基于改进遗传算法的海上风电场集电系统拓扑优化

海上风电的集电系统的投资成本占比高,对集电系统的拓扑进行优化对降低固定投资有重要意义。集电系统的拓扑优化问题可转化成一个动态变权的最小生成树问题,由于边权变化与拓扑优化相互耦合,无法用传统的生成树方法求解。采用改进的遗传算法,通过优选初始种群、采用链表式编码、精英选择算子的环节改进,既提高了算法效率,又可处理海缆不可交叉等复杂约束。算例表明优化算法具有较好的寻优性和收敛性。

Optimization of Offshore Wind Farm Collector Systems Based on Improved Genetic Algorithm

The cost of offshore wind farm's collector system constitutes a significant proportion of the wind farm's total investment, it is thus very significant to make a topology optimization of the collector system for reducing the fixed investment. The topology optimal problem can be modeled as a minimum spanning tree problem with dynamic edge weight. Because the edge weight is coupled with topology optimization, it cannot be solved by traditional methods. Through improvement in initial population selection, use of linked list coding and elite genetic operators, the improved genetic algorithm is engaged in the paper, which can not only improve the algorithm's efficiency, but also better address the complicated restrains of uncrossed marine cables. The case study shows the improved GA has good capability in optimization searching and convergence.