED:21.45, 19.9, 4.95, 52,and 1.7 percent, respectively E Electricity Consumption Light bulbs are sold in many wattages, but the most common for incandescent bulbs is 60 W; for fluorescentT8, 40 W; for FluorescentT5, 20 W; for CFL, 15 W; and for LED, 5 W. For this study, these wattages for the respective bulbs have been used. All the bulbs are assumed to operate for an average of four hours/day. For the estimated 70 million bulbs of all types, the electricity consumption is calculated to be 3,565 GWh. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The demand for lighting (bulbs of all types) will grow due to growth in population/household, per capita income, and extent of electrification. A composite growth rate has been developed to reflect the influence of these factors. For the baseline scenario, growth rates for all types of bulbs were assumed to be 6, 7, and 8 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. 19 The Project for Development of Energy Efficiency and Conservation Master Plan (March 2015), prepared by JICA and Electric Power Development Co., Ltd. 20 Extrapolated from 2012–13 data of Statistical Pocketbook of Bangladesh, 2013. 21 Market Research on Equipment and Appliances (November 2014), prepared by New Vision Solutions Ltd. With the support of JICA. 49 EE Scenario: It is envisaged that an incandescent bulb phaseout plan starting in 2017 will lead to efficient bulbs penetrating the market. Consumers will need to be motivated to adopt the more efficient but expensive LED bulbs. The concerns with mercury pollution from CFLs may lead to regulations that severely restrict their growth. Also, a price decline of LED bulbs will make those competitive with CFLs. It is assumed that the number of LED bulbs will be approximately half that of CFLs in 2030. Fluorescent lamps will experience growth but T8 lamps will be gradually replaced by T5 lamps. The 2-feet T5 lamp may experience an unusual growth in the event of incandescent phaseout. For the EE scenario, the reduction in the number of incandescent bulbs was accounted for by negative growth rates and was assumed to be −5, −11, and −20 percent for 2015–2020, 2021–2025, and 2026–2030, respectively; growth rates for T8 lamps were assumed to be 0, −5, and −12 percent for 2015–2020, 2021–2025, and 2026–2030, respectively; growth rates for T5 lamps were assumed to be 8, 12, and 15 percent for 2015–2020, 2021–2025, and 2026–2030, respectively; growth rates for LED bulbs were assumed to be 20, 30, and 40 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. For the cost-effectiveness calculations, the following assumptions were made: • Wattage for mixture of efficient lights is assumed to be 20W based on weighted average, which indicates 40 W savings compared to incandescent bulbs. • Price of an incandescent bulb is assumed to be US$0.375 and that of an average efficient bulb to be US$3.0. 50 G The Reduction in Electricity use in 2020, 2025, and 2030 51 Electricity ElectricitySa Consumption in Electricity Consumption Year vings Baseline Scenario in EEScenario (GWh) (GWh) (GWh) 2015 3,565 3,565 — 2020 4,770 3,901 869 2025 6,253 4,234 2,019 2030 9,831 4,744 5,087 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Incandescent: 39.5 million (decreased) Fluorescent T8: 32.8 million (decreased) Fluorescent T5: 8.6 million (increased) CFL: 8.4 million (increased) LED: 55.4 million (increased) I For 2030: The Reduction in Power Plant Requirement (MW) 581 J For 2030: The % Reduction of the Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 52 percent of lighting electricity demand will be reduced by efficient bulbs. • 13.2 percent of total household electricity demand will be reduced by efficient bulbs. • 1.82 percent of total primary energy demand will be reduced by efficient bulbs. Assumptions: • The household electricity demand in 2030 is projected to be 38,500 GWh.22 • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. • In 2030, it is assumed that the average efficiency of grid power plants will be 40 percent and T&D losses will be 10 percent; in 2015 these were 33 percent and 15 percent. K Final Explanatory Comments This option has considered only the household sector. If all the sectors were considered, the potential would have increased by 40–50 percent. Lack of data for the other sectors prevented this extension. 22 According to the SNC, projected energy demand for electricity generation in 2030 is 1,100 PJ. Assuming 40 percent generation efficiency and 10 percent T&D loss, this is equivalent to 110,000 GWh. Household electricity demand in 2030 is assumed to be 38,500 GWh (35 percent of the total). 52 Appendix B: Efficiency Improvement of Fans in Residential Sector A Name and Brief Description of Option Household Efficient Fans Inefficient fans to be replaced by efficient fans B Present Situation Currently fans are responsible for approximately 30 percent of household electricity consumption and 15 percent of the total electricity consumption.23 In 2013–14,the total household electricity consumption was 18,300 GWh.24 C Efficient Technology Inefficient fans are rated on an average 100 W, whereas efficient fans consume 65 W for similar performance. D Number of Units or Output Number of fans of all types: 45.2 million25 Number of inefficient fans: 85 percent (assumption) E Electricity Consumption of Device The power rating of inefficient fans varies from manufacturer to manufacturer, but the most common rating is 100 W. This study is based on all inefficient fans being 100 W and all efficient fans being 65 W and are assumed to operate for an average of 3.5 hours/day. For 365 days, the electricity consumption per inefficient and efficient fan is 128 kWh and 83 kWh, respectively. The annual saving per fan is therefore 45 kWh. For the estimated 45.2 million fans of all types (inefficient and efficient), electricity consumption is 5,465 GWh F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The demand for fans will grow due to growth in population/household, per capita income, and extent of electrification. A composite growth rate has been developed to reflect the influence of these factors. For the baseline scenario, growth rates for all types of fans were assumed to be 6, 7, and 8 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. EE Scenario: It is assumed that inefficient fans will be discouraged through a variety of measures undertaken by SREDA leading to efficient fans penetrating the market. As the price will not be significantly different, consumers should be motivated to adopt the more efficient fan for energy saving. It is assumed that the efficient fans will be approximately 90 percent of the 23 The Project for Development of EnergyEfficiency and Conservation Master Plan (March 2015), prepared by JICAand Electric Power Development Co., Ltd. 24 Extrapolated from 2012–13 data of Statistical Pocketbook of Bangladesh, 2013. 25 Market Research on Equipment and Appliances (November 2014), prepared by New Vision Solutions Ltd. With the support of JICA. 53 total fans in 2030. For the EE scenario, growth rates for inefficient fans were assumed to be 5, −5, and −20 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. Assumption Used for Cost-Effectiveness Calculations: • Price of inefficient and efficient fans is assumed to be US$35 and US$47.5, respectively. 54 G The Reduction in Electricity in 2020, 2025, and 2030 Electricity Electricity ElectricityS Consumption in Year Consumption in avings Baseline Scenario EEScenario (GWh) (GWh) (GWh) 2015 5,465 5,465 2020 7,314 7,207 107 2025 10,258 8,731 1,527 2030 15,072 10,895 4,177 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Regular fans 93.4 million (decreased) Efficient fans 93.4 million (increased) I For 2030: The Reduction in Power Plant Requirement (MW) 477 J For 2030: The % Reduction of Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 28 percent of fan electricity demand will be reduced by efficient fans. • 10.8 percent of total household electricity demand will be reducedby efficient fans. 55 • 1.5 percent of total primary energy demand will be reduced by efficient fans. Assumptions: • The household electricity demand in 2030 is projected to be 38,500 GWh.26 • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. • In 2030, it is assumed that the average efficiency of grid power plants will be 40 percent and T&D losses will be 10 percent. In 2015 these were 33 percent and 15 percent. K Final Explanatory Comments This option has considered only the household sector. If all the sectors were considered, the potential would have increased by 40–50 percent. Lack of data for the other sectors prevented this extension. 26 According to the SNC, projected energy demand for electricity generation in 2030 is 1,100 PJ. Assuming 40 percent generation efficiency and 10 percent T&D loss, this is equivalent to 110,000 GWh. Household electricity demand in 2030 is assumed to be 38,500 GWh (35 percent of the total). 