Application of genetic algorithms to determine worst-case switching overvoltage of MRT systems

Genetic algorithms (GAs) are applied to determine the worst-case overvoltage caused by nonsimultaneous energisation of mass rapid transit (MRT) power distribution systems. Two GA-based optimisation methods are compared, using case studies performed on a typical MRT system. Simulation results show that the objective function of the GA problem is highly multimodal, discontinuous and noisy, which makes it difficult for the traditional sequential search method to obtain global optimisation. Although the effectiveness of the GA approach is verified, one drawback of the approach is that it can be CPU time-intensive. The GA approach performs many executions of the Electromagnetic Transient Program for function evaluations. The micro-GA (μGA) is proposed as an alternative to the simple GA. Results show that the μGA performs fewer function evaluations as it searches over the response surface more efficiently than the simple GA