Integration of SQP and PSO for optimal planning of harmonic filters

This paper presents an approach of combined sequential quadratic programming and particle swarm optimization (SQP–PSO) to optimize the planning of large-scale passive harmonic filters (PHF). The optimal filter scheme can be obtained for a system under abundant harmonic current sources where harmonic amplification problems should be avoided. The objective is to minimize the cost of the filter, filters loss, the total demand distortion of harmonic currents and the total harmonic distortion of voltages at each bus simultaneously. Meanwhile, based on the concept of multi-objective optimization, how to define the fitness function of the PSO to include different performance criteria is also discussed. The designed heuristic SQP–PSO is applied to a practical harmonic problem in a steel plant, where both AC and DC arc furnaces are used and a static var compensator (SVC) is installed. Three design schemes are compared to demonstrate the performance of the SQP–PSO.