A bi‐level programming model and differential evolution for optimizing offshore wind farm layout

The optimization of offshore wind farms is mainly performed through the deployment and submarine cables to maximize power output minimize cable costs. However, above results are affected by wake effect, equipment layout, cost cables. To effectively complete turbines lines, first, a bi-level constrained model based on maximum profit shortest route proposed in this paper; then, differential evolution improved Prim algorithm (IPADE) used optimize upper- lower-level objective function, respectively. Moreover, fitness values divide population, surrogate evaluate approximate for sub-population with poor performance; best individual selected as offspring according values. Next, clustering method position farm, roulette wheel selection designed deploy every subwind farm. Finally, compared five other popular algorithms under two conditions. simulation experimental show that IPADE performs better than terms output, profit, length