Performance improvement of railway power conditioner with model predictive control approach

Power Quality (PQ) conditioning in electric railway systems (ERSs) is an increasing concern with the rapid development process of high-speed and high-power trains. Over the years, several solutions have been presented to mitigate the PQ problems of ERSs. Railway power conditioners (RPCs) are known as one of the most promising solutions. They have attracted experts attention during the last decade due to their prominent performance. The complexity, and time-varying features of ERS and trains as loads have led the difficulties of RPCs controlling. In this paper, a model predictive control based method using modified dual-loop instantaneous reactive power theory (MPC-DIRP) is proposed to enhance the compensation and dynamic performance of RPC. Improving dynamic tracking capability, higher accuracy and lower fluctuation, together with the simple implementation structure are the worth-mentioning advantages of the proposed method. The detailed simulations have been to verify the proposed control method effectiveness.