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Optimal design of neighbouring offshore wind farms: A co-evolutionary approach

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  • Serrano González, Javier
  • Burgos Payán, Manuel
  • Riquelme Santos, Jesús Manuel

Abstract

This paper presents a new approach for the optimization of neighbouring offshore wind farms. Offshore wind energy is one of the most promising and developed low-carbon generation technologies. However, the high capital costs, which are strongly dependent on seabed depth, currently limit the geographical expansion of this technology to areas with relatively shallow waters and appropriate wind resource. This, along with the advantages of sharing a submarine transmission system among several projects, leads to a high concentration of offshore wind farms in certain zones, as happens, for example, in the North Sea. The presence of other neighbouring offshore wind farms has to be taken into account when a developer plans a new project, since the wake effect of wind turbines belonging to other neighbouring wind farms will affect the annual energy production and, consequently, the profitability of the project under study. However, not only already operating or installed neighbouring projects have to be borne in mind, but also the possible design of future neighbouring wind farms yet to be developed. In order to tackle this issue, an innovative co-evolutionary algorithm is proposed in this paper with the objective of determining a Nash equilibrium solution that would provide the best possible configuration of the wind farm under study by taking into account and limiting the disturbance introduced by other neighbouring projects. The performance of the proposed methodology has been successfully tested through the analysis of a realistic case and compared with other collaborative approaches and the classic single-project optimization methods already existing in the literature.

Suggested Citation

  • Serrano González, Javier & Burgos Payán, Manuel & Riquelme Santos, Jesús Manuel, 2018. "Optimal design of neighbouring offshore wind farms: A co-evolutionary approach," Applied Energy, Elsevier, vol. 209(C), pages 140-152.
    • Handle: RePEc:eee:appene:v:209:y:2018:i:c:p:140-152
    DOI: 10.1016/j.apenergy.2017.10.120
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    References listed on IDEAS

    as
    1. 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.
    2. Kelly,Anthony, 2003. "Decision Making Using Game Theory," Cambridge Books, Cambridge University Press, number 9780521814621, September.
    3. Wan, Chunqiu & Wang, Jun & Yang, Geng & Gu, Huajie & Zhang, Xing, 2012. "Wind farm micro-siting by Gaussian particle swarm optimization with local search strategy," Renewable Energy, Elsevier, vol. 48(C), pages 276-286.
    4. 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.
    5. González, J. Serrano & Rodríguez, Á.G. González & Mora, J. Castro & Burgos Payán, M. & Santos, J. Riquelme, 2011. "Overall design optimization of wind farms," Renewable Energy, Elsevier, vol. 36(7), pages 1973-1982.
    6. Park, Jinkyoo & Law, Kincho H., 2015. "Layout optimization for maximizing wind farm power production using sequential convex programming," Applied Energy, Elsevier, vol. 151(C), pages 320-334.
    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. González, Javier Serrano & Gonzalez Rodriguez, Angel G. & Mora, José Castro & Santos, Jesús Riquelme & Payan, Manuel Burgos, 2010. "Optimization of wind farm turbines layout using an evolutive algorithm," Renewable Energy, Elsevier, vol. 35(8), pages 1671-1681.
    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. Mittal, Prateek & Kulkarni, Kedar & Mitra, Kishalay, 2016. "A novel hybrid optimization methodology to optimize the total number and placement of wind turbines," Renewable Energy, Elsevier, vol. 86(C), pages 133-147.
    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. Silvio Rodrigues & Carlos Restrepo & George Katsouris & Rodrigo Teixeira Pinto & Maryam Soleimanzadeh & Peter Bosman & Pavol Bauer, 2016. "A Multi-Objective Optimization Framework for Offshore Wind Farm Layouts and Electric Infrastructures," Energies, MDPI, vol. 9(3), pages 1-42, March.
    14. 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.
    15. Song, Mengxuan & Wen, Yi & Duan, Bin & Wang, Jun & Gong, Qi, 2017. "Micro-siting optimization of a wind farm built in multiple phases," Energy, Elsevier, vol. 137(C), pages 95-103.
    16. Pérez, Beatriz & Mínguez, Roberto & Guanche, Raúl, 2013. "Offshore wind farm layout optimization using mathematical programming techniques," Renewable Energy, Elsevier, vol. 53(C), pages 389-399.
    17. Hou, Peng & Enevoldsen, Peter & Hu, Weihao & Chen, Cong & Chen, Zhe, 2017. "Offshore wind farm repowering optimization," Applied Energy, Elsevier, vol. 208(C), pages 834-844.
    18. Mayo, Michael & Daoud, Maisa, 2016. "Informed mutation of wind farm layouts to maximise energy harvest," Renewable Energy, Elsevier, vol. 89(C), pages 437-448.
    19. Serrano González, Javier & Trigo García, Ángel Luis & Burgos Payán, Manuel & Riquelme Santos, Jesús & González Rodríguez, Ángel Gaspar, 2017. "Optimal wind-turbine micro-siting of offshore wind farms: A grid-like layout approach," Applied Energy, Elsevier, vol. 200(C), pages 28-38.
    20. Rodrigues, S. & Bauer, P. & Bosman, Peter A.N., 2016. "Multi-objective optimization of wind farm layouts – Complexity, constraint handling and scalability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 587-609.
    21. Guirguis, David & Romero, David A. & Amon, Cristina H., 2017. "Gradient-based multidisciplinary design of wind farms with continuous-variable formulations," Applied Energy, Elsevier, vol. 197(C), pages 279-291.
    22. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Risk management of wind farm micro-siting using an enhanced genetic algorithm with simulation optimization," Renewable Energy, Elsevier, vol. 107(C), pages 508-521.
    23. Vasel-Be-Hagh, Ahmadreza & Archer, Cristina L., 2017. "Wind farm hub height optimization," Applied Energy, Elsevier, vol. 195(C), pages 905-921.
    24. 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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    6. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).

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