A comparative study of harmonic current identification for active power filter

Active power filter requires accurate harmonic current identification to compensate harmonics in power system distribution. The purpose of this paper is to present a comparative study of two techniques for harmonics currents identification based on P-Q theory and Adaline(ADAptiveLINear Element) neural networks. The harmonic current can be identified from powers or currents. The first method is based on the instantaneous powers taking advantage from relationship between load currents and power transferred from the supply source to the loads. The second method concerns the artificial neural networks based on the LMS (least mean square) algorithm. This approach adjusts the weights by iteration and provides more flexibility to perform the compensation. The developed architecture is validated by computer simulation proving its effectiveness, capability and robustness.