Real-time frequency and harmonic evaluation using artificial neural networks

L. L. Lai, C. T. Tse, Wai Lok Chan, A. T.P. So

Research output: Journal article publicationReview articleAcademic researchpeer-review

241 Citations (Scopus)


With increasing harmonic pollution in the power system, real-time monitoring and analysis of harmonic variations have become important. Because of limitations associated with conventional algorithms, particularly under supply-frequency drift and transient situations, a new approach based on non-linear least-squares parameter estimation has been proposed as an alternative solution for high-accuracy evaluation. However, the computational demand of the algorithm is very high and it is more appropriate to use Hopfield type feedback neural networks for real-time harmonic evaluation. The proposed neural network implementation determines simultaneously the supply-frequency variation, the fundamental-amplitude/phase variation as well as the harmonics-amplitude/phase variation. The distinctive feature is that the supply-frequency variation is handled separately from the amplitude/phase variations, thus ensuring high computational speed and high convergence rate. Examples by computer simulation are used to demonstrate the effectiveness of the implementation. A set of data taken on site was used as a real application of the system.
Original languageEnglish
Pages (from-to)52-57
Number of pages6
JournalIEEE Transactions on Power Delivery
Issue number1
Publication statusPublished - 1 Dec 1999

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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