Abstract

In order to bring railway static power conditioner (RPC) into full play in suppressing negative sequence current in the V/v traction power supply system, the reason of negative sequence current and compensation mechanism were analyzed, and the mathematical model with minimum negative sequence current under the constraint of voltage fluctuation, power factor, device capacity, transformer winding capacity, and energy conservation was set up. For solving the small-scale multidimensional nonlinear and constrained optimization problem, an intelligent algorithm based on sequential quadratic programming (SQP) method is proposed through a comparative analysis of existing optimization algorithms and the traditional analytical method. The proposed algorithm is capable to complete an optimizing computation process in several milliseconds with the precision of 0.1 A, and its computational efficiency and precision can meet the needs for real-time control of RPC. A self-adaption real-time optimization computing platform was built in combination with detectable analogue quantities of traction power supply system and RPC, including catenary network voltages, feeder currents, and compensation currents. Simulation and engineering experimentation results are provided to illustrate that the model and its computation are effective and feasible.

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