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A Novel Neural Network Approach for Harmonic Distortion Detection in Power Systems

Suchita S. Ingle*, Ashpana Shiralkar**, Shashikant Bakre***

*-*** Department of Electrical Engineering, AISSMS Institute of Information Technology, Pune, Maharashtra, India.

Periodicity:January - June'2025

Abstract

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.

Keywords

ANN, Sigmoid function, Chaining, THD, Gradient Descent.

How to Cite this Article?

Ingle, S. S., Shiralkar, A., and Bakre, S. (2025). A Novel Neural Network Approach for Harmonic Distortion Detection in Power Systems. i-manager’s Journal on Circuits and Systems, 13(1), 18-24.

References

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A Novel Neural Network Approach for Harmonic Distortion Detection in Power Systems

Abstract

Keywords

How to Cite this Article?

References

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