Optimization of inverter placement for mass rapid transit systems using genetic algorithm

This paper has presented a methodology to solve the optimal planning of inverter substations for an electrified mass rapid transit (MRT) system by using the genetic algorithm (GA). The mathematical models of power converters in traction substations have been derived for different operation modes. With the variation of power demand of train sets along the main line, the AC/DC load flow analysis has been performed to find the energy consumption and braking regeneration restoration at each power converting substation for system peak and off peak operation over the study period. The overall cost of power consumption, inverter investment, and service reliability are included in the objective function, and each feasible solution is expressed as a chromosome in the GA simulation process. The fitness is then enhanced by considering the diversity of chromosomes so that the global optimization during the solution process can be obtained. It is found that the energy regeneration, which has been resulted from braking operation of train sets approaching the next station, can be restored effectively by the optimal planning of inverters using the proposed genetic algorithm