基于自适应蚁群算法的含分布式电源配电网故障定位研究

Research on Fault Location of Distribution Network With Distributed Generation Based on Adaptive Ant Colony Algorithm

由于含分布式电源的新型配电网不同于传统配电网,新型配电网的结构更加复杂,系统潮流方向发生改变导致传统的定位方法可靠性下降,为此提出一种自适应蚁群算法。在传统蚁群算法基础上,改进信息素挥发因子表达式、更换信息素更新机制及限定信息素浓度的取值,改进后的自适应蚁群算法的容错能力和快速性得到大幅提高。仿真结果表明,自适应蚁群算法不受故障区段数量的影响,能够准确进行故障定位;此外,当多个分布式电源同时接入配电网发生三重故障且有2处故障信息畸变的情况下,自适应蚁群算法求解速度更快,比传统蚁群算法求解速度提升了18.63%,准确率提升了10%,验证了自适应蚁群算法具有很好的容错能力和搜索速度。

Due to the new distribution network with distributed generation being different from the traditional distribution network,the structure of the new distribution network is more complex.The power flow direction of the system changes leads to the reliability of the traditional positioning method decreases.An adaptive ant colony algorithm is proposed.Based on the traditional ant colony algorithm,the expression of pheromone volatilization factor is improved.It changes the pheromone updating mechanism and limits the value of pheromone concentration.The fault tolerance and rapidity of the improved adaptive ant colony algorithm are greatly improved.The simulation results prove that the adaptive ant colony algorithm is not affected by the number of fault sections and can accurately locate the fault.In addition,when multiple distributed generation are connected to the distribution network at the same time,a triple fault occurs and there are two fault information distortions,the adaptive ant colony algorithm has a faster solution speed,which is 18.63%faster than the traditional ant colony algorithm.The accuracy rate is increased by 10%,which verifies that the adaptive ant colony algorithm has good fault tolerance and search speed.