基于灾变遗传算法的无功规划优化

摘要： 提出了应用于电力系统无功规划优化的灾变遗传算法。算法中引入“灾变”的概念来保证解空间的多样性;采用了分组整数编码技术和锦标赛选择机制;提出采用与十进制整数编码策略相结合的邻近变异操作算子,以避免二进制编码中的海明悬崖。将此算法应用在佛山226个节点的电力系统中。结果表明它能克服一般遗传算法（GA）的早熟收敛倾向和改善GA的局部搜索能力,比常规GA的寻优效率高得多。

CATACLYSMIC GENETIC ALGORITHMS BASED OPTIMAL REACTIVE POWER PLANNING

This paper presents a Cataclysmic Genetic Algorithm for optimal reactive power planning of power systems. "Cataclysm" is introduced to ensure the diversities of the solution spaces; Grouping integer encoding technique and tournament selection method are adopted in this paper; Adjacent mutation operator integrating with integer encoding strategy is presented to avoid the Hamming cliffs by binary encoding strategy. The proposed algorithm applied to optimal reactive power planning on Foshan 226 bus power system. The results show that it is able to overcome the premature convergence tendency and to improve the local search performance of GA. It can be concluded that Cataclysmic Genetic Algorithm is much more efficient than traditional GA.