56 Appendix C: Replacement of Inefficient Refrigerators A Name and Brief Description of Option Household Efficient Refrigerators Inefficient refrigerators to be replaced by efficient refrigerators B Present Situation ‘Refrigerators’ considered here are mainly of refrigerators, freezers, or combination of both with varying capacities. Currently, these are responsible for approximately 18–19 percent of household electricity consumption and 9 percent of the total electricity consumption.27 In 2013–14,the total household electricity consumption was 18,300 GWh.28 C Efficient Technology Currently 14 cft regular refrigerators (energy rating less than 3 star) consume on an average 300 W, whereas relatively efficient refrigerators (energy rating 3 star or more)with advanced technologies such as inverters and variable speed compressor consume 150 W for similar capacity. D Number of Units or Output Number of refrigerators of all types: 5.2 million29 Number of regular, relatively inefficient refrigerators: 90 percent of the total (assumption) E Energy Consumption of Device Refrigerators are sold in many sizes (for example,10 cft, 14 cft, 20 cft, or higher), but the most common one is 14 cft. On an average, a regular, relatively inefficient 14 cft refrigerator consumes 300 W, and this was considered for this study. All the refrigerators of 300 W are assumed to operate for an average of 8 hours/day. For 365 days, the electricity consumption per regular refrigerator is 876 kWh. For the estimated 5.2 million refrigerators of all types, the electricity consumption is 4,361 GWh. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The demand for refrigerators (both regular and efficient) will grow due to growth in population/household, per capita income, and extent of electrification. For the baseline scenario, growth rates for all types of refrigerators were assumed to be 6, 7, and 8 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. EE Scenario: It is assumed that regular refrigerators will not available in the market after next five years. During that time, the efficient ones will be promoted and will thus be penetrating the market. Currently, the price difference is significant and therefore the efficient ones will 27 The Project for Development of EnergyEfficiency and Conservation Master Plan (March 2015), prepared by JICAand Electric Power Development Co., Ltd. 28 Extrapolated from 2012–13 data of Statistical Pocketbook of Bangladesh, 2013. 29 Market Research on Equipment and Appliances (November 2014), prepared by New Vision Solutions Ltd. With the support of JICA. 57 grow slowly. However, over time, the price difference will not be significant and the inefficient ones will not be manufactured by the renowned brands any more. Moreover, the consumers should be motivated to adopt the more efficient refrigerators for energy saving. It is assumed that the efficient refrigerators will be more than 65 percent of the total refrigerators in 2030. For the EE scenario, growth rates for inefficient refrigerators were assumed to be 5, 0, and −5 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. Assumption Used for Cost-Effectiveness Calculations: • Price of inefficient and efficient refrigerators is assumed to be US$687.5 and US$875, respectively. 58 G The Reduction in Energy in 2020, 2025, and 2030 59 Energy Consumption Energy Energy Consumption in Year in Baseline Scenario Savings EEScenario GWh GWh GWh 2015 4361 4361 2020 5836 5707 129 2025 8185 6944 1241 2030 12026 8369 3657 H For 2030 (Difference between EE and Baseline scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Number of units reduced or increased: Regular refrigerators 8.35 million (decreased) Efficient refrigerators 8.35 million (increased) I For 2030: Reduction in Power Plant Requirement (MW) 417 J For 2030: The % Reduction of Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 30 percent of refrigerator electricity demand will be reduced by efficient refrigerators. • 9.5 percent of total household electricity demand will be reducedby efficient refrigerators. • 1.3 percent of total primary energy demand will be reduced by efficient refrigerators. Assumptions: • The household electricity demand in 2030 is projected to be 38,500 GWh.30 • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. • In 2030, it is assumed that the average efficiency of grid power plants will be 40 percent and T&D losses will be 10 percent. In 2015 these were 33 percent and 15 percent. K Final Explanatory Comments (if any) Only the household sector was considered, but there are refrigerators and freezers in the commercial and industrial sectors. 30 According to the SNC, projected energy demand for electricity generation in 2030 is 1,100 PJ. Assuming 40 percent generation efficiency and 10 percent T&D loss, this is equivalent to 110,000 GWh. Household electricity demand in 2030 is assumed to be 38,500 GWh (35 percent of the total). 60 Appendix D: Replacement of Inefficient ACs A Name and Brief Description of Option Household Efficient ACs Regular inefficient ACs to be replaced by relatively more efficient ACs B Present Situation ACs are mainly of window type and split type with varying cooling capacities. Currently, these are responsible for approximately 12 percent of household electricity consumption and 6 percent of the total electricity consumption.31 In 2013–14,the total household electricity consumption was 18,300 GWh.32 C Efficient Technology Currently 1.5 ton regular window and split ACs (energy rating 3 star or less)consume on an average 2,000 W, whereas relatively efficient ACs (energy rating 4 star or more)with high COP, large heat exchanging coil, and variable speed compressor consume 1,300 W for similar performance. D Number of Units or Output Number of ACs of all types: 1.1 million33 Number of regular, relatively inefficient ACs: 95 percent of the total (assumption) E Energy Consumption Regular ACs are sold in many sizes (1 ton, 1.5 ton, 2 ton, and so on), but the most common one is 1.5 ton. Both window and split forms of regular 1.5 ton AC consume 2,000 W, and this was considered for this study. All the ACs of 2,000 W are assumed to operate for an average of 3 hours/day. For 365 days, the electricity consumption per regular AC is 2,190 kWh. For the estimated 1.1 million ACs of all types, the electricity consumption is 2,442 GWh. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The demand for ACs (both regular and efficient) will grow due to growth in population/household, per capita income, and extent of electrification. For the baseline scenario, growth rates for all types of ACs were assumed to be 6, 7, and 8 percent for 2015– 2020, 2021–2025, and 2026–2030, respectively. EE Scenario: It is assumed that regular window ACs will not be available and the regular split ACs will start to lose popularity, leading to efficient ACs penetrating the market. Currently, the price 31 The Project for Development of EnergyEfficiency and Conservation Master Plan (March 2015), prepared by JICAand Electric Power Development Co., Ltd. 32 Extrapolated from 2012–13 data of Statistical Pocketbook of Bangladesh, 2013. 33 Market Research on Equipment and Appliances (November 2014), prepared by New Vision Solutions Ltd. With the support of JICA. 61 difference is significant and therefore the efficient ones will grow slowly. However, over time, the price difference will not be significant and consumers should be motivated to adopt the more efficient ACs for energy saving. It is assumed that the efficient ACs will be more than 70 percent of the total ACs in 2030. For the EE scenario, growth rates for inefficient window ACs were assumed to be 0, −5, and −10 percent for 2015–2020, 2021–2025, and 2026–2030, respectively; growth rates for inefficient split ACs were assumed to be 10, 5, and 0 percent for 2015–2020, 2021–2025, and 2026–2030, respectively Assumption Used for Cost-Effectiveness Calculations: • Price of inefficient and efficient ACs is assumed to be US$812.5 and US$1,000, respectively 62 G Reduction in Electricity in 2020, 2025, and 2030 63 Energy Consumption Energy Energy Consumption in Year in Baseline Scenario Savings EEScenario (GWh) (GWh) (GWh) 2015 2,442 2,442 — 2020 3,268 3,095 173 2025 4,584 3,895 689 2030 6,735 5,112 1,623 H For 2030:(Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Number of units reduced or increased: Regular window ACs: 1.96 million (decreased) Regular split ACs: 0.16 million (decreased) Efficient ACs: 2.12 million (increased) I For 2030: Reduction in Power Plant Requirement (MW) 185 J For 2030: The % Reduction of Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 24 percent of AC electricity demand will be reduced by efficient ACs. • 4.2 percent of total household electricity demand will be reducedby efficient ACs. • 0.6 percent of total primary energy demand will be reduced by efficient ACs. Assumptions: • The household electricity demand in 2030 is projected to be 38,500 GWh.34 • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. • In 2030, it is assumed that the average efficiency of grid power plants will be 40 percent and T&D losses will be 10 percent. In 2015, these were 33 percent and 15 percent. K Final Explanatory Comments (if any) Due to lack of data for the other sectors only the household sector was considered. ACs are widely used in the Commercial and Industrial sectors. Therefore, the potential of this option can easily double 34 According to the SNC, projected energy demand for electricity generation in 2030 is 1,100 PJ. Assuming 40 percent generation efficiency and 10 percent T&D loss, this is equivalent to 110,000 GWh. Household electricity demand in 2030 is assumed to be 38,500 GWh (35 percent of the total). 