Wind Resource Mapping in Zambia 12 MONTH SITE RESOURCE REPORT May 2018 This report was prepared by DNV GL, under contract to The World Bank. It is one of several outputs from the wind resource mapping component of the activity “Renewable Energy Resource Mapping and Geospatial Planning – Zambia” [Project ID: P145271]. This activity is funded and supported by the Energy Sector Management Assistance Program (ESMAP), a multi-donor trust fund administered by The World Bank, under a global initiative on Renewable Energy Resource Mapping. Further details on the initiative can be obtained from the ESMAP website. This document is an interim output from the above-mentioned project, and the content is the sole responsibility of the consultant authors. Users are strongly advised to exercise caution when utilizing the information and data contained, as this may include preliminary data and/or findings, and the document has not been subject to full peer review. Final outputs from this project will be marked as such, and any improved or validated solar resource data will be incorporated into the Global Wind Atlas. Copyright © 2018 THE WORLD BANK Washington DC 20433 Telephone: +1-202-473-1000 Internet: www.worldbank.org The World Bank, comprising the International Bank for Reconstruction and Development (IBRD) and the International Development Association (IDA), is the commissioning agent and copyright holder for this publication. However, this work is a product of the consultants listed, and not of World Bank staff. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work and accept no responsibility for any consequence of their use. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for non-commercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: +1-202-522-2625; e-mail: pubrights@worldbank.org. Furthermore, the ESMAP Program Manager would appreciate receiving a copy of the publication that uses this publication for its source sent in care of the address above, or to esmap@worldbank.org. RENEWABLE ENERGY WIND MAPPING FOR ZAMBIA 12-month Site Resource Report The World Bank Document No.: 10003564-HOU-R-01 Date: 8 May 2018 Issue: C IMPORTANT NOTICE AND DISCLAIMER 1. This document is intended for the sole use of the Customer as detailed on the front page of this document to whom the document is addressed and who has entered into a written agreement with the DNV GL entity issuing this document (“DNV GL”). To the extent permitted by law, neither DNV GL nor any group company (the "Group") assumes any responsibility whether in contract, tort including without limitation negligence, or otherwise howsoever, to third parties (being persons other than the Customer), and no company in the Group other than DNV GL shall be liable for any loss or damage whatsoever suffered by virtue of any act, omission or default (whether arising by negligence or otherwise) by DNV GL, the Group or any of its or their servants, subcontractors or agents. 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This document has been produced from information relating to dates and periods referred to in this document. This document does not imply that any information is not subject to change. Except and to the extent that checking or verification of information or data is expressly agreed within the written scope of its services, DNV GL shall not be responsible in any way in connection with erroneous information or data provided to it by the Customer or any third party, or for the effects of any such erroneous information or data whether or not contained or referred to in this document. 4. Any energy forecasts estimates or predictions are subject to factors not all of which are within the scope of the probability and uncertainties contained or referred to in this document and nothing in this document guarantees any particular wind speed or energy output. KEY TO DOCUMENT CLASSIFICATION For disclosure only to named individuals within the Customer’s Strictly Confidential : organization. For disclosure only to individuals directly concerned with the Private and Confidential : subject matter of the document within the Customer’s organization. Commercial in Confidence : Not to be disclosed outside the Customer’s organization. DNV GL only : Not to be disclosed to non-DNV GL staff Distribution for information only at the discretion of the Customer (subject to the above Important Notice and Disclaimer and the Customer’s Discretion : terms of DNV GL’s written agreement with the Customer). Available for information only to the general public (subject to the Published : above Important Notice and Disclaimer). DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page i www.dnvgl.com Project name: Renewable Energy Wind Mapping for Zambia GL Garrad Hassan Canada, Inc. Report title: 12-month Site Resource Report Energy, Advisory Americas Customer: The World Bank 4100 Rue Molson, Suite 100 1818 H Street, N.W. Montreal, QC H1Y 3N1, Canada Washington, DC 20433 Tel: +1 (514) 272-2175 Enterprise No.: 860480037 Contact person: Kenta Usui Date of issue: 8 May 2018 Project No.: 10034303 Document No.: 10003564-HOU-R-01, Issue C Task and objective: Wind resource assessment at eight mast locations across Zambia, and energy estimates for eight preliminary wind farms. Prepared by: Verified by: Approved by: J. Basson P. Gurbas S. Dokouzian Energy Analyst, Energy Services Energy Analyst, Energy Services Senior Project Manager, Development and Engineering Services S. Bourne KVP Leader, Renewable Energy Project Development ☐ Strictly Confidential Keywords: ☐ Private and Confidential Wind Resource, Energy Assessment, ESMAP, Zambia ☐ Commercial in Confidence ☐ DNV GL only ☒ Customer’s Discretion ☐ Published © Garrad Hassan America, Inc.. All rights reserved. Reference to part of this report which may lead to misinterpretation is not permissible. Issue Date Reason for Issue Prepared by Verified by Approved by A 19 March 2018 Initial revision for review J. Basson P. Gurbas / S. Bourne, S. Dokouzian B 4 May 2018 Added WB comments - Final J. Basson P. Gurbas / S. Bourne, S. Dokouzian C 8 May 2018 Additional WB comments - J. Basson P. Gurbas / S. Bourne, S. Dokouzian Final DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page ii www.dnvgl.com Table of contents EXECUTIVE SUMMARY ..................................................................................................................... 6 1 INTRODUCTION ........................................................................................................................... 9 2 PROJECT DESCRIPTION .............................................................................................................. 10 2.1 Site description ....................................................................................................................... 10 2.2 Turbine technology .................................................................................................................. 11 2.3 Neighboring wind farms ........................................................................................................... 12 3 ON-SITE WIND MONITORING ...................................................................................................... 13 3.1 Wind resource measurements ................................................................................................... 13 3.2 Data processing ...................................................................................................................... 13 4 WIND ANALYSIS ........................................................................................................................ 15 4.1 Measurement height wind regime .............................................................................................. 15 4.2 Hub-height wind regime ........................................................................................................... 17 4.3 Wind regime across the site ...................................................................................................... 21 5 ENERGY ANALYSIS ..................................................................................................................... 22 5.1 Preliminary wind turbine layouts ................................................................................................ 22 5.2 Gross and net energy estimates ................................................................................................ 22 5.3 Seasonal and diurnal distributions ............................................................................................. 24 6 UNCERTAINTY ........................................................................................................................... 26 7 SITE CONDITIONS ..................................................................................................................... 27 7.1 Turbulence Intensity ................................................................................................................ 27 7.2 Extreme wind speeds ............................................................................................................... 29 8 OBSERVATIONS AND RECOMMENDATIONS .................................................................................... 32 9 CONCLUSION ............................................................................................................................ 34 10 REFERENCES ........................................................................................................................... 35 Appendices APPENDIX A WIND DATA STATISTICS APPENDIX B REFERENCE STATIONS CONSIDERED APPENDIX C WIND FARM SITE INFORMATION AND LAYOUTS APPENDIX D TURBINE LAYOUT RESULTS APPENDIX E MONTHLY AND DIURNAL PRODUCTION PROFILES APPENDIX F UNCERTAINTY ANALYSIS DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page iii www.dnvgl.com APPENDIX G SITE CONDITIONS DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page iv www.dnvgl.com List of tables Table 2-1 Site descriptions ............................................................................................................. 11 Table 2-2 Proposed turbine model parameters .................................................................................. 11 Table 3-1 Met mast summary ......................................................................................................... 13 Table 3-2 Summary of site masts data coverage ............................................................................... 14 Table 4-1 Site period wind speeds ................................................................................................... 15 Table 4-2 Reference data sets considered for correlation to site data .................................................... 16 Table 4-3 Reference data sets considered for correlation to site data .................................................... 16 Table 4-4 Applied long-term wind speed adjustments ........................................................................ 17 Table 4-5 Shear exponents and hub height wind speeds ..................................................................... 17 Table 4-6 Average long-term hub height wind speed estimates at the turbine locations........................... 21 Table 5-1 Generic power curve ....................................................................................................... 23 Table 5-2 Energy production summary............................................................................................. 23 Table 6-1 Summary of project net average energy production for each site ........................................... 26 Table 6-2 Site average sensitivity ratios ........................................................................................... 26 Table 7-1 Predicted extreme wind speeds by Method of Independent Storms (MIS) at selected turbine locations ..................................................................................................................................... 30 Table 7-2 Maximum 10-min and 3-sec wind speeds at mast locations ................................................... 31 Table G-1 Predicted profiles of design equivalent turbulence intensity at the Choma site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................... 1 Table G-2 Predicted profiles of design equivalent turbulence intensity at the Mwinilunga site for a Generic 4 MW wind turbine at a hub height of 130 m ......................................................................................... 3 Table G-3 Predicted profiles of design equivalent turbulence intensity at the Lusaka site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................... 5 Table G-4 Predicted profiles of design equivalent turbulence intensity at the Mpika site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................... 7 Table G-5 Predicted profiles of design equivalent turbulence intensity at the Chanka site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................... 9 Table G-6 Predicted profiles of design equivalent turbulence intensity at the Petauke site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................. 11 Table G-7 Predicted profiles of design equivalent turbulence intensity at the Mansa site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................. 13 Table G-8 Predicted profiles of design equivalent turbulence intensity at the Malawi site for a Generic 4 MW wind turbine at a hub height of 130 m ............................................................................................. 15 List of figures Figure 2-1 Mast locations ............................................................................................................... 10 Figure 4-1 Long-term hub-height frequency distribution and wind roses ............................................... 21 Figure 5-1 Annual energy production profiles .................................................................................... 25 Figure 7-1 Predicted profiles of site minimum, maximum and average design equivalent turbulence intensity for the Mpika site using a Generic 4.0 MW wind turbine at a hub height of 130 m ...................... 29 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page v www.dnvgl.com EXECUTIVE SUMMARY The World Bank (the “Customer”) retained Garrad Hassan America, Inc. (DNV GL) to complete a 12-month Site Resource Report, which consists of an independent analysis of the wind regime and energy production at eight locations across Zambia, as part of the Renewable Energy Wind Mapping for Zambia (part of the ESMAP Program). The results of the work are reported here. The overall mandate consists of providing a validated mesoscale wind atlas for Zambia, including associated deliverables and wind energy development training courses. Meteorological data is collected at eight sites over a 2-year period. The 12-month Site Resource Report provides interim wind resource statistics at the eight masts and energy production estimates for generic wind farms in the vicinity of the masts. The program’s goal is to provide Zambian policy makers, stakeholders, and independent power producers with accurate and valuable knowledge of the national wind resource, including complementary tools, which can be of direct practical use, both for formulating energy policy and implementing wind projects. The eight meteorological masts were installed and commissioned in November and December 2016. Based on a single year of data collection, DNV GL has evaluated the wind resource at each location, the long-term wind regime, and the estimated energy production based on a generic 4 MW wind turbine, with a rotor of 140 m and a hub height of 130 m. A brief summary of the key results is presented in the table below. Results Choma Mwinilunga Lusaka Mpika Average air density at hub elevation [kg/m3] 1.00 0.99 1.03 1.00 On-site measurement period [years] 1.2 1.1 1.1 1.1 Long-term reference period [years] 16.0 16.0 16.0 16.0 Long-term hub height wind speed at met mast [m/s] 7.4 7.4 7.9 7.3 Average turbine wind speed [m/s] 7.4 7.5 8.2 7.3 10-year P50 Net Energy [GWh/annum] 303.0 323.3 386.0 320.3 10-year P50 Net Capacity Factor [%] 34.6% 36.9% 44.0% 36.5% Results Chanka Petauke Mansa Malawi Average air density at hub elevation [kg/m3] 1.01 1.04 1.01 1.04 On-site measurement period [years] 1.1 1.1 1.1 1.1 Long-term reference period [years] 16.0 16.0 16.0 16.0 Long-term hub height wind speed at met mast [m/s] 7.4 6.5 6.9 6.9 Average turbine wind speed [m/s] 7.5 7.0 7.3 7.1 10-year P50 Net Energy [GWh/annum] 345.6 291.5 314.7 303.7 10-year P50 Net Capacity Factor [%] 39.4% 33.2% 35.9% 34.6% Other key conclusions and recommendations from the study are as follows: • The net energy predictions presented above represent the long-term mean, 50% exceedance level, for the annual energy production of the generic wind farms. These values are the best estimate of the long-term mean values to be expected from the project. There is therefore a 50% chance that, DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 6 www.dnvgl.com even when taken over very long periods, the mean energy production will be less than the values given. • The standard error associated with the prediction of energy capture has been calculated and the confidence limits for the prediction are given in the table below. Site Choma Mwinilunga Lusaka Mpika Probability of exceedance 10-year average [GWh/annum] 50% 303.0 323.3 386.0 320.3 75% 276.2 297.0 353.9 292.1 90% 251.8 272.4 323.3 266.5 95% 236.8 257.0 304.7 250.5 99% 209.2 227.6 268.1 222.6 Site Chanka Petauke Mansa Malawi Probability of exceedance 10-year average [GWh/annum] 50% 345.6 291.5 314.7 303.7 75% 311.2 261.5 286.4 274.2 90% 279.9 233.6 260.6 247.3 95% 260.3 217.2 244.5 230.5 99% 223.3 186.3 214.2 201.7 • Some of the uncertainties in the table above are considered to be high based on DNV GL expectations for a modern utility-scale wind farm. The