Optimizing Turbine Siting and Wind Farm Layout in Indonesia
Abstract
Wind resource assessments are required to identify a specific area capable of producing valuable energy from wind speeds. This paper aims to optimize wind assessment through wind farm siting and layout in Indonesia’s semi-arid region. Wind data collected on Sumba Island over a one-year period was analyzed to assess the area's wind energy potential. Wind Atlas Analysis and Application Programme (WAsP) and Windographer were used to generate a generalized wind climate and resource maps for the area. Wind farm layout and preliminary turbine micro-sitting were completed with various scenarios in mind to achieve the best possible result. Four different scenarios are considered to maximize power output. There are 34 identical wind turbines with a unit capacity of 90 kW in Scenario 1. Scenario 2 includes 20 identical wind turbines with a total capacity of 3000 kW. In Scenario 3, 14 identical wind turbines with 225 kW of unit capacity are used. There are 12 identical wind turbines with a unit capacity of 250 kW in Scenario 4. The results showed that scenario 1 produced the highest total net Annual Energy Production (AEP) of 11,287 MWh/year with a 3.73 % wake loss. The minimum wake loss seemed to be 2.62 % in scenario 4, with a total net AEP of 10,22MWh/year.
Keywords
Full Text:
PDFReferences
Saeed MA, Ahmed Z, Hussain S, Zhang W. Wind resource assessment and economic analysis for wind energy development in Pakistan. Sustain Energy Technol Assessments 2021;44:101068. https://doi.org/10.1016/j.seta.2021.101068.
Tang XY, Zhao S, Fan B, Peinke J, Stoevesandt B. Micro-scale wind resource assessment in complex terrain based on CFD coupled measurement from multiple masts. Appl Energy 2019;238:806–15. https://doi.org/10.1016/j.apenergy.2019.01.129.
Jung C, Schindler D. Introducing a new approach for wind energy potential assessment under climate change at the wind turbine scale. Energy Convers Manag 2020;225:113425. https://doi.org/10.1016/j.enconman.2020.113425.
Hesty NW, Cendrawati DG, Nepal R, Al Irsyad MI. Wind Energy Potential Assessment Based-on WRF Four-Dimensional Data Assimilation System and Cross-Calibrated Multi-Platform Dataset. IOP Conf Ser Earth Environ Sci 2021;897:0–7. https://doi.org/10.1088/1755-1315/897/1/012004.
Pranoto B, Soekarno H, Cendrawati DG, Akrom IF, Irsyad MIA, Hesty NW, et al. Indonesian hydro energy potential map with run-off river system. IOP Conf Ser Earth Environ Sci 2021;926. https://doi.org/10.1088/1755-1315/926/1/012003.
Nurliyanti V, Ahadi K, Muttaqin R, Pranoto B, Srikandi GP, Al Irsyad MI. Fostering Rooftop Solar PV Investments Toward Smart Cities through e-SMART PV. 5th Int Conf Smart Grid Smart Cities, ICSGSC 2021 2021:146–50. https://doi.org/10.1109/ICSGSC52434.2021.9490406.
Winrock International. Fuel Indenpendent Renewable Energy “ Iconic Island ” Preliminary Resource Assessment Sumba & Buru Islands - Indonesia. 2010.
Pramuwardani I, Hartono, Sunarto, Sopaheluwakan A. Indonesian rainfall variability during Western North Pacific and Australian monsoon phase related to convectively coupled equatorial waves. Arab J Geosci 2018;11. https://doi.org/10.1007/s12517-018-4003-7.
Alifdini I, Shimada T, Wirasatriya A. Seasonal distribution and variability of surface winds in the Indonesian seas using scatterometer and reanalysis data. Int J Climatol 2021;41:4825–43. https://doi.org/10.1002/joc.7101.
Fisher R, Bobanuba WE, Rawambaku A, Hill GJE, Russell-Smith J. Remote sensing of fire regimes in semi-arid Nusa Tenggara Timur, eastern Indonesia: Current patterns, future prospects. Int J Wildl Fire 2006;15:307–17. https://doi.org/10.1071/WF05083.