64 Appendix E: Improvement of EE of Electrical Motors A Name and Brief Description of Option Industrial Electrical Motors EE of the industrial motors may be improved by replacement of existing V-belts with synchronous belts or installation of VSDs and efficient motors. B Present Situation Currently industrial motors are responsible for approximately 70 percent35 of industrial electricity consumption and 22 percent of the total electricity consumption. In 2014,the total electricity consumption by electric motors was approximately 5,531 GWh. C Efficient Technology Replacement of V-belts with synchronous belts. Synchronous belts have an efficiency that is 5 percent higher than that of standard V-belts. An adjustable speed drive (ASD) is a device that controls the rotational speed of motor- driven equipment. A VSD is the most common type of ASD. Energy savings in VSD applications range from 20 percent to 40 percent. Energy efficient motors can have 4–5 percent higher efficiency compared to the standard efficiency motors. D Number of Units or Output Number of motors of all types: 158,000 Electricity consumed by all motors: 5,531 GWh E Electricity Consumption Industrial motors used in Bangladesh currently are V-belt-driven standard efficiency motors. With V-belts, EE can deteriorate by as much as 5 percent over time. Many SMEs use rewound electric motors, the efficiency of which can be as low as 80 percent. It is estimated that approximately 158,000 electric motors of different capacities are currently operational in the industrial sector. This study is based on an average of 12 hours/day operation. The estimated electricity consumption by these motors is 5,531 GWh. A VSD is a device that regulates the speed and rotational force or output torque of mechanical equipment. There are many types of equipment currently in use that need to be retrofitted because they are running inefficiently. VSDs increase efficiency by allowing motors to be operated at the ideal speed for every load condition. In many applications, VSDs reduce motor electricity consumption by 30–60 percent. On the other hand, energy efficient motors are constructed with improved manufacturing techniques and superior materials, and they usually have higher service factors, longer insulation and bearing lives, lower waste heat output, and less vibration, all of which increase reliability. Efficiencies of energy efficient motors are 4–5 percent higher than the standard efficiency motors. 35 USDOE. 2008.Improving Motor and Drive System Performance: A Sourcebook for Industry. 65 F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of industrial motors will increase due to growth in the industrial sector. The electricity consumption in the industrial sector in Bangladesh has a growth rate of 8 percent/year. The rate is therefore used for the growth in power consumption by the electric motors. The motor size distribution was estimated from the growth rate of small-, medium-, and large-scale industries. EE Scenario: It is assumed that the replacement of V-belt drives by synchronous belts will improve the efficiency by 5 percent. The V-belt-driven motors have lower efficiency and will be almost phased out by 2030. Belt replacement will take place for motors of all sizes. Installation of VSDs is assumed to have 30 percent saving of energy. However, VSDs will be feasible options for motors with capacity of 5HP or more. Moreover, only in certain applications can VSDs can be employed. The number of VSDs installed has been assumed to be 25 percent of the total motor population in 2030. On the other hand, premium efficiency motors are assumed to be installed for larger capacity motors only, above 10HP. Efficient motors are expensive. Therefore, only 5 percent of the motors above 10HP capacity are assumed to have been replaced by efficient motors in the EE scenario. The growth rates of EE technologies assumed in the EE scenario are shown in the Table below. Units Growth rates of Baseline and EE technologies 2015-2020 2021-2025 2026-2030 Motors with V-belt (<5 hp) -20% -20% -25% Motors with V-belt (5-10 hp) -30% -30% -30% Motors with V-belt (>10 hp) -30% -30% -30% Motors with synchronous belt (<5 hp) 35% 10% 10% Motors with synchronous belt (5-10 hp) 30% 10% 8% Motors with synchronous belt (>10 hp) 30% 10% 8% Motors with VFD (5-10 hp) 30% 10% 8% Motors with VFD (>10 hp) 30% 10% 8% Premium efficiency motors (>10 hp) 30% 10% 8% Assumptions: Incremental investment for each efficient motor is US$800. Power saving from each unit is 1.3 kW. 66 G The Reduction in Electricity in 2020, 2025, and 2030 67 Electricity Consumption in Electricity Consumption Electricity Year Baseline Scenario in EE Scenario (GWh) Savings (GWh) (GWh) 2015 5,531 5,531 0 2020 8,777 7,477 1,300 2025 12,896 10,824 2,072 2030 18,948 15,870 3,078 H For 2030 (Difference between EE and Baseline scenarios): The number of Inefficient Units Reduced and Efficient Units Increased Motors with V-belt drive 155,000 (decreased) Motors with synchronous belt drive 400,350 (increased) Motors with VSDs 135,000 (increased) Premium efficiency motors 2,700 (increased) I For 2030: The Reduction in Power Plant Requirement (MW) 351 J For 2030: The % Reduction of the Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 18 percent of electricity consumption by electric motors will be reduced. • 1.10 percent of total primary energy demand will be reduced. Assumptions: • The electricity consumption by motors in 2030 is projected to be 18,948 GWh. • The total primary energy consumption in 2030 is projected to be 2,800 Million GJ. K Final Explanatory Comments 68 The potential of motors can be even greater but considering the fact that SREDA is very new, it may not be possible to achieve more than this. 69 Appendix F: EE Improvement of Boilers A Name and Brief Description of Option Improvement of Energy Efficiency of Boilers Efficiency of the NG-fired boilers may be improved by installation ofeconomizers and boiler blowdown heat recovery. B Present Situation Currently boilers are solely responsible for approximately 80 percent NG consumption by industries. In 2014, NG consumption by industrial boilers was 3,139 MMcm (111 BCF), approximately 13 percent of total NG consumption. C Efficient Technology Insulations for the currently operating steam boilers are insufficient to minimize heat loss through surface. Properly designed insulation systems can save up to 5 percent of the heat loss. One of the ways to improve boiler efficiency is to look at how excess air levels are being controlled. A rule of thumb is that the boiler efficiency can be increased by 1 percent for each 15 percent reduction in excess air. With a properly controlled air feed system, combustion efficiency of the boiler can be maximized and the loss through the stack can be minimized. Installation of economizers to capture and transfer the exhaust heat of the flue gases to preheat incoming boiler feedwater can improve efficiency by 3–5 percent. Therefore, three options are proposed here to improve EE: (a) installation of proper insulation (b) reduction of excess air, and (c) installation of economizers D Number of Units or Output Number of boilers of all types: 4,382 NG consumed by all boilers: 3,139 MM cm (111 BCF) – 109,860 TJ E Energy Consumption of Equipment or Process The capacity of the industrial boilers in Bangladesh varies from 1 to 10 tons/hour. A larger fraction of these boilers have capacities lower than 5 tons/hour. Most of the industries using boilers do not take any measure for waste heat recovery. Most of the boilers are once- through and condensate recovery is rarely practiced since this is not a viable option. According to the Office of the Chief Inspector of Boilers, 4,382 boilers were licensed to operate in 2014.This study is based on an average of 6 hours/day operation. The estimated NG consumption by these boilers is 3,139 MM cm, with an approximate energy content of 10,860 TJ. Most of the boilers do not have proper insulation. Therefore, a significant amount of heat loss can be saved by installation of proper insulation. A net improvement of 5 percent EE was assumed by using a properly designed insulation system. 70 The boilers currently in operation do not have any control system to have appropriate fuel- to-air ratio in the furnace. Generally, a leaner mixture is used, and therefore, reduced efficiency is achieved. By maintaining excess air at an optimum level, 3–4 percent efficiency improvement can be achieved. In boilers, useful amounts of energy exist in the flue gas. Economizers are designed to recover this waste heat by preheating the boiler feedwater. In general, for each flue gas temperature decrease of 22°C, boiler efficiency is increased by 1 percent. A rule of thumb is that installation of economizers can improve boiler efficiency by up to 5 percent. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of boilers will increase mainly due to growth in the garment sector. It was assumed that the growth will be 10 percent for next five years, which is in line with the growth of the textile sector. The growth was assumed to be 8 percent and 6 percent, respectively, for 2021–2025 and 2026–2030. EE Scenario: An efficiency increment by 5 percent was assumed with proper insulation of boilers. Controlling/reducing excess air is assumed to increase the efficiency by 4 percent.It is assumed that the installation of economizers will increase the boiler efficiency by 4 percent. Recovery and reuse of condensate will further increase the efficiency by 4 percent. Only boilers with capacity more than 5 tons/hour were assumed to accommodate this technology. The growth rates of various EE technologies assumed in the EE scenario are shown in the Table below. Small boilers will be refurbished by either changing their insulation and/or by installation of feed air controllers. For larger boilers (5 tons/hr or more) in addition to the above refurbishment, installation of economizer and condensate recovery are considered. Units Growth rates of Baseline and EE technologies 2015-2020 2021-2025 2026-2030 Old boilers (1-5 ton/h) -25% -50% -70% Old boilers (5+ ton/h) -25% -45% -50% Boilers with proper insulation (1-5 ton/h) 70% 50% 40% Boilers with proper insulation (5+ ton/h) 60% 50% 25% Boilers with feed air controller (1-5 ton/h) 30% 50% 60% Boilers with feed air controller (5+ ton/h) 20% 30% 35% Boilers with economizer and condensate recovery (5+ ton/h) 20% 20% 40% Assumptions: Modification of each boiler will cost US$18,800 and each unit is expected to save 1,200 MJ. 71 G The Reduction in Energy in 2020, 2025, and 2030 72 Energy Consumption Energy Consumption in Energy Year in Baseline Scenario EEScenario (TJ) Savings (TJ) (TJ) 2014 109,859 109,859 0 2020 194,622 177,672 16,950 2025 285,963 256,620 29,343 2030 382,684 336,962 45,721 H For 2030 (Difference between EEand Baseline Scenarios):The Number of Inefficient Units Reduced and Efficient Units Increased Boilers without proper insulation 4,382 (decreased) Boilers with feed air control 8,461(increased) Boilers with economizer plus condensate 1,115 (increased) recovery I For 2030: The % Reduction of Energy Demand for the Option and the Sector • 11.95 percent of NG consumption by boilers will be reduced. Assumption: • Total NG consumption by industrial boilers in 2030 is projected to be 10,934MMcm (386 BCF; 382,684 TJ). J For 2030: The Reduction in Energy as a % of Total Primary Energy • 1.63 percent of total primary energy consumption will be reduced. Assumption: • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. 73 K Final Explanatory Comments A detailed study is required to ascertain which option can be applied to which boiler. This is an important option because with gas price increasing efficiency of boilers will become extremely important. 74 Appendix G: Efficiency Improvement through Cogeneration A Name and Brief Description of Option Cogeneration (Combined Heat and Power) Use of waste heat from the CPPs to produce steam can improve EE by saving NG, which will be otherwise used to generate steam. B Present Situation Currently CPPs account for 17 percent of total NG consumption. In 2014, NG consumption by 1,415 CPPs was 3,810 MMcm (134 BCF). Approximately 75 percent of these CPPs have a capacity lower than 1 MW, while the rest produce more than 1 MW of electricity. Only 15 percent of these power plants are currently using the waste heat to generate steam. C Efficient Technology Cogeneration technology provides greater conversion efficiencies than traditional generation methods since it captures heat that will otherwise be wasted. This can result in more than doubling the thermal efficiency. By recycling the waste heat, cogeneration systems achieve overall efficiencies of 74 percent to 88 percent. Higher efficiencies reduce air emissions and leading GHGs, which are associated with climate change. D Number of Units or Output Number of CPPs: 1,415 NG consumed by CPPs: 3,810 MMcm (134 BCF) – 133,343 TJ Number of CHPs: 425 NG savings by cogeneration plants: 571 MMcm (20 BCF) – 20,000 TJ E Energy Consumption of Equipment or Process There are 1,415 operational CPPs in the country, 75 percent of which have capacities lower than 1 MW. An average capacity of 0.8 MW was used for the study. For larger capacity CPPs, an average capacity of 1.78 MW was used. All these CPPs operates round the clock. Some of these CPPs are currently recovering waste heat from the power plants, while for some recovering waste heat is not an option, since they do not have any immediate on-site application of steam. Converting engine-generator combinations to CHP can improve overall efficiencies up to 85 percent. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of CPPs is not going to increase since there will be no NG allocation for new CPPs. Therefore, the NG consumption by CPPs will be the same till 2030. Approximately 15 percent of the CPPs have found use for the waste heat from the power plants. The baseline scenario assumes that this number will increase to 30 percent by 2030. 75 EE Scenario: It is assumed that CHPs will have an improved overall efficiency of 75 percent due to thermal recovery. The EEscenario assumes that maximum potential of energy saving by CPPs will be achieved by 2025. Not all the CPPs have potential as CHP and therefore operate as they are operating now.It is assumed that the number of CHPs will increase by 10% every year over the period of study. Assumptions for Cost Effectiveness Calculation: Investment required for modification of each unit is US$1,968,700. This is expected to save 4,299 MJ/unit. 76 G The Reduction in Energy in 2020, 2025, and 2030 Energy consumption Energy consumption in EE Energy savings Year in baseline scenario scenario TJ TJ TJ 2015 122776 119942 2834 2020 120026 105767 14259 2025 115892 95364 20528 2030 113480 95364 18116 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased CPPs without cogeneration: 384 (decreased) CPPs with cogeneration: 384 (increased) I For 2030: The % Reduction of Energy Demand for the Option and the Sector • 16 percent of energy consumption by CPPs can be reduced. Assumption: • The energy consumption by CPPs in 2030 is projected to be 113,480 TJ. J For 2030: The Reduction in Energy as a % of Total Primary Energy • 0.65 percent of total primary energy consumption can be reduced. Assumption: • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments 77 The potential has been limited to the present installations because the government has decided to stop any further captive generation gas connections. 78 Appendix H: Improvement of EE of Chillers A Name and Brief Description of Option Chillers (Industrial and Commercial) EE of the industrial chillers may be improved by using the temperature control system for chilled water or installation of VSDs for the compressors. B Present Situation Currently commercial and industrial chillers are responsible for approximately 6.70 percent of the total electricity consumption. In 2014, total electricity consumption by chillers was approximately 1,671 GWh. C Efficient Technology Raising chilled water supply temperature by an average of 3°C will save about 5 percent in chiller energy. Chillers’ energy usage can be reduced by installing a VSD. Energy savings with a VFD can be significant, up to 30 percent annually. D Number of Units or Output Number of chillers of all types: 660 Electricity consumed by all motors: 1,671 GWh E Electricity Consumption Chiller efficiency is affected by many factors, including size, components such as chiller motor efficiency, temperature delta (or ‘lift’) of chilled water, sizing of the evaporator and condenser heat exchangers, cooling loads, and condensing temperatures. While the EE of individual components influences the overall chiller plant efficiency, how the equipment is controlled and operated also largely affects the actual chiller system efficiency and therefore its energy usage. Chillers were divided into three subgroups for this study: Chillers with capacity less than 100 refrigeration ton (RT), those with capacity between 100 and 500 RT, and those with capacity above 500 RT. Average capacity for these three subgroups were assumed to be 50, 200, and 1,200 RT, respectively. 18 hours of operation/day was used for the calculations. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The growth in the number of chillers is assumed to be 8 percent. The numbers of chillers in different load groups were assumed from the data obtained from one of the vendors supplying chiller equipment. The COP of the existing chillers is assumed to be 4.8. EE Scenario: Modern chillers can vary the chilled water supply temperature as the cooling load decreases. Raising chilled water supply temperature by an average of 3°C will save about 5 percent in chiller energy. It is assumed that the number of chillers with capacities less than 500 RT will decrease by 10% per year till 2020 and will decrease by 5% per year from 2021-2030. This decrement 79 will be compensated by the increase in number of chillers with chilled water temperature control. For larger capacity chillers the decrement rate is assumed to be 5% per year till 2030. This decrease in inefficient units will be compensated by the chillers with VSD. The COPs of the chillers with water temperature control and VSD were assumed to be 5.1 and 6.4, respectively. Assumptions for Cost Effectiveness Calculations: Improvement of each chiller will cost US$3,500 and each unit is expected to save 140kW. G The Reduction in Electricity in 2020, 2025, and 2030 80 Electricity Electricity Consumption in Electricity Consumption Year Savings Baseline Scenario in EE Scenario (GWh) (GWh) (GWh) 2015 1,671 1,671 0 2020 2,652 2,116 535 2025 3,896 2,827 1,069 2030 5,275 3,935 1,790 H For 2030 (Difference between EE and Baseline Scenarios): The number of Inefficient Units Reduced and Efficient Units Increased Chillers (less energy efficient) 1,984 (decreased) Chillers with temperature control 358 (increased) Chillers with VSD 1,627 (increased) I For 2030: The Reduction in Power Plant Requirement (MW) 204 J For 2030: The % Reduction of the Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 31 percent of electricity consumption by chillers will be reduced. • 0.64 percent of total primary energy consumption will be reduced. Assumptions: • The electricity consumption by chillers in 2030 is projected to be 5,275 GWh. • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments The potential of chillers is high in Bangladesh because it has been estimated that nearly 50 percent of the load is due to cooling demand. 81 Appendix I: Efficiency of Improvement of RMG Industries A Name and Brief Description of Option Ready-Made Garment Improving EE of RMG industries by implementing a variety of EE measures B Present Situation The RMG industry is the largest industrial subsector in Bangladesh. It is responsible for 80 percent of the exports and brings in huge quantity of foreign exchange. The RMG sector is projected to grow in the next decade and contribute significantly in Bangladesh's GDP growth. Since the present condition of these garment industries is not up to international standards, a concerted effort to improve these industries can significantly increase their EE. Despite its huge importance and significance for the economy, the conditions and standards of technology and working conditions are poor. Fires and other accidents are common. Several studies have shown that even simple housekeeping and low-cost EE measures can save 15 percent energy. A government-sponsored effort is ongoing to make these garment industries internationally risk and safety compliant. C Efficient Technology The RMG sector of Bangladesh can reduce energy consumption by about 35 percent by adopting and implementing the following EE measures2,3: (a) Switching to electronic ballasts and servo motors (b) Ensuring electrical load management (c) Using energy efficient motors (d) Automation of aeration system (e) Heat recovery from boilers, electrical generators, stenters, and driers (f) General housekeeping and maintenance D Number of Units or Output In 2015, number of RMG industries: 4,300 Average production capacity of RMG industries: 1,250,000 pieces/month/factory E Energy Consumption of Equipment or Process The RMG industries in Bangladesh produce knit and woven products. The RMG industries use different kinds of knitting, sewing, and spinning machines, including lighting and air- conditioning systems, which consume significant amount of energy. RMG factories use approximately 25 percent, equivalent to 3,223 GWh, of the electricity consumed by the 82 industrial sector. Assuming that each factory produces 1,250,000 pieces of RMG (knit and woven)/month, 0.05 kWh energy is required to produce every piece of RMG.36 An RMG industry with an average production capacity of 1.25 million pieces of RMG/month and 12 months of operation (330 days/year; 18 hours/day) consumes approximately 749 MWh. Energy (gas and electricity) consumed by all RMG dyeing industries is 3,223 GWh equivalent. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: In 2015, there were 4,300 RMG industries. With a growth rate of 3.5 percent, this number will increase to 5,107 in 2020. Assuming 3.0 percent and 2.5 percent growth rates for 2021– 2025 and 2026–2030, respectively, it is projected that the number of RMG industries will increase to 5,920 and 6,698 by the end of 2025 and 2030. EE Scenario: By implementing efficient technologies, the RMG industries will be able to reduce power consumption from 50 kWh/1,000 pieces to 32 kWh/1,000 pieces. It is assumed that the RMG industries will adopt efficient technologies at the rates of 5 percent for 2015–2020, 7 percent for 2021–2025, and 10 percent for 2026–2030. It is projected that, by the end of 2030, 5,332 out of total 6,698 RMG industries will adopt efficient technologies. Assumptions: Implementation of efficient technology will cost US$5,000/unit and will save 2,205 kW/unit. These units are expected to be operated 18 hours a day and 330 days a year. 36 GTZ. 2007.Identification of Eco-Efficiency Measures for the Readymade Garment Factories in Bangladesh . Working Paper No. 5. Dhaka, Bangladesh; GTZ. 2012.Promoting Energy Efficiency in the Textile and Garment Industry. Dhaka, Bangladesh; SREDA and Power Division, MPEMR, Government of the People’s Republic of Bangladesh. 2014. Energy Efficiency and Conservation Master Plan up to 2030 . Dhaka, Bangladesh; Bangladesh Garment Manufacturers and Exporters Association (BGMEA), homepage: www.bgmea.com.bd 83 G The Reduction in Energy in 2020, 2025, and 2030 84 Electricity Electricity Consumption in Electricity Consumption in Year Savings Baseline Scenario EEScenario (GWh) (GWh) (GWh) 2015 3,223 3,223 — 2020 3,828 3,361 467 2025 4,437 3,491 946 2030 5,020 3,622 1,399 H For 2030 (Difference between EE and Baseline Scenarios): The number of Inefficient Units Reduced and Efficient Units Increased RMG Units (Inefficient): 1367 (reduced) (baseline number in 2030 was 6,699) RMG Units adopting efficient technologies: 5,332 (increased) (baseline number in 2030 was 0) I For 2030: The Reduction in Power Plant Requirement (MW) 235 J For 2030: The % Reduction of Electricity Demand for the Option and the Sector and the % Reduction of Total Primary Energy Demand • In 2030, electricity consumption in RMG industries will be reduced by 28 percent. • 0.5 percent of total primary energy will be reduced by this option. Assumptions • Total primary energy demand in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments The future growth of Bangladesh will critically depend on the growth of RMG industries. Many industry experts opine that the industry will saturate in the next decade, while others claim that growth will continue beyond 2030. The growth of the RMG industries has been modeled such that it will continue at least up to 2030. 85 Appendix J: Efficiency of Improvement of Textile Dyeing A Name and Brief Description of Option Textile Dyeing CP options to improve EE: Improving dyeing technique and using compatible dyes to save water, steam, chemicals, and power B Present Situation In 2012 there were approximately 240 textile dyeing-printing industries in Bangladesh. Considering a growth rate of 4 percent, the number would have increased to 270 by 2015. The dyeing industry is projected to grow along with RMG and textile weaving. The entire chain of making finished clothing products constitutes an import chain of industries and will contribute significantly to the economic growth of Bangladesh. The energy consumed to dye 1 kg of fabric using traditional dyeing technique is approximately 0.47kWh.37 Considering average dyeing capacity of 15 tons fabric/day/factory, the energy consumption of the dyeing industries in 2015 was 647 GWh. C Efficient Technology CPoptions include substitution of raw materials and auxiliary materials (especially renewable materials and energy), increase of useful life of auxiliary materials and process liquids, and use of indicators and controlling. Adopting CP options reduces number of dyeing and washing bathes, time consumption, water consumption, steam consumption and overall power consumption of dyeing process.38 By adopting CP options, energy consumption of the textile dyeing industries can be reduced from 0.47 kWh/kg fabric to 0.26 kWh/kg fabric.2 D Number of Units or Output Number of textile dyeing industries: 270 Average production capacity: 15,000 kg fabric/day/factory E Energy Consumption of Equipment or Process Conventional dyeing techniques use the existing reactive dyes and disperse dyes. Dyeing process using conventional reactive disperse dyes requires higher amount of water, chemicals, and steam compared to new generation reactive and disperse dyes. Besides, to achieve the right shade, industries re-shade about 20 percent fabric and re-dye about 10 percent fabric, which increase the energy consumption. Using the conventional practice, 37 IFC. 2012.Industry Specific Study on Sustainable Finance Market Potential for Financial Institutions in Bangladesh. Dhaka, Bangladesh; GTZ. 2007.Identification of Eco-Efficiency Measures for the Readymade Garment Factories in Bangladesh. Working Paper No. 5. Dhaka, Bangladesh; Primary data collected from management of a knit dyeing factory. 38 S. Ahmed, A. Clemette, M. Clark, and K. Tapley. 2006.