Offshore wind farm micro-siting based on two-phase hybrid optimization

Boan Lu, Xinwei Shen, Yunfei Du, Zehai Huang and Renshen Tan

Applied Energy, 2025, vol. 381, issue C, No S0306261924024899

Abstract: The wake effect among wind turbines (WTs) will lead to a decrease in the total power generation of offshore wind farms (OWFs). The layout of WTs directly affects the efficiency and profits of OWF. Hence, a two-phase optimization method is proposed for the micro-siting of WTs in OWF. In the first phase, a mixed integer programming (MIP) model is established to solve the grid-based WTs micro-siting problem, while in the second phase, the Multiple Population Genetic Algorithm (MPGA) is applied to further optimize the coordinates of WTs within the selected grids. The proposed method is tested in 3 wind scenarios: 1) one wind direction with constant wind speed; 2) multiple wind directions with constant wind speed; and 3) multiple wind directions with multiple wind speeds. Besides, the case studies verify the superiority of the proposed method based on the actual data of an OWF in Jiangsu, China. Compared to the layout produced by other methods, the two-phase hybrid optimization can reduce the wake effects significantly by producing a micro-siting result with better optimality, thus improving the overall economic benefits of OWF.

Keywords: Offshore wind farm; Micro-siting; Wake effect; Two-phase hybrid optimization method (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.125105

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