A Novel Swarm Optimization Algorithm for Optimal Performance of NPC Rectifiers

With steps towards green energy, the demand of electric vehicles has increased in recent years. The electric vehicle charging is the trending research area including all the interdisciplinary fields. The neutral point clamped (NPC) rectifiers play crucial role in charging, power handling and enhancing the performance of the electric vehicle charging stations. The increase in dc and non linear loads, causes the problem of power quality in the ac side of three level NPC Rectifiers. Also, the NPC rectifier faces the problem of variations in the neutral point voltages, which is a great cause of concern for optimal charging of DC link capacitors. The paper proposes implementation of a novel swarm optimization algorithm (NSOA) based on cloud travel phenomena in Balanced Decoupled Controller (BDC) of NPC rectifiers to achieve optimal and robust performance. The NSOA comparison with standard Particle Swarm Optimization (PSO) algorithm is done on standard test function. Further, using proposed NSOA algorithm the optimized control parameters are obtained for balanced decoupled controller of NPC rectifier. The reliable performance of NPC rectifiers is validated using the MATLAB simulations results.