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Topology optimization of wind farm layouts

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  • Pollini, Nicolò

Abstract

A novel approach for the solution of the wind farm layout optimization problem is presented. The annual energy production is maximized with constraints on the minimum and maximum number of wind turbines placed, and on the minimum spacing between the wind turbines. The proposed approach relies on a density-based topology optimization method, where continuous density variables varying between zero and one are assigned to each potential wind turbine location. A wind turbine exists if its associated variable equals one, otherwise it does not exist if the associated variable is zero. Intermediate values of the density variables are penalized with interpolation schemes traditionally used in the context of multi-material structural topology optimization. The penalized intermediate values of the design variables become uneconomical and the optimization algorithm is implicitly pushed towards a preference of crisp 0–1 final values. The optimization problem is solved with a gradient-based algorithm based on first-order information. Because of the proposed problem formulation, the functions involved are formulated explicitly in terms of the design variables and their analytical gradients can be calculated directly. The numerical results highlight the capability of the proposed approach in finding optimized wind farm layouts with small computational resources and time.

Suggested Citation

  • Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
  • Handle: RePEc:eee:renene:v:195:y:2022:i:c:p:1015-1027
    DOI: 10.1016/j.renene.2022.06.019
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    1. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Wu, Yuan-Kang, 2016. "Wake effect modeling: A review of wind farm layout optimization using Jensen׳s model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1048-1059.
    2. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    3. Khan, Salman A. & Rehman, Shafiqur, 2013. "Iterative non-deterministic algorithms in on-shore wind farm design: A brief survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 370-384.
    4. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
    5. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    6. Zergane, Saïd & Smaili, Arezki & Masson, Christian, 2018. "Optimization of wind turbine placement in a wind farm using a new pseudo-random number generation method," Renewable Energy, Elsevier, vol. 125(C), pages 166-171.
    7. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    8. Martina Fischetti & Michele Monaci, 2016. "Proximity search heuristics for wind farm optimal layout," Journal of Heuristics, Springer, vol. 22(4), pages 459-474, August.
    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. 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.
    11. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    12. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, vol. 7(11), pages 1-87, October.
    13. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
    14. Reddy, Sohail R., 2020. "Wind Farm Layout Optimization (WindFLO) : An advanced framework for fast wind farm analysis and optimization," Applied Energy, Elsevier, vol. 269(C).
    15. Feng, Ju & Shen, Wen Zhong, 2015. "Solving the wind farm layout optimization problem using random search algorithm," Renewable Energy, Elsevier, vol. 78(C), pages 182-192.
    16. Mytilinou, Varvara & Kolios, Athanasios J., 2019. "Techno-economic optimisation of offshore wind farms based on life cycle cost analysis on the UK," Renewable Energy, Elsevier, vol. 132(C), pages 439-454.
    17. Salcedo-Sanz, S. & Gallo-Marazuela, D. & Pastor-Sánchez, A. & Carro-Calvo, L. & Portilla-Figueras, A. & Prieto, L., 2014. "Offshore wind farm design with the Coral Reefs Optimization algorithm," Renewable Energy, Elsevier, vol. 63(C), pages 109-115.
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