largest contributors to uncertainty in the estimates above included the evaluation of the long-term wind regime, wind shear extrapolation, and horizontal extrapolation. DNV GL notes the following observations and opinions regarding uncertainty: - The uncertainty in the long-term analysis was driven by the lack of viable ground-stations to verify the reanalysis data used to conduct the long-term analysis. For this reason, there is increased uncertainty in the long-term wind regime at each site. - The uncertainty associated with the vertical extrapolation to hub height was elevated at all sites due to the large extrapolation distance. It was particularly high at Mwinilunga, Lusaka, Mansa, and Malawi where low wind speeds and strong thermal heating patterns resulting in high values of measured wind shear at the met mast locations. There is uncertainty that these measurements will remain constant to the estimated turbine hub height of 130 m and additional uncertainty where the wind turbines are site large distances away from the met mast where the measurements were taken. To reduce the uncertainty associated with the vertical wind speed extrapolation, DNV GL strongly recommends the use of taller met masts and/or remote sensing to characterize the wind regime above the existing mast height. - The uncertainty associated with the horizontal extrapolation of the wind speeds is high at some sites due to the distance of the turbine locations from the proposed met mast and the unavailability of high resolution elevation data. Some turbines were sited in locations far from DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 7 www.dnvgl.com the met masts in an effort to maximize energy production. For a bankable wind energy assessment, DNV GL recommends placing measurements at the location of the proposed wind turbines, with each of the wind turbines at least 2 km from a met mast. • The proposed wind turbine layouts are preliminary and consider general siting requirements, but not detailed environmental, technical, or construction constraints. A more thorough feasibility analysis shall be undertaken to evaluate if the areas can host wind turbines and interconnect to the transmission network. The purpose of the analysis is to provide a general understanding of how a generic wind farm would be sited and how it would perform, while taking into consideration the uncertainties and recommendations above. • The turbine capacity [MW] and power curve for the generic turbine is a conservative representation of current technology and reflects the type of technology that is expected to be deployed in the near future. Careful selection of a wind turbine model suitable for the site should be considered, including transportation logistics feasibility. • The met masts were sited in their current locations primarily for the purpose of validating the national wind atlas, upon completion of 24 months of data acquisition. Some of the locations may also be suitable for large scale wind development, but not all are ideal for this purpose. As such, DNV GL recommends that stakeholders wishing to develop a wind project in Zambia not restrict their site selection to the eight mast locations, as there is wind energy potential in locations across the country that are not currently well-represented by a met mast. To conclude, there is now an established network of state-of-the-art wind measurement masts in Zambia that can be used to support stakeholder wind analysis activities and future utility-scale wind development in-country. In the future, this network of masts will also provide the industry with a source of long-term reference station data which could greatly reduce uncertainties for potential developers. The data collected from the eight met masts are considered very good both in terms of data quality and data coverage. Further investment by stakeholders in well-organized measurement campaigns and in feasibility analysis that are focused on reducing uncertainties will help support future growth of the Zambian wind market. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 8 www.dnvgl.com 1 INTRODUCTION The World Bank (the “Customer”) retained Garrad Hassan America, Inc. (DNV GL) to complete a 12-month Site Resource Report, which consists of an independent analysis of the wind regime and energy production at eight locations across Zambia, as part of the Renewable Energy Wind Mapping for Zambia (part of the ESMAP Program). The results of the work are reported here. This report presents a description of the project sites and turbine technology. It then describes the available measurements and analysis of the wind data followed by an evaluation of the expected project gross and net energy for preliminary wind farms in the vicinity of the masts, as influenced by assumed losses and uncertainties. Finally, it presents DNV GL’s observations and recommendations. The overall mandate consists of providing a validated mesoscale wind atlas for Zambia, including associated deliverables and wind energy development training courses. Meteorological data is collected at eight sites over a 2-year period. The 12-month Site Resource Report provides interim wind resource statistics at the eight masts and energy production estimates for preliminary wind farms in the vicinity of the masts. The program’s goal is to provide Zambian policy makers, stakeholders, and independent power producers with accurate and valuable knowledge of the national wind resource, including complementary tools, which can be of direct practical use, both for formulating energy policy and implementing wind projects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 9 www.dnvgl.com 2 PROJECT DESCRIPTION The masts that form part of the ESMAP program are located across Zambia to inform the wind mapping studies. Measurements of the wind regime have been made at eight meteorological (met) masts locations across Zambia as shown in Figure 2-1. DNV GL has analyzed a preliminary 25-turbine layout for a Generic 4 MW wind turbine at a hub height of 130 m close to each mast location to assess the potential energy production at each location. Figure 2-1 Mast locations 2.1 Site description The met masts and proposed preliminary wind farms are located throughout Zambia, and the terrain complexity and ground cover vary from site to site. DNV GL has generated a preliminary turbine layout for each site based on a Generic 4 MW wind turbine at a hub height of 130 m. Figures showing the location of the proposed wind turbines and the met masts for each site are provided in Appendix C. DNV GL commissioned the eight masts, therefore the measurement equipment has been inspected and the ground cover at the eight mast locations has been assessed. Table 2-1 below provides a brief summary of each site in terms of the terrain and ground cover and also provides insight into the range of turbine base DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 10 www.dnvgl.com elevations. Note that some wind turbine layouts are at significant distances from the masts in an effort to maximize energy production. Table 2-1 Site descriptions Site Turbine base Brief description location elevations [m] The site is located in an area of rural agricultural land approximately 20 km west of the town of Choma in the Southern Province. The ground cover consists Choma 1346-1390 mainly of low shrub-like vegetation interspersed with small trees and residences. The site is located on a slightly elevated and lightly forested plateau approximately 60 km southeast of the town of Mwinilunga in the North-West Mwinilunga 1512-1545 Province. The ground cover consists mainly of shrub-like vegetation interspersed with trees. The site is located in an area of flat, rural agricultural land approximately 70 km Lusaka northwest of the city of Lusaka in the Central Province. The ground cover 1157-1183 consists mainly of low crops interspersed with trees and residences. The site is located in an area of low lying bush and rural agricultural land approximately 25 km northwest of the town of Mpika in the Northern Province. Mpika 1383-1415 The ground cover consists mainly of low shrub-like vegetation interspersed with trees and sparse residences. The site is located in an area of rural agricultural land approximately 80 km northeast of the town of Isoka in the Northern Province. The site is located Chanka between 35 and 50 km from the Malawi and Tanzanian borders, respectively on 1273-1332 the crest of a plateau. The ground cover consists mainly of low shrub-like vegetation interspersed with small residences. The site is located in an area of rolling hills approximately 15 km northwest of Petauke the town of Petauke in the Eastern Province. The ground cover consists mainly 982-1090 of low lying crops and bush interspersed with small trees. The site is located in on a small southwest-northeast ridge approximately 35 Mansa km north of the town of Mansa in the Luapula Province. The ground cover 1300-1390 consists mainly of low shrub-like vegetation. The site is located in an area of flat, rural agricultural land approximately 80 km Malawi east of the town of Chipata in the Eastern Province. The ground cover consists 1039-1080 mainly of low lying crops and bush interspersed with small trees. A map of each site is presented in Appendix C showing the meteorological mast and turbine locations. 2.2 Turbine technology The power curve used in this analysis represents a blended generic turbine model that has been generated by DNV GL. Table 2-2 summarizes the turbine model under consideration for each site. Table 2-2 Proposed turbine model parameters Valid PC Rated power Peak power Valid PC density turbulence Turbine Hub height [m] [MW] coefficient [Cp] [kg/m3] intensity range [%] Generic 4 MW 4.0 130 0.44 1.225 6-12 Given the preliminary nature of the generic power curve used in this assessment, DNV GL recommends that potential stakeholders conduct a thorough market review of available technologies when assessing a potential wind farm site in Zambia. Turbine manufacturers should be approached at an early stage to gain acceptance of proposed turbine layouts and turbine suitability for each site and evaluate the need, if any, for DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 11 www.dnvgl.com mitigation of fatigue loads through wind sector management. It shall also be noted that some turbine models may provide better energy capture and therefore improve the overall performance at the sites. 2.3 Neighboring wind farms To DNV GL’s knowledge, there are no utility-scale operational wind farms currently in Zambia. Therefore, no external wake effects are considered in the analysis. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 12 www.dnvgl.com 3 ON-SITE WIND MONITORING 3.1 Wind resource measurements Wind resource measurements have been recorded at the eight sites using met masts with measurements taken from November 2016 to January 2018. The characteristics of these measurements are summarized in Table 3-1. Table 3-1 Met mast summary Calibration Anemometer(s) Anemometer Anemometer certificate by mounted in Mast manufacturer Period heights MEASNET compliance with and model facility? IEC guidance?a 80 m (x2), 60 m (x2), Thies FCA, November 2016 – Choma Yes Compliant 42 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, December 2016 – Mwinilunga Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, November 2016 – Lusaka Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, November 2016 – Mpika Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, November 2016 – Chanka Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, December 2016 – Petauke Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, November 2016 – Mansa Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 80 m (x2), 60 m (x2), Thies FCA, December 2016 – Malawi Yes Compliant 41 m (x2), 20 m (x2) NRG Class 1 January 2018 a. IEC 61400-12:2005 E [1] The mounting arrangements of the instrumentation at the site masts are consistent with the recommendations of the IEC [1] and therefore considered to be in accordance with industry best practice for good quality wind measurements. Additional details about the configuration of each mast are available in the mast Commissioning Reports [2]. 3.2 Data processing Raw data from the met mast at each site have been collected by DNV GL. The wind data have been subject to a quality checking procedure by DNV GL to identify records which were affected by equipment malfunction and other anomalies. These records were excluded from the analysis. To minimize mast effects in the measured wind speed data, selective averaging was undertaken of the data recorded at the all instrumentswhere parallel measurements were available. The duration, basic statistics, and data coverage for the masts are summarized in Appendix A. Wind data coverage is generally very good, with only minor data loss. Overall data coverage levels for the key parameters and instruments on each mast are shown in the following Table 3-2. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 13 www.dnvgl.com Table 3-2 Summary of site masts data coverage Wind speed Available period Valid period Measured wind Mast Height [m] data coverage [years] [years] speed [m/s] [%] Choma 80 1.2 1.1 6.5 95 Mwinilunga 80 1.1 1.1 6.0 100 Lusaka 80 1.1 1.1 6.2 99 Mpika 80 1.1 1.1 6.2 100 Chanka 80 1.1 1.1 6.5 100 Petauke 80 1.1 1.1 5.7 100 Mansa 80 1.1 1.1 5.8 100 Malawi 80 1.1 1.1 5.8 100 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 14 www.dnvgl.com 4 WIND ANALYSIS The analysis of the site wind regime involved several steps. A summary of the results for each step of the process are provided in the following sections. 4.1 Measurement height wind regime 4.1.1 Site period wind speeds Data were recorded at the site masts up to a measurement height of 80 m and over data period ranging from November 2016 to January 2018. Data coverage at the eight masts was between 95% and 100% and the measured mean wind speeds ranged from 5.7 m/s to 6.5 m/s. The values for each individual site are shown in Table 4-1 and in Appendix A. Table 4-1 Site period wind speeds Measured mean Mast Height [m] Data Period Data coverage [%] wind speed [m/s] Choma 80.0 01/11/2016 – 10/01/2018 95 6.5 Mwinilunga 80.0 03/12/2016– 09/01/2018 100 6.0 Lusaka 80.0 21/11/2016– 09/01/2018 99 6.2 Mpika 80.0 20/11/2016– 09/01/2018 100 6.2 Chanka 80.0 23/11/2016– 10/01/2018 100 6.5 Petauke 80.0 09/12/2016– 09/01/2018 100 5.7 Mansa 80.0 26/11/2016– 10/01/2018 100 5.8 Malawi 80.0 21/12/2016– 10/01/2018 100 5.8 It should be noted that the wind speeds presented in Table 4-1 represent only the measured period of data at each location. DNV GL conducts a review of the representativeness of the measured data of the long-term wind regime in the following sections of this report. 4.1.2 Extension of the site period to the reference period The inclusion of quality reference data can reduce the uncertainty in the estimate of the long-term wind regime at the site. When selecting appropriate reference data for this purpose it is important that the reference data’s wind regime is driven by similar factors as the site wind regime and the reference data are consistent over the measurement period being considered. 4.1.2.1 Reference data considered DNV GL has undertaken a review of the sources of reference data at each site in order to identify appropriate long-term reference stations for this analysis. Given the lack of viable ground station networks in Zambia with long-term, consistent data periods, this analysis has relied heavily upon reanalysis and virtual datasets. At each site, DNV GL has correlated the measured wind data to DNV GL’s Virtual Met Data (VMD), ERA-Interim and MERRA-2. More information about these reference stations are provided in Appendix B. Table 4-2 summarizes the stations considered. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 15 www.dnvgl.com Table 4-2 Reference data sets considered for correlation to site data Meteorological Distance from Site location Network Start date End date data source site VMD DNV GL On-site 02 Jan 2002 26 Nov 2017 Choma ERA ECMWF 158 km northeast 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 67 km northwest 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 01 Jan 2002 26 Nov 2017 Mwinilunga ERA ECMWF 115 km northwest 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 82 km north 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 26 Nov 2017 Lusaka ERA ECMWF 79 km northeast 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 35 km north 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 26 Nov 2017 Mpika ERA ECMWF 78 km northwest 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 80 km west 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 27 Dec 2017 Chanka ERA ECMWF 110 km northwest 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 80 km north 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 27 Dec 2017 Petauke ERA ECMWF 50 km west 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 34 km south 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 26 Nov 2017 Mansa ERA ECMWF 70 km northwest 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 59 km northeast 01 Jan 2002 01 Jan 2018 VMD DNV GL On-site 02 Jan 2002 27 Dec 2017 Malawi ERA ECMWF 97 km northeast 01 Jan 2002 01 Jan 2018 MERRA-2 NASA 52 km northwest 01 Jan 2002 01 Jan 2018 To determine whether use of reference data will reduce uncertainty, a correlation of monthly mean wind speeds between each consistent reference station and the site was completed. The results of this analysis are summarized in Table 4-3. Table 4-3 Reference data sets considered for correlation to site data Coefficient of determination, R2 Site VMD ERA MERRA-2 Choma 0.81 0.88 0.87 Mwinilunga 0.95 0.92 0.97 Lusaka 0.91 0.88 0.90 Mpika 0.89 0.93 0.97 Chanka 0.93 0.93 0.98 Petauke 0.91 0.95 0.97 Mansa 0.94 0.97 0.98 Malawi 0.79 0.97 0.97 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 16 www.dnvgl.com During the analysis, DNV GL evaluates each long-term reference source for each site based on: • how representative the location at which the reference source is defined is of the mast location, • the strength of the correlation between the reference source data and the site mast data, and • the consistency of the reference source data. DNV GL’s resulting choice of reference data sources and the corresponding long term adjustment for each site are shown in Table 4-4. Table 4-4 Applied long-term wind speed adjustments Reference data sources Long-term adjusted Site included in long-term Long term adjustment mean wind speed, [m/s] adjustment Choma ERA 1.6% 6.6 Mwinilunga VMD, MERRA-2 -0.4% 6.0 Lusaka VMD, ERA, MERRA-2 4.3% 6.5 Mpika VMD, MERRA-2 2.4% 6.3 Chanka VMD 1.9% 6.6 Petauke VMD 0.0% 5.7 Mansa VMD, MERRA-2 1.4% 5.9 Malawi VMD, MERRA-2 1.3% 5.8 It is noted that there is a lack of viable ground-station reference data to evaluate the consistency of the reanalysis and virtual datasets considered in this assessment. For this reason, there is increased uncertainty in the long-term wind regime at each site. This elevated uncertainty is considered in Section 6. 