Topology Optimization of Wind Farm in the Sea Based on Improved Whale Optimization Algorithm

Offshore wind power holds a crucial place in the global clean energy development plan. Optimizing its topological structure is highly significant for boosting power generation efficiency and cutting costs. In this article, a novel approach for offshore wind farm topology optimization, relying on the Algorithm (IWOA), is proposed. Through integration of an adaptive weight regulation strategy and an elite opposition - based learning mechanism, the algorithm remarkably improves its global search ability and convergence rate. A real - world offshore wind farm is used as a case study. When comparing the optimization outcomes of the enhanced algorithm with those of traditional algorithms, it becomes evident that IWOA has distinct benefits in minimizing total investment costs and energy losses. This comparison verifies the effectiveness and superiority of IWOA in offshore wind farm topology optimization. Moreover, it offers fresh technical assistance for efficient and stable operation of offshore power generation system. The research results provide key technical support and new optimization ideas for the scientific planning and efficient construction of offshore wind farms, and strongly promote the technological progress and sustainable development of offshore wind power field.