Region-partitioned obstacle avoidance strategy for large-scale offshore wind farm collection system considering buffer zone

Xiaoshun Zhang, Jincheng Li and Zhengxun Guo

Energy, 2024, vol. 313, issue C

Abstract: For a wind farm, the collection system can directly influence the investment cost, the connected number of wind turbines, and the operation reliability. In general, it is difficult to generate a high-quality design solution for the collection system when considering various constraints (e.g., bypassing the obstacle zone), especially for a large-scale wind farm with numerous wind turbines. To address this complex and challenging issue, a region-partitioned obstacle avoidance strategy for large-scale offshore wind farm collection systems (OWFCS) considering buffer zones is innovatively presented. Firstly, the optimization model for OWFCS is formulated to minimize both cable investment and construction costs. A buffer zone with several buffer points is originally constructed, upon which the obstacle zone can be bypassed via connecting with buffer points instead of the inner points of the obstacle zone. Subsequently, a radial fuzzy C-means (RFCM) based region-partitioned clustering strategy for OWFCS is developed to narrow the solution space, thus reducing the complexity and difficulty of optimization. Furthermore, an automated submarine cable selection method named obstacle spanning tree (OST) is presented and integrated into a firefly algorithm (FA) to seek the optimal collector system topology. Finally, the case studies validate that the proposed method is effective in optimizing OWFCS topology with both single and multiple obstacle zones. Compared with other approaches, the proposed method demonstrated advantages in terms of stability and cost optimization effectiveness for OWFCS with obstacle zones after 10 independent runs.

Keywords: Offshore wind farm; Collection system; Obstacle avoidance; Graph theory; Fuzzy C-Means (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224035369

DOI: 10.1016/j.energy.2024.133758

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