4.2 Hub-height wind regime 4.2.1 Hub-height wind speed To extrapolate the wind speed estimates from the measurement height to the 130 m hub height, the average power law at the site masts has been evaluated between all relevant measurement heights and applied to the upper level measurements. The results of this analysis are shown in Table 4-5. Table 4-5 Shear exponents and hub height wind speeds Long-term upper Hub Height wind speed Mast measurement height Wind shear exponent estimate [m/s] wind speed [m/s] Choma 6.6 0.24 7.4 Mwinilunga 6.0 0.29 7.4 Lusaka 6.5 0.34 7.9 Mpika 6.3 0.21 7.3 Chanka 6.6 0.21 7.4 Petauke 5.7 0.26 6.5 Mansa 5.9 0.31 6.9 Malawi 5.8 0.34 6.9 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 17 www.dnvgl.com It is noted that the measured wind shear at some mast locations is considered to be high (>0.25). Based on further review, DNV GL determined that the high wind shear measured at these masts is driven by the low wind speeds experienced on-site and thermal heating and cooling close to the ground surface. The thermal convection from the ground decreases wind speeds at the surface and this attenuating effect tends to decrease with altitude as the flow becomes more free stream and laminar. The thermal heating and cooling at the surface results in relatively high magnitudes of measured wind shear at some of the met masts. There is uncertainty that the wind shear measured at the met masts will remain constant with increasing altitude, and this uncertainty is higher when the estimated wind shear exponents are higher. DNV GL recommends the use of remote sensing for site prospecting in Zambia, in order to more accurately characterize the vertical wind speed profile. Remote sensing measurements will further the understanding of the vertical wind speed profile and has the potential to drastically reduce the vertical extrapolation uncertainty, especially at sites where the extrapolation distance is large. 4.2.2 Hub-height wind speed and direction distributions The hub-height wind speed and direction distributions were developed by extrapolating the measured wind speed data on a time series basis. Key project specific aspects of the analysis were: • The distribution from each site mast was used as the basis of the analysis. • The frequency distribution of each site mast was scaled to the representative long term hub height mean wind speed. A representative long-term hub-height wind rose and wind speed histogram for each site are shown in Figure 4-1. Choma 10% 20% 30% 0-3 3-6 6-9 >9m/s DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 18 www.dnvgl.com Mwinilunga 10% 20% 30% 40% 0-3 3-6 6-9 >9m/s Lusaka 10%20%30%40%50% 0-3 3-6 6-9 >9m/s Mpika 10%20%30%40%50% 0-3 3-6 6-9 >9m/s DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 19 www.dnvgl.com Chanka 20% 40% 60% 0-3 3-6 6-9 >9m/s Petauke 10% 20% 30% 40% 0-3 3-6 6-9 >9m/s Mansa 10% 20% 30% 40% 0-3 3-6 6-9 >9m/s DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 20 www.dnvgl.com Malawi 10% 20% 30% 0-3 3-6 6-9 >9m/s Figure 4-1 Long-term hub-height frequency distribution and wind roses DNV GL notes that most of the wind speed frequency distributions measured by the site masts do not exhibit a standard Weibull shape. This factor should be considered when modeling the energy production at proposed sites across Zambia, as it could lead to inaccuracies in energy production estimates. 4.3 Wind regime across the site The variation in wind speed over each site was predicted using the industry standard commercial WAsP wind flow modelling software. Each mast has been used to initiate the wind flow modeling used to predict the long-term wind regimes at the turbine locations at its respective site. The average extrapolation distances across the eight sites ranges from 3.6 km at Mpika to 24.1 km at Chanka. Through this approach, the predicted long-term mean wind speeds at each turbine at the proposed hub height are presented in Appendix D. Table 4-6 summarizes the average turbine wind speed at each site at 130 m. It should be noted that WAsP calculations have high uncertainties when calculations: extend over large spatial distances; are initiated from positions with markedly different elevations, wind climates or exposure to those of the proposed turbine locations. The WAsP wind flow model is also not suited to stable atmospheric conditions. For further wind assessment studies in Zambia, DNV GL recommends the use of CFD wind flow modeling to decrease horizontal extrapolation uncertainties. Table 4-6 Average long-term hub height wind speed estimates at the turbine locations Average turbine wind Site speed at 130 m [m/s] Choma 7.4 Mwinilunga 7.5 Lusaka 8.2 Mpika 7.3 Chanka 7.5 Petauke 7.0 Mansa 7.3 Malawi 7.1 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 21 www.dnvgl.com 5 ENERGY ANALYSIS 5.1 Preliminary wind turbine layouts DNV GL produced 100 MW preliminary wind turbine layouts in the vicinity of the eight masts. The proposed wind turbine layouts are preliminary and consider general siting requirements, but not detailed environmental, technical, or construction constraints. The purpose of the layouts is to provide a general understanding of how a wind farm would be sited and how it would perform, while taking into consideration the uncertainties and recommendations throughout this report. The layouts are comprised of 25 – 4 MW generic wind turbines, with a rotor of 140 m and a hub height of 130 m. DNV GL designed the preliminary wind farm layouts with the objective of maximizing the energy output of the wind farm, while generally considering balance-of-plant (BOP). In addition to best practices, the following parameters were considered: • A minimum of 3 rotor diameters spacing perpendicular to prevailing winds. • A minimum of 6 rotor diameters spacing parallel to prevailing winds. • No turbines in areas of terrain slope greater than 15%. • Nearby roadway access, and access in terrain with slopes no greater than 10%. • No turbines in general environmentally constrained areas as defined at the national level under the initial site selection report [3]. Site-specific and in-depth analysis of environmental constraints were not conducted. • Reasonable setbacks to dwellings and settlements, broadly identified using aerial imagery. Site specific review and field validation of inhabited areas was not conducted and firm setbacks to be established for a more final layout optimization study. In addition, DNV GL did not consider mechanical loading on wind turbines to ensure suitability with site conditions, sound levels at nearby inhabited areas, and interconnection feasibility. The wind turbine layouts are presented in Appendix C, and the coordinates in Appendix D. 5.2 Gross and net energy estimates The gross energy production at the individual turbine locations has been calculated using the WindFarmer software and the results of the wind flow modeling. A theoretical and generic power curve was created by DNV GL for a 4 MW wind turbine. The power curve is shown in Table 5-1 for an air density of 1.225 kg/m3. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 22 www.dnvgl.com Table 5-1 Generic power curve Wind speed [m/s] Power production [kW] 0-2 0 3 17 4 190 5 471 6 880 7 1429 8 2145 9 2956 10 3630 11 3925 12 - 25 4000 The projected net energy production of each wind farm shown in Table 5-2 was calculated by applying a number of energy loss factors to the gross energy production. The predictions represent the estimate of the annual production expected over the first 10 years of operation. The individual turbine results are presented in Appendix D. Table 5-2 Energy production summary Scenario Choma Mwinilunga Lusaka Mpika Chanka Petauke Mansa Malawi Wind Farm Rated 100 100 100 100 100 100 100 100 Power [MW] Gross Energy Output 356.6 374.8 435.9 364.2 387.5 337.3 355.6 345.3 [GWh/annum] Array effects [%] 95.0 95.9 98.4 97.4 98.3 95.3 98.0 97.3 Availability [%] 94.1 94.1 94.1 94.1 94.1 94.1 94.1 94.1 Electrical efficiency 97.5 97.5 97.5 97.5 97.5 97.5 97.5 97.5 [%] Turbine performance 97.6 98.1 98.1 98.5 99.0 98.9 98.4 98.5 [%] Environmental [%] 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Curtailments [%] 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Total Losses (%) 85.0 86.2 88.6 88.0 89.2 86.4 88.5 88.0 Asymmetric production 100.0 99.9 100.0 100.0 100.0 100.0 100.0 100.0 effect [%] Net Energy Output 303.0 323.3 386.0 320.3 345.6 291.5 314.7 303.7 [GWh/annum] Net Capacity Factor 34.6 36.9 44.0 36.5 39.4 33.2 35.9 34.6 [%] DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 23 www.dnvgl.com Table 5-2 includes potential sources of energy loss that have been either assumed to be the DNV GL standard values or estimated for this project. Project specific aspects of the loss estimates are provided in the following bullets: • Array effect – The array effects have been calculated using the WindFarmer 5 wake model and consider internal and external array effects. No neighboring or future wind farms are currently considered in the loss estimates. • Availability – This category considers turbine availability, balance of plant, and grid availability. Considering the Generic 4 MW turbine model, the turbine availability for year 1 of operation was estimated to be 94.0% and for years 2-5 to be 96.0%. Subsequent years were adjusted in accordance with DNV GL’s standard method. Generic values were used to estimate balance of plant and grid availability losses. • Operational electrical efficiency – Details of the specific balance of plant infrastructure and grid connection point have not been considered. Therefore, DNV GL has considered a standard loss value. • Turbine performance – As part of the turbine performance category, DNV GL has considered high wind speed hysteresis, site specific power curve adjustment, and performance degradation over time. • Environmental – Detailed environmental losses were not considered in this analysis. • Curtailments – Detailed curtailment losses were not considered in this analysis. 5.3 Seasonal and diurnal distributions The expected seasonal and diurnal variation in energy production at 130 m is presented at each site in Appendix E in the form of a 12-month by 24-hour (12 x 24) matrix, and generally presented in Figure 5-1 below. It is noted that the uncertainty associated with the prediction of any given month or hour of day is significantly greater than that associated with the prediction of the annual energy production. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 24 www.dnvgl.com 16 14 % of annual production 12 10 8 6 4 2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Choma Mwinilunga Lusaka Mpika Chanka Petauke Mansa Malawi Figure 5-1 Annual energy production profiles DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 25 www.dnvgl.com 6 UNCERTAINTY The main sources of deviation from the central estimate (P50) have been quantified and combined using a probabilistic model, assuming full independence between the sources. The results of the probabilistic simulation of net energy production are summarized for the Generic 4 MW scenario in Table 6-1 and detailed in Appendix F. The average calculated sensitivity ratio for variations of 10% on wind speed is shown in Table 6-2. Table 6-1 Summary of project net average energy production for each site Choma, Mwinilunga, Lusaka, Mpika, Site [GWh/annum] [GWh/annum] [GWh/annum] [GWh/annum] Probability of 10-year 10-year 10-year 10-year 1-Year 1-Year 1-Year 1-Year exceedance average average average average 50% 303.1 303.0 323.7 323.3 386.7 386.0 320.5 320.3 75% 266.7 276.2 289.2 297.0 346.0 353.9 282.3 292.1 90% 233.2 251.8 256.2 272.4 306.8 323.3 246.9 266.5 95% 213.3 236.8 235.7 257.0 282.2 304.7 225.3 250.5 99% 176.8 209.2 196.5 227.6 236.0 268.1 185.9 222.6 Chanka, Petauke, Mansa, Malawi, Site [GWh/annum] [GWh/annum] [GWh/annum] [GWh/annum] Probability of 10-year 10-year 10-year 10-year 1-Year 1-Year 1-Year 1-Year exceedance average average average average 50% 346.4 345.6 291.2 291.5 314.7 314.7 303.7 303.7 75% 303.0 311.2 253.0 261.5 278.2 286.4 265.8 274.2 90% 261.3 279.9 217.3 233.6 243.6 260.6 230.3 247.3 95% 236.2 260.3 196.4 217.2 222.7 244.5 209.0 230.5 99% 189.5 223.3 158.1 186.3 183.3 214.2 170.7 201.7 Table 6-2 Site average sensitivity ratios Site Sensitivity ratio Choma 2.04 Mwinilunga 1.67 Lusaka 1.53 Mpika 2.00 Chanka 1.87 Petauke 2.06 Mansa 1.84 Malawi 1.97 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 26 www.dnvgl.com 7 SITE CONDITIONS The site meteorological conditions assessment reported here uses inputs and analysis detailed in the energy production assessment of each site, and it is recommended that this is considered in conjunction with the present report. It is noted that this report provides a comparison of the on-site meteorological conditions to the limits of the wind class, using the assumption that all the sites are Class IIIA. A generic turbine power curve has been used in this assessment, and therefore, a conclusion on the suitability of the turbine is not appropriate. However, it is recommended that the turbine manufacturer being considered for each site considers suitable margins in the context of confirming turbine suitability, turbine supply agreement and warranties, and that the results of this assessment are reviewed with consideration of the inherent uncertainties. 7.1 Turbulence Intensity 7.1.1 Frandsen design equivalent turbulence intensity at the turbine locations Fatigue loading on wind turbines and their support structures is primarily the result of stochastic loading, originating from wind turbulence. In order to fully capture the turbulence conditions for the purposes of such load calculations, the cumulative effect of the ambient flow characteristics of the site and the wind farm must be taken into account, as differing layout spacing will result in differing fatigue loading for deeply embedded turbines. According to IEC 61400-1 [4], increased loading due to turbine wakes can be represented through the use of effective turbulence intensity, as defined by Frandsen [5]. This parameter characterises the effect of loading of ambient and wake induced turbulence. The Frandsen methodology is one of several methods accepted for certification studies. This methodology is based on the calculation of an effective turbulence intensity that accounts for both wake and non-wake turbulence intensity contributions. For a given wind speed, an effective turbulence intensity is calculated based on the ambient measured turbulence intensity at a representative mast location and the proximity of neighbouring turbines and results in a curve of turbulence intensity against wind speed. One of the main input parameters in this model is the thrust coefficient curve of the specific turbine model under consideration. The thrust curve for the generic turbine model under consideration has been generated by DNV GL. Therefore, the turbulence intensity estimates using the Frandsen methodology in this analysis should be considered indicative only, as they do not represent a specific turbine model in the market at present. However, the indicative results can be used to gauge possible levels of effective turbulence at each of the site locations. The individual effective turbulence values for all turbines at the sites are presented in Appendix G. These tables show any turbines that are predicted to exceed IEC subclass A for wind speeds within the 0.2Vref to 0.4Vref range, and turbines which exceed the profile at lower wind speeds. It is noted that there is a low data coverage of measurements available to define the turbulence intensity profile at high wind speeds, leading to increased uncertainty in these values. The site minimum, maximum and average profiles for the Mpika mast are presented in Figure 7-1 along with the profiles for the turbulence subclasses. Refer to Appendix G for all of the masts. