A novel neural network approach for harmonic distortion detection in power systems

Harmonic distortion in power systems can lead to inefficiencies, equipment failures and operational risks. Generally, the high order harmonics are introduced in a system when the electricity is controlled by electronics. Traditional detection methods, such as Fourier and wavelet analysis, typically face challenges with real-time detection due to high computational demands. The harmonic measurements are conducted on Power Quality Analyzers, Harmonic Analyzers and numeric meters. This paper proposes a novel neural network-based approach for harmonic distortion detection, utilizing the pattern recognition capabilities of Artificial Neural Networks (ANNs). The proposed method is simple, cost effective and feasible.