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A comparison of optimizers in a unified standard for optimization on wind farm layout optimization

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  • Croonenbroeck, Carsten
  • Hennecke, David

Abstract

Wind Farm Layout Optimization (WFLO) is a vivid field of research dealing with the difficult problem of optimally arranging a given number of wind turbines inside a local area (wind farm). There are several types of objective functions, varying optimization strategies, different sets of underlying data, assumptions and simplifications to the problem, among other issues making fair comparisons of problem solving techniques challenging. We discuss a new unified framework that provides highly accurate data, a modular approach to economically driven objective functions, and a unified and fair benchmark for mathematical optimizers that are easily plugged into that framework. Finally, we provide an exemplary work flow and use it to show a comparison study of optimizing techniques within the framework, focussing on types of optimizers frequently used in this field.

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  • Croonenbroeck, Carsten & Hennecke, David, 2021. "A comparison of optimizers in a unified standard for optimization on wind farm layout optimization," Energy, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:energy:v:216:y:2021:i:c:s0360544220323513
    DOI: 10.1016/j.energy.2020.119244
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    1. 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.
    2. 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.
    3. 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.
    4. Abdulrahman, Mamdouh & Wood, David, 2017. "Investigating the Power-COE trade-off for wind farm layout optimization considering commercial turbine selection and hub height variation," Renewable Energy, Elsevier, vol. 102(PB), pages 267-278.
    5. Jan Stede & Nils May, 2020. "Way Off: The Effect of Minimum Distance Regulation on the Deployment of Wind Power," Discussion Papers of DIW Berlin 1867, DIW Berlin, German Institute for Economic Research.
    6. 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.
    7. 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.
    8. Croonenbroeck, Carsten & Hennecke, David, 2020. "Does the German renewable energy act provide a fair incentive system for onshore wind power? — A simulation analysis," Energy Policy, Elsevier, vol. 144(C).
    9. Hou, Peng & Hu, Weihao & Soltani, Mohsen & Chen, Cong & Chen, Zhe, 2017. "Combined optimization for offshore wind turbine micro siting," Applied Energy, Elsevier, vol. 189(C), pages 271-282.
    10. 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.
    11. Turner, S.D.O. & Romero, D.A. & Zhang, P.Y. & Amon, C.H. & Chan, T.C.Y., 2014. "A new mathematical programming approach to optimize wind farm layouts," Renewable Energy, Elsevier, vol. 63(C), pages 674-680.
    12. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2020. "Optimal design of wind farms in complex terrains using computational fluid dynamics and adjoint methods," Applied Energy, Elsevier, vol. 261(C).
    13. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
    14. Mebane Jr., Walter R. & Sekhon, Jasjeet S., 2011. "Genetic Optimization Using Derivatives: The rgenoud Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i11).
    15. P. Kaelo & M. M. Ali, 2006. "Some Variants of the Controlled Random Search Algorithm for Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 130(2), pages 253-264, August.
    16. 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.
    17. Guirguis, David & Romero, David A. & Amon, Cristina H., 2016. "Toward efficient optimization of wind farm layouts: Utilizing exact gradient information," Applied Energy, Elsevier, vol. 179(C), pages 110-123.
    18. Song, Zhe & Zhang, Zijun & Chen, Xingying, 2016. "The decision model of 3-dimensional wind farm layout design," Renewable Energy, Elsevier, vol. 85(C), pages 248-258.
    19. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2018. "Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model," Energies, MDPI, vol. 11(12), pages 1-26, November.
    20. Salomon, Hannes & Drechsler, Martin & Reutter, Felix, 2020. "Minimum distances for wind turbines: A robustness analysis of policies for a sustainable wind power deployment," Energy Policy, Elsevier, vol. 140(C).
    21. 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.
    22. Kuo, Jim Y.J. & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2016. "Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming," Applied Energy, Elsevier, vol. 178(C), pages 404-414.
    23. Serrano González, Javier & Burgos Payán, Manuel & Santos, Jesús Manuel Riquelme & González-Longatt, Francisco, 2014. "A review and recent developments in the optimal wind-turbine micro-siting problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 133-144.
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    Cited by:

    1. Zhichang Liang & Haixiao Liu, 2023. "Layout Optimization Algorithms for the Offshore Wind Farm with Different Densities Using a Full-Field Wake Model," Energies, MDPI, vol. 16(16), pages 1-15, August.
    2. Masoudi, Seiied Mohsen & Baneshi, Mehdi, 2022. "Layout optimization of a wind farm considering grids of various resolutions, wake effect, and realistic wind speed and wind direction data: A techno-economic assessment," Energy, Elsevier, vol. 244(PB).

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    More about this item

    Keywords

    Wind energy; WFLO; Wind farm layout optimization; Optimization; NP-Hard; R package; Wake models; Open data; Genetic algorithm; Benchmark;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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