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 27 www.dnvgl.com It is recommended that turbine suppliers be approached at an early stage to gain approval for the proposed layout and to ensure that sufficient warranty provisions are in place to address the predicted effective turbulence at each site. It should also be noted that the Frandsen method is a generic means of estimating design equivalent turbulence intensity, and there is scope for uncertainty in its application to the specific site and turbine type considered in this study. A list of potential sources of uncertainty that should be considered when interpreting the results for load analysis is provided below: • Statistical scatter in the turbulence at any mean wind speed and consequent non-linear impacts on wind turbine loads. • Non-linear behaviour of the turbine, most notably in the control system and the aerodynamics. Explicit time-domain simulations would be required to model these effects. • It should be noted that the predictions of ambient turbulence intensity as input to the representative turbulence calculations rely on the assumption that the standard deviation of wind speed recorded at the mast location remains constant over the site area. Therefore, it is important that the mast is reasonably representative of the turbine locations. Due to this assumption, the predictions do not include any estimation of the effects of the varying ground roughness around the turbines. • The effective turbulence intensity values estimated by the Frandsen method do not account for all the environmental parameters which influence turbine loads. The effect of wind shear, upflow angles and air density should all be included if a more rigorous load analysis is required. This would be achieved through explicit time-domain load simulations of the turbine on the site of interest. • It is noted that DNV GL has assumed a Wöhler coefficient of 10 to be appropriate for this calculation, as it is understood that the turbine blades will likely consist of glass fibre. • The fatigue loading of a wind turbine is, in general, not a simple direct function of turbulence intensity but depends on other sources of loading including, but not limited to, gravity, centrifugal loads and dynamic response. • The specific implementation used for the calculation has a relevant influence on the results. It should be noted that DNV GL considered only generic turbine thrust curves and not a specific turbine curve. Due to these issues the turbulence predictions presented should be reviewed with consideration of the inherent assumptions and large uncertainties. It should be noted that the Frandsen method provides only an estimate of the loading levels to be experienced at the turbine locations. For a detailed study of the fatigue loading at the turbines, explicit time- domain simulations would be required. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 28 www.dnvgl.com Figure 7-1 Predicted profiles of site minimum, maximum and average design equivalent turbulence intensity for the Mpika site using a Generic 4.0 MW wind turbine at a hub height of 130 m Frequency Distribution 0.2 - 0.4 Vref IEC Subclass A IEC Subclass B IEC Subclass C Site Minimum Site Maximum Site Average 45% 14 40% 12 35% 10 Effective Turbulence Intensity Frequency of Occurance [%] 30% 25% 8 20% 6 15% 4 10% 2 5% 0% 0 0 5 10 15 20 25 Wind Speed [m/s] 7.1.2 Uncertainty in turbulence prediction It should be noted that all the predictions of turbulence intensity, ambient and design equivalent, rely on the assumption that the standard deviation of wind speed recorded at the site mast location remains constant over the area of the site with respect to the measured values, is representative of the turbine locations, and does not vary with height. This standard assumption inherently implies that the turbulence predictions do not explicitly account for the effects of the varying ground roughness around the turbines i.e. this is only modelled through the associated variations in mean wind speeds. Therefore, it is important that the mast is reasonably representative of the turbine locations. 7.2 Extreme wind speeds The extreme wind speed at a site is best determined by a Method of Independent Storms (MIS) or Gumbel analysis, using data recorded at the site over a period of at least 7 years. At the sites, approximately one DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 29 www.dnvgl.com year of 10-minute mean wind speed data were available. This period is less than ideal to obtain an accurate prediction. Despite this, estimates using the MIS method are provided below but it should be noted that the estimates are subject to a very high level of uncertainty given the limited on-site measurement period. Furthermore, for indicative purposes the maximum value recorded on site is presented in Section 7.2.2. 7.2.1 Method of Independent Storms (MIS) DNV GL has undertaken a Gumbel analysis, using the Method of Independent Storms (MIS) defined by Cook [6] and further developed by Harris [7][8]. This method has been employed to provide an estimate based on the measured data available at the site masts, as detailed below. It is possible to use the Method of Independent Storms (MIS) to determine a 10-minute mean extreme wind speed for a return period of 50 years from a continuous time series. Guidance within Cook recommends that a data set of at least 7 years’ duration is ideally used for an MIS analysis. As the site dataset used in this analysis is limited to a single year, caution must be exercised in the interpretation of the extreme gust wind speeds determined from this analysis. Using the code and inputs described above, DNV GL has undertaken an MIS analysis as follows. The measured time series at the masts were extrapolated to the proposed hub height of 130 m using time series based shear method, in order to derive a continuous time series at hub height at each mast location. Applying the MIS procedure to these time series, the extreme 10-minute mean wind speed for a return period of 50 years was estimated at the locations of the mast. The predicted 10 minute and 3 second gust extreme wind speeds for each mast are presented in Table 7-1. The 3 second gust wind speeds were predicted by applying appropriate wind speed ratios to the extreme 10- minute wind speeds. The highest extreme 10-minute mean and 3 second gust obtained from the MIS analysis, over a 50-year return period, are predicted to be 25.0 m/s at the Chanka mast and 42.0 m/s at the Petauke mast, respectively. It is however noted that there are no values exceeding the IEC Class III for 10-minute average and 3- second gust extreme wind speed thresholds. Table 7-1 Predicted extreme wind speeds by Method of Independent Storms (MIS) at selected turbine locations Maximum 10-minute mean with a return Maximum 3-sec gust with a return period of Turbine ID period of 50 years at 130 m 50 years at 130 m [m/s] [m/s] Choma 24.0 40.0 Mwinilunga 20.0 37.5 Lusaka 23.5 40.5 Mpika 21.5 31.5 Chanka 25.0 40.0 Petauke 22.0 42.0 Mansa 24.0 36.0 Malawi 21.5 34.5 Class III limit 37.5 52.5 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 30 www.dnvgl.com 7.2.2 Extreme wind speeds recorded at the masts A review of the maximum wind speeds recorded on site was also undertaken. The loggers installed at the masts have been programmed to record 1-second gust values and 10-minute averages. The Wieringa equation has been used to derive a conversion factor to adjust the predicted 1-second gusts measured at the mast location to 3-second gusts. The Wieringa equation is defined as follows: () = 1 + 0.42×× ( ) Where: γt is the gust ratio; I is the turbulence intensity; T is the averaging period in seconds; t is the gust period in seconds. Using the measured period at the masts, the maximum 10-minute mean wind speed and the maximum 3- second gust wind speed are provided in Table 7-2. Table 7-2 Maximum 10-min and 3-sec wind speeds at mast locations Maximum 10-minute mean wind speed at Maximum 3-sec measured at Mast at 80 m Turbine ID Mast at 130 m [m/s] [m/s] Choma 20.5 28.4 Mwinilunga 17.9 27.6 Lusaka 21.2 26.9 Mpika 18.7 25.3 Chanka 19.9 27.7 Petauke 18.6 31.5 Mansa 20.7 23.8 Malawi 19.0 25.2 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 31 www.dnvgl.com 8 OBSERVATIONS AND RECOMMENDATIONS DNV GL makes the following observations and recommendations regarding this analysis: 1. The met masts were sited in their current locations primarily for the purpose of validating the national wind atlas, upon completion of 24-months of data acquisition. Some of the locations may also be suitable for large scale wind development, but not all are ideal for this purpose. As such, DNV GL recommends that stakeholders wishing to develop a wind project in Zambia not restrict their site selection to the eight mast locations, as there is wind energy potential in locations across the country that are not currently well-represented by a met mast. 2. Based on approximately one year of wind data, DNV GL evaluated the representativeness of the on- site data to the long-term wind regime based on DNV GL VMD, the ERA-Interim data set and the MERRA-2 data set. Where applicable, long-term adjustments were applied to the on-site wind data to adjust the data to represent long-term expectations. It is noted that there is a lack of viable ground-station reference data to evaluate the consistency of the reanalysis and virtual datasets considered in this assessment. For this reason, there is increased uncertainty in the long-term wind regime at each site, which has been considered in the uncertainty analysis. 3. DNV GL evaluated the measured wind shear at the masts. DNV GL applied the measured wind shear at each mast to the upper-level wind speeds on a timeseries basis to estimate hub height wind speeds. Thermal heating and cooling at the surface results in relatively high magnitudes of measured wind shear at some of the met masts. There is uncertainty that the wind shear measured at the met masts will remain constant with increasing altitude, and this uncertainty is higher when the estimated wind shear exponents are higher. DNV GL would recommend the use of remote sensing for site prospecting in Zambia, in order to more accurately characterize the vertical wind speed profile. Remote sensing measurements will further the understanding of the vertical wind speed profile and has the potential to drastically reduce the vertical extrapolation uncertainty, especially at sites where the extrapolation distance is large. 4. The table below summarizes the measured mast height wind speeds, long-term mast height wind speeds, and long-term hub height wind speeds at each of the eight met mast locations. Measured mean wind Long-term mean Long-term hub Mast speed at mast height wind speed at mast height mean wind [m/s] height [m/s] speed [m/s] Choma 6.5 6.6 7.4 Mwinilunga 6.0 6.0 7.4 Lusaka 6.2 6.5 7.9 Mpika 6.2 6.3 7.3 Chanka 6.5 6.6 7.4 Petauke 5.7 5.7 6.5 Mansa 5.8 5.9 6.9 Malawi 5.8 5.8 6.9 5. The average horizontal extrapolation distances across the eight sites ranges from 3.6 km at Mpika to 24.1 km at Chanka. It should be noted that WAsP calculations have high uncertainties when calculations: extend over large spatial distances; are initiated from positions with markedly different elevations, wind climates or exposure to those of the proposed turbine locations. The WAsP wind flow model is also not suited to stable atmospheric conditions. For further wind assessments studies DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 32 www.dnvgl.com in Zambia, DNV GL would recommend the use of CFD wind flow modeling to decrease horizontal extrapolation uncertainties. 6. The power curve used in this analysis represents a blended generic turbine model that has been generated by DNV GL. Given the preliminary nature of the generic power curve used in this assessment, DNV GL recommends that potential stakeholders conduct a thorough market review of available technologies when assessing a potential wind farm site in Zambia. 7. There are a number of losses and uncertainties for which DNV GL’s standard assumptions have been made at this stage, or for which an analysis was out of DNV GL’s scope of work. It is recommended that The World Bank considers each of the loss categories carefully when using the results in this report for stakeholder engagement. They may vary materially from standard assumptions and can often be mitigated to some extent, especially in early years of the project, through appropriate contractual provisions. 8. DNV GL notes the following observations and opinions regarding uncertainty. a. Aside from inter-annual variability, the uncertainty in the analysis is driven by spatial extrapolation and the vertical extrapolation from mast height to hub height. b. DNV GL recommends that all proposed turbine locations be within 2 km of a measurement mast that is at least ¾ of the proposed hub height and that wind measurements are conducted to fully represent typical turbine exposures and reasonably characterize the expected range of the wind climate on site. The distance criterion is generally not met and some turbines are located as far as 24 km from the nearest mast. The height criterion has also not been met for a suggested hub height of 130 m. DNV GL recommends that future development in Zambia be conducted in accordance with the guidelines set forth above, so as to minimize the uncertainty in future energy production estimates. c. The wind speed predictions have been based on WAsP modeling, which provides elevated uncertainty in predicting the wind flow variation across the sites over large extrapolation distances or complex terrain. 9. The results of the energy production assessments are provided in the tables below. Site Choma Mwinilunga Lusaka Mpika Probability of exceedance 10-year average [GWh/annum] 50% 303.0 323.3 386.0 320.3 75% 276.2 297.0 353.9 292.1 90% 251.8 272.4 323.3 266.5 95% 236.8 257.0 304.7 250.5 99% 209.2 227.6 268.1 222.6 Site Chanka Petauke Mansa Malawi Probability of exceedance 10-year average [GWh/annum] 50% 345.6 291.5 314.7 303.7 75% 311.2 261.5 286.4 274.2 90% 279.9 233.6 260.6 247.3 95% 260.3 217.2 244.5 230.5 99% 223.3 186.3 214.2 201.7 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 33 www.dnvgl.com 9 CONCLUSION The overall Zambia ESMAP program consists of providing a validated mesoscale wind atlas for Zambia, including associated deliverables and wind energy development training courses. Meteorological data is collected at eight sites over a 2-year period. This 12-month Site Resource Report provides interim wind resource statistics at the eight masts and energy production estimates for preliminary wind farms in the vicinity of the masts. The program’s goal is to provide Zambian policy makers, stakeholders and independent power producers with accurate and valuable knowledge of the national wind resource, including complementary tools, which can be of direct practical use, both for formulating energy policy and implementing wind projects. A key conclusion from this study is that there is now an established network of state-of-the-art wind measurement masts in Zambia that can be used to support stakeholder wind analysis activities and future utility-scale wind development in-country. In the future, this network of masts will also provide the industry with a source of long-term reference station data which could greatly reduce uncertainties for potential developers. The data collected from the eight met masts are considered very good both in terms of data quality and data coverage. The primary goal of the met masts was not to provide potential wind farm locations, but instead to validate a country-wide wind map. However, and as a secondary goal, it is noted that from this analysis, several met mast locations are sited in areas where wind development could be considered viable and potentially bankable with current turbine technology. Further investment by stakeholders in well-organized measurement campaigns and in feasibility analysis that are focused on reducing uncertainties will help support future growth of the Zambian wind market. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 34 www.dnvgl.com 10 REFERENCES [1] IEC 61400-12-1:2005(E), “Wind turbines - Part 12-1: Power performance measurements of electricity producing wind turbines.” [2] Mast Commissioning Reports, 10003564-USSD-R04 to R12, Rev A, March 2017, by DNV GL (one individual report per mast). [3] Candidate Site Identification Report, 702833-USSD-R01-C, 22 December 2014, DNV GL. [4] IEC 61400-1:2005/A1:2010 (E): 61400-1 Ed3 Amendment 1: Wind turbines – Part 1: Design requirements. [5] “Turbulence and turbulence-generated fatigue loading in wind turbine clusters”, S Frandsen, Riso-R- 1188(EN), July 2003. [6] Cook N J, “The Designer’s Guide to Wind Loading of Building Structures”, Butterworths 1985. [7] Harris I, “Gumbel revisited: A new look at extreme value statistics applied to wind speeds”, Journal of Wind Engineering and Industrial Aerodynamics 59, 1996. [8] Harris I, “Improvements to the Method of Independent Storms”, Journal of Wind Engineering and Industrial Aerodynamics 80, 1999. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page 35 www.dnvgl.com APPENDIX A WIND DATA STATISTICS DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page A-1 www.dnvgl.com Choma Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 423 423 204 204 801 801 602 602 423 423 204 204 77 58 [m] Nov-16 6.6 6.6 6.1 6.1 5.5 5.5 4.3 4.4 97 97 97 97 97 97 97 97 97 97 Dec-16 5.3 5.3 4.9 4.9 4.4 4.4 3.4 3.5 100 100 100 100 100 100 100 100 100 100 Jan-17 5.0 5.0 4.6 4.6 4.1 4.2 3.3 3.3 100 100 100 100 100 100 100 100 100 100 Feb-17 5.1 5.1 4.6 4.7 4.1 4.2 3.2 3.2 100 100 100 100 100 100 100 100 100 100 Mar-17 5.6 5.7 5.2 5.3 4.7 4.8 3.7 3.8 100 100 100 100 100 100 100 100 100 100 Apr-17 6.8 6.9 6.3 6.4 5.6 5.7 4.3 4.3 100 100 100 100 100 100 100 100 100 100 May-17 6.5 6.5 6.1 6.2 5.5 5.5 4.0 4.1 100 100 100 100 100 100 100 100 100 100 Jun-17 6.9 6.9 6.4 6.5 5.8 5.8 4.2 4.3 100 100 100 100 100 100 100 100 100 100 Jul-17 6.5 6.5 6.1 6.1 5.5 5.5 4.1 4.2 100 100 100 100 100 100 100 100 100 100 Aug-17 6.6 6.5 6.1 6.1 5.5 5.5 4.2 4.3 90 100 90 100 90 100 100 100 91 91 Sep-17 7.9 7.7 7.3 7.2 6.5 6.4 4.8 4.9 61 100 61 100 61 100 100 100 61 61 Oct-17 7.0 7.0 6.5 6.5 5.8 5.8 4.5 4.5 100 100 100 100 100 100 100 100 100 100 Nov-17 6.0 6.0 5.5 5.5 4.9 5.0 3.8 3.9 100 100 100 100 100 100 100 100 100 100 Dec-17 5.5 5.5 5.1 5.1 4.6 4.6 3.5 3.6 100 100 100 100 100 100 100 100 100 100 Jan-18 5.6 5.6 5.3 5.3 4.8 4.8 3.7 3.7 31 31 31 31 31 31 31 31 31 31 Mwinilunga Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Dec-16 4.1 4.1 3.7 3.8 3.2 3.3 2.4 2.4 92 92 92 92 92 92 92 92 92 92 Jan-17 4.8 4.8 4.3 4.3 3.6 3.7 2.6 2.7 100 100 100 100 100 100 100 100 100 100 Feb-17 4.5 4.6 4.0 4.1 3.4 3.5 2.6 2.6 100 100 100 100 100 100 100 100 100 100 Mar-17 5.0 5.1 4.5 4.5 3.8 3.9 2.7 2.8 100 100 100 100 100 100 100 100 100 100 Apr-17 6.4 6.5 5.7 5.8 4.8 4.9 3.3 3.4 100 100 100 100 100 100 100 100 100 100 May-17 7.3 7.3 6.4 6.5 5.3 5.4 3.4 3.6 100 100 100 100 100 100 100 100 100 100 Jun-17 7.7 7.7 6.7 6.8 5.6 5.6 3.6 3.7 100 100 100 100 100 100 100 100 100 100 Jul-17 7.7 7.8 6.8 6.9 5.6 5.7 3.7 3.8 100 100 100 100 100 100 100 100 100 100 Aug-17 7.5 7.5 6.6 6.7 5.5 5.6 3.7 3.8 100 100 100 100 100 100 100 100 100 100 Sep-17 7.0 7.1 6.3 6.3 5.3 5.3 3.5 3.6 100 100 100 100 100 100 100 100 100 100 Oct-17 5.5 5.5 4.9 5.0 4.2 4.3 3.0 3.1 100 100 100 100 100 100 100 100 100 100 Nov-17 4.9 4.9 4.4 4.4 3.7 3.8 2.7 2.8 100 100 100 100 100 100 100 100 100 100 Dec-17 4.1 4.1 3.7 3.8 3.2 3.2 2.4 2.4 100 100 100 100 100 100 100 100 100 100 Jan-18 4.7 4.7 4.2 4.3 3.6 3.7 2.8 2.9 28 28 28 28 28 28 28 28 28 28 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page A-2 www.dnvgl.com Lusaka Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Nov-16 4.7 4.8 4.3 4.4 3.7 3.8 2.9 2.9 31 31 31 31 31 31 31 31 31 31 Dec-16 4.5 4.6 4.1 4.1 3.5 3.6 2.6 2.6 100 100 100 100 100 100 100 100 100 100 Jan-17 4.4 4.5 4.0 4.0 3.4 3.5 2.5 2.5 100 100 100 100 100 100 100 100 100 100 Feb-17 4.3 4.4 3.9 4.0 3.4 3.4 2.4 2.4 100 100 100 100 100 100 100 100 100 100 Mar-17 5.6 5.7 5.0 5.0 4.2 4.3 3.0 3.0 100 100 100 100 100 100 100 100 100 100 Apr-17 6.8 6.9 6.0 6.0 5.0 5.1 3.5 3.6 100 100 100 100 100 100 100 100 100 100 May-17 6.9 6.9 6.1 6.1 5.0 5.1 3.4 3.5 100 100 100 100 100 100 100 100 100 100 Jun-17 7.6 7.6 6.7 6.7 5.5 5.6 3.6 3.7 100 100 100 100 100 100 100 100 100 100 Jul-17 6.9 6.9 6.2 6.2 5.2 5.2 3.5 3.6 100 100 100 100 100 100 100 100 100 100 Aug-17 7.2 7.2 6.4 6.4 5.4 5.5 3.8 3.8 100 100 100 100 100 100 100 100 100 100 Sep-17 7.9 7.9 7.0 7.0 5.9 5.9 4.1 4.2 100 100 100 100 100 100 100 100 100 100 Oct-17 6.7 6.7 5.9 6.0 5.0 5.1 3.6 3.7 98 98 98 98 98 98 98 98 98 98 Nov-17 5.3 5.3 4.8 4.8 4.1 4.2 3.0 3.0 95 95 95 95 95 95 95 95 95 95 Dec-17 4.7 4.7 4.2 4.3 3.6 3.7 2.6 2.6 100 100 100 100 100 100 100 99 100 100 Jan-18 4.9 4.9 4.4 4.5 3.8 3.9 2.7 2.7 28 28 28 28 28 28 28 28 28 28 Mpika Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Nov-16 5.6 5.6 5.2 5.1 4.6 4.6 3.7 3.6 35 35 35 35 35 35 35 35 35 35 Dec-16 4.3 4.2 4.0 3.9 3.5 3.5 2.8 2.7 100 100 100 100 100 100 100 100 100 100 Jan-17 3.9 3.9 3.7 3.6 3.3 3.2 2.6 2.5 100 100 100 100 100 100 100 100 100 100 Feb-17 4.2 4.1 3.9 3.8 3.5 3.4 2.7 2.6 100 100 100 100 100 100 100 100 100 100 Mar-17 5.5 5.5 5.1 5.0 4.5 4.4 3.6 3.4 100 100 100 100 100 100 100 100 100 100 Apr-17 6.9 6.9 6.5 6.4 5.7 5.6 4.5 4.4 100 100 100 100 100 100 100 100 100 100 May-17 7.0 7.0 6.5 6.5 5.8 5.7 4.5 4.4 100 100 100 100 100 100 100 100 100 100 Jun-17 7.2 7.2 6.7 6.7 5.9 5.9 4.5 4.4 100 100 100 100 100 100 100 100 100 100 Jul-17 7.3 7.3 6.8 6.7 6.0 6.0 4.6 4.4 100 100 100 100 100 100 100 100 100 100 Aug-17 7.5 7.5 7.0 6.9 6.2 6.1 4.7 4.6 100 100 100 100 100 100 100 100 100 100 Sep-17 7.9 7.9 7.3 7.3 6.5 6.5 5.1 5.0 100 100 100 100 100 100 100 100 100 100 Oct-17 6.7 6.7 6.3 6.2 5.6 5.5 4.4 4.3 100 100 100 100 100 100 100 100 100 100 Nov-17 5.4 5.4 5.0 5.0 4.4 4.4 3.5 3.4 100 100 100 100 100 100 100 100 100 100 Dec-17 4.3 4.3 4.1 4.0 3.6 3.6 2.9 2.8 100 100 100 100 100 100 100 100 100 100 Jan-18 5.4 5.4 5.0 4.9 4.4 4.4 3.5 3.4 28 28 28 28 28 28 28 28 28 28 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page A-3 www.dnvgl.com Chanka Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Nov-16 5.9 5.9 5.6 5.5 5.1 5.1 4.4 4.3 25 25 25 25 25 25 25 25 25 25 Dec-16 4.7 4.7 4.4 4.4 4.0 4.0 3.3 3.3 100 100 100 100 100 100 100 100 100 100 Jan-17 4.0 4.0 3.8 3.8 3.5 3.5 2.9 2.9 100 100 100 100 100 100 100 100 100 100 Feb-17 4.3 4.2 4.0 3.9 3.6 3.6 3.0 3.0 100 100 100 100 100 100 100 100 100 100 Mar-17 4.6 4.6 4.3 4.3 3.9 3.9 3.3 3.3 100 100 100 100 100 100 100 100 100 100 Apr-17 7.0 6.9 6.5 6.5 6.0 5.9 5.1 5.0 100 100 100 100 100 100 100 100 100 100 May-17 7.7 7.7 7.2 7.2 6.6 6.6 5.6 5.5 100 100 100 100 100 100 100 100 100 100 Jun-17 7.7 7.7 7.2 7.2 6.6 6.6 5.6 5.6 100 100 100 100 100 100 100 100 100 100 Jul-17 7.6 7.6 7.2 7.1 6.5 6.5 5.6 5.5 100 100 100 100 100 100 100 100 100 100 Aug-17 8.1 8.1 7.7 7.6 7.1 7.1 6.1 6.1 100 100 100 100 100 100 100 100 100 100 Sep-17 8.8 8.8 8.4 8.4 7.7 7.8 6.8 6.7 100 100 100 100 100 100 100 100 100 100 Oct-17 7.4 7.4 7.0 7.0 6.5 6.5 5.7 5.6 100 100 100 100 100 100 100 100 100 100 Nov-17 6.0 5.9 5.7 5.6 5.2 5.2 4.5 4.5 100 100 100 100 100 100 100 100 100 100 Dec-17 4.7 4.7 4.4 4.4 4.0 4.0 3.5 3.4 100 100 100 100 100 100 100 100 100 100 Jan-18 5.0 5.0 4.6 4.6 4.1 4.1 3.5 3.4 31 31 31 31 31 31 31 31 31 31 Petauke Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Dec-16 4.2 4.2 3.9 3.9 3.5 3.5 2.8 2.9 73 73 73 73 73 73 73 73 73 73 Jan-17 4.0 4.0 3.6 3.7 3.2 3.3 2.5 2.6 100 100 100 100 100 100 100 100 100 100 Feb-17 3.8 3.9 3.5 3.6 3.1 3.2 2.5 2.5 100 100 100 100 100 100 100 100 100 100 Mar-17 5.5 5.4 5.0 5.0 4.5 4.5 3.6 3.7 100 100 100 100 100 100 100 100 100 100 Apr-17 5.8 5.8 5.4 5.4 4.8 4.8 3.9 3.9 100 100 100 100 100 100 100 100 100 100 May-17 5.6 5.6 5.1 5.1 4.6 4.6 3.7 3.8 100 100 100 100 100 100 100 100 100 100 Jun-17 6.2 6.2 5.7 5.7 5.1 5.1 4.1 4.2 100 100 100 100 100 100 100 100 100 100 Jul-17 6.4 6.4 5.9 5.9 5.3 5.3 4.3 4.3 100 100 100 100 100 100 100 100 100 100 Aug-17 6.7 6.7 6.2 6.2 5.6 5.5 4.6 4.6 100 100 100 100 100 100 100 100 100 100 Sep-17 7.1 7.1 6.5 6.5 5.8 5.8 4.8 4.8 100 100 100 100 100 100 100 100 100 100 Oct-17 6.8 6.8 6.3 6.3 5.6 5.6 4.6 4.6 100 100 100 100 100 100 100 100 100 100 Nov-17 5.3 5.3 5.0 5.0 4.5 4.5 3.7 3.7 100 100 100 100 100 100 100 100 100 100 Dec-17 4.7 4.7 4.3 4.4 3.9 3.9 3.1 3.2 100 99 100 100 100 100 100 100 100 100 Jan-18 4.9 4.9 4.5 4.6 4.1 4.1 3.3 3.3 28 28 28 28 28 28 28 28 28 28 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page A-4 www.dnvgl.com Mansa Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Nov-16 4.7 4.6 4.3 4.2 3.8 3.7 3.1 3.0 15 15 15 15 15 15 15 15 15 15 Dec-16 4.1 4.0 3.7 3.6 3.3 3.2 2.7 2.6 100 100 100 100 100 100 100 100 100 100 Jan-17 4.1 4.0 3.7 3.7 3.3 3.2 2.7 2.6 100 100 100 100 100 100 99 100 100 100 Feb-17 4.2 4.1 3.8 3.8 3.4 3.3 2.7 2.6 100 100 100 100 100 100 100 100 100 100 Mar-17 4.9 4.9 4.5 4.4 3.9 3.9 3.1 3.0 100 100 100 100 100 100 100 100 100 100 Apr-17 6.5 6.5 6.0 5.9 5.2 5.1 4.1 3.9 100 100 100 100 100 100 100 100 100 100 May-17 7.0 7.0 6.4 6.3 5.5 5.4 4.2 4.0 100 100 100 100 100 100 100 100 100 100 Jun-17 7.0 7.0 6.3 6.3 5.4 5.3 4.1 3.9 100 100 100 100 100 100 100 100 100 100 Jul-17 7.1 7.1 6.4 6.4 5.6 5.5 4.2 4.1 100 100 100 100 100 100 100 100 100 100 Aug-17 7.1 7.1 6.4 6.3 5.6 5.5 4.3 4.1 100 100 100 100 100 100 100 100 100 100 Sep-17 7.2 7.3 6.6 6.5 5.8 5.7 4.6 4.4 100 100 100 100 100 100 100 100 100 100 Oct-17 5.6 5.6 5.2 5.1 4.6 4.5 3.6 3.5 100 100 100 100 100 100 100 100 100 100 Nov-17 4.8 4.8 4.4 4.3 3.9 3.8 3.1 3.0 100 100 100 100 100 100 100 100 100 100 Dec-17 3.9 3.9 3.6 3.6 3.2 3.2 2.6 2.5 100 100 100 100 100 100 97 100 100 100 Jan-18 4.8 4.8 4.4 4.3 3.8 3.8 3.1 3.0 31 31 31 31 31 31 31 31 31 31 Malawi Monthly Statistics and Data Coverage Month Mean wind speed [m/s] Wind speed data coverage [%] Wind direction data coverage [%] Height 801 801 602 602 413 413 204 204 801 801 602 602 423 423 204 204 77 58 [m] Dec-16 5.2 5.2 4.8 4.7 4.2 4.1 3.3 3.3 34 34 34 34 34 34 34 34 34 34 Jan-17 4.0 3.9 3.6 3.5 3.2 3.1 2.6 2.5 100 100 100 100 100 100 100 100 100 100 Feb-17 3.8 3.8 3.5 3.4 3.0 3.0 2.5 2.4 100 100 100 100 100 100 100 100 100 100 Mar-17 4.8 4.8 4.4 4.3 3.9 3.8 3.2 3.1 100 100 100 100 100 100 100 100 100 100 Apr-17 5.8 5.8 5.2 5.2 4.6 4.5 3.6 3.6 100 100 100 100 100 100 100 100 100 100 May-17 6.1 6.1 5.5 5.4 4.7 4.6 3.7 3.6 100 100 100 100 100 100 100 100 100 100 Jun-17 6.2 6.2 5.6 5.5 4.7 4.7 3.7 3.6 100 100 100 100 100 100 100 100 100 100 Jul-17 6.2 6.2 5.7 5.6 4.8 4.8 3.7 3.6 100 100 100 100 100 100 100 100 100 100 Aug-17 6.9 6.9 6.2 6.1 5.3 5.3 4.2 4.1 100 100 100 100 100 100 100 100 100 100 Sep-17 7.4 7.4 6.7 6.7 5.7 5.7 4.6 4.5 100 100 100 100 100 100 100 100 100 100 Oct-17 7.3 7.4 6.6 6.6 5.8 5.8 4.7 4.7 100 100 100 100 100 100 100 100 100 100 Nov-17 5.7 5.7 5.2 5.2 4.6 4.6 3.9 3.8 100 100 100 100 100 100 100 100 100 100 Dec-17 4.5 4.5 4.1 4.0 3.6 3.6 3.0 2.9 100 100 100 100 100 100 100 100 100 100 Jan-18 4.9 4.8 4.5 4.4 4.0 3.9 3.3 3.2 31 31 31 31 31 31 31 31 31 31 DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page A-5 www.dnvgl.com APPENDIX B REFERENCE STATIONS CONSIDERED DNV GL Virtual Met Data (VMD) The DNV GL Virtual Met Data (VMD) is developed from a mesoscale-model-based downscaling system that provides high-resolution long-term reference time series data for any location in the world. DNV GL VMD is primarily based on the Weather Research and Forecasting (WRF) Model, a mesoscale model developed and maintained by a consortium of more than 150 international agencies, laboratories, and universities. VMD is driven by a number of new high-resolution inputs, such as MERRA, global 25 km resolution 3-hourly and daily analyses of soil temperature and moisture, sea surface temperature, sea ice, and snow depth. A sophisticated land surface model predicts surface fluxes of heat and moisture to the atmosphere, reflected shortwave radiation, and longwave radiation emitted to the atmosphere. Data is typically produced as a virtual hourly time series on a 2 km horizontal resolution grid, centred on the subject wind farm site at the location of a met-mast on the site. ERA-Interim Reanalysis data DNV GL has considered ERA-Interim data as part of this analysis. The ECMWF Interim Reanalysis (ERA- Interim) is a global atmospheric reanalysis product of the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim dataset uses weather measurements from a number of sources as inputs to a numerical atmospheric model in order to produce a description of the state of the atmosphere, including wind speed. The analysis is performed at a spatial resolution of 0.75° longitude by 0.75° latitude with a 6 hourly temporal resolution. DNV GL has some concerns over the long-term consistency of reanalysis data, and hence in order to mitigate against potential inclusion of inconsistent data in the long- term analysis, DNV GL has considered the same long-term reference period for the ERA-Interim dataset as for the MERRA datasets, i.e. from January 2002 to the present. DNV GL procured 6-hourly time series of two-dimensional diagnostic data, at a surface height of 10 m for the nearest grid points near the project site. MERRA-2 Reanalysis data The Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) data set has been produced by the National Aeronautics and Space Administration (NASA) by assimilating satellite observations with conventional land-based meteorology measurement sources using the Goddard Earth Observing System Data Assimilation System Version 5.12.4 (GEOS-5.12.4) atmospheric data assimilation system. The analysis is performed at a spatial resolution of 0.625° longitude by 0.5° latitude. MERRA-2 replaces the MERRA dataset previously produced by NASA. DNV GL typically procures hourly time series of two-dimensional diagnostic data, at a surface height of 50 m for suitable grid cells near the project site. DNV GL has some concerns over the long-term consistency of reanalysis data and has conducted investigations into the consistency of the MERRA-2 dataset close to the site. On the basis of these investigations the long-term reference period considered for the MERRA-2 dataset is from January 2002 to the present. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page B-1 www.dnvgl.com APPENDIX C WIND FARM SITE INFORMATION AND LAYOUTS DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-1 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-2 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-3 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-4 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-5 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-6 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-7 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-8 www.dnvgl.com DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page C-9 www.dnvgl.com APPENDIX D TURBINE LAYOUT RESULTS Choma turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting1 Northing1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Cho_01 130 483,294 8,134,287 1,348 7.4 12.4 96.8 Cho_02 130 483,290 8,134,764 1,346 7.4 12.7 99.2 Cho_03 130 482,472 8,135,199 1,350 7.4 12.2 95.3 Cho_04 130 481,847 8,135,635 1,355 7.4 12.2 94.4 Cho_05 130 481,410 8,136,148 1,360 7.4 12.3 95.7 Cho_06 130 481,135 8,136,669 1,365 7.5 12.4 95.4 Cho_07 130 481,308 8,137,210 1,365 7.4 12.4 96.4 Cho_08 130 481,416 8,137,738 1,371 7.4 12.8 98.9 Cho_09 130 479,109 8,134,131 1,365 7.4 11.9 94.3 Cho_10 130 479,246 8,134,643 1,370 7.4 12.1 93.4 Cho_11 130 479,352 8,135,139 1,367 7.4 11.8 92.1 Cho_12 130 479,473 8,135,627 1,365 7.4 11.5 91.1 Cho_13 130 479,669 8,136,142 1,363 7.4 11.8 92.8 Cho_14 130 480,310 8,138,661 1,385 7.4 11.8 92.6 Cho_15 130 480,609 8,139,176 1,390 7.4 12.2 96.0 Cho_16 130 480,435 8,139,721 1,389 7.4 12.1 95.9 Cho_17 130 481,878 8,139,687 1,388 7.4 12.4 96.6 Cho_18 130 482,029 8,140,198 1,382 7.3 12.5 99.7 Cho_19 130 474,906 8,137,142 1,368 7.4 11.8 93.2 Cho_20 130 475,548 8,137,568 1,374 7.4 11.9 92.7 Cho_21 130 475,951 8,138,040 1,370 7.4 11.6 92.2 Cho_22 130 476,508 8,138,500 1,368 7.3 11.8 93.5 Cho_23 130 477,371 8,139,308 1,377 7.4 12.3 95.4 Cho_24 130 477,008 8,139,886 1,370 7.4 12.0 94.1 Cho_25 130 476,939 8,140,408 1,365 7.4 12.2 96.6 Average 1,369 7.4 12.1 95.0 Total 303.0 a. Coordinate system is UTM Zone 35, datum WGS84. b. Wind speed at the location of the turbine, not including wake effects. c. Individual turbine output figures include all wind farm losses. d. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-1 www.dnvgl.com Mwinilunga turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Mwi_01 130 282,492 8,692,683 1,520 7.5 12.8 94.6 Mwi_02 130 282,892 8,693,051 1,525 7.7 12.9 93.0 Mwi_03 130 282,556 8,692,155 1,525 7.7 13.0 93.8 Mwi_04 130 282,652 8,691,610 1,526 7.6 13.0 94.6 Mwi_05 130 282,748 8,691,040 1,525 7.6 13.0 95.1 Mwi_06 130 282,897 8,690,458 1,524 7.5 12.7 95.4 Mwi_07 130 284,023 8,693,483 1,530 7.5 12.9 96.0 Mwi_08 130 284,298 8,693,918 1,535 7.5 13.1 98.1 Mwi_09 130 284,738 8,691,525 1,523 7.5 13.2 97.5 Mwi_10 130 285,014 8,691,921 1,530 7.5 13.1 97.4 Mwi_11 130 285,350 8,692,305 1,530 7.5 13.1 98.4 Mwi_12 130 279,793 8,692,256 1,515 7.5 12.8 95.6 Mwi_13 130 280,113 8,692,640 1,515 7.5 12.6 94.5 Mwi_14 130 280,470 8,693,003 1,512 7.5 12.8 94.6 Mwi_15 130 283,052 8,689,877 1,525 7.4 12.9 97.4 Mwi_16 130 281,511 8,694,070 1,526 7.5 12.6 94.0 Mwi_17 130 281,737 8,694,566 1,530 7.4 12.6 95.2 Mwi_18 130 275,536 8,693,525 1,545 7.5 13.0 97.7 Mwi_19 130 275,968 8,693,854 1,545 7.5 13.1 97.1 Mwi_20 130 276,360 8,694,230 1,545 7.6 13.3 97.0 Mwi_21 130 276,680 8,694,670 1,545 7.6 13.3 96.9 Mwi_22 130 276,960 8,695,078 1,545 7.5 12.9 96.5 Mwi_23 130 277,176 8,695,574 1,534 7.5 12.8 96.3 Mwi_24 130 283,635 8,693,124 1,528 7.6 12.9 94.8 Mwi_25 130 277,360 8,696,070 1,533 7.5 13.0 97.2 Average 1,529 7.5 12.9 95.9 Total 323.3 e. Coordinate system is UTM Zone 35, datum WGS84. f. Wind speed at the location of the turbine, not including wake effects. g. Individual turbine output figures include all wind farm losses. h. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-2 www.dnvgl.com Lusaka turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Lus_01 130 611,766 8,363,817 1,183 8.0 15.1 98.9 Lus_02 130 611,782 8,364,359 1,180 8.1 15.2 98.7 Lus_03 130 611,796 8,364,904 1,180 8.1 15.5 99.0 Lus_04 130 612,055 8,365,719 1,180 8.2 15.5 98.7 Lus_05 130 612,154 8,366,186 1,180 8.1 15.4 98.8 Lus_06 130 612,189 8,366,888 1,179 8.1 15.4 98.7 Lus_07 130 612,019 8,367,551 1,177 8.1 15.4 98.6 Lus_08 130 612,293 8,368,131 1,177 8.2 15.4 98.2 Lus_09 130 612,252 8,368,612 1,176 8.2 15.5 98.2 Lus_10 130 611,840 8,369,047 1,174 8.2 15.2 96.7 Lus_11 130 611,895 8,369,562 1,173 8.2 15.4 98.2 Lus_12 130 611,909 8,370,082 1,170 8.2 15.5 98.6 Lus_13 130 611,187 8,370,572 1,164 8.2 15.1 96.4 Lus_14 130 611,574 8,371,105 1,165 8.2 15.5 98.5 Lus_15 130 611,590 8,371,630 1,165 8.2 15.4 98.4 Lus_16 130 611,858 8,372,123 1,165 8.2 15.5 98.4 Lus_17 130 611,351 8,372,678 1,162 8.2 15.5 97.8 Lus_18 130 611,599 8,373,159 1,163 8.2 15.5 98.9 Lus_19 130 611,855 8,374,183 1,163 8.2 15.5 98.8 Lus_20 130 611,933 8,374,672 1,162 8.2 15.5 98.6 Lus_21 130 612,121 8,375,140 1,163 8.2 15.6 99.0 Lus_22 130 612,004 8,376,287 1,161 8.2 15.5 98.6 Lus_23 130 611,802 8,376,825 1,160 8.2 15.6 98.5 Lus_24 130 611,822 8,377,341 1,160 8.2 15.6 98.6 Lus_25 130 611,763 8,377,887 1,157 8.2 15.6 99.3 Average 1,169 8.2 15.4 98.4 Total 386.0 i. Coordinate system is UTM Zone 35, datum WGS84. j. Wind speed at the location of the turbine, not including wake effects. k. Individual turbine output figures include all wind farm losses. l. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-3 www.dnvgl.com Mpika turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Mpi_01 130 318,920 8,708,915 1,414 7.2 12.7 98.9 Mpi_02 130 318,825 8,709,528 1,415 7.3 13.1 98.0 Mpi_03 130 318,758 8,710,141 1,415 7.3 13.1 98.2 Mpi_04 130 318,691 8,710,687 1,415 7.4 13.2 98.0 Mpi_05 130 318,623 8,711,319 1,415 7.3 13.1 98.3 Mpi_06 130 318,652 8,711,913 1,415 7.3 13.0 98.7 Mpi_07 130 318,693 8,712,552 1,415 7.3 12.9 98.6 Mpi_08 130 318,714 8,713,112 1,415 7.2 12.8 98.6 Mpi_09 130 318,865 8,713,587 1,411 7.3 13.0 98.8 Mpi_10 130 319,102 8,714,104 1,409 7.3 13.2 98.7 Mpi_11 130 319,253 8,714,729 1,410 7.4 13.3 98.7 Mpi_12 130 319,706 8,715,073 1,410 7.3 13.1 98.5 Mpi_13 130 319,943 8,715,526 1,410 7.3 12.9 97.9 Mpi_14 130 320,697 8,715,741 1,405 7.3 12.9 98.6 Mpi_15 130 321,042 8,716,151 1,402 7.2 12.8 98.7 Mpi_16 130 321,322 8,716,690 1,400 7.4 13.3 98.8 Mpi_17 130 321,710 8,717,056 1,399 7.4 13.5 98.8 Mpi_18 130 321,990 8,717,508 1,397 7.3 13.2 98.9 Mpi_19 130 322,378 8,717,939 1,395 7.3 13.0 99.2 Mpi_20 130 318,046 8,717,034 1,398 7.2 11.8 92.4 Mpi_21 130 318,391 8,717,444 1,401 7.2 12.1 93.3 Mpi_22 130 318,714 8,717,875 1,399 7.2 12.0 93.3 Mpi_23 130 319,059 8,718,284 1,395 7.2 12.2 93.5 Mpi_24 130 319,382 8,718,650 1,389 7.2 12.1 93.7 Mpi_25 130 319,706 8,719,038 1,383 7.2 12.0 94.1 Average 1,405 7.3 12.8 97.3 Total 320.3 m. Coordinate system is UTM Zone 36, datum WGS84. n. Wind speed at the location of the turbine, not including wake effects. o. Individual turbine output figures include all wind farm losses. p. