摘要
直流系统线路发生短路故障后故障电流上升迅速,对系统安全造成极大危害。为解决此问题,提出基于遗传算法的直流配电网线路故障定位方法。首先,对极间短路故障和单极接地故障2种情况下的直流系统分别建立数学模型,利用双端电气量消除中间量过渡电阻;然后,分别利用2种故障的数学模型构造适应度函数,将故障定位问题转化为参数识别问题,采用遗传算法(genetic algorithm,GA)对其进行识别,避免由于数据采集误差对定位造成的干扰;最后硬件在环模拟(hardware-in-the-loop simulation,HILS)实验平台上搭建6端直流配电网模型进行实时仿真验证,结果显示该方法抗过渡电阻能力强、定位精度高,具有很强的鲁棒性。
After the short-circuit fault of the line in DC system,the fault current rises rapidly,which causes great harm to the system safety. To solve this problem,a fault location method of the DC distribution network based on genetic algorithm is proposed. First,the mathematical models are established respectively for the DC system under the conditions of pole-topole fault and the pole-to-ground fault,and the intermediate-quantity transition resistance was eliminated by using the double-ended electrical quantity. Then,two kinds of fault mathematical model are used to construct the fitness function respectively,and the fault location problem is transformed into a parameter identification problem. The genetic algorithm(GA)is used to identify it which avoids the interference caused by incorrect data collection. Finally,a six-terminal DC distribution network model is built on the HILS platform to verify the simulation results. The results show that this method has strong resistance to transient resistance,high positioning accuracy,and has strong robustness.
作者
徐岩
刘婧妍
张诗杭
付媛
Xu Yan;Liu Jingyan;Zhang Shihang;Fu Yuan(State Key Laboratory of New Energy and Electric Power Systems(North China Electric Power University),Baoding 071003,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2020年第12期1-8,共8页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51607070)
中央高校基本科研业务费专项资金(2018ZD001)。
关键词
配电网
故障定位
参数识别
遗传算法
直流系统
distribution networks
fault location
parameter identification
genetic algorithm
DC power distribution