Yulianto B, Maarif S, Wijaya C, Hardjomidjojo H. Energy Security Scenario based on Renewable Resources: A Case Study of East Sumba, East Nusa Tenggara, Indonesia. Bisnis Birokrasi J 2019;26. https://doi.org/10.20476/jbb.v26i1.10170.
Brower MC, Bailey BH, Beaucage P, Bernadett DW, Doane J, Eberhard MJ, et al. Wind Resource Assessment: A Practical Guide to Developing a Wind Project. Wind Resour Assess A Pract Guid to Dev a Wind Proj 2012. https://doi.org/10.1002/9781118249864.
Mathew S. Wind Energy Fundamentals, Resource Analysis and Economics. Wind Energy 2006:1–252.
J. F. Manwell, McGowan JG, Rogers AL. Wind Energy Explained: Theory, Design and Application, Second Edition. 2009.
Djamai M, Kasbadji Merzouk N. Wind farm feasibility study and site selection in Adrar, Algeria. Energy Procedia 2011;6:136–42. https://doi.org/10.1016/j.egypro.2011.05.016.
Flay RGJ, King AB, Revell M, Carpenter P, Turner R, Cenek P, et al. Wind speed measurements and predictions over Belmont Hill, Wellington, New Zealand. J Wind Eng Ind Aerodyn 2019;195:104018. https://doi.org/10.1016/j.jweia.2019.104018.
Yilmaz U, Balo F, Sua LS. Simulation Framework for Wind Energy Attributes with WAsP. Procedia Comput Sci 2019;158:458–65. https://doi.org/10.1016/j.procs.2019.09.076.
Ratjiranukool P, Ratjiranukool S. Evaluating Wind Speed by WRF Model over Northern Thailand. Energy Procedia 2017;138:1171–6. https://doi.org/10.1016/j.egypro.2017.10.228.
Mahmood FH, Resen AK, Khamees AB. Wind characteristic analysis based on Weibull distribution of Al-Salman site, Iraq. Energy Reports 2020;6:79–87. https://doi.org/10.1016/j.egyr.2019.10.021.
Azlan F, Kurnia JC, Tan BT, Ismadi MZ. Review on optimisation methods of wind farm array under three classical wind condition problems. Renew Sustain Energy Rev 2021;135:110047. https://doi.org/10.1016/j.rser.2020.110047.
Ramadan HS. Wind energy farm sizing and resource assessment for optimal energy yield in Sinai Peninsula, Egypt. J Clean Prod 2017;161:1283–93. https://doi.org/10.1016/j.jclepro.2017.01.120.
Romanic D, Parvu D, Refan M, Hangan H. Wind and tornado climatologies and wind resource modelling for a modern development situated in “Tornado Alley.” Renew Energy 2018;115:97–112. https://doi.org/10.1016/j.renene.2017.08.026.
Tiam Kapen P, Jeutho Gouajio M, Yemélé D. Analysis and efficient comparison of ten numerical methods in estimating Weibull parameters for wind energy potential: Application to the city of Bafoussam, Cameroon. Renew Energy 2020;159:1188–98. https://doi.org/10.1016/j.renene.2020.05.185.
Ali M Bin, Ahmad Z, Alshahrani S, Younis MR, Talib I, Imran M. A Case Study: Layout Optimization of Three Gorges Wind Farm Pakistan, Using Genetic Algorithm. Sustain 2022;14. https://doi.org/10.3390/su142416960.
Builtjes PJH, Smit. J. Calculation of Wake Effects in Wind Turbine Parks. Wind Eng 1978;2:135–45.
DOI (PDF): https://doi.org/10.20508/ijrer.v13i3.14070.g8806
Refbacks
- There are currently no refbacks.
Online ISSN: 1309-0127
Publisher: Gazi University
IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);
IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.
WEB of SCIENCE in 2025;
h=35,
Average citation per item=6.59
Last three Years Impact Factor=(1947+1753+1586)/(146+201+78)=5286/425=12.43
Category Quartile:Q4