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-4 www.dnvgl.com Chanka turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Cha_01 130 472,264 8,923,114 1,320 7.4 13.5 99.0 Cha_02 130 472,132 8,922,609 1,320 7.4 13.6 98.2 Cha_03 130 472,349 8,922,165 1,320 7.4 13.5 97.6 Cha_04 130 472,605 8,921,703 1,318 7.4 13.6 98.6 Cha_05 130 472,427 8,921,205 1,324 7.4 13.6 98.4 Cha_06 130 472,493 8,920,699 1,327 7.5 13.9 98.6 Cha_07 130 472,214 8,920,211 1,326 7.5 14.0 98.2 Cha_08 130 472,408 8,919,699 1,332 7.5 13.9 98.1 Cha_09 130 472,393 8,919,253 1,332 7.5 13.9 97.5 Cha_10 130 472,422 8,918,790 1,327 7.5 13.8 97.0 Cha_11 130 474,056 8,917,915 1,332 7.6 14.0 98.4 Cha_12 130 474,166 8,917,485 1,330 7.6 14.0 98.2 Cha_13 130 474,207 8,917,058 1,327 7.6 14.0 98.1 Cha_14 130 474,302 8,916,626 1,322 7.5 14.0 98.5 Cha_15 130 474,286 8,916,069 1,313 7.5 13.9 98.6 Cha_16 130 474,290 8,915,638 1,312 7.5 14.0 98.5 Cha_17 130 474,293 8,915,204 1,315 7.5 14.0 98.5 Cha_18 130 474,592 8,914,296 1,311 7.4 13.7 99.0 Cha_19 130 474,375 8,913,861 1,310 7.4 13.8 98.8 Cha_20 130 474,166 8,913,424 1,312 7.5 13.8 98.7 Cha_21 130 474,007 8,912,771 1,315 7.5 14.0 98.6 Cha_22 130 474,530 8,912,025 1,302 7.5 14.1 98.8 Cha_23 130 472,928 8,911,715 1,316 7.5 13.6 96.1 Cha_24 130 472,955 8,911,272 1,288 7.5 14.0 98.4 Cha_25 130 472,955 8,910,818 1,273 7.4 13.6 98.8 Average 1,317 7.5 13.8 98.3 Total 345.6 q. Coordinate system is UTM Zone 36, datum WGS84. r. Wind speed at the location of the turbine, not including wake effects. s. Individual turbine output figures include all wind farm losses. t. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-5 www.dnvgl.com Petauke turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Pet_01 130 302,892 8,418,177 982 6.9 12.1 99.5 Pet_02 130 303,159 8,418,963 993 6.9 11.8 98.1 Pet_03 130 302,547 8,419,330 1,005 6.9 11.4 93.5 Pet_04 130 304,823 8,420,025 1,040 7.3 13.3 99.4 Pet_05 130 305,117 8,420,656 1,059 7.5 13.9 99.1 Pet_06 130 303,859 8,421,473 1,025 6.8 11.1 96.1 Pet_07 130 303,726 8,422,801 1,025 6.8 11.0 93.9 Pet_08 130 302,873 8,422,997 1,030 6.8 10.9 94.0 Pet_09 130 306,342 8,422,491 995 6.9 12.1 99.7 Pet_10 130 305,068 8,423,340 1,035 7.0 11.9 96.9 Pet_11 130 305,438 8,423,700 1,041 7.0 11.7 94.7 Pet_12 130 305,863 8,424,016 1,065 7.3 13.1 96.9 Pet_13 130 304,872 8,424,751 1,067 7.0 11.3 90.7 Pet_14 130 305,264 8,425,012 1,070 7.1 11.7 91.4 Pet_15 130 302,522 8,425,170 1,057 6.9 11.4 94.0 Pet_16 130 302,931 8,425,431 1,060 6.9 11.4 93.9 Pet_17 130 303,568 8,425,660 1,063 6.8 11.0 93.2 Pet_18 130 304,590 8,426,250 1,052 6.8 10.9 92.8 Pet_19 130 303,813 8,427,130 1,090 7.2 11.7 90.5 Pet_20 130 304,156 8,427,440 1,050 6.9 11.1 92.9 Pet_21 130 304,499 8,427,726 1,045 6.8 11.1 94.7 Pet_22 130 304,793 8,428,102 1,048 6.8 11.1 95.2 Pet_23 130 305,103 8,428,510 1,044 6.8 11.0 95.8 Pet_24 130 305,438 8,428,935 1,057 6.8 11.3 96.2 Pet_25 130 306,067 8,428,882 1,080 7.0 12.1 98.3 Average 1,043 7.0 11.7 95.2 Total 291.5 u. Coordinate system is UTM Zone 36, datum WGS84. v. Wind speed at the location of the turbine, not including wake effects. w. Individual turbine output figures include all wind farm losses. x. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-6 www.dnvgl.com Mansa turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Man_01 130 708,393 8,796,244 1,374 7.3 12.7 97.7 Man_02 130 708,740 8,796,547 1,385 7.4 12.9 97.5 Man_03 130 709,041 8,796,870 1,381 7.4 12.8 98.0 Man_04 130 708,499 8,798,153 1,380 7.3 12.5 97.4 Man_05 130 708,731 8,798,527 1,386 7.3 12.7 97.8 Man_06 130 708,967 8,798,908 1,390 7.3 12.8 98.0 Man_07 130 709,206 8,799,290 1,390 7.3 12.7 98.0 Man_08 130 709,423 8,799,668 1,390 7.3 12.7 98.0 Man_09 130 709,688 8,800,021 1,389 7.4 13.0 98.0 Man_10 130 710,026 8,800,360 1,375 7.5 13.1 98.1 Man_11 130 710,329 8,800,711 1,360 7.4 12.9 98.1 Man_12 130 710,583 8,801,086 1,350 7.3 12.6 98.2 Man_13 130 710,812 8,801,485 1,335 7.2 12.4 98.1 Man_14 130 711,063 8,801,848 1,327 7.2 12.2 98.0 Man_15 130 711,377 8,802,184 1,316 7.1 12.2 98.5 Man_16 130 713,233 8,803,811 1,305 7.2 12.4 98.5 Man_17 130 713,432 8,804,196 1,300 7.2 12.4 98.0 Man_18 130 713,630 8,804,589 1,304 7.2 12.6 98.5 Man_19 130 714,359 8,805,195 1,303 7.2 12.4 98.2 Man_20 130 714,718 8,805,486 1,320 7.3 12.7 97.9 Man_21 130 715,040 8,805,804 1,320 7.3 12.6 97.9 Man_22 130 715,320 8,806,159 1,310 7.1 12.3 98.7 Man_23 130 707,288 8,795,300 1,343 7.1 12.2 98.5 Man_24 130 707,643 8,795,651 1,351 7.2 12.3 97.9 Man_25 130 708,036 8,795,954 1,361 7.3 12.6 97.8 Average 1,350 7.3 12.6 98.0 Total 314.7 y. Coordinate system is UTM Zone 35, datum WGS84. z. Wind speed at the location of the turbine, not including wake effects. aa. Individual turbine output figures include all wind farm losses. bb. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-7 www.dnvgl.com Malawi turbine layout with predicted wind speed and energy production Long-term wind speed Energy Turbine Hub height Easting 1 Northing 1 Elevation Wake Loss4 at hub output3 height2 [GWh/ann [m] [m] [m] [m/s] [%] um] Mal_01 130 488,449 8,547,193 1,075 7.1 12.3 99.0 Mal_02 130 488,391 8,547,880 1,074 7.1 12.2 97.3 Mal_03 130 488,251 8,548,555 1,068 7.2 12.3 95.5 Mal_04 130 488,047 8,549,442 1,065 7.1 11.9 95.4 Mal_05 130 488,469 8,550,030 1,060 7.1 11.9 94.2 Mal_06 130 488,880 8,550,401 1,054 7.1 11.9 95.4 Mal_07 130 489,195 8,550,805 1,050 7.1 12.1 96.0 Mal_08 130 489,316 8,551,257 1,050 7.1 12.2 96.2 Mal_09 130 490,547 8,548,361 1,054 7.0 12.3 99.5 Mal_10 130 490,853 8,548,851 1,055 7.1 12.4 99.5 Mal_11 130 490,898 8,549,364 1,051 7.1 12.4 99.1 Mal_12 130 490,936 8,549,874 1,046 7.1 12.4 99.3 Mal_13 130 490,983 8,552,399 1,060 7.2 12.7 99.6 Mal_14 130 491,019 8,552,895 1,054 7.1 12.5 99.1 Mal_15 130 491,019 8,553,379 1,045 7.1 12.3 99.0 Mal_16 130 490,466 8,554,199 1,039 7.0 11.7 94.8 Mal_17 130 491,821 8,555,470 1,057 7.1 12.3 98.5 Mal_18 130 492,106 8,556,024 1,055 7.2 12.3 96.5 Mal_19 130 492,106 8,556,479 1,061 7.0 11.5 93.9 Mal_20 130 492,060 8,556,939 1,065 7.0 11.5 93.8 Mal_21 130 493,713 8,556,152 1,070 7.1 12.3 99.2 Mal_22 130 493,949 8,556,582 1,070 7.0 11.9 96.6 Mal_23 130 494,403 8,556,924 1,075 7.0 12.2 99.7 Mal_24 130 494,269 8,557,743 1,080 7.0 12.2 98.9 Mal_25 130 494,127 8,558,335 1,078 7.0 11.9 97.3 Average 1,060 7.1 12.1 97.3 Total 303.7 cc. Coordinate system is UTM Zone 36, datum WGS84. dd. Wind speed at the location of the turbine, not including wake effects. ee. Individual turbine output figures include all wind farm losses. ff. Individual turbine wake loss including all wake effects. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page D-8 www.dnvgl.com APPENDIX E MONTHLY AND DIURNAL PRODUCTION PROFILES Choma monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.25 0.21 0.28 0.47 0.47 0.54 0.40 0.40 0.63 0.53 0.45 0.31 0100 0.25 0.21 0.31 0.46 0.45 0.54 0.38 0.42 0.64 0.59 0.48 0.35 0200 0.26 0.22 0.29 0.51 0.45 0.51 0.38 0.44 0.70 0.61 0.45 0.34 0300 0.27 0.21 0.30 0.52 0.49 0.49 0.43 0.48 0.71 0.67 0.47 0.36 0400 0.26 0.22 0.32 0.53 0.50 0.46 0.50 0.52 0.70 0.66 0.50 0.36 0500 0.26 0.23 0.35 0.54 0.52 0.51 0.52 0.53 0.72 0.67 0.49 0.35 0600 0.25 0.24 0.34 0.58 0.57 0.54 0.58 0.59 0.76 0.71 0.45 0.29 0700 0.23 0.18 0.30 0.49 0.54 0.53 0.57 0.61 0.61 0.57 0.40 0.22 0800 0.22 0.18 0.33 0.43 0.37 0.35 0.39 0.44 0.46 0.51 0.41 0.22 0900 0.25 0.20 0.35 0.42 0.36 0.37 0.34 0.37 0.45 0.50 0.36 0.21 1000 0.24 0.18 0.33 0.35 0.30 0.40 0.34 0.32 0.43 0.44 0.27 0.19 1100 0.22 0.14 0.29 0.26 0.23 0.33 0.31 0.26 0.38 0.34 0.20 0.20 1200 0.19 0.12 0.23 0.21 0.18 0.28 0.26 0.22 0.34 0.27 0.18 0.18 1300 0.17 0.13 0.21 0.17 0.15 0.24 0.22 0.18 0.31 0.20 0.18 0.16 1400 0.18 0.12 0.18 0.17 0.14 0.23 0.21 0.16 0.33 0.18 0.21 0.15 1500 0.19 0.10 0.19 0.20 0.17 0.23 0.22 0.16 0.33 0.18 0.22 0.16 1600 0.15 0.10 0.20 0.23 0.19 0.26 0.24 0.18 0.41 0.17 0.23 0.17 1700 0.10 0.10 0.22 0.25 0.27 0.29 0.28 0.24 0.47 0.25 0.22 0.14 1800 0.10 0.10 0.22 0.35 0.51 0.46 0.49 0.35 0.46 0.30 0.24 0.14 1900 0.13 0.13 0.29 0.48 0.58 0.52 0.55 0.49 0.56 0.43 0.28 0.19 2000 0.14 0.17 0.27 0.46 0.53 0.46 0.43 0.45 0.52 0.47 0.30 0.26 2100 0.20 0.20 0.24 0.52 0.51 0.47 0.39 0.39 0.49 0.44 0.33 0.26 2200 0.24 0.19 0.24 0.50 0.50 0.51 0.42 0.35 0.56 0.45 0.39 0.26 2300 0.26 0.19 0.27 0.51 0.50 0.52 0.43 0.31 0.61 0.48 0.42 0.28 All 4.96 4.08 6.57 9.62 9.48 10.03 9.29 8.86 12.59 10.64 8.11 5.76 a. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-1 www.dnvgl.com Mwinilunga monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.22 0.14 0.29 0.44 0.68 0.72 0.76 0.69 0.61 0.36 0.24 0.16 0100 0.22 0.15 0.29 0.44 0.69 0.72 0.78 0.71 0.64 0.39 0.26 0.17 0200 0.25 0.17 0.28 0.48 0.71 0.74 0.78 0.74 0.63 0.40 0.28 0.16 0300 0.24 0.20 0.30 0.50 0.69 0.75 0.79 0.74 0.63 0.42 0.30 0.14 0400 0.24 0.21 0.28 0.51 0.69 0.76 0.80 0.75 0.61 0.39 0.30 0.14 0500 0.26 0.23 0.31 0.52 0.70 0.78 0.79 0.74 0.64 0.43 0.30 0.15 0600 0.24 0.19 0.29 0.50 0.68 0.79 0.80 0.74 0.67 0.40 0.31 0.17 0700 0.23 0.19 0.27 0.45 0.66 0.76 0.80 0.72 0.64 0.35 0.25 0.14 0800 0.17 0.15 0.24 0.44 0.49 0.52 0.63 0.61 0.49 0.27 0.19 0.08 0900 0.17 0.16 0.24 0.47 0.50 0.49 0.59 0.58 0.50 0.27 0.19 0.08 1000 0.17 0.17 0.22 0.40 0.43 0.46 0.51 0.47 0.41 0.25 0.16 0.09 1100 0.17 0.17 0.20 0.30 0.33 0.31 0.33 0.33 0.27 0.21 0.18 0.10 1200 0.19 0.18 0.15 0.20 0.26 0.22 0.19 0.23 0.17 0.19 0.17 0.12 1300 0.22 0.16 0.12 0.17 0.21 0.17 0.13 0.17 0.13 0.16 0.13 0.13 1400 0.24 0.20 0.14 0.15 0.19 0.14 0.11 0.15 0.15 0.13 0.11 0.16 1500 0.22 0.16 0.17 0.16 0.19 0.13 0.11 0.15 0.15 0.13 0.14 0.16 1600 0.19 0.12 0.16 0.20 0.21 0.16 0.16 0.19 0.17 0.13 0.11 0.11 1700 0.13 0.12 0.19 0.20 0.23 0.22 0.22 0.25 0.20 0.16 0.12 0.14 1800 0.14 0.11 0.19 0.24 0.36 0.46 0.46 0.41 0.31 0.22 0.11 0.10 1900 0.15 0.09 0.25 0.34 0.53 0.64 0.65 0.63 0.50 0.26 0.17 0.13 2000 0.16 0.13 0.28 0.43 0.64 0.71 0.74 0.66 0.58 0.29 0.18 0.12 2100 0.21 0.12 0.29 0.43 0.68 0.73 0.74 0.68 0.58 0.34 0.20 0.11 2200 0.22 0.15 0.30 0.46 0.64 0.73 0.75 0.68 0.58 0.33 0.25 0.13 2300 0.23 0.14 0.30 0.44 0.65 0.71 0.76 0.68 0.59 0.38 0.21 0.13 All 4.90 3.84 5.74 8.89 12.04 12.80 13.37 12.71 10.87 6.87 4.87 3.12 b. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-2 www.dnvgl.com Lusaka monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.19 0.15 0.30 0.44 0.58 0.60 0.50 0.56 0.62 0.49 0.25 0.24 0100 0.19 0.17 0.29 0.46 0.57 0.59 0.50 0.54 0.62 0.52 0.27 0.22 0200 0.18 0.17 0.29 0.47 0.54 0.59 0.51 0.56 0.63 0.54 0.26 0.23 0300 0.17 0.14 0.29 0.48 0.53 0.59 0.50 0.57 0.63 0.54 0.28 0.22 0400 0.19 0.12 0.30 0.51 0.56 0.59 0.51 0.56 0.63 0.55 0.27 0.22 0500 0.21 0.18 0.30 0.52 0.55 0.59 0.52 0.57 0.64 0.55 0.26 0.22 0600 0.22 0.16 0.31 0.48 0.56 0.59 0.54 0.58 0.63 0.54 0.27 0.19 0700 0.20 0.13 0.27 0.42 0.51 0.60 0.54 0.56 0.59 0.46 0.25 0.14 0800 0.19 0.12 0.33 0.45 0.42 0.41 0.39 0.44 0.53 0.48 0.29 0.15 0900 0.20 0.14 0.39 0.55 0.48 0.51 0.47 0.52 0.58 0.48 0.29 0.16 1000 0.18 0.14 0.37 0.53 0.43 0.51 0.48 0.48 0.54 0.43 0.25 0.13 1100 0.17 0.12 0.34 0.45 0.35 0.43 0.39 0.42 0.47 0.33 0.19 0.11 1200 0.16 0.10 0.30 0.36 0.30 0.35 0.31 0.37 0.40 0.24 0.16 0.12 1300 0.12 0.10 0.25 0.27 0.25 0.29 0.25 0.30 0.36 0.22 0.13 0.12 1400 0.12 0.09 0.22 0.25 0.22 0.23 0.21 0.28 0.33 0.20 0.14 0.12 1500 0.13 0.08 0.20 0.20 0.20 0.21 0.20 0.25 0.31 0.21 0.14 0.10 1600 0.13 0.07 0.17 0.20 0.21 0.20 0.22 0.26 0.32 0.19 0.14 0.12 1700 0.08 0.07 0.19 0.22 0.23 0.25 0.26 0.28 0.34 0.21 0.18 0.12 1800 0.08 0.06 0.23 0.35 0.42 0.49 0.46 0.33 0.41 0.26 0.17 0.14 1900 0.11 0.14 0.34 0.46 0.53 0.60 0.57 0.50 0.51 0.36 0.22 0.20 2000 0.13 0.18 0.37 0.51 0.56 0.61 0.58 0.57 0.58 0.44 0.23 0.21 2100 0.15 0.16 0.37 0.51 0.57 0.62 0.58 0.60 0.60 0.46 0.23 0.22 2200 0.18 0.15 0.36 0.47 0.58 0.62 0.56 0.61 0.61 0.45 0.24 0.24 2300 0.18 0.18 0.36 0.45 0.58 0.61 0.54 0.57 0.62 0.48 0.25 0.23 All 3.84 3.14 7.12 10.01 10.71 11.69 10.56 11.27 12.47 9.62 5.38 4.18 c. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-3 www.dnvgl.com Mpika monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.14 0.15 0.35 0.52 0.60 0.69 0.64 0.66 0.56 0.50 0.29 0.17 0100 0.13 0.10 0.33 0.55 0.57 0.71 0.65 0.63 0.59 0.51 0.29 0.15 0200 0.15 0.09 0.34 0.54 0.55 0.67 0.64 0.66 0.61 0.44 0.26 0.13 0300 0.13 0.11 0.34 0.53 0.54 0.64 0.63 0.66 0.61 0.45 0.27 0.12 0400 0.12 0.12 0.34 0.53 0.56 0.62 0.63 0.66 0.61 0.43 0.28 0.13 0500 0.12 0.11 0.34 0.47 0.55 0.60 0.62 0.65 0.61 0.41 0.26 0.12 0600 0.11 0.11 0.32 0.45 0.55 0.57 0.61 0.66 0.59 0.38 0.26 0.11 0700 0.07 0.08 0.26 0.46 0.43 0.45 0.52 0.57 0.54 0.30 0.25 0.08 0800 0.08 0.07 0.27 0.47 0.47 0.41 0.46 0.56 0.63 0.37 0.29 0.10 0900 0.08 0.06 0.26 0.43 0.52 0.47 0.53 0.57 0.64 0.37 0.25 0.11 1000 0.11 0.06 0.25 0.35 0.46 0.41 0.45 0.47 0.55 0.32 0.22 0.11 1100 0.10 0.09 0.18 0.28 0.38 0.30 0.35 0.36 0.45 0.29 0.17 0.10 1200 0.12 0.09 0.16 0.27 0.32 0.24 0.29 0.31 0.38 0.28 0.15 0.11 1300 0.13 0.09 0.16 0.27 0.29 0.22 0.26 0.30 0.35 0.29 0.18 0.13 1400 0.14 0.11 0.18 0.26 0.29 0.22 0.26 0.30 0.37 0.33 0.17 0.13 1500 0.10 0.12 0.22 0.28 0.31 0.26 0.27 0.30 0.41 0.35 0.16 0.14 1600 0.11 0.14 0.25 0.31 0.32 0.34 0.33 0.36 0.48 0.36 0.24 0.14 1700 0.16 0.11 0.24 0.34 0.35 0.40 0.38 0.40 0.50 0.39 0.27 0.17 1800 0.15 0.12 0.27 0.40 0.39 0.46 0.45 0.49 0.46 0.45 0.31 0.21 1900 0.15 0.16 0.30 0.41 0.36 0.41 0.46 0.45 0.48 0.47 0.26 0.20 2000 0.17 0.16 0.31 0.41 0.36 0.35 0.48 0.44 0.57 0.49 0.28 0.18 2100 0.18 0.15 0.30 0.48 0.41 0.34 0.51 0.47 0.69 0.58 0.34 0.17 2200 0.15 0.15 0.33 0.54 0.47 0.45 0.56 0.56 0.66 0.59 0.36 0.17 2300 0.14 0.14 0.33 0.57 0.56 0.60 0.59 0.66 0.61 0.52 0.31 0.18 All 3.02 2.69 6.63 10.12 10.62 10.84 11.60 12.16 12.95 9.86 6.12 3.40 d. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-4 www.dnvgl.com Chanka monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.12 0.15 0.12 0.35 0.43 0.49 0.44 0.49 0.57 0.47 0.26 0.20 0100 0.11 0.13 0.13 0.34 0.48 0.48 0.45 0.54 0.60 0.44 0.25 0.16 0200 0.11 0.12 0.12 0.35 0.54 0.53 0.51 0.60 0.63 0.43 0.26 0.15 0300 0.13 0.10 0.11 0.36 0.54 0.57 0.57 0.62 0.67 0.43 0.25 0.16 0400 0.14 0.11 0.12 0.35 0.55 0.57 0.60 0.60 0.66 0.41 0.24 0.14 0500 0.13 0.13 0.12 0.35 0.55 0.54 0.60 0.59 0.66 0.36 0.21 0.15 0600 0.10 0.08 0.11 0.33 0.50 0.52 0.58 0.56 0.61 0.31 0.15 0.14 0700 0.07 0.05 0.09 0.30 0.44 0.42 0.51 0.51 0.58 0.32 0.16 0.12 0800 0.08 0.06 0.11 0.35 0.51 0.43 0.49 0.58 0.67 0.33 0.18 0.13 0900 0.09 0.05 0.11 0.37 0.53 0.48 0.51 0.65 0.70 0.36 0.22 0.13 1000 0.11 0.05 0.13 0.38 0.53 0.55 0.52 0.64 0.69 0.40 0.25 0.12 1100 0.11 0.05 0.12 0.37 0.52 0.53 0.49 0.58 0.61 0.42 0.25 0.11 1200 0.16 0.06 0.13 0.40 0.51 0.44 0.43 0.50 0.53 0.38 0.25 0.10 1300 0.13 0.07 0.12 0.38 0.48 0.37 0.38 0.43 0.45 0.35 0.27 0.16 1400 0.16 0.12 0.12 0.38 0.47 0.35 0.35 0.42 0.44 0.34 0.31 0.17 1500 0.13 0.10 0.15 0.39 0.47 0.35 0.36 0.43 0.48 0.42 0.32 0.22 1600 0.14 0.10 0.19 0.41 0.47 0.39 0.42 0.51 0.59 0.54 0.37 0.24 1700 0.09 0.08 0.15 0.40 0.47 0.41 0.47 0.53 0.64 0.63 0.43 0.17 1800 0.11 0.11 0.17 0.40 0.49 0.48 0.45 0.49 0.58 0.58 0.42 0.15 1900 0.10 0.18 0.15 0.41 0.43 0.49 0.42 0.48 0.55 0.53 0.37 0.15 2000 0.09 0.17 0.16 0.41 0.41 0.48 0.46 0.54 0.55 0.54 0.39 0.18 2100 0.13 0.15 0.17 0.43 0.44 0.43 0.45 0.56 0.59 0.54 0.35 0.21 2200 0.12 0.14 0.17 0.38 0.46 0.45 0.41 0.54 0.57 0.56 0.31 0.20 2300 0.11 0.15 0.16 0.37 0.43 0.46 0.42 0.50 0.57 0.50 0.28 0.19 All 2.79 2.52 3.21 8.95 11.66 11.23 11.29 12.91 14.20 10.59 6.76 3.86 e. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-5 www.dnvgl.com Petauke monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.17 0.13 0.39 0.47 0.41 0.56 0.61 0.69 0.57 0.63 0.29 0.22 0100 0.20 0.11 0.37 0.47 0.39 0.51 0.63 0.58 0.57 0.55 0.26 0.21 0200 0.17 0.12 0.35 0.44 0.42 0.49 0.57 0.60 0.57 0.53 0.27 0.20 0300 0.18 0.13 0.36 0.40 0.43 0.48 0.49 0.57 0.59 0.54 0.34 0.17 0400 0.19 0.15 0.33 0.40 0.40 0.49 0.47 0.51 0.60 0.51 0.34 0.20 0500 0.18 0.11 0.32 0.40 0.42 0.50 0.51 0.51 0.62 0.52 0.37 0.19 0600 0.15 0.09 0.31 0.40 0.38 0.49 0.49 0.52 0.61 0.53 0.39 0.17 0700 0.07 0.06 0.26 0.32 0.30 0.41 0.46 0.46 0.47 0.50 0.35 0.16 0800 0.07 0.08 0.34 0.37 0.33 0.31 0.40 0.51 0.49 0.64 0.30 0.19 0900 0.08 0.08 0.37 0.35 0.31 0.33 0.48 0.51 0.57 0.60 0.25 0.17 1000 0.13 0.05 0.30 0.30 0.24 0.27 0.39 0.45 0.53 0.47 0.23 0.15 1100 0.14 0.06 0.25 0.22 0.18 0.22 0.25 0.36 0.44 0.38 0.22 0.14 1200 0.15 0.06 0.21 0.16 0.15 0.18 0.19 0.29 0.38 0.33 0.15 0.11 1300 0.12 0.06 0.20 0.16 0.13 0.15 0.19 0.26 0.37 0.29 0.14 0.12 1400 0.14 0.07 0.15 0.14 0.13 0.15 0.20 0.24 0.34 0.30 0.13 0.12 1500 0.14 0.08 0.19 0.17 0.13 0.19 0.20 0.23 0.36 0.29 0.15 0.12 1600 0.13 0.08 0.22 0.20 0.17 0.23 0.25 0.26 0.43 0.30 0.23 0.15 1700 0.13 0.09 0.25 0.24 0.25 0.33 0.33 0.34 0.47 0.37 0.29 0.17 1800 0.18 0.14 0.35 0.39 0.41 0.56 0.52 0.50 0.61 0.44 0.37 0.23 1900 0.23 0.17 0.42 0.52 0.48 0.64 0.69 0.67 0.73 0.61 0.46 0.27 2000 0.21 0.13 0.47 0.52 0.50 0.64 0.73 0.69 0.71 0.71 0.45 0.28 2100 0.19 0.13 0.50 0.51 0.48 0.69 0.71 0.74 0.67 0.69 0.39 0.25 2200 0.15 0.10 0.45 0.46 0.49 0.66 0.70 0.77 0.67 0.71 0.30 0.22 2300 0.15 0.11 0.40 0.48 0.45 0.63 0.67 0.76 0.62 0.71 0.29 0.24 All 3.65 2.38 7.74 8.49 7.96 10.09 11.13 12.04 12.98 12.12 6.96 4.47 f. