A Novel Adaptive LSHADE Algorithm for Wind Farm Layout Optimization with Complex Wake Effect

As fossil fuel reserves diminish, the urgency for clean, renewable energy has grown, with wind energy emerging as a leading solution. However, optimizing wind farm layouts remains particularly challenging due to the complex wake effect, which significantly reduces energy conversion efficiency. Traditional mathematical approaches struggle to effectively solve the Wind Farm Layout Optimization (WFLO) problem. In response, this study proposes a Novel Adaptive LSHADE Algorithm (A-LSHADE) designed to address WFLO with complex wake effect. The algorithm adaptively guides the search process by selecting the optimal individuals at each iteration. Comprehensive experiments were performed under three different wind scenarios, analyzing the impact of varying turbine quantities on conversion efficiency. The results demonstrate that the proposed LSHADE variant consistently outperforms six state-of-the-art competitors in all tested conditions, delivering superior conversion efficiency.