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Optimizing wind farm cable routing considering power losses

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  • Fischetti, Martina
  • Pisinger, David

Abstract

Wind energy is the fastest growing source of renewable energy, but as wind farms are getting larger and more remotely located, installation and infrastructure costs are rising. It is estimated that the expenses for electrical infrastructures account for 15–30% of the overall initial costs, hence it is important to optimize their design. This paper focuses on offshore inter-array cable routing optimization. The routing should connect all turbines to one (or more) offshore substation(s) while respecting cable capacities, no-cross restrictions, connection-limits at the substation, and obstacles at the site. The objective is to minimize both the capital that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. We present a Mixed-Integer Linear Programming approach to optimize the routing using both exact and math-heuristic methods. In the power losses computation, wind scenarios are handled efficiently as part of the preprocessing, resulting in a model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our methods, proving that savings in the order of millions of Euro can be achieved.

Suggested Citation

  • Fischetti, Martina & Pisinger, David, 2018. "Optimizing wind farm cable routing considering power losses," European Journal of Operational Research, Elsevier, vol. 270(3), pages 917-930.
    • Handle: RePEc:eee:ejores:v:270:y:2018:i:3:p:917-930
    DOI: 10.1016/j.ejor.2017.07.061
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    Citations

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    Cited by:

    1. Cazzaro, Davide & Koza, David Franz & Pisinger, David, 2023. "Combined layout and cable optimization of offshore wind farms," European Journal of Operational Research, Elsevier, vol. 311(1), pages 301-315.
    2. José Baptista & Beatriz Jesus & Adelaide Cerveira & Eduardo J. Solteiro Pires, 2023. "Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    3. Hugo Díaz & C. Guedes Soares, 2022. "Multicriteria Decision Approach to the Design of Floating Wind Farm Export Cables," Energies, MDPI, vol. 15(18), pages 1-18, September.
    4. 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).
    5. Chandra Ade Irawan & Majid Eskandarpour & Djamila Ouelhadj & Dylan Jones, 2019. "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," Post-Print hal-02509382, HAL.
    6. Siyu Tao & Andrés Feijóo & Jiemin Zhou & Gang Zheng, 2020. "Topology Design of an Offshore Wind Farm with Multiple Types of Wind Turbines in a Circular Layout," Energies, MDPI, vol. 13(3), pages 1-16, January.
    7. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    8. Chakib El Mokhi & Adnane Addaim, 2020. "Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms," Sustainability, MDPI, vol. 12(14), pages 1-24, July.
    9. Ruijuan Sun & Gayan Abeynayake & Jun Liang & Kewen Wang, 2021. "Reliability and Economic Evaluation of Offshore Wind Power DC Collection Systems," Energies, MDPI, vol. 14(10), pages 1-24, May.
    10. Stålhane, Magnus & Halvorsen-Weare, Elin E. & Nonås, Lars Magne & Pantuso, Giovanni, 2019. "Optimizing vessel fleet size and mix to support maintenance operations at offshore wind farms," European Journal of Operational Research, Elsevier, vol. 276(2), pages 495-509.
    11. Jin, Rongsen & Hou, Peng & Yang, Guangya & Qi, Yuanhang & Chen, Cong & Chen, Zhe, 2019. "Cable routing optimization for offshore wind power plants via wind scenarios considering power loss cost model," Applied Energy, Elsevier, vol. 254(C).
    12. Wu, Yan & Xia, Tianqi & Wang, Yufei & Zhang, Haoran & Feng, Xiao & Song, Xuan & Shibasaki, Ryosuke, 2022. "A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network," Renewable Energy, Elsevier, vol. 185(C), pages 302-320.
    13. Yuanhang Qi & Peng Hou & Guisong Liu & Rongsen Jin & Zhile Yang & Guangya Yang & Zhaoyang Dong, 2021. "Cable Connection Optimization for Heterogeneous Offshore Wind Farms via a Voronoi Diagram Based Adaptive Particle Swarm Optimization with Local Search," Energies, MDPI, vol. 14(3), pages 1-21, January.
    14. Magnus Daniel Kallinger & José Ignacio Rapha & Pau Trubat Casal & José Luis Domínguez-García, 2023. "Offshore Electrical Grid Layout Optimization for Floating Wind—A Review," Clean Technol., MDPI, vol. 5(3), pages 1-37, June.
    15. Ade Irawan, Chandra & Starita, Stefano & Chan, Hing Kai & Eskandarpour, Majid & Reihaneh, Mohammad, 2023. "Routing in offshore wind farms: A multi-period location and maintenance problem with joint use of a service operation vessel and a safe transfer boat," European Journal of Operational Research, Elsevier, vol. 307(1), pages 328-350.
    16. Irawan, Chandra Ade & Eskandarpour, Majid & Ouelhadj, Djamila & Jones, Dylan, 2021. "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," European Journal of Operational Research, Elsevier, vol. 289(3), pages 912-926.
    17. López-Ramos, Francisco & Nasini, Stefano & Sayed, Mohamed H., 2020. "An integrated planning model in centralized power systems," European Journal of Operational Research, Elsevier, vol. 287(1), pages 361-377.

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