摘要
通过开关的优化组合可以提高配电系统运行的可靠性、电能质量和经济性。为改善配电网络重构模糊遗传算法的优化速度,提出了一种模糊遗传算法和蚁群算法相结合的方法。该方法将总的种群分为两部分进行搜索,一方面通过选择算子寻找总的种群中较优个体作为模糊遗传算法的子种群进行交叉、变异操作;另一面通过设定适应度函数阈值筛选总的种群中优秀个体,并将其适应度函数值对网络信息矩阵进行全局更新,用蚁群搜索另一部分子种群。该方法设定适应度函数阈值改进了蚁群算法的信息素更新机制;把模糊遗传算法和蚁群算法的子种群融合构成总的新种群,并用选择操作和信息素更新实现了种群之间的信息共享。通过对IEEE 69节点测试系统的计算和分析表明,该方法在解决配网重构问题上比模糊遗传算法具有更好的寻优效率。
The reliability, power quality and economics of distribution system operation can be improved through the combinative optimum of the switches. For improving speed of distribution network reconfiguration based on fuzzy genetic algorithm, the combination method of Fuzzy Genetic Algorithm （FGA） and Ant Colony System Algorithm （ACSA） is presented to handle distribution network reconfiguration problem. Colony is divided into two parts to search in presented algorithm, as one part of colony, those excellent individuals are searched by the select operation in FGA and are treated with the operation of crossover and mutation. On the other hand, excellent individuals are filtered by setting threshold of the fitness function, and are then network information matrix is global updated according to its fitness value, the rest individuals of colony are searched by ACSA. The pheromone-updating mechanism is improved by threshold of the fitness function in presented method; the total of the new population is constituted by integration of sub-population searched by FGA and ACSA, information-sharing between populations is realized by selection operation and pheromone-updating. The test results on IEEE 69-bus distribution networks show the presented algorithm has a prominent searching efficiency and significant optima performance than fuzzy genetic algorithm.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2009年第17期26-31,共6页
Power System Protection and Control
关键词
模糊遗传算法
蚁群算法
网络重构
信息共享
fuzzy genetic algorithm
ant colony system
network reconfiguration
information-sharing
