Worst-case performance assessment of switching overvoltage and mitigation for mass rapid transit system using genetic algorithm

For effective insulation coordination of mass rapid transit systems, it is important to develop techniques for determining the worst-case switching overvoltages and for evaluating the most appropriate mitigation scheme. The appropriate techniques should provide accurate modelling of various system-related and device-related factors. The latter factors are however subjected to performance degradation due to ageing of switching devices or mitigation schemes, mechanical imperfections, pre-strikes etc. This paper proposes a genetic-algorithm-based optimisation method, which formulates all these factors into a rigorous mathematical framework. The paper shows that the proposed method is more reliable, accurate, comprehensive and consistent than two well-accepted statistical techniques. Case studies are performed with the switching of utility capacitor on a typical mass rapid transit system