Application of differential evolution for harmonic worst-case identification of mass rapid transit power supply system

Mass rapid transit (MRT) operation results in voltage and current harmonic distortions in AC supply systems. Power-supply standards limit the acceptable harmonic-distortion levels. In order to observe these limits, it is necessary to identify the worst-case harmonic distortion in MRT system. Train operating modes and system configurations affect the level of harmonic distortions. Harmonic worst-case identification can be treated as an optimization problem in terms of train separations and traffic conditions. The approach uses approximate train movement and consumption models, and AC/DC harmonic loadflow for evaluating the harmonic distortions. This paper uses a new method called differential evolution (DE) for solving the problem. Parallel studies using genetic algorithm (GA) are also carried out. Comparative results demonstrate the favourable features of DE for large-scale optimization with real variables, as the method is efficient and fast converging.