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-6 www.dnvgl.com Mansa monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.17 0.14 0.32 0.55 0.66 0.68 0.71 0.64 0.67 0.34 0.25 0.15 0100 0.18 0.13 0.29 0.51 0.71 0.70 0.73 0.65 0.67 0.32 0.26 0.15 0200 0.18 0.14 0.28 0.50 0.67 0.69 0.71 0.67 0.59 0.33 0.21 0.15 0300 0.19 0.12 0.23 0.47 0.67 0.69 0.71 0.63 0.56 0.35 0.26 0.15 0400 0.18 0.16 0.21 0.46 0.63 0.67 0.69 0.64 0.56 0.35 0.23 0.14 0500 0.16 0.17 0.21 0.46 0.61 0.66 0.66 0.65 0.57 0.38 0.21 0.12 0600 0.14 0.14 0.20 0.43 0.61 0.64 0.69 0.63 0.57 0.34 0.23 0.12 0700 0.09 0.11 0.16 0.41 0.46 0.54 0.62 0.54 0.44 0.27 0.19 0.07 0800 0.08 0.06 0.21 0.50 0.50 0.46 0.45 0.47 0.52 0.33 0.22 0.07 0900 0.08 0.06 0.27 0.52 0.59 0.53 0.57 0.59 0.61 0.35 0.19 0.07 1000 0.09 0.05 0.26 0.49 0.52 0.45 0.57 0.58 0.57 0.30 0.18 0.06 1100 0.08 0.04 0.19 0.41 0.43 0.35 0.46 0.49 0.45 0.23 0.15 0.06 1200 0.06 0.06 0.17 0.34 0.35 0.27 0.36 0.40 0.37 0.19 0.11 0.07 1300 0.08 0.08 0.16 0.31 0.32 0.22 0.30 0.34 0.33 0.15 0.10 0.09 1400 0.09 0.08 0.15 0.27 0.30 0.23 0.28 0.31 0.33 0.15 0.10 0.12 1500 0.12 0.11 0.17 0.28 0.34 0.21 0.29 0.30 0.38 0.22 0.16 0.12 1600 0.12 0.13 0.16 0.26 0.38 0.24 0.31 0.34 0.42 0.29 0.13 0.12 1700 0.16 0.16 0.18 0.28 0.34 0.28 0.33 0.34 0.43 0.32 0.15 0.09 1800 0.14 0.15 0.22 0.36 0.48 0.52 0.49 0.50 0.51 0.34 0.14 0.09 1900 0.15 0.13 0.27 0.45 0.59 0.62 0.58 0.65 0.58 0.40 0.20 0.13 2000 0.15 0.10 0.31 0.49 0.59 0.66 0.59 0.64 0.56 0.41 0.22 0.12 2100 0.17 0.12 0.33 0.47 0.60 0.63 0.62 0.58 0.60 0.39 0.24 0.14 2200 0.18 0.14 0.34 0.49 0.66 0.64 0.63 0.61 0.64 0.38 0.25 0.15 2300 0.18 0.14 0.35 0.55 0.65 0.64 0.66 0.64 0.69 0.37 0.24 0.15 All 3.17 2.74 5.64 10.27 12.64 12.22 13.01 12.82 12.63 7.51 4.64 2.70 g. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-7 www.dnvgl.com Malawi monthly and diurnal production matrix Energy Production a [%] Hour Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0000 0.18 0.07 0.27 0.35 0.42 0.60 0.56 0.62 0.62 0.65 0.30 0.22 0100 0.16 0.10 0.28 0.34 0.44 0.61 0.62 0.64 0.64 0.63 0.29 0.24 0200 0.12 0.10 0.28 0.42 0.49 0.58 0.64 0.68 0.64 0.60 0.28 0.20 0300 0.11 0.09 0.22 0.37 0.53 0.59 0.65 0.66 0.60 0.59 0.30 0.20 0400 0.16 0.08 0.27 0.38 0.47 0.58 0.57 0.63 0.59 0.58 0.30 0.22 0500 0.11 0.09 0.26 0.36 0.43 0.59 0.58 0.63 0.58 0.55 0.29 0.21 0600 0.09 0.10 0.24 0.34 0.45 0.57 0.50 0.62 0.59 0.48 0.29 0.17 0700 0.07 0.07 0.22 0.26 0.28 0.36 0.32 0.46 0.41 0.47 0.34 0.14 0800 0.10 0.08 0.25 0.35 0.36 0.27 0.24 0.49 0.47 0.63 0.40 0.20 0900 0.11 0.08 0.23 0.40 0.42 0.33 0.34 0.59 0.61 0.59 0.38 0.22 1000 0.11 0.08 0.18 0.33 0.39 0.32 0.34 0.48 0.56 0.53 0.32 0.17 1100 0.11 0.06 0.13 0.26 0.30 0.21 0.24 0.40 0.49 0.48 0.28 0.18 1200 0.14 0.06 0.12 0.20 0.23 0.15 0.19 0.32 0.44 0.46 0.26 0.15 1300 0.16 0.07 0.12 0.22 0.20 0.13 0.17 0.28 0.42 0.44 0.24 0.18 1400 0.16 0.10 0.10 0.19 0.18 0.13 0.16 0.27 0.43 0.46 0.29 0.16 1500 0.18 0.15 0.12 0.22 0.20 0.13 0.17 0.31 0.47 0.50 0.35 0.21 1600 0.13 0.07 0.11 0.25 0.23 0.15 0.18 0.28 0.50 0.60 0.43 0.26 1700 0.13 0.11 0.15 0.24 0.26 0.20 0.21 0.30 0.52 0.67 0.46 0.18 1800 0.15 0.12 0.19 0.34 0.47 0.44 0.47 0.54 0.62 0.62 0.41 0.18 1900 0.17 0.18 0.27 0.40 0.55 0.64 0.69 0.70 0.75 0.69 0.37 0.23 2000 0.21 0.17 0.30 0.32 0.52 0.51 0.62 0.69 0.73 0.66 0.34 0.28 2100 0.21 0.18 0.29 0.34 0.47 0.47 0.55 0.62 0.64 0.67 0.31 0.30 2200 0.21 0.15 0.27 0.39 0.40 0.54 0.52 0.53 0.56 0.68 0.33 0.24 2300 0.23 0.11 0.28 0.35 0.39 0.58 0.53 0.54 0.60 0.68 0.25 0.22 All 3.50 2.48 5.18 7.62 9.08 9.68 10.04 12.27 13.46 13.91 7.83 4.96 h. Only wake and hysteresis losses have been included in the calculation DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page E-8 www.dnvgl.com APPENDIX F UNCERTAINTY ANALYSIS Uncertainty in the projected energy output for the Choma site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 10.4 3.4% Long-term measurement height wind regime 26.7 8.8% Vertical extrapolation 21.3 7.0% Spatial extrapolation 12.2 4.0% Loss factors 5.1 1.7% Inter-annual variability 37.1 12.3% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 54.6 40.0 18.0% 13.2% Uncertainty in the projected energy output for the Mwinilunga site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 9.3 2.9% Long-term measurement height wind regime 22.3 6.9% Vertical extrapolation 24.7 7.6% Spatial extrapolation 13.7 4.2% Loss factors 5.1 1.6% Inter-annual variability 33.5 10.4% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 52.7 39.7 16.3% 12.3% Uncertainty in the projected energy output for the Lusaka site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 10.4 2.7% Long-term measurement height wind regime 31.8 8.2% Vertical extrapolation 27.4 7.1% Spatial extrapolation 15.4 4.0% Loss factors 5.3 1.4% Inter-annual variability 37.3 9.7% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 62.4 48.9 16.2% 12.7% DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page F-1 www.dnvgl.com Uncertainty in the projected energy output for the Mpika site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 11.1 3.5% Long-term measurement height wind regime 27.7 8.6% Vertical extrapolation 22.7 7.1% Spatial extrapolation 12.8 4.0% Loss factors 4.7 1.5% Inter-annual variability 39.5 12.3% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 57.4 42.0 17.9% 13.1% Uncertainty in the projected energy output for the Chanka site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 11.3 3.3% Long-term measurement height wind regime 34.4 9.9% Vertical extrapolation 23.2 6.7% Spatial extrapolation 23.3 6.7% Loss factors 4.8 1.4% Inter-annual variability 40.6 11.8% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 66.4 51.3 19.2% 14.8% Uncertainty in the projected energy output for the Petauke site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 10.1 3.5% Long-term measurement height wind regime 23.7 8.1% Vertical extrapolation 26.9 9.2% Spatial extrapolation 20.8 7.1% Loss factors 4.8 1.7% Inter-annual variability 36.3 12.4% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 57.6 45.2 19.8% 15.5% DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page F-2 www.dnvgl.com Uncertainty in the projected energy output for the Mansa site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 9.8 3.1% Long-term measurement height wind regime 22.7 7.2% Vertical extrapolation 26.0 8.3% Spatial extrapolation 17.4 5.5% Loss factors 4.4 1.4% Inter-annual variability 35.5 11.3% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 55.5 42.2 17.6% 13.4% Uncertainty in the projected energy output for the Malawi site Source of uncertainty/variability [GWh/annum] Equivalent standard deviation [%] Measurement accuracy 10.3 3.4% Long-term measurement height wind regime 23.9 7.9% Vertical extrapolation 26.8 8.8% Spatial extrapolation 17.9 5.9% Loss factors 4.3 1.4% Inter-annual variability 36.5 12.0% Future period under consideration 1 year 10 year 1 year 10 year Overall energy uncertainty 57.2 44.1 18.8% 14.5% DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page F-3 www.dnvgl.com APPENDIX G SITE CONDITIONS Table G-1 Predicted profiles of design equivalent turbulence intensity at the Choma site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho Cho A B C [m/s] _01 _02 _03 _04 _05 _06 _07 _08 _09 _10 _11 _12 _13 _14 _15 _16 _17 3 36.0 35.2 35.3 35.6 35.9 36.1 36.1 35.0 35.9 36.2 36.3 36.3 35.1 35.8 35.7 35.1 35.9 41.9 36.6 31.4 4 30.0 28.7 28.9 29.3 29.6 30.2 30.2 28.4 30.1 30.4 30.6 30.4 28.5 29.9 29.3 28.6 30.0 34.4 30.1 25.8 5 26.4 24.2 24.9 25.4 25.5 26.2 26.2 24.0 26.2 26.5 26.7 26.3 24.0 25.8 25.3 24.3 26.1 29.9 26.2 22.4 6 24.0 21.0 22.0 22.7 22.6 23.5 23.5 20.7 23.5 23.9 24.0 23.5 20.7 23.1 22.3 21.3 23.5 26.9 23.6 20.2 7 21.7 18.2 19.3 20.2 20.1 21.1 21.1 17.8 21.2 21.6 21.8 21.2 17.7 20.7 19.7 18.5 21.2 24.8 21.7 18.6 8 20.1 16.4 17.4 18.4 18.2 19.3 19.4 15.8 19.5 19.9 20.1 19.5 15.7 18.9 17.9 16.5 19.5 23.2 20.3 17.4 9 18.8 15.3 15.7 16.8 16.6 17.8 17.9 14.4 18.1 18.4 18.6 18.0 14.1 17.4 16.3 15.1 18.1 22.0 19.2 16.5 10 16.9 14.0 14.0 15.0 14.8 16.1 16.1 13.0 16.4 16.7 16.9 16.3 12.6 15.8 14.6 13.6 16.4 21.0 18.3 15.7 11 14.9 12.2 12.2 13.2 13.1 14.3 14.2 11.4 14.5 14.7 14.9 14.5 11.1 14.1 12.8 12.2 14.6 20.1 17.6 15.1 12 13.0 10.8 10.6 11.5 11.5 12.5 12.5 10.0 12.7 12.9 13.1 12.7 9.7 12.3 11.2 10.8 12.8 19.5 17.0 14.6 13 11.9 9.8 9.5 10.3 10.4 11.1 11.2 9.0 11.3 11.6 11.7 11.2 8.7 10.8 10.2 9.7 11.3 18.9 16.5 14.2 14 11.0 8.8 8.8 9.5 9.6 10.2 10.2 8.2 10.3 10.5 10.7 10.1 8.0 9.8 9.5 9.1 10.4 18.4 16.1 13.8 15 10.3 8.0 8.3 9.0 9.1 9.6 9.7 7.5 9.8 9.9 10.1 9.8 7.4 9.3 8.9 8.5 9.7 18.0 15.7 13.5 16 10.3 8.2 9.0 9.4 9.5 10.0 10.3 8.2 10.5 10.4 10.7 10.8 8.7 10.0 9.3 8.7 10.2 17.6 15.4 13.2 17 11.2 10.1 10.5 10.7 10.7 11.5 11.6 10.2 12.1 11.7 12.0 12.3 10.9 11.9 10.9 10.7 11.9 17.3 15.1 13.0 18 11.6 11.7 11.8 11.8 11.9 12.5 12.4 11.8 12.8 12.4 12.8 12.8 12.1 13.2 12.1 12.2 13.0 17.0 14.9 12.7 19 11.7 11.8 11.8 11.8 11.9 12.9 12.8 12.0 12.8 12.6 13.1 12.6 12.1 13.1 12.0 12.1 13.1 16.7 14.6 12.5 20 11.6 11.7 11.7 11.7 11.7 11.7 - - - - - - - - - - - 16.5 14.4 12.4 21 11.8 11.8 12.4 12.7 12.2 11.7 11.7 11.7 11.8 11.7 11.8 11.8 11.7 - 11.7 11.7 11.7 16.3 14.2 12.2 22 11.7 11.7 12.2 12.5 12.0 11.5 11.5 11.5 11.7 11.6 11.7 11.7 11.6 11.4 11.5 11.6 11.6 16.1 14.1 12.1 23 - - - - 11.4 11.4 11.4 11.4 - 11.3 11.4 - 11.4 11.3 11.4 11.4 11.3 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-1 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Cho Cho Cho Cho Cho Cho Cho Cho A B C [m/s] _18 _19 _20 _21 _22 _23 _24 _25 3 35.0 35.2 35.6 35.5 35.1 35.1 36.0 35.1 41.9 36.6 31.4 4 28.5 28.8 29.4 29.2 28.5 28.6 29.8 28.6 34.4 30.1 25.8 5 24.0 24.8 25.4 25.1 24.1 24.3 26.0 24.2 29.9 26.2 22.4 6 20.7 21.8 22.7 22.2 20.9 21.1 23.3 21.1 26.9 23.6 20.2 7 17.8 19.3 20.4 19.7 18.0 18.2 20.9 18.3 24.8 21.7 18.6 8 15.8 17.5 18.7 17.9 15.8 16.0 19.1 16.4 23.2 20.3 17.4 9 14.4 16.0 17.3 16.5 14.1 14.3 17.7 15.1 22.0 19.2 16.5 10 13.0 14.5 15.7 14.9 12.6 12.6 15.9 13.7 21.0 18.3 15.7 11 11.4 13.0 14.1 13.4 11.1 11.0 13.9 12.1 20.1 17.6 15.1 12 10.0 11.6 12.4 11.9 9.7 9.6 12.2 10.7 19.5 17.0 14.6 13 9.0 10.5 11.1 10.8 8.7 8.7 11.1 9.7 18.9 16.5 14.2 14 8.3 9.8 10.2 10.0 8.2 8.2 10.3 8.9 18.4 16.1 13.8 15 7.6 9.0 9.4 9.2 7.7 7.8 9.7 8.2 18.0 15.7 13.5 16 8.8 9.2 9.5 9.5 8.7 8.4 9.9 8.5 17.6 15.4 13.2 17 11.1 10.9 11.3 11.2 10.8 10.2 11.0 10.4 17.3 15.1 13.0 18 12.2 12.4 13.0 12.5 12.3 11.9 11.6 12.0 17.0 14.9 12.7 19 12.2 12.1 13.1 12.3 12.1 11.9 11.8 11.9 16.7 14.6 12.5 20 - - 12.9 12.1 - 11.7 11.6 11.7 16.5 14.4 12.4 21 11.7 11.8 11.7 11.8 11.7 11.7 11.7 11.7 16.3 14.2 12.2 22 11.6 11.7 11.6 11.7 11.6 11.5 11.6 11.6 16.1 14.1 12.1 23 11.4 - 11.4 - - 11.4 - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-2 www.dnvgl.com Table G-2 Predicted profiles of design equivalent turbulence intensity at the Mwinilunga site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi A B C [m/s] _01 _02 _03 _04 _05 _06 _07 _08 _09 _10 _11 _12 _13 _14 _15 _16 _17 3 34.1 33.1 34.0 33.7 33.6 33.7 33.8 32.8 33.2 33.5 32.6 33.2 33.7 32.8 32.9 33.0 32.7 41.9 36.6 31.4 4 29.0 27.9 29.3 29.0 28.9 28.9 28.4 27.3 28.0 28.3 27.3 27.9 28.4 27.4 27.9 27.7 27.3 34.4 30.1 25.8 5 25.8 24.7 26.3 26.0 25.9 25.9 25.0 24.0 24.7 25.1 23.9 24.7 25.1 24.0 24.7 24.4 23.9 29.9 26.2 22.4 6 23.6 22.5 24.3 23.9 23.8 23.8 22.6 21.5 22.4 22.8 21.5 22.3 22.9 21.6 22.5 22.0 21.4 26.9 23.6 20.2 7 21.7 20.7 22.7 22.3 22.2 22.1 20.8 19.3 20.7 21.0 19.4 20.5 21.0 19.4 20.8 20.1 19.3 24.8 21.7 18.6 8 19.8 19.0 21.1 20.7 20.6 20.4 18.8 17.4 19.0 19.2 17.5 18.8 19.2 17.4 19.3 18.4 17.3 23.2 20.3 17.4 9 18.0 17.4 19.4 18.9 18.8 18.5 16.7 15.7 17.1 17.4 15.7 16.9 17.3 15.5 17.7 16.6 15.5 22.0 19.2 16.5 10 15.6 15.2 16.8 16.4 16.3 16.0 14.1 13.4 14.7 15.0 13.5 14.4 14.8 13.1 15.3 14.2 13.4 21.0 18.3 15.7 11 13.2 12.7 14.0 13.6 13.6 13.3 11.4 10.9 12.1 12.5 11.3 11.8 12.1 10.4 12.4 11.5 11.1 20.1 17.6 15.1 12 11.5 10.6 11.8 11.4 11.5 11.5 9.2 8.7 10.0 10.4 9.3 9.9 10.0 7.9 9.9 9.2 9.2 19.5 17.0 14.6 13 10.4 9.4 10.5 10.2 10.4 10.4 7.7 7.0 8.7 9.1 7.7 8.7 8.9 6.7 8.3 7.7 8.0 18.9 16.5 14.2 14 9.7 8.9 9.8 9.4 9.7 9.5 7.3 6.6 8.1 8.4 6.7 8.1 8.3 7.0 7.4 7.1 7.5 18.4 16.1 13.8 15 9.0 8.5 9.1 8.6 8.8 8.7 7.3 6.4 7.9 8.1 6.6 7.6 7.5 6.7 7.2 6.9 7.3 18.0 15.7 13.5 16 8.4 8.1 8.3 8.2 8.9 9.8 7.8 8.7 8.4 8.7 9.0 7.8 7.7 6.7 8.7 9.5 9.9 17.6 15.4 13.2 17 10.5 10.6 10.0 9.6 9.9 11.0 11.1 10.4 11.8 11.3 11.1 9.7 9.9 10.0 10.8 10.6 10.8 17.3 15.1 13.0 18 11.8 12.7 11.1 11.0 11.5 11.7 12.0 10.4 12.0 11.9 12.0 11.5 11.6 11.6 11.5 11.7 11.2 17.0 14.9 12.7 19 11.6 12.7 11.3 11.3 11.4 11.7 - 11.2 11.5 11.5 11.6 11.4 11.4 11.4 11.6 - - 16.7 14.6 12.5 20 - - 11.1 11.1 10.9 11.0 - - - - - 11.2 - - 11.0 - - 16.5 14.4 12.4 21 - - - - - - - - - - - - - - - - - 16.3 14.2 12.2 22 - - - - - - - - - - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-3 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Mwi Mwi Mwi Mwi Mwi Mwi Mwi Mwi A B C [m/s] _18 _19 _20 _21 _22 _23 _24 _25 3 33.2 33.4 33.5 33.9 33.8 33.9 33.4 33.0 41.9 36.6 31.4 4 27.8 28.1 28.1 28.5 28.4 28.5 28.1 27.6 34.4 30.1 25.8 5 24.5 24.8 24.7 25.1 25.0 25.2 24.9 24.2 29.9 26.2 22.4 6 22.2 22.5 22.3 22.7 22.7 22.9 22.6 21.7 26.9 23.6 20.2 7 20.3 20.6 20.5 20.9 20.8 21.1 20.6 19.6 24.8 21.7 18.6 8 18.3 18.7 18.6 18.9 19.0 19.4 18.6 17.7 23.2 20.3 17.4 9 16.5 16.9 16.6 16.8 17.1 17.4 16.6 15.8 22.0 19.2 16.5 10 14.1 14.6 14.2 14.3 14.6 14.8 14.1 13.6 21.0 18.3 15.7 11 11.5 12.1 11.6 11.6 11.9 12.0 11.6 11.3 20.1 17.6 15.1 12 9.8 10.2 9.7 9.4 9.4 9.6 9.8 9.5 19.5 17.0 14.6 13 8.8 8.7 8.1 8.0 7.6 8.1 8.6 8.3 18.9 16.5 14.2 14 8.4 8.1 7.4 7.4 7.0 7.4 7.8 7.4 18.4 16.1 13.8 15 7.7 7.6 7.3 7.2 7.2 7.4 7.1 6.8 18.0 15.7 13.5 16 8.5 8.4 7.7 7.7 10.0 9.7 6.7 8.2 17.6 15.4 13.2 17 10.0 10.2 9.5 10.7 10.5 10.9 11.0 11.4 17.3 15.1 13.0 18 11.6 11.6 11.5 11.7 11.5 11.7 11.9 12.1 17.0 14.9 12.7 19 11.5 11.5 11.4 9.2 7.8 - - - 16.7 14.6 12.5 20 - - 11.2 - - - - - 16.5 14.4 12.4 21 - - - - - - - - 16.3 14.2 12.2 22 - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-4 www.dnvgl.com Table G-3 Predicted profiles of design equivalent turbulence intensity at the Lusaka site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ A B C [m/s] 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3 34.0 34.5 33.8 34.3 34.2 33.9 33.9 34.8 34.6 34.6 34.8 34.0 33.9 34.4 34.4 33.8 34.0 41.9 36.6 31.4 4 28.7 29.1 28.3 29.1 28.8 28.4 28.4 29.5 29.3 29.5 29.5 28.5 28.5 29.1 29.0 28.3 28.7 34.4 30.1 25.8 5 25.1 25.5 24.6 25.6 25.1 24.7 24.8 25.9 25.8 26.1 25.8 24.9 25.1 25.5 25.4 24.7 25.3 29.9 26.2 22.4 6 22.9 23.3 22.3 23.5 22.8 22.5 22.5 23.9 23.6 24.1 23.7 22.6 22.9 23.3 23.2 22.5 23.2 26.9 23.6 20.2 7 21.0 21.3 20.3 21.6 20.9 20.5 20.5 22.0 21.7 22.4 21.7 20.6 21.1 21.3 21.2 20.6 21.3 24.8 21.7 18.6 8 19.2 19.5 18.5 19.8 19.2 18.8 18.7 20.2 19.9 20.9 19.9 18.8 19.6 19.5 19.4 18.9 19.7 23.2 20.3 17.4 9 17.4 17.6 16.6 18.0 17.2 16.9 16.8 18.3 17.7 19.3 18.0 16.8 17.9 17.6 17.3 17.0 17.9 22.0 19.2 16.5 10 15.3 15.4 14.5 15.8 15.0 14.7 14.7 16.1 15.3 17.4 15.8 14.6 16.0 15.5 15.1 14.8 16.0 21.0 18.3 15.7 11 12.6 12.7 11.8 13.3 12.3 12.0 12.0 13.4 12.6 15.1 13.1 12.0 13.7 12.9 12.4 12.2 13.6 20.1 17.6 15.1 12 10.3 10.3 9.4 11.0 10.0 9.6 9.6 11.1 10.2 13.0 10.7 9.5 11.5 10.6 9.9 9.8 11.4 19.5 17.0 14.6 13 9.1 9.1 8.0 9.6 8.6 8.2 8.2 9.7 8.7 11.5 9.3 8.1 10.1 9.1 8.5 8.3 10.0 18.9 16.5 14.2 14 7.7 7.8 6.9 8.4 7.4 6.9 7.1 8.2 7.6 10.3 8.0 7.1 8.9 7.8 7.5 7.1 8.9 18.4 16.1 13.8 15 7.0 7.0 6.2 7.5 6.4 6.1 6.4 7.3 6.6 9.2 7.1 6.2 7.9 6.9 6.9 6.1 8.0 18.0 15.7 13.5 16 6.4 6.3 5.7 6.9 5.8 5.8 6.1 6.5 5.9 8.5 6.4 5.7 7.4 6.3 6.3 5.7 7.4 17.6 15.4 13.2 17 7.2 6.9 6.8 6.9 6.6 6.6 6.6 6.6 6.4 8.4 6.5 6.5 7.5 6.5 6.6 6.5 7.4 17.3 15.1 13.0 18 4.4 5.2 5.9 5.3 5.2 5.5 5.5 5.7 6.3 7.4 5.6 5.6 6.6 5.6 5.6 5.6 6.7 17.0 14.9 12.7 19 9.6 8.9 8.7 7.1 7.1 7.2 7.0 7.1 6.9 7.9 6.6 6.6 7.2 6.5 6.6 6.8 6.5 16.7 14.6 12.5 20 12.2 12.1 12.0 12.1 12.1 12.1 12.1 12.1 12.0 12.2 12.1 12.1 12.1 12.1 12.1 12.1 12.1 16.5 14.4 12.4 21 12.1 12.0 11.9 12.0 12.0 11.9 11.9 12.0 11.9 12.0 12.0 12.0 12.0 12.0 12.0 12.0 11.9 16.3 14.2 12.2 22 12.0 12.1 12.0 12.0 12.0 12.1 12.1 12.3 12.3 12.3 12.3 12.3 12.4 12.3 12.4 12.3 12.2 16.1 14.1 12.1 23 11.8 - 11.8 11.8 11.9 12.0 12.0 - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-5 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ Lus_ A B C [m/s] 18 19 20 21 22 23 24 25 3 33.6 34.3 34.5 33.6 33.9 34.5 34.5 33.5 41.9 36.6 31.4 4 28.0 29.1 29.2 28.1 28.5 29.3 29.3 28.0 34.4 30.1 25.8 5 24.3 25.5 25.7 24.4 25.1 25.7 25.6 24.3 29.9 26.2 22.4 6 22.0 23.4 23.6 22.1 23.0 23.5 23.4 22.0 26.9 23.6 20.2 7 20.1 21.5 21.7 20.3 21.1 21.6 21.5 20.1 24.8 21.7 18.6 8 18.6 19.6 19.9 18.7 19.4 19.8 19.7 18.4 23.2 20.3 17.4 9 16.7 17.7 17.9 16.9 17.4 17.9 17.7 16.6 22.0 19.2 16.5 10 14.6 15.6 15.6 14.8 15.2 15.8 15.4 14.6 21.0 18.3 15.7 11 12.0 13.0 12.9 12.2 12.5 13.1 12.7 12.0 20.1 17.6 15.1 12 9.7 10.7 10.5 9.9 10.1 10.8 10.4 9.6 19.5 17.0 14.6 13 8.3 9.3 9.1 8.4 8.6 9.4 8.9 8.2 18.9 16.5 14.2 14 7.0 8.0 8.0 7.3 7.2 8.1 7.7 7.1 18.4 16.1 13.8 15 6.0 7.2 7.3 6.3 6.3 7.2 6.8 6.4 18.0 15.7 13.5 16 5.7 6.6 6.7 5.7 5.8 6.5 6.2 5.8 17.6 15.4 13.2 17 6.5 6.6 6.7 6.5 6.5 6.7 6.4 6.5 17.3 15.1 13.0 18 5.6 5.6 5.6 5.6 5.9 5.8 5.9 5.6 17.0 14.9 12.7 19 6.5 6.5 6.5 6.5 7.2 6.3 6.6 6.4 16.7 14.6 12.5 20 12.1 12.1 12.1 12.1 12.1 12.1 12.1 12.1 16.5 14.4 12.4 21 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 16.3 14.2 12.2 22 12.3 12.3 12.3 12.3 12.3 12.3 12.3 12.3 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-6 www.dnvgl.com Table G-4 Predicted profiles of design equivalent turbulence intensity at the Mpika site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ A B C [m/s] 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3 32.6 33.0 33.2 33.2 33.0 32.9 33.0 33.3 33.2 32.9 33.0 33.4 32.9 33.1 33.1 33.1 33.3 41.9 36.6 31.4 4 27.3 27.8 28.0 28.0 27.7 27.5 27.7 28.2 27.9 27.5 27.7 28.3 27.6 27.9 27.9 27.9 28.2 34.4 30.1 25.8 5 23.9 24.6 24.6 24.7 24.3 24.0 24.2 24.7 24.3 24.0 24.1 24.7 24.1 24.3 24.3 24.3 24.6 29.9 26.2 22.4 6 21.6 22.5 22.5 22.7 22.2 21.7 22.1 22.4 21.9 21.6 21.7 22.3 21.7 21.9 21.8 21.9 22.1 26.9 23.6 20.2 7 19.2 20.2 20.3 20.5 19.9 19.3 19.8 20.1 19.4 19.1 19.2 19.8 19.2 19.4 19.1 19.4 19.6 24.8 21.7 18.6 8 17.0 18.3 18.2 18.6 17.9 17.1 17.7 18.0 17.2 16.9 16.9 17.5 17.2 17.1 16.8 17.1 17.3 23.2 20.3 17.4 9 15.3 16.8 16.6 17.1 16.3 15.5 16.1 16.3 15.4 15.2 15.1 15.6 15.6 15.3 15.0 15.3 15.4 22.0 19.2 16.5 10 13.9 15.3 15.0 