Optimal Estimation of Harmonics in Power System using Intelligent Computing Techniques

Harmonic distortion is one of the important problems associated with power quality and creates several disturbances to power system. To obtain suitable control strategy for harmonic mitigation, the harmonics present in the system is to be estimated accurately. This paper presents algorithms to estimate the harmonics in power systems using genetic algorithm (GA), hybrid genetic algorithm-least square (GA-LS), hybrid particle swarm optimization-least square (PSO-LS) and adaptive neural network (ANN) techniques. The objective is to estimate the magnitude and phase angle of the harmonics by analyzing the waveform. The four techniques are analyzed and the results are compared in terms of percentage of error and processing time for finding suitable efficient technique to estimate harmonics. It is identified that ANN is the effective tool to estimate the harmonics in power system and it can be applied online.