基于多源信息和遗传算法的配电网故障定位模型

准确地定位配电网的故障区段对于用户供电可靠性有十分重大的意义。目前所提出的配电网故障定位算法有一定的局限性，当信号发生畸变时，很容易出现误判，导致无法快速准确定位到故障区段。针对现有算法的局限性，考虑增加信息多源性，在遗传算法的基础上引入低压侧用户信息，构建了一个高鲁棒性的故障定位模型。通过算例仿真分析，最终证明了该算法相比于不考虑低压侧用户停电信息的算法具有更高的准确性，更加适用于实际工程。

Fault Location Model for Distribution Networks Based on Multi-source Information and Genetic Algorithm

The accurate location of fault section in distribution network is of great importance to the reliability of power supply to the users. Current methods for fault location are constrained by some limitations. When signal distortion occurs， the methods have high possibility of misjudgment， leading to a failure to locate the fault section accurately and quickly. To avoid this limitation， the paper considers multiple information sources， introduces the power outage information from the low-voltage user side based on generic algorithm， and establishes a mathematical model for fault location with high robustness. The simulation results show the higher accuracy of the model compared to the method without considering the power outage information from the low-voltage user side， and better adaptability to application in actual engineering.