15.6 14.7 14.0 14.5 14.6 13.8 13.7 13.7 14.0 14.3 13.8 13.6 13.8 13.8 21.0 18.3 15.7 11 12.8 14.1 13.7 14.4 13.5 12.9 13.2 13.3 12.8 12.7 12.7 12.9 13.4 12.8 12.8 12.7 12.8 20.1 17.6 15.1 12 12.3 13.2 12.8 13.5 12.7 12.1 12.2 12.4 12.2 12.1 12.0 12.2 12.5 12.2 12.2 12.1 12.1 19.5 17.0 14.6 13 12.7 13.2 12.8 13.3 12.7 12.3 12.4 12.6 12.4 12.2 12.1 12.3 12.5 12.4 12.4 12.1 12.0 18.9 16.5 14.2 14 13.2 13.5 13.3 13.5 13.2 13.1 13.2 13.2 13.1 12.9 12.8 12.9 13.2 13.1 13.2 12.7 12.5 18.4 16.1 13.8 15 14.0 13.8 13.6 13.8 13.3 13.2 12.9 13.2 12.9 13.1 13.1 13.1 13.3 13.3 13.3 12.9 12.9 18.0 15.7 13.5 16 14.9 15.0 15.1 15.1 15.4 15.6 16.1 15.8 15.9 15.3 14.9 15.3 15.6 15.7 15.9 15.1 14.5 17.6 15.4 13.2 17 14.1 14.5 14.2 14.1 13.8 13.6 13.7 13.6 13.3 13.6 13.8 13.6 13.5 13.4 13.2 13.8 14.1 17.3 15.1 13.0 18 12.6 12.5 12.6 12.7 12.8 13.2 13.6 14.1 14.0 13.4 13.2 13.9 13.1 14.3 14.4 13.5 13.7 17.0 14.9 12.7 19 12.6 12.5 12.5 12.7 12.7 12.7 13.0 14.5 14.4 14.1 13.5 15.2 12.9 14.2 14.8 13.9 14.2 16.7 14.6 12.5 20 12.2 12.1 12.2 12.6 12.7 12.7 12.6 12.5 12.5 12.6 12.7 12.6 12.9 12.5 12.6 12.7 12.8 16.5 14.4 12.4 21 12.1 11.9 12.0 12.3 12.4 - - 12.3 12.3 12.3 12.3 12.3 12.7 12.3 - 12.3 12.3 16.3 14.2 12.2 22 - 11.8 - - - - - - - - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-7 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ Mpi_ A B C [m/s] 18 19 20 21 22 23 24 25 3 33.1 32.6 32.8 33.2 33.2 33.5 33.6 32.8 41.9 36.6 31.4 4 27.8 27.2 27.6 28.0 28.0 28.3 28.5 27.5 34.4 30.1 25.8 5 24.2 23.6 24.0 24.4 24.4 24.8 24.9 23.9 29.9 26.2 22.4 6 21.7 21.0 21.7 22.0 22.0 22.3 22.4 21.4 26.9 23.6 20.2 7 19.1 18.4 19.2 19.5 19.5 19.8 19.8 18.6 24.8 21.7 18.6 8 16.8 16.1 17.0 17.2 17.2 17.6 17.5 16.3 23.2 20.3 17.4 9 15.0 14.4 15.2 15.4 15.4 15.7 15.7 14.6 22.0 19.2 16.5 10 13.6 13.2 13.8 13.9 13.9 14.1 14.1 13.4 21.0 18.3 15.7 11 12.6 12.5 12.9 12.9 12.9 13.0 13.0 12.7 20.1 17.6 15.1 12 12.1 12.0 12.4 12.3 12.3 12.4 12.4 12.3 19.5 17.0 14.6 13 12.1 12.2 12.7 12.6 12.6 12.6 12.6 12.7 18.9 16.5 14.2 14 12.7 12.7 13.3 13.2 13.2 13.1 13.2 13.3 18.4 16.1 13.8 15 13.1 13.1 14.0 13.7 13.9 13.9 14.1 14.4 18.0 15.7 13.5 16 14.3 13.9 15.5 15.7 15.7 15.3 15.2 15.5 17.6 15.4 13.2 17 14.1 14.7 13.2 13.2 13.2 13.4 13.5 13.2 17.3 15.1 13.0 18 13.2 12.6 14.2 14.3 14.4 14.3 14.6 13.3 17.0 14.9 12.7 19 13.6 13.2 14.3 14.5 14.2 14.2 13.9 13.2 16.7 14.6 12.5 20 12.9 13.0 12.7 12.7 12.8 12.9 12.9 13.0 16.5 14.4 12.4 21 - - - - - - - - 16.3 14.2 12.2 22 - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-8 www.dnvgl.com Table G-5 Predicted profiles of design equivalent turbulence intensity at the Chanka site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ A B C [m/s] 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3 32.0 33.8 33.9 32.7 33.3 32.5 33.3 33.2 33.4 32.5 33.2 33.8 33.9 33.1 33.3 33.9 32.8 41.9 36.6 31.4 4 25.8 28.6 28.7 26.8 27.5 26.5 27.7 27.4 27.9 26.6 28.0 28.5 28.9 27.4 27.4 28.0 27.1 34.4 30.1 25.8 5 22.3 25.6 25.6 23.4 24.2 22.9 24.6 24.3 24.7 22.9 25.3 25.5 25.9 24.1 24.3 24.8 23.5 29.9 26.2 22.4 6 20.0 23.4 23.4 21.2 21.9 20.8 22.3 22.1 22.6 21.1 23.2 23.4 23.8 22.1 22.1 22.8 21.6 26.9 23.6 20.2 7 18.2 21.0 21.3 19.8 19.8 19.3 20.0 20.3 20.8 19.7 20.8 21.5 21.7 20.6 20.0 20.9 20.1 24.8 21.7 18.6 8 16.7 18.8 19.1 18.0 18.0 17.8 18.0 18.5 19.1 18.3 18.5 19.5 19.7 19.0 18.2 19.2 18.7 23.2 20.3 17.4 9 15.5 16.7 17.1 16.4 16.3 16.3 16.2 16.8 17.3 16.6 16.5 17.6 17.7 17.2 16.6 17.4 17.0 22.0 19.2 16.5 10 14.8 15.3 15.7 15.4 15.2 15.2 14.9 15.5 15.7 15.3 15.0 16.0 15.9 15.8 15.2 15.7 15.5 21.0 18.3 15.7 11 14.2 14.4 14.6 14.4 14.3 14.3 14.1 14.3 14.6 14.4 14.1 14.7 14.7 14.6 14.3 14.6 14.5 20.1 17.6 15.1 12 13.9 13.9 13.9 13.8 13.9 13.8 13.7 13.7 13.9 13.8 13.6 13.9 14.0 13.9 13.8 14.0 13.9 19.5 17.0 14.6 13 13.9 13.8 13.8 13.8 13.8 13.7 13.5 13.5 13.7 13.6 13.5 13.6 13.7 13.6 13.7 13.7 13.7 18.9 16.5 14.2 14 14.3 14.1 14.1 14.1 14.1 13.9 13.7 13.7 13.8 13.8 13.6 13.7 13.8 13.8 13.9 13.8 13.8 18.4 16.1 13.8 15 16.7 16.2 16.2 16.2 16.2 15.7 15.3 15.3 15.3 15.3 15.2 15.2 15.2 15.3 15.7 15.3 15.3 18.0 15.7 13.5 16 18.7 18.5 18.5 18.5 18.5 18.1 17.6 17.6 17.7 17.7 17.6 17.7 17.7 17.6 18.1 17.7 17.6 17.6 15.4 13.2 17 15.0 15.6 14.9 14.9 15.3 15.6 16.2 16.0 16.0 15.9 15.8 16.0 16.0 16.0 15.2 15.9 16.0 17.3 15.1 13.0 18 13.5 14.8 13.7 13.7 15.5 13.9 14.9 13.5 13.9 13.5 13.5 13.7 13.8 13.7 13.6 13.5 13.8 17.0 14.9 12.7 19 13.4 14.8 13.6 13.6 15.2 13.4 15.2 13.3 13.4 13.3 13.4 13.4 13.4 13.4 13.6 13.4 13.4 16.7 14.6 12.5 20 13.2 14.5 13.4 13.4 14.9 13.2 14.9 13.1 13.3 13.1 13.2 13.2 13.2 13.2 13.4 13.2 13.2 16.5 14.4 12.4 21 13.1 14.2 13.3 13.3 14.6 13.1 14.6 13.0 13.1 13.0 13.1 13.1 13.1 13.1 13.3 13.1 13.1 16.3 14.2 12.2 22 13.0 14.0 13.1 13.0 13.8 13.0 14.4 12.9 13.0 12.9 13.0 13.0 13.0 13.0 13.2 13.0 13.0 16.1 14.1 12.1 23 12.6 12.6 - - 12.5 12.5 12.6 - - - - - 12.6 - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-9 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ Cha_ A B C [m/s] 18 19 20 21 22 23 24 25 3 31.9 32.7 32.5 31.9 31.3 32.6 33.6 32.3 41.9 36.6 31.4 4 25.7 26.8 26.6 26.0 25.0 27.0 27.9 26.6 34.4 30.1 25.8 5 21.9 23.3 23.1 22.3 21.2 24.0 24.6 22.9 29.9 26.2 22.4 6 19.5 20.8 20.7 20.0 19.0 21.8 22.5 21.1 26.9 23.6 20.2 7 17.9 19.0 18.9 18.2 17.5 19.7 20.7 19.7 24.8 21.7 18.6 8 16.5 17.5 17.5 16.7 16.2 17.8 19.0 18.3 23.2 20.3 17.4 9 15.3 16.1 16.1 15.4 15.1 16.1 17.2 16.6 22.0 19.2 16.5 10 14.7 15.2 15.1 14.7 14.6 15.0 15.6 15.4 21.0 18.3 15.7 11 14.1 14.3 14.3 14.1 14.0 14.1 14.5 14.5 20.1 17.6 15.1 12 13.8 13.9 13.9 13.7 13.6 13.7 13.9 14.0 19.5 17.0 14.6 13 13.7 13.8 13.8 13.7 13.6 13.7 13.7 13.9 18.9 16.5 14.2 14 14.0 14.1 14.0 13.9 13.8 13.9 13.8 14.2 18.4 16.1 13.8 15 16.2 16.1 16.0 15.9 15.6 16.0 15.3 16.2 18.0 15.7 13.5 16 18.5 18.6 18.6 18.3 18.0 18.4 17.7 18.5 17.6 15.4 13.2 17 15.3 16.4 16.4 15.8 16.0 15.6 16.1 15.1 17.3 15.1 13.0 18 13.4 15.6 15.5 14.0 13.4 14.0 13.4 13.5 17.0 14.9 12.7 19 13.2 15.6 15.5 13.9 12.9 12.8 13.2 13.4 16.7 14.6 12.5 20 13.0 15.2 15.2 13.7 12.8 12.7 13.0 13.2 16.5 14.4 12.4 21 12.9 14.9 14.8 13.5 12.7 12.5 12.9 13.1 16.3 14.2 12.2 22 12.8 14.6 14.5 13.3 12.6 12.4 12.8 13.0 16.1 14.1 12.1 23 - - - - 12.5 12.3 12.6 - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-10 www.dnvgl.com Table G-6 Predicted profiles of design equivalent turbulence intensity at the Petauke site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ A B C [m/s] 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3 33.2 33.3 33.4 32.9 32.7 32.9 33.0 33.1 32.8 33.9 34.5 33.0 34.5 33.3 34.6 34.0 33.2 41.9 36.6 31.4 4 27.5 27.7 28.2 27.2 26.9 27.1 27.5 27.7 27.0 28.8 29.4 27.4 29.8 27.9 29.7 28.8 27.7 34.4 30.1 25.8 5 23.4 23.8 24.8 23.5 23.2 23.1 23.5 23.8 23.0 25.2 25.7 23.6 26.5 24.3 26.1 24.8 23.6 29.9 26.2 22.4 6 20.1 20.6 22.1 20.5 20.2 19.7 20.1 20.6 19.7 22.2 22.7 20.5 23.7 21.5 23.0 21.6 20.2 26.9 23.6 20.2 7 17.2 18.0 19.9 17.9 17.6 16.8 17.4 18.0 16.8 19.5 20.0 18.1 21.1 19.3 20.2 18.9 17.3 24.8 21.7 18.6 8 14.9 16.3 17.9 15.6 15.5 14.7 15.6 15.9 14.7 17.2 17.9 15.9 18.8 17.4 17.8 16.8 15.2 23.2 20.3 17.4 9 13.4 15.2 16.3 13.7 14.3 13.3 14.4 14.3 13.2 15.5 16.3 14.6 17.1 16.1 16.5 15.4 13.7 22.0 19.2 16.5 10 12.3 14.2 14.9 12.4 13.1 12.3 13.3 13.2 12.2 14.2 15.0 13.3 15.7 14.8 15.0 14.0 12.7 21.0 18.3 15.7 11 11.6 13.1 13.7 11.4 12.1 11.7 12.5 12.3 11.5 13.0 13.7 12.1 14.3 13.4 13.9 12.9 11.9 20.1 17.6 15.1 12 11.1 12.1 12.7 10.8 11.2 11.2 11.7 11.6 11.0 12.2 12.7 11.3 13.4 12.5 12.9 12.0 11.4 19.5 17.0 14.6 13 10.8 11.5 12.0 10.3 10.6 11.2 11.4 11.3 10.7 11.6 11.9 10.7 12.6 11.8 12.1 11.3 11.0 18.9 16.5 14.2 14 11.2 11.7 11.8 10.2 10.1 11.8 11.8 11.6 11.0 11.5 11.7 10.3 12.2 11.5 11.9 11.3 11.3 18.4 16.1 13.8 15 12.4 13.0 12.5 10.7 10.2 13.2 13.2 13.1 11.9 12.2 12.3 10.5 12.5 11.8 13.2 12.4 12.7 18.0 15.7 13.5 16 13.1 13.6 13.6 11.7 10.8 13.0 13.7 13.5 13.2 13.9 13.8 11.4 14.3 12.8 13.6 13.4 13.6 17.6 15.4 13.2 17 12.7 13.0 12.9 12.7 11.9 12.8 12.9 12.8 12.6 12.9 12.8 12.8 13.2 13.1 13.3 13.4 12.9 17.3 15.1 13.0 18 12.1 12.3 12.5 12.0 12.1 12.1 12.4 12.3 12.1 12.5 12.9 12.2 13.0 12.8 12.8 12.9 12.6 17.0 14.9 12.7 19 11.6 11.6 12.7 11.5 11.4 11.5 11.7 11.9 11.8 12.2 12.6 12.0 12.8 12.7 11.8 13.0 12.3 16.7 14.6 12.5 20 11.3 11.5 12.4 11.3 11.1 11.4 11.6 11.8 11.8 11.3 11.6 11.7 11.9 11.7 11.8 13.8 12.2 16.5 14.4 12.4 21 11.3 11.5 - 11.3 11.2 11.1 11.6 11.7 11.4 11.4 12.5 12.4 11.6 13.5 - - 12.5 16.3 14.2 12.2 22 11.2 - - 11.1 11.3 11.0 - - 11.3 11.3 12.6 12.7 - 13.5 - - - 16.1 14.1 12.1 23 - - - 10.8 - - - - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-11 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ Pet_ A B C [m/s] 18 19 20 21 22 23 24 25 3 33.1 34.2 35.7 35.1 34.8 34.8 34.1 32.9 41.9 36.6 31.4 4 27.5 29.5 30.7 29.9 29.6 29.5 29.0 27.4 34.4 30.1 25.8 5 23.3 26.2 26.9 25.9 25.6 25.4 25.2 23.5 29.9 26.2 22.4 6 19.8 23.4 23.8 22.8 22.5 22.2 22.1 20.2 26.9 23.6 20.2 7 16.9 20.9 21.1 20.1 19.9 19.4 19.7 17.5 24.8 21.7 18.6 8 14.7 18.6 19.0 18.1 18.1 17.6 17.9 15.4 23.2 20.3 17.4 9 13.3 16.7 17.6 16.7 16.7 16.3 16.5 13.8 22.0 19.2 16.5 10 12.3 15.3 15.9 14.9 15.1 14.6 15.0 12.6 21.0 18.3 15.7 11 11.6 13.9 14.7 13.6 13.6 13.3 13.6 12.0 20.1 17.6 15.1 12 11.1 12.9 13.4 12.5 12.4 12.2 12.3 11.4 19.5 17.0 14.6 13 10.8 12.1 12.6 11.7 11.8 11.7 11.6 11.0 18.9 16.5 14.2 14 11.2 11.6 12.5 11.9 11.7 11.7 11.6 11.0 18.4 16.1 13.8 15 12.6 11.7 13.5 13.1 13.4 13.8 12.6 11.7 18.0 15.7 13.5 16 13.6 13.4 13.2 13.2 13.3 13.4 13.9 13.0 17.6 15.4 13.2 17 12.7 13.1 13.8 13.5 13.0 13.0 12.9 13.0 17.3 15.1 13.0 18 12.4 12.6 12.3 12.2 12.5 12.5 12.4 12.4 17.0 14.9 12.7 19 12.2 12.1 13.7 14.0 12.3 12.0 12.5 11.9 16.7 14.6 12.5 20 12.4 11.5 11.8 11.9 13.1 12.7 12.8 11.8 16.5 14.4 12.4 21 - 11.3 - - - 12.5 - 11.6 16.3 14.2 12.2 22 - 11.2 - - - - - 11.5 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-12 www.dnvgl.com Table G-7 Predicted profiles of design equivalent turbulence intensity at the Mansa site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Man Man Man Man Man Man Man Man Man Man Man Man Man Man Man Man Man A B C [m/s] _01 _02 _03 _04 _05 _06 _07 _08 _09 _10 _11 _12 _13 _14 _15 _16 _17 3 34.1 34.5 33.0 33.9 34.5 34.3 34.6 34.6 34.2 34.3 34.4 34.4 34.5 34.4 33.0 33.9 34.7 41.9 36.6 31.4 4 29.2 29.3 27.8 28.6 29.2 29.1 29.2 29.3 29.0 29.1 29.2 29.0 29.2 29.2 27.7 28.5 29.3 34.4 30.1 25.8 5 25.6 25.8 24.0 24.9 25.5 25.4 25.5 25.6 25.4 25.4 25.5 25.3 25.5 25.5 23.7 24.8 25.6 29.9 26.2 22.4 6 23.3 23.5 21.9 22.5 23.3 23.2 23.4 23.5 23.1 23.1 23.2 23.0 23.2 23.2 21.5 22.5 23.4 26.9 23.6 20.2 7 21.1 21.3 20.0 20.2 21.0 20.9 21.1 21.2 21.0 20.9 21.0 20.8 20.9 20.9 19.6 20.3 21.2 24.8 21.7 18.6 8 19.5 19.7 18.6 18.2 19.2 19.1 19.3 19.5 19.3 19.1 19.1 19.0 19.1 19.2 18.1 18.4 19.3 23.2 20.3 17.4 9 17.6 17.8 17.0 16.1 17.2 17.0 17.3 17.5 17.4 17.1 17.0 16.9 17.1 17.2 16.4 16.3 17.3 22.0 19.2 16.5 10 15.5 15.7 15.1 14.2 15.0 14.9 15.1 15.3 15.3 14.9 14.8 14.8 14.9 15.1 14.3 14.2 15.1 21.0 18.3 15.7 11 13.1 13.4 12.8 12.6 13.2 13.1 13.4 13.5 13.2 12.9 12.9 13.0 13.1 13.1 12.3 12.7 13.3 20.1 17.6 15.1 12 11.2 11.5 11.1 10.9 11.4 11.3 11.5 11.6 11.4 11.0 11.1 11.1 11.3 11.2 10.6 11.0 11.3 19.5 17.0 14.6 13 9.7 9.9 9.5 9.6 9.9 9.8 10.0 9.9 9.8 9.7 9.8 9.8 9.9 9.8 9.3 9.7 10.1 18.9 16.5 14.2 14 8.8 8.9 8.8 8.3 9.1 9.0 9.1 9.2 8.9 8.6 8.6 8.8 8.9 8.9 8.6 8.4 8.9 18.4 16.1 13.8 15 7.8 7.9 8.1 8.6 8.3 8.3 8.1 8.0 8.0 7.6 8.0 8.2 8.4 8.2 7.8 8.3 8.4 18.0 15.7 13.5 16 8.1 8.4 7.5 9.1 9.0 9.0 9.0 8.7 7.9 8.2 8.8 9.2 9.4 9.2 8.2 9.3 9.7 17.6 15.4 13.2 17 8.9 8.8 8.6 10.0 10.0 9.9 9.9 9.9 9.0 8.9 9.3 9.9 10.3 10.5 10.1 9.9 10.0 17.3 15.1 13.0 18 10.5 10.5 10.5 11.9 11.2 11.0 11.0 10.8 10.1 9.9 10.6 11.4 12.0 12.2 11.7 11.7 11.6 17.0 14.9 12.7 19 12.1 12.4 11.4 11.7 12.3 12.0 12.9 12.6 12.0 11.3 11.9 12.5 13.1 13.1 11.9 13.0 12.9 16.7 14.6 12.5 20 13.3 14.0 11.9 15.1 15.0 14.9 15.0 14.7 11.8 12.2 14.0 14.8 14.9 14.1 12.0 15.0 14.9 16.5 14.4 12.4 21 13.1 13.8 11.8 - 14.5 14.5 14.6 14.2 13.2 13.7 14.3 14.4 14.4 13.7 11.9 14.6 14.5 16.3 14.2 12.2 22 - - - - - - - - 11.5 - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-13 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Man Man Man Man Man Man Man Man A B C [m/s] _18 _19 _20 _21 _22 _23 _24 _25 3 33.2 33.8 34.4 34.5 33.1 33.3 33.9 34.1 41.9 36.6 31.4 4 27.9 28.5 29.3 29.2 27.7 27.8 28.7 29.0 34.4 30.1 25.8 5 24.0 24.9 25.7 25.6 23.8 24.1 25.0 25.5 29.9 26.2 22.4 6 21.8 22.4 23.3 23.3 21.6 21.6 22.6 23.0 26.9 23.6 20.2 7 19.7 20.0 21.2 21.1 19.6 19.3 20.4 20.8 24.8 21.7 18.6 8 18.2 18.3 19.5 19.5 18.1 17.7 18.8 19.3 23.2 20.3 17.4 9 16.4 16.3 17.6 17.5 16.4 15.7 16.9 17.3 22.0 19.2 16.5 10 14.3 14.3 15.4 15.3 14.3 13.8 14.8 15.3 21.0 18.3 15.7 11 12.5 12.4 13.2 13.2 12.3 12.1 12.7 13.0 20.1 17.6 15.1 12 10.7 10.5 11.2 11.3 10.6 10.3 10.8 11.1 19.5 17.0 14.6 13 9.4 9.2 9.8 9.9 9.3 9.1 9.4 9.6 18.9 16.5 14.2 14 8.8 8.0 8.7 8.9 8.6 8.2 8.5 8.6 18.4 16.1 13.8 15 7.7 7.8 7.7 7.9 7.8 7.9 8.0 7.8 18.0 15.7 13.5 16 8.3 8.3 8.3 8.7 8.4 8.6 8.2 8.2 17.6 15.4 13.2 17 9.6 9.2 9.2 9.7 10.1 9.9 9.7 9.0 17.3 15.1 13.0 18 10.6 10.9 10.6 11.1 11.6 12.2 11.8 10.9 17.0 14.9 12.7 19 11.5 12.0 12.3 12.8 11.7 13.2 12.3 12.1 16.7 14.6 12.5 20 12.2 13.4 13.7 14.2 12.1 13.5 12.9 13.3 16.5 14.4 12.4 21 12.1 13.1 13.5 14.0 12.0 13.2 12.6 13.0 16.3 14.2 12.2 22 - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-14 www.dnvgl.com Table G-8 Predicted profiles of design equivalent turbulence intensity at the Malawi site for a Generic 4 MW wind turbine at a hub height of 130 m Hub IEC 61400-1 Ed3 Design equivalent turbulence intensity for individual turbine [%] height Turbine Subclass wind speed Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ A B C [m/s] 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 3 33.7 33.9 33.8 33.9 34.5 34.8 34.8 34.1 34.0 34.3 34.7 34.0 34.1 34.8 34.2 33.6 33.9 41.9 36.6 31.4 4 27.7 28.1 28.1 28.1 29.0 29.2 29.0 28.3 28.2 28.4 28.9 28.3 28.2 29.0 28.6 27.9 28.1 34.4 30.1 25.8 5 23.7 24.1 24.2 24.2 25.4 25.3 25.0 24.4 24.2 24.4 24.9 24.4 24.2 25.1 24.7 23.9 24.0 29.9 26.2 22.4 6 20.9 21.3 21.7 21.4 22.9 22.6 22.2 21.7 21.3 21.6 22.2 21.6 21.5 22.4 22.0 21.3 21.1 26.9 23.6 20.2 7 18.8 19.3 20.1 19.6 21.3 20.7 19.9 19.8 19.1 19.4 20.2 19.9 19.3 20.5 20.3 19.6 19.0 24.8 21.7 18.6 8 16.7 17.3 18.5 17.7 19.8 18.9 17.7 18.0 16.9 17.4 18.3 18.0 17.4 18.6 18.4 17.9 16.8 23.2 20.3 17.4 9 14.9 15.6 17.1 16.1 18.3 17.4 15.7 16.3 15.1 15.5 16.6 16.4 15.5 16.8 16.8 16.5 15.0 22.0 19.2 16.5 10 13.0 13.7 15.3 14.3 16.4 15.5 13.6 14.4 13.0 13.5 14.5 14.4 13.6 14.8 14.8 14.6 13.0 21.0 18.3 15.7 11 11.2 11.8 13.4 12.4 14.6 13.7 11.6 12.4 11.3 11.4 12.3 12.2 11.5 12.5 12.6 12.7 11.3 20.1 17.6 15.1 12 9.4 10.0 11.3 10.4 12.9 12.1 9.9 10.7 9.2 9.7 10.7 10.6 9.9 11.0 11.0 10.5 9.2 19.5 17.0 14.6 13 7.9 8.6 9.7 9.0 11.5 10.8 8.7 9.5 8.0 8.4 9.4 9.4 8.5 9.7 9.7 9.0 7.9 18.9 16.5 14.2 14 6.9 7.4 8.2 7.8 10.3 9.6 7.8 8.1 7.0 7.5 8.0 7.6 7.6 8.2 8.0 7.6 6.8 18.4 16.1 13.8 15 6.9 6.8 7.5 7.3 9.5 9.0 7.3 6.6 6.1 7.1 7.3 6.2 7.1 7.5 6.4 7.1 6.0 18.0 15.7 13.5 16 9.2 8.8 8.6 8.9 10.2 9.7 8.8 7.8 8.5 8.7 9.0 8.3 8.4 8.7 8.1 9.1 8.1 17.6 15.4 13.2 17 11.4 11.4 11.6 11.9 12.2 12.1 11.4 11.2 12.0 11.6 11.5 11.7 10.8 11.3 11.6 12.4 11.6 17.3 15.1 13.0 18 12.8 12.7 12.6 12.9 13.6 13.1 12.8 12.6 12.8 12.6 12.9 12.7 12.5 12.5 12.6 13.0 12.7 17.0 14.9 12.7 19 13.3 13.1 13.1 13.1 12.8 12.7 13.9 12.7 12.8 13.9 14.1 12.7 14.1 14.3 12.7 13.2 12.8 16.7 14.6 12.5 20 - 13.1 13.0 12.5 12.5 12.4 12.4 12.4 12.5 13.7 12.4 12.4 13.1 13.7 12.4 13.0 12.5 16.5 14.4 12.4 21 - - - - - - - - - - - - - - - - - 16.3 14.2 12.2 22 - - - - - - - - - - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - - - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - - - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - - - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass B limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-15 www.dnvgl.com Hub Design equivalent turbulence intensity for IEC 61400-1 Ed3 height individual turbine [%] Turbine Subclass wind speed Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ Mal_ A B C [m/s] 18 19 20 21 22 23 24 25 3 34.3 35.1 34.0 34.4 34.9 33.9 34.0 33.9 41.9 36.6 31.4 4 28.5 29.4 28.8 28.7 29.3 28.0 28.2 28.4 34.4 30.1 25.8 5 24.6 25.5 25.2 24.7 25.8 24.0 24.2 24.6 29.9 26.2 22.4 6 21.9 22.8 23.0 21.9 23.3 21.2 21.5 22.3 26.9 23.6 20.2 7 19.7 21.0 21.6 19.7 21.7 19.0 19.6 20.9 24.8 21.7 18.6 8 17.8 19.2 20.5 17.5 20.1 16.9 17.7 19.6 23.2 20.3 17.4 9 15.8 17.5 19.2 15.5 18.6 15.1 16.1 18.3 22.0 19.2 16.5 10 13.9 15.4 17.6 13.4 16.7 13.1 14.1 16.5 21.0 18.3 15.7 11 11.7 13.0 15.7 11.7 14.8 11.2 12.3 14.6 20.1 17.6 15.1 12 10.2 11.5 13.6 9.8 13.0 9.1 10.2 12.4 19.5 17.0 14.6 13 8.8 10.3 12.1 8.7 11.6 7.8 8.8 10.8 18.9 16.5 14.2 14 8.0 8.7 10.7 7.7 10.3 6.5 7.5 9.2 18.4 16.1 13.8 15 7.6 7.7 9.7 6.7 9.8 6.1 7.0 8.6 18.0 15.7 13.5 16 8.8 9.3 10.4 8.4 10.6 8.9 9.0 9.9 17.6 15.4 13.2 17 10.9 12.2 12.9 11.8 13.1 12.4 12.3 12.9 17.3 15.1 13.0 18 12.5 12.7 13.5 12.8 13.7 12.8 12.9 13.2 17.0 14.9 12.7 19 14.5 14.3 13.2 12.6 12.7 13.1 13.3 13.3 16.7 14.6 12.5 20 13.5 14.0 13.0 12.4 12.5 12.5 13.4 12.6 16.5 14.4 12.4 21 - - 11.9 - - - - - 16.3 14.2 12.2 22 - - - - - - - - 16.1 14.1 12.1 23 - - - - - - - - 15.9 13.9 11.9 24 - - - - - - - - 15.7 13.8 11.8 25 - - - - - - - - 15.6 13.6 11.7 Note: The wind speed range corresponding to 0.2Vref to 0.4Vref, for IEC Class II is shown in bold font. Turbulence intensities that exceed subclass A limits within 0.2Vref to 0.4Vref are shown in red font. DNV GL – Document No.: 10003564-HOU-R-01, Issue: C Page G-16 www.dnvgl.com DNV GL Driven by our purpose of safeguarding life, property and the environment, DNV GL enables organizations to advance the safety and sustainability of their business. We provide classification and technical assurance along with software and independent expert advisory services to the maritime, oil and gas, and energy industries. We also provide certification services to customers across a wide range of industries. Operating in more than 100 countries, our 16,000 professionals are dedicated to helping our customers make the world safer, smarter, and greener.