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Optimal Micro-Siting of Weathervaning Floating Wind Turbines

Author

Listed:
  • Javier Serrano González

    (Department of Electrical Engineering, University of Seville, 41092 Seville, Spain)

  • Manuel Burgos Payán

    (Department of Electrical Engineering, University of Seville, 41092 Seville, Spain)

  • Jesús Manuel Riquelme Santos

    (Department of Electrical Engineering, University of Seville, 41092 Seville, Spain)

  • Ángel Gaspar González Rodríguez

    (Department of Electronic Engineering, Telecommunications and Automation, University of Jaen, 23071 Jaen, Spain)

Abstract

This paper presents a novel tool for optimizing floating offshore wind farms based on weathervaning turbines. This solution is grounded on the ability of the assembly (wind turbine plus floater) to self-orientate into the wind direction, as this concept is allowed to freely pivot on a single point. This is a passive yaw potential solution for floating wind farms currently in the demonstration phase. A genetic algorithm is proposed for optimizing the levelised cost of energy by determining the geographical coordinates of the pivot points (i.e., the position over which the assembly can rotate to self-orient to the incoming wind direction). A tailored evaluation module is proposed to take into account the weathervaning motion around the pivot point depending on the incoming wind direction. The results obtained show the suitability of the proposed method to solve the addressed problem under realistic conditions. Additionally, the influence of the feasible region defined by the plot and the maximum area occupied on floating offshore wind farm design are also analysed in the proposed test cases. These deployable area constraints are of great importance for the viability of this technology, as it requires more space than classical solutions anchored to a fixed point.

Suggested Citation

  • Javier Serrano González & Manuel Burgos Payán & Jesús Manuel Riquelme Santos & Ángel Gaspar González Rodríguez, 2021. "Optimal Micro-Siting of Weathervaning Floating Wind Turbines," Energies, MDPI, vol. 14(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:886-:d:495806
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    References listed on IDEAS

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    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. Nouri, Reza & Vasel-Be-Hagh, Ahmad & Archer, Cristina L., 2020. "The Coriolis force and the direction of rotation of the blades significantly affect the wake of wind turbines," Applied Energy, Elsevier, vol. 277(C).
    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. Kausche, Michael & Adam, Frank & Dahlhaus, Frank & Großmann, Jochen, 2018. "Floating offshore wind - Economic and ecological challenges of a TLP solution," Renewable Energy, Elsevier, vol. 126(C), pages 270-280.
    5. Clark, Caitlyn E. & Miller, Annalise & DuPont, Bryony, 2019. "An analytical cost model for co-located floating wind-wave energy arrays," Renewable Energy, Elsevier, vol. 132(C), pages 885-897.
    6. 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.
    7. Myhr, Anders & Bjerkseter, Catho & Ågotnes, Anders & Nygaard, Tor A., 2014. "Levelised cost of energy for offshore floating wind turbines in a life cycle perspective," Renewable Energy, Elsevier, vol. 66(C), pages 714-728.
    8. 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.
    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. 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.
    11. Horn, Jan-Tore & Leira, Bernt J., 2019. "Fatigue reliability assessment of offshore wind turbines with stochastic availability," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    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. Sun, Haiying & Yang, Hongxing & Gao, Xiaoxia, 2019. "Investigation into spacing restriction and layout optimization of wind farm with multiple types of wind turbines," Energy, Elsevier, vol. 168(C), pages 637-650.
    15. Castro-Santos, Laura & Filgueira-Vizoso, Almudena & Carral-Couce, Luis & Formoso, José Ángel Fraguela, 2016. "Economic feasibility of floating offshore wind farms," Energy, Elsevier, vol. 112(C), pages 868-882.
    16. 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.
    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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