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Cable routing optimization for offshore wind power plants via wind scenarios considering power loss cost model

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  • Jin, Rongsen
  • Hou, Peng
  • Yang, Guangya
  • Qi, Yuanhang
  • Chen, Cong
  • Chen, Zhe

Abstract

Offshore wind power plants have been considered as one of the fastest-growing types of renewable energy technologies that is superior to the onshore wind farms with low impacts on habitat, better wind condition, higher energy efficiency, etc. The cost of submarine cables takes a significant proportion of the overall capital cost for a large-scale offshore wind farm, rendering the task of optimization of electrical infrastructure a critical role in modern wind farm design. With the increasing capacity and offshore distance, the impact of power losses in the cables on the economic performance of the wind farm becomes significant. Therefore, both the investment on the cables and the cost from the associated energy loss need to be considered in the optimization model. In this work, a detailed power loss cost model accounting for the wake effect’s impact on the wind turbine output is proposed. The cable cost and the associated power losses cost are considered in the objective function. The offshore substation location, cable connection layout, and cable sectional area are optimized simultaneously while ensuring an uncrossed cable connection layout via a line segment intersection detection algorithm. Due to the non-convexity of the optimization model, an adaptive particle swarm optimization algorithm is adopted. The proposed method was validated through a case of a real offshore wind farm, where the simulation results show that the cable connection layout formulation and sectional area selection varies significantly when different power loss model is applied. A 3.14% total cost reduction can be achieved by using the proposed method compared with the case without the power loss model.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919314060
    DOI: 10.1016/j.apenergy.2019.113719
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    References listed on IDEAS

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    1. Wędzik, Andrzej & Siewierski, Tomasz & Szypowski, Michał, 2016. "A new method for simultaneous optimizing of wind farm’s network layout and cable cross-sections by MILP optimization," Applied Energy, Elsevier, vol. 182(C), pages 525-538.
    2. Joanna Bauer & Jens Lysgaard, 2015. "The offshore wind farm array cable layout problem: a planar open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 360-368, March.
    3. 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.
    4. Hou, Peng & Hu, Weihao & Chen, Cong & Soltani, Mohsen & Chen, Zhe, 2016. "Optimization of offshore wind farm layout in restricted zones," Energy, Elsevier, vol. 113(C), pages 487-496.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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