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当配电网发生故障时,会出现剩余电源容量不够恢复所有的停电区域的情况,此时应以尽可能恢复更多的停电区域为目的。针对配电网自身的特点,确定了故障恢复模型所采用的目标函数及其约束条件,在基于种间竞争的遗传算法的基础上,引入了自适应策略,运用交叉算子和变异算子的自适应技术协调种内进化过程,通过种间竞争频率的自适应调剂促进最优个体的生成,并根据实际情况,对于染色体交叉、变异加以改进。算例分析表明,该算法具有更强的全局搜索能力和收敛速度,可以恢复更多的停电区域。
When the distribution network fails, there will be insufficient capacity of the remaining power to recover all the blackouts. In this case, it is necessary to recover more blackouts as much as possible. According to the characteristics of the distribution network itself, the objective function and the constraints of the fault recovery model are determined. Based on the genetic algorithm based on interspecific competition, an adaptive strategy is introduced, using crossover operator and mutation operator The adaptive technique coordinates the intraspecific evolution and promotes the generation of the optimal individuals through the adaptive adjustment of interspecific competition frequencies. Based on the actual situation, the chromosome crossover and mutation are improved. The case study shows that this algorithm has stronger global search ability and convergence speed and can recover more power outages.