“Alternative Production and Cost Savings in Winch Dyeing.” Booklet series, Managing Industrial Pollution from Small and Medium Scale Industries in Bangladesh, R8161-ETP, Department for International Development (DFID), United Kingdom (ISBN: 984-8121-08-0); DFID. 2006. Alternative Production for Pollution Reduction . Report, Key Document, R8161 – Section6, Research for Development, DFID, United Kingdom. 86 dyeing 1 kg of fabric requires approximately 0.47 kWh energy. Therefore, an existing textile dyeing industry of dyeing capacity 15 tons of fabric/day, and 340 working days/year, consumes approximately 2.4 GWh energy/year. For 270 textile dyeing industries, the energy consumption is 647 GWh (2015). F Baseline and Mitigation Scenarios for the Option up to 2030 Baseline Scenario: In 2015, there were approximately 270 textile dyeing-printing industries in Bangladesh. With a growth rate of 4 percent, this number will increase to 328 by end of 2020. Considering 6 percent and 8 percent growth rates for 2021–2025 and 2026–2030, respectively, it is projected that the number of textile dyeing industries will increase to 440 and 646 by end of 2025 and 2030, respectively. EE Scenario: Adopting CP options by the textile dyeing industries will reduce the power consumption required to dye each kilogram of fabric from 0.47 kWh to 0.26 kWh. It is projected that, by the end of 2030, about 86 percent of the textile dyeing industries will adopt CP options to improve their EE; hence, the energy consumption would be about 953 GWh. Assumptions: Adopting CP will cost US$20,000/unit and will save 175kW/unit. These units will operate 18 hours a day for 340 days in a year. 87 G The Reduction in Energy in 2020, 2025, and 2030 88 Energy Consumption Energy Consumption in Energy Year in Baseline Scenario Mitigation Scenario Savings (GWh) (GWh) (GWh) 2015 647 647 — 2020 787 671 116 2025 1,054 747 307 2030 1,549 953 595 H For 2030 (Difference between Mitigation and Baseline Scenarios): The number of Inefficient Units Reduced and Efficient Units Increased Textile Dyeing Units without CP options 556 (reduced) (2030 baseline number was 646) Textile Dyeing Units with CP options 556 (increased) (2030 baseline number was zero) I For 2030: The Reduction in Power Plant Requirement (MW) 97 J For 2030: The % Reduction of Electricity Demand for the Option and the % Reduction of Total Primary Energy Demand • 38 percent of the energy requirement of the textile dyeing industries will be reduced. • 0.21 percent of the total primary energy demand will be reduced by this option. Assumptions: • Total primary energy in 2030 is projected to be 2,800 million GJ K Final Explanatory Comments The option considered here is CP. Even though focus has been given on optimum use of dyes, all sorts of small and big EE options including housekeeping can be initiated here. In that scenario, achieving the stated reduction in energy consumption will not be difficult to attain. The challenge remains in convincing industries to adopt CP options. 89 Appendix K: Efficiency Improvement of Steel Making Furnaces A Name and Brief Description of Option Steel Melting Induction furnace to be replaced by electric arc furnace. B Present Situation Steel making and rerolling industry is one of the largest private sector energy consumers. In 2013, total energy consumption for steel making and rerolling was 17.6 million GJ or 3 percent of total industrial energy consumption of 574 million GJ. The steel scrap melting business is more capital intensive and therefore controlled by a few large ones.39 Around 50 percent of the steel is supplied by 20–25 large mills. These mills are integrated, that is, having both melting and rerolling.40 In the last decade, many of the large ones have grown at the expense of the smaller ones, many of which have gone out of business. The larger ones have invested in technology and are much more efficient than the older traditional ones. The changeover from induction furnace to arc furnace is not straightforward because arc furnaces are usually of large size. Therefore, promoting this option will require smaller ones to merge. In the natural course of competition in the last decade, this has already taken place. Presently there are only 4–5 arc furnaces. C Efficient Technology Maximum potential of energy saving can be attained by the replacement of induction furnace with more energy efficient electric arc furnace (30 percent efficient41). D Number of Units or Output Number of steel mills (scrap melting): 150 Total steel production: 3.5 million tons E Electricity Consumption of Device Induction furnace: (212 kgOE/ton)Arc furnace: (130 kgOE/ton) Assumed average production in one unit: 20,000 ton/year F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of steel making and rerolling mills will increase due to growth in the construction sector, which has been growing at an average of 8 percent/year in the last decade. The annual growth rate considered is 6 percent during the period of 2015–2030. EE Scenario: 39 Bangladesh Steel Industry Review, EBL Securities Ltd Research, 2016 40 Market Insight: Emerging Steel Industry in Bangladesh, 2016 41 Industrial Energy Efficiency Opportunities and Challenges in Bangladesh, Final Report | TA 45916-01 BAN Industrial Energy Efficiency Finance Program, 2014 90 It is assumed that about 75 percent of steel RRM will implement the energy efficient process by 2030 either on their own volition or as a result of SREDA's regulatory pressure. It is also envisaged the transformation will be facilitated by donor funding and soft loans For the EE scenario, growth rates for arc furnace were assumed to be 28, 30, and 28 percent for 2015–2020, 2021–2025, and 2026–2030, respectively Assumption Used for Cost-Effectiveness Calculations: Price of Induction furnace: US$0.44×106 Price of arc furnace: US$2.2×106 Baseline Scenario 400 350 Induction Furnace 300 Electric Arc Furnace Number of Unit 250 200 150 100 50 0 2027 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2028 2029 2030 Year 91 Mitigation Scenario 400 350 Induction Furnace 300 Electric Arc Furnace Number of Unit 250 200 150 100 50 0 Year G The Reduction in Electricity in 2020, 2025, and 2030 Energy Consumption 7000 6000 Baseline 5000 Mitigation 4000 GWh 3000 2000 1000 0 Year 92 Electricity Consumption in Electricity Consumption in EE Electricity Year Baseline Scenario scenario (GWh) Savings (GWh) (GWh) 2015 2,569 2,569 0 2020 3,438 3,321 117 2025 4,600 4,104 496 2030 6,156 4,375 1,781 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Induction furnace: 267(decreased) Arc furnace: 267(increased) I For 2030: The Reduction in Power Plant Requirement (MW) 203 J For 2030: The % Reduction of Electricity Demand for the Option and the % Reduction of Total Primary Energy Demand • 29 percent of electricity consumption for steel melting industries will be reduced. • 0.64 percent of total primary energy will be saved by implementing this option. Assumptions: • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments In many industries, the steel melting to make ingots from scrap steel and rerolling operation to make rods are integrated. Moreover, many of these large integrated mills have captive power generation. Therefore, it is very difficult to segregate the electricity consumption for the steel melting furnace part from the electricity used in the rerolling part. Also, because the electricity is generated in situ, it is difficult to cost it. 93 Appendix L: Efficiency Improvement of Steel RRMs A Name and Brief Description of Option Rerolling Mills EE of RRMs can be enhanced by introducing combustion control and automation of the reheating furnace, waste heat recovery, and improved insulation of furnace and the hot air pipe. B Present Situation There are an estimated 150 steel melting and 250 RRMs in the country.42 The steel scrap melting business is more capital intensive and therefore controlled by a few large ones. Around 50 percent of the steel is supplied by 20–25 large mills. These mills are integrated, that is, having both melting and rerolling. In the last decade, many of the large ones have grown at the expense of the smaller ones. As a result, many traditional mills have gone out of business. The larger ones have invested in technology and are much more efficient than the older traditional ones. For rerolling, the SEC can vary between 40 and 80 m3 of NG/ton of steel. The traditional mills, many of which were established a long time back, are small operations. The owners are reluctant to invest in new equipment to make these mills more energy efficient. It is possible to bring down the SEC of the inefficient RRMs because the efficient ones are using standard technologies.43 C Efficient Technology In RRMs, up to 40 percent energy can be saved by implementing a waste heat recovery unit, combustion control unit, and improved insulation. D Number of Units or Output Number of RRM: 250 Total steel production: 3.5 million tons E Energy Consumption of Equipment or Process Average energy consumption in an inefficient RRM is 70 m3 NG/ton. Each unit capacity is considered to be 20 tons/day and will operate 350 days/year. Average production per unit is 7,000 tons/year. Energy consumption per unit is 1,400 m3 NG/day. Total energy consumption in an RRM is 8.94 million GJ. