Application of combined feasible-direction method and genetic algorithm to optimal planning of harmonic filters considering uncertainty conditions

Abstract

The paper presents an approach of combining a feasible-direction method and a genetic algorithm (FDM+GA) to investigate the planning of large-scale passive harmonic filters. The optimal filter scheme can be obtained for a system under abundant harmonic-current sources where harmonic-amplification problems should be avoided. The design is to minimise the total demand distortion of harmonic currents and total harmonic distortion of load bus voltages. Filter loss, reactive-power compensation and constraints of individual harmonics can be considered in the design procedures. The constraints of harmonics with orders lower than the filter tuned points have been set stricter to avoid amplification of noncharacteristic harmonics. The search for the global optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC are furnaces are used and a static Var compensator (SVC) is installed. Three design schemes are compared to demonstrate the performance of the proposed method. Finally, expectations and standard deviations of objective functions are used to present effects of filter-parameter detuning, loading uncertainty and changes of system impedance.