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A design methodology for wind farm layout considering cable routing and economic benefit based on genetic algorithm and GeoSteiner

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  • Wu, Yan
  • Zhang, Shuai
  • Wang, Ruiqi
  • Wang, Yufei
  • Feng, Xiao

Abstract

Wind farm designing is a crucial stage to realize the application of wind energy. This work studies the problem of wind farm layout optimization (WFLO). A new method based on power production, wind distribution, wake loss is proposed to optimize the layout of wind farm. Genetic algorithm (GA) is utilized to optimize the locations of wind turbine in the wind farm. GeoSteiner algorithm is used to optimize the layouts of cable which has important influence on power transmission. The objective function is annual economic benefit (AEB) including annual production benefit (APB) and the costs of energy, cable and land. In the case study, the wind farm size is 3850 m × 3850 m. The number of wind turbines (WTs) of the cases changes from 2 to 58. The capacity achieves 87 MW when the number of WTs is 58. The result shows that the case considering all factors mentioned above has the highest AEB with 1.87 × 109 ¥ per year. There is a 27.01% increase compared with the original case with APB as objective function. Specifically, the investment of cable is 3.68 × 106 ¥ comparing with 4.06 × 106 ¥ of the case only considering APB.

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  • Wu, Yan & Zhang, Shuai & Wang, Ruiqi & Wang, Yufei & Feng, Xiao, 2020. "A design methodology for wind farm layout considering cable routing and economic benefit based on genetic algorithm and GeoSteiner," Renewable Energy, Elsevier, vol. 146(C), pages 687-698.
    • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:687-698
    DOI: 10.1016/j.renene.2019.07.002
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    1. Wędzik, Andrzej & Siewierski, Tomasz & Szypowski, Michał, 2016. "A new method for simultaneous optimizing of wind farm’s network layout and cable cross-sections by MILP optimization," Applied Energy, Elsevier, vol. 182(C), pages 525-538.
    2. Wang, Longyan & Tan, Andy C.C. & Gu, Yuantong & Yuan, Jianping, 2015. "A new constraint handling method for wind farm layout optimization with lands owned by different owners," Renewable Energy, Elsevier, vol. 83(C), pages 151-161.
    3. Bansal, Jagdish Chand & Farswan, Pushpa, 2017. "Wind farm layout using biogeography based optimization," Renewable Energy, Elsevier, vol. 107(C), pages 386-402.
    4. Seo, Seokho & Oh, Si-Doek & Kwak, Ho-Young, 2019. "Wind turbine power curve modeling using maximum likelihood estimation method," Renewable Energy, Elsevier, vol. 136(C), pages 1164-1169.
    5. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Rasheed, Nadia, 2016. "Wind farm layout optimization using area dimensions and definite point selection techniques," Renewable Energy, Elsevier, vol. 88(C), pages 154-163.
    6. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2019. "Improving CFD wind farm simulations incorporating wind direction uncertainty," Renewable Energy, Elsevier, vol. 133(C), pages 1011-1023.
    7. Wang, Longyan & Tan, Andy C.C. & Cholette, Michael E. & Gu, Yuantong, 2017. "Optimization of wind farm layout with complex land divisions," Renewable Energy, Elsevier, vol. 105(C), pages 30-40.
    8. Cheng, Yu & Zhang, Mingming & Zhang, Ziliang & Xu, Jianzhong, 2019. "A new analytical model for wind turbine wakes based on Monin-Obukhov similarity theory," Applied Energy, Elsevier, vol. 239(C), pages 96-106.
    9. Grady, S.A. & Hussaini, M.Y. & Abdullah, M.M., 2005. "Placement of wind turbines using genetic algorithms," Renewable Energy, Elsevier, vol. 30(2), pages 259-270.
    10. Wilson, Dennis & Rodrigues, Silvio & Segura, Carlos & Loshchilov, Ilya & Hutter, Frank & Buenfil, Guillermo López & Kheiri, Ahmed & Keedwell, Ed & Ocampo-Pineda, Mario & Özcan, Ender & Peña, Sergio Iv, 2018. "Evolutionary computation for wind farm layout optimization," Renewable Energy, Elsevier, vol. 126(C), pages 681-691.
    11. Gentils, Theo & Wang, Lin & Kolios, Athanasios, 2017. "Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm," Applied Energy, Elsevier, vol. 199(C), pages 187-204.
    12. Archer, Cristina L. & Vasel-Be-Hagh, Ahmadreza & Yan, Chi & Wu, Sicheng & Pan, Yang & Brodie, Joseph F. & Maguire, A. Eoghan, 2018. "Review and evaluation of wake loss models for wind energy applications," Applied Energy, Elsevier, vol. 226(C), pages 1187-1207.
    13. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    14. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2017. "Wind farm layout optimization using a Gaussian-based wake model," Renewable Energy, Elsevier, vol. 107(C), pages 531-541.
    15. Arteaga-López, Ernesto & Ángeles-Camacho, Cesar & Bañuelos-Ruedas, Francisco, 2019. "Advanced methodology for feasibility studies on building-mounted wind turbines installation in urban environment: Applying CFD analysis," Energy, Elsevier, vol. 167(C), pages 181-188.
    16. Li, Wenwen & Özcan, Ender & John, Robert, 2017. "Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation," Renewable Energy, Elsevier, vol. 105(C), pages 473-482.
    17. Sun, Haiying & Yang, Hongxing, 2018. "Study on an innovative three-dimensional wind turbine wake model," Applied Energy, Elsevier, vol. 226(C), pages 483-493.
    18. Abdelsalam, Ali M. & El-Shorbagy, M.A., 2018. "Optimization of wind turbines siting in a wind farm using genetic algorithm based local search," Renewable Energy, Elsevier, vol. 123(C), pages 748-755.
    19. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.
    20. Xu Luo & Yongmin Yang & Zhexue Ge & Xisen Wen & Fengjiao Guan, 2015. "Maintainability-based facility layout optimum design of ship cabin," International Journal of Production Research, Taylor & Francis Journals, vol. 53(3), pages 677-694, February.
    21. Ulku, I. & Alabas-Uslu, C., 2019. "A new mathematical programming approach to wind farm layout problem under multiple wake effects," Renewable Energy, Elsevier, vol. 136(C), pages 1190-1201.
    22. Ju, Xinglong & Liu, Feng, 2019. "Wind farm layout optimization using self-informed genetic algorithm with information guided exploitation," Applied Energy, Elsevier, vol. 248(C), pages 429-445.
    23. Katzenstein, Warren & Apt, Jay, 2012. "The cost of wind power variability," Energy Policy, Elsevier, vol. 51(C), pages 233-243.
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