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of steel-making and rerolling mills will increase due to growth in the construction sector, which has been growing at an average of 8 percent/year in the last decade. The annual growth rate considered is 6 percent during 2015–2030. 42 A Bankable Report on Energy Efficiency Finance Program - Bangladesh, Piyush Kumar Jain, 2013. 43 Industrial Energy Efficiency Opportunities and Challenges in Bangladesh, Final Report | TA 45916-01 BAN Industrial Energy Efficiency Finance Program,2014; Increasing Energy Efficiency in the Manufacturing Process in Bangladesh’s Re-Rolling Mills, IFC Smart Lessons, May 2009. 94 EE Scenario: Waste heat recovery units along with improved insulation, regenerative gas burners, and combustion control will be installed in inefficient mills. It is assumed that approximately 90 percent of steel RRMs (energy inefficient that are responsible for 50 percent of the total production) will implement the energy efficient process by 2030 either on their own volition or as a result of SREDA's regulatory pressure. It is also envisaged that the transformation will be facilitated by donor funding and soft loans. For the EE scenario, growth rates for efficient RRMs were assumed to be 20, 24, and 20 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. Assumption Used for Cost-Effectiveness Calculations: Incremental cost per unit of RRM (20 tons/day):US$0.0875×106 Baseline Scenario 700 600 Regular 500 Efficient Number of Unit 400 300 200 100 0 Year 95 Energy Efficiency Scenario 700 600 Regular 500 Efficient Number of Unit 400 300 200 100 0 Year G The Reduction in Energy in 2020, 2025, and 2030 Energy Consumption 12000 10000 Regular 8000 Efficient TJ 6000 4000 2000 0 Year 96 Energy Consumption Energy Consumption in EnergySavings Year in Baseline Scenario EEScenario (TJ) (TJ) (TJ) 2015 4,168 4,168 2020 5,577 5,314 263 2025 7,463 6,205 1,258 2030 9,988 6,386 3,602 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Regular: 473 (decreased) Energy efficient: 473 (increased) I For 2030: The % Reduction of Energy Demand for the Option • 36 percent of energy consumption by RRMs will be reduced. J For 2030: The Reduction in Energy as a % of Total Primary Energy • 0.13 percent of total primary energy will be saved by this option. Assumption: • Total primary energy in 2030 is projected to be approximately 2,800 million GJ. K Final Explanatory Comments The growth of the RRMs will critically depend on the availability and price of gas. With NG depleting fast in the country, both the supply and price will become uncertain. The impact of the proposed LNG import to boost the shortage of supply is unknown but is sure to have a depressing effect on this energy intensive industry. 97 Appendix M: Efficiency of Improvement of Clinker Grinding A Name and Brief Description of Option Clinker Grinding Ball mills to be replaced by efficient VRMs B Present Situation The cement industry is growing at an average rate of 10–12 percent/year. The production capacity is approximately 25 percent higher than the current local market demand. Cement is also exported to different states of India and export demand has been increasing over the years. The cement factories produce cement from imported clinker obtained from India, Vietnam, China, Thailand, and Indonesia. The top 10 companies (Shah, Heidelberg, Meghna, Seven Circle, Lafarge, Surma, Holcim, Unique, MI, Premier, and Akij) control about 70 percent of the market. Of these, only Lafarge produces its own clinker, while all others make cement by grinding imported clinker. In 2014, the total production was 28 million tons, whereas the local market utilization capacity was 18 million tons. Currently 123 companies are listed as cement manufacturers in the country but only 45 companies are operating.44 Ball mills are the traditional grinding equipment, but more efficient grinding mills are available. The VRMs are the choice equipment for grinding, but because these are much more expensive, entrepreneurs avoid using these. C Efficient Technology VRMs have the potential to reduce energy consumption by 30 percent.45 D Number of Units or Output Production: 28 million tons Number of units: 45 E Electricity Consumption of Device Average energy consumption for grinding in ball mills: 40 kWh/ton Average energy consumption for grinding in VRM: 30 kWh/ton Each unit capacity is considered to be 2,000 tons/day and will operate for 300 days/year. Energy savings potential from one unit is 6 GWh/year. F Baseline and Mitigation Scenarios for the Option up to 2030 Baseline Scenario: The production capacity or number of cement factories will increase due to growth in the construction sector, which has been growing at an average of 8 percent/year in the last 44 Market Insight: Cement Industry, http://www.lightcastlebd.com/blog/2016/03/market-insight-cement- industry, 2014. 45 Industrial Energy Efficiency Opportunities and Challenges in Bangladesh, Final Report | TA 45916-01 BAN Industrial Energy Efficiency Finance Program, 2014. 98 decade. The annual growth rate of the cement sector is considered to be 6 percent during 2015–2030. Mitigation Scenario: It is assumed that the less efficient Ball mills will be gradually replaced (80 percent by 2030) by VRMs. For the EE scenario, growth rates for efficient clinker grinding were assumed to be 24, 26, and 25 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. Assumption Used for Cost-Effectiveness Calculations: Ball mill investment:US$2×106 VRM investment:US$3×106 Baseline Scenario 120 100 Ball Mill 80 VRM Number 60 40 20 0 Year 99 Energy Efficiency Scenario 120 100 Ball Mill Number of Unit 80 Vertical Roller Mill 60 40 20 0 Year G The Reduction in Electricity in 2020, 2025, and 2030 Energy Consumption 3000.00 2500.00 Baseline 2000.00 Mitigation GWh 1500.00 1000.00 500.00 0.00 Year 100 Electricity Electricity Consumption Consumption in ElectricitySa Year in Mitigation Scenario Baseline Scenario vings (GWh) (GWh) (GWh) 2015 1,101 1,101 0 2020 1,473 1,444 29 2025 1,972 1,831 140 2030 2,638 2,153 485 H For 2030 (Difference between Mitigation and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Ball mill: 78(decreased) VRM: 78(increased) I For 2030: The Reduction in Power Plant Requirement (MW) 56 J For 2030: The % Reduction of Electricity Demand for the Option and the Sector andthe % Reduction of Total Primary Energy Demand • 18 percent of electricity will be reduced in the cement industry. • 0.17 percent of total primary energy demand will be reduced by VRM. Assumptions: • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments Only clinker grinding industries have been considered here. Electricity drawn from the national grid or generated on-site using NG is the main source of energy. 101 Appendix N: Efficiency Improvement of Cold Storage Facilities A Name and Brief Description of Option Cold Storage Incorporation of energy efficient refrigeration unit with improved insulation B Present Situation There are approximately 400 cold storage facilities in Bangladesh with 5 million tons of storage capacity.46 Most cold storages are old and poorly constructed. The operators have very little knowledge about efficient operation. The electricity consumption is 70– 150 kWh/ton of product. Power consumption depends on the quality of the building, room size, stock turnover, temperature of the incoming product, outside temperature, food condition (whether chilled or frozen),and so on. C Efficient Technology In cold storage units, up to 50 percent of energy can be saved47 by optimizing compressor and system operation, reducing temperature lifts in refrigeration plants (increased COP), improving defrosting system, and reducing heat load with improved insulation, reducing air leakage, lights, and auxiliary load (fans, pumps, and other machineries).48 D Number of Units or Output Total number of cold storage unit: 400 Average size of cold storage unit (assumed): 200 kW E Electricity consumption of Device The power ratings of inefficient cold storages vary depending on the size of the storage available. This study is based on all cold storages being 200 kW (most common size) and all efficient cold storages being 100 kW and are assumed to operate for an average of 15 hours/day and 220 days/year. Average energy consumption for one inefficient cold storage unitis3,000 kWh/day and energy savings potential is 1,500 kWh/day. F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: The number of cold storage units will increase due to population growth and increasing demand for preserving vegetables. The annual growth rate49 considered is 6 percent during the period of 2015–2030. 46 Power price spike puts cold storage owners in a tight corner, the Financial Express, October 4, 2015. 47 Cold Storage: A View of Energy Efficient Technologies and Practices, Vipin Yadab, Rajiv Gandhi Institute of Petroleum Technology (RGIPT), 2010. 48 Reducing Energy Use in the Cold Storage Industry – A Case Study, Gabor Hilton M.I.E. Aust, M. Airah, Engineering manager, Oxford Cold Storage Company, 2013. 