IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v314y2022ics0306261922002719.html
   My bibliography  Save this article

Multi-scale optimization of the design of offshore wind farms

Author

Listed:
  • Cazzaro, Davide
  • Trivella, Alessio
  • Corman, Francesco
  • Pisinger, David

Abstract

The traditional optimization of a wind farm layout consisted of arranging the wind turbines inside a designated area. In contrast, the 2021 tender from the UK government, Offshore Wind Leasing Round 4 (“UK Round-4”), and upcoming bids only specify large regions where the wind farm can be built. This leads to the new challenge of selecting the wind farm shape and area out of a larger region to maximize its profitability. We introduce this problem as the “wind farm area selection problem” and present a novel optimization framework to solve it efficiently. Specifically, our framework combines three scales of design: (i) on a macro-scale, choosing the approximate location of the wind farm out of larger regions, (ii) on a meso-scale, generating the optimal shape of the wind farm, and (iii) on a micro-scale, choosing the exact position of the turbines within the shape. In particular, we propose a new constructive heuristic to choose the best shape of a wind farm at the meso-scale, which is scarcely studied in the literature. Moreover, while macro and micro-scales have already been investigated, our framework is the first to integrate them. We perform a detailed computational analysis using real-life data and constraints from the recent UK Round-4 tender. Compared to the best rectangular-shaped wind farm at the same location, our results show that optimizing the shape increases profitability by 1.1% on average and up to 2.8%, corresponding to 46 and 109 million Euro respectively.

Suggested Citation

  • Cazzaro, Davide & Trivella, Alessio & Corman, Francesco & Pisinger, David, 2022. "Multi-scale optimization of the design of offshore wind farms," Applied Energy, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:appene:v:314:y:2022:i:c:s0306261922002719
    DOI: 10.1016/j.apenergy.2022.118830
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922002719
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.118830?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. van Haaren, Rob & Fthenakis, Vasilis, 2011. "GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(7), pages 3332-3340, September.
    4. Yin, Peng-Yeng & Wang, Tai-Yuan, 2012. "A GRASP-VNS algorithm for optimal wind-turbine placement in wind farms," Renewable Energy, Elsevier, vol. 48(C), pages 489-498.
    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. 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.
    7. 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.
    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. Kim, Taeyun & Park, Jeong-Il & Maeng, Junho, 2016. "Offshore wind farm site selection study around Jeju Island, South Korea," Renewable Energy, Elsevier, vol. 94(C), pages 619-628.
    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. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    12. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    13. Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Odigie, O. & Munda, J.L., 2018. "A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria," Applied Energy, Elsevier, vol. 228(C), pages 1853-1869.
    14. Gu, Huajie & Wang, Jun, 2013. "Irregular-shape wind farm micro-siting optimization," Energy, Elsevier, vol. 57(C), pages 535-544.
    15. Benjamin Pakenham & Anna Ermakova & Ali Mehmanparast, 2021. "A Review of Life Extension Strategies for Offshore Wind Farms Using Techno-Economic Assessments," Energies, MDPI, vol. 14(7), pages 1-23, March.
    16. Antonini, Enrico G.A. & Caldeira, Ken, 2021. "Atmospheric pressure gradients and Coriolis forces provide geophysical limits to power density of large wind farms," Applied Energy, Elsevier, vol. 281(C).
    17. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2012. "Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation," Renewable Energy, Elsevier, vol. 38(1), pages 16-30.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Italo Fernandes & Felipe M. Pimenta & Osvaldo R. Saavedra & Arcilan T. Assireu, 2022. "Exploring the Complementarity of Offshore Wind Sites to Reduce the Seasonal Variability of Generation," Energies, MDPI, vol. 15(19), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. 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.
    4. Dhoot, Aditya & Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2021. "Optimizing wind farms layouts for maximum energy production using probabilistic inference: Benchmarking reveals superior computational efficiency and scalability," Energy, Elsevier, vol. 223(C).
    5. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2018. "Continuous adjoint formulation for wind farm layout optimization: A 2D implementation," Applied Energy, Elsevier, vol. 228(C), pages 2333-2345.
    6. Kyoungboo Yang & Kyungho Cho, 2019. "Simulated Annealing Algorithm for Wind Farm Layout Optimization: A Benchmark Study," Energies, MDPI, vol. 12(23), pages 1-15, November.
    7. 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).
    8. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
    9. Yamani Douzi Sorkhabi, Sami & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2018. "Constrained multi-objective wind farm layout optimization: Novel constraint handling approach based on constraint programming," Renewable Energy, Elsevier, vol. 126(C), pages 341-353.
    10. Tao, Siyu & Xu, Qingshan & Feijóo, Andrés & Zheng, Gang & Zhou, Jiemin, 2020. "Wind farm layout optimization with a three-dimensional Gaussian wake model," Renewable Energy, Elsevier, vol. 159(C), pages 553-569.
    11. Aguayo, Maichel M. & Fierro, Pablo E. & De la Fuente, Rodrigo A. & Sepúlveda, Ignacio A. & Figueroa, Dante M., 2021. "A mixed-integer programming methodology to design tidal current farms integrating both cost and benefits: A case study in the Chacao Channel, Chile," Applied Energy, Elsevier, vol. 294(C).
    12. Brogna, Roberto & Feng, Ju & Sørensen, Jens Nørkær & Shen, Wen Zhong & Porté-Agel, Fernando, 2020. "A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain," Applied Energy, Elsevier, vol. 259(C).
    13. Lo Brutto, Ottavio A. & Thiébot, Jérôme & Guillou, Sylvain S. & Gualous, Hamid, 2016. "A semi-analytic method to optimize tidal farm layouts – Application to the Alderney Race (Raz Blanchard), France," Applied Energy, Elsevier, vol. 183(C), pages 1168-1180.
    14. Lo Brutto, Ottavio A. & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2017. "Assessing the effectiveness of a global optimum strategy within a tidal farm for power maximization," Applied Energy, Elsevier, vol. 204(C), pages 653-666.
    15. 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.
    16. 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.
    17. 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.
    18. Souma Chowdhury & Ali Mehmani & Jie Zhang & Achille Messac, 2016. "Market Suitability and Performance Tradeoffs Offered by Commercial Wind Turbines across Differing Wind Regimes," Energies, MDPI, vol. 9(5), pages 1-31, May.
    19. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:314:y:2022:i:c:s0306261922002719. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.