Application of three intelligent methods for harmonic estimation: Adaline, Adaline-LS, PSO-LS

H. Erdem, E. O. Tartan, A. Berkol

Abstract


Harmonic estimation is one of the main challenges in electric power quality discussion. During the last decade many deterministic and machine learning based methods have been applied for estimation of harmonics’ parameters. Concerning learning capacity of intelligent systems, adaptive linear combiner (Adaline) based method is the most used learning method among the artificial neural networks (ANN). On the other hand, some meta-heuristic optimization algorithms and the related hybrid algorithms have been applied for harmonic estimation in recent studies. This study discuses and compares, application of three Artificial Intelligent (AI) methods (Adaline, Adaline-Least squares (LS) and Particle Swarm Optimization-LS) for harmonic parameters estimation in power signals. The proposed algorithms have been applied to a sample test signal and the performances of methods have been compared considering estimation accuracy and estimation time.

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