49 Cold Chain: Discover/Invest/Profit, www.boi.gov.bd 102 EE Scenario: It is assumed that approximately 70 percent of the cold storages will implement the energy efficient process by 2030 to reduce operational cost and electricity cost. For the EE scenario, growth rates for efficient cold storages were assumed to be 32, 32, and 30 percent for 2015–2020, 2021–2025, and 2026–2030, respectively. Assumption Used for Cost-Effectiveness Calculations: • Price of an inefficient and efficient cold storage refrigeration unit including insulation is assumed to be 1.2×106 BDT and 1.5 ×106 BDT, respectively Baseline Scenario 1200 1000 Number of Cold Storage Regular 800 Efficient 600 400 200 0 Year 103 Energy Efficiency Scenario 1200 1000 Number of Cold Storage Regular 800 Efficient 600 400 200 0 Year G The Reduction in Electricity in 2020, 2025, and 2030 Energy Consumption 700 600 Baseline 500 Mitigation 400 GWh 300 200 100 0 Year 104 Electricity Electricity Electricity consumption in EE consumption in savings Year scenario baseline scenario GWh GWh GWh 2015 262 262 0 2020 351 338 13 2025 470 413 57 2030 629 409 220 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Regular cold storage: 666 (decreased) Efficient cold storage: 666 (increased) I For 2030: The Reduction in Power Plant Requirement (MW) 25 J For 2030: The % Reduction of Electricity Demand for the Option and the % Reduction of Total Primary Energy Demand • 35 percent of the total energy consumption in cold storage units will be reduced. • 0.08 percent of total primary energy demand will be reduced by efficient cold storages. Assumptions: • The primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments This is a special case of the chiller option. 105 Appendix O: Efficiency Improvement of Urea Fertilizer Plants A Name and Brief Description of Option Urea Fertilizer Plants Gradually replacing old and less efficient urea fertilizer plants with high-capacity and high- efficient plants B Present Situation At present, there are seven urea fertilizer plants in Bangladesh: six plants are under BCIC and one in the private sector. These plants produce on average 1.3 million tons of urea/year and annually consume 50,306 MMCF NG (53,100 TJ/year). On average, the existing urea plants consume about 39.20 MCF NG to produce 1 ton of urea fertilizer (39.20 MCF/MT). The private company KAFCO has better EE, which is about 26.45 MCF/MT. Most of the BCIC plants are less efficient and consume more NG (above 45 MCF/MT) than the average consumption. To meet the future demands, the Government of Bangladesh plans to gradually replace old fertilizer plants with more efficient and high capacity plants. In 2016, Natural Gas Fertilizer Factory Limited (NGFFL) has replaced Shahjalal Fertilizer Company Limited (SFCL). It is assumed that by 2020 Urea Fertilizer Factory Limited (UFFL) and Polash Urea Fertilizer Limited (PUFFL) will be replaced by efficient plants. Ashuganj Fertilizer and Chemical Company Limited (AFCCL), Chittagong Urea Fertilizer Limited (CUFL), and Jamuna Fertilizer Company Limited (JFCL) are expected to be replaced by new state-of-the-art efficient plants by 2022, 2024, and 2026, respectively. The new plants will have double the production capacity compared to the old fertilizer plants. C Efficient Technology The efficient technology is a new state-of-the-art ammonia-urea fertilizer complex. This will be a completely new installation and will not use anything of the old existing plant. The SEC will be 24 MCF/ton of urea. D Number of Units or Output (2015) Number of Urea fertilizer plants: 7 Yearly production of Urea Fertilizer: 1,283,412 MT/year Natural Gas Consumption: 50,306 MMCF/year (53,100 TJ/year) E Energy Consumption of Equipment or Process BCIC Plants KAFCO Overall 45 MCF/MT (average) 26.45 MCF/MT 39.20 MCF/MT F Baseline and EE Scenarios for the OPTION up to 2030 106 Natural Gas Consumption Production Efficiency Yearly Production (million GJ) (MCF NG/MT Urea) Year of Urea Fertilizer Baseline Baseline (million MT) EE Scenario EE Scenario Scenario Scenario 2015 1.28 53.07 — — 2020 2.05 84.78 63.16 29.20 39.20 2025 2.27 93.72 63.64 26.62 2030 2.78 114.91 71.45 24.37 107 G The reduction in energy in 2020, 2025 and 2030 Energy Consumption Energy Energy Consumption in Year in Baseline Scenario Savings EE Scenario (million GJ) (million GJ) (million GJ) 2015 53.07 53.07 0.00 2020 84.78 63.16 21.62 2025 93.72 63.64 30.08 2030 114.91 71.45 43.45 H For 2030 (Difference between EE and Baseline Scenarios): The number of Inefficient Units Reduced and Efficient Units Increased Number of inefficient plant: 4(last inefficient plant replaced in 2026 Number of efficient plants: 4 I For 2030: The % Reduction of Energy Demand for the Option and the Sector • NG consumption for urea fertilizer production will be reduced by 38 percent. J For 2030: The Reduction in Energy as a % of Total Primary Energy 108 • Primary energy will be reduced up to 1.55 percent. Assumption: • The total primary energy consumption in 2030 is projected to be 2,800 million GJ. K Final Explanatory Comments Since NG supplied to industry is used both for process heat and power generation, the percentage saving of this option with respect to industrial gas consumption could not be shown. 109 Appendix P: Efficiency Improvement of Textile Weaving A Name and Brief Description of Option Textile Weaving Replacing standard rapier looms by high productivity, energy efficient air-jet looms B Present Situation Textile weaving or fabric production is an important industry in Bangladesh. It complements the very successful large garment industry. This industry along with the RMG industry is projected to grow and contribute significantly to the economic growth of the country. In 2015–16 the fabric production in Bangladesh was approximately 4.3 billion meters. Approximately 90 percent of the fabrics is produced using rapier looms, the rest produced using air-jet looms. To save energy, industries are replacing rapier looms by energy efficient air-jet looms.50 C Efficient Technology The fabric production capacity per year of a rapier loom and an air-jet loom is 30,631 meters and 120,789 meters, respectively. It is reported that to produce 3.676 million meters of fabric/year, conventional rapier looms consume 2,606 MWh (that is, power consumption of a rapier loom is 0.709 kWh/m fabric). Air-jet looms consume 2,214 MWh to produce 6.523 million meters of fabric annually (that is, power consumption of an air-jet loom is 0.339 kWh/m fabric). An air-jet loom improves the productivity 1.8 times.51 D Number of Units or Output Yearly production capacity: 4,300 million meters of fabric Number of rapier looms: 126,343 Number of air-jet looms: 3,560(total number of looms: 129,903) E Energy consumption of equipment or process Annual electricity consumption by a rapier loom: 21,721 kWh/year Annual electricity consumption by an air-jet loom: 40,994 kWh/year Annual electricity consumption: 2,890 GWh F Baseline and EE Scenarios for the Option up to 2030 Baseline Scenario: In 2015, the annual production of fabric was 4.3 billion meters. With a growth rate of 2.5 percent, this number will increase to 4.87 billion meters by end of 2020. Considering 3 percent and 3.5 percent growth rates for 2021–2025 and 2026–2030, respectively, it is projected that the annual fabric production will increase to 5.64 billion meters and 6.70 billion meters by the end of 2025 and 2030, respectively. It is assumed that the number of 50 J. E. Lagos and T. Hossain. 2016. Bangladesh Cotton and Products Annual Report 2016. USDA Foreign Agricultural Service. 51 MOEJ BOCM Project Planning Study in Asian Region (BOCM PS). 2014.“Summary of the Final Report.” Saving Energy through the installation of High Efficiency Air-Jet Loom in Weaving Field. Toyota Tsusho Corporation. 110 air-jet looms will increase but will maintain the same ratio of fabric production as in 2015, that is, 10 percent of the total. EE Scenario: It is assumed that an EE program driven by SREDA or some donor agency will replace rapier looms by air-jet looms such that, by the end of 2030, 65 percent looms will be energy efficient air-jet looms. Assumptions: Investment required for the modification of each unit is US$68354. Each unit is expected to save 7.52 kW. 111 G The Reduction in Electricity in 2020, 2025, and 2030 112 Electricity Electricity Consumption in Electricity Consumption in Year Savings Baseline Scenario EE Scenario (GWh) (GWh) (GWh) 2015 2,890 2,890 0 2020 3,270 2,758 512 2025 3,791 2,568 1,223 2030 4,502 2,563 1,939 H For 2030 (Difference between EE and Baseline Scenarios): The Number of Inefficient Units Reduced and Efficient Units Increased Number of rapier looms: 171,202 (reduced) (2030 baseline 196,816) Number of air-jet looms: 43,415 (increased) (2030 baseline 5,546) I For 2030: The Reduction in Power Plant Requirement (MW) 326 J For 2030: The % Reduction of Electricity Demand for the Option and the % Reduction of Total Primary Energy Demand • 43 percent of loom electricity demand will be reduced by air-jet looms. • 0.7 percent of total primary energy demand will be reduced by air-jet looms. K Final Explanatory Comments As a result of the substitution, the number of looms will come down significantly. 113