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基于蚁群算法的分布式配电网局部故障定位方法 被引量:8

Local fault location method of distributed distribution network based on ant colony algorithm
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摘要 为快速精准定位分布式配电网局部故障,隔离故障分支降低经济损失,提出一种基于蚁群算法的分布式配电网局部故障定位方法。利用蚁群集体行动的信息正反馈机制组建故障定位模型,创建蚁群算法评价函数,使用随机比率准则计算蚂蚁转移概率及残留信息,引入信息素更新方法动态调节原始信息素浓度,通过信息缺失校准策略提升算法容错性,依照评价函数大小,在可能解对应设备状态中释放信息素,避免产生局部最优解,能够精准定位分布式配电网局部故障位置。仿真实验结果证明,该设计方法可以有效地对分布式配电网局部故障进行高精度定位,故障定位计算收敛速度快,耗时短,拥有极强的实用性,为分布式配电网的可靠应用发挥应有作用。 In order to quickly and accurately locate local faults in distributed distribution networks and isolate fault branches to reduce economic losses,a local fault location method in distributed distribution networks based on ant colony algorithm was proposed.The information positive feedback mechanism of ant colony collective action is used to establish the fault location model,the evaluation function of ant colony algorithm is created,and the random ratio criterion is used to calculate the ant transfer probability and residual information,the pheromone updating method is introduced to dynamically adjust the original pheromone concentration,improve the fault tolerance of the algorithm through the information loss calibration strategy,and release the pheromone in the possible corresponding equipment state according to the size of the evaluation function,at the same time,the local optimal solution is avoided,and the local fault location of distributed distribution network can be accurately located.The simulation experiment can prove that,the design method can effectively locate the local faults of the distributed distribution network with high precision.Fault location calculation has fast convergence speed,short time-consuming and strong practicability,which plays a due role in the reliable application of distributed distribution network.
作者 张亚东 茅东华 余洋 Zhang Yadong;Mao Donghua;Yu Yang(State Grid Xinchang Electric Power Supply Company,Shaoxing 312500,China;State Grid Shaoxing Electric Power Supply Company,Shaoxing 312000,China)
出处 《能源与环保》 2021年第11期182-187,共6页 CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金 国网浙江有限公司创新咨询项目(CXXJ201916)。
关键词 蚁群算法 分布式配电网 信息素浓度 定位故障 评价函数 ant colony algorithm distributed distribution network pheromone concentration fault location evaluation function
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