Open AccessHarmonics Current Detection in Three-phase Circuit using Neural Network
Author(s) -
Jian Liang,
Shuang Zhang,
Yang Ren,
Yuanchu Cheng
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2242/1/012043
Subject(s) - harmonics , harmonic , total harmonic distortion , current (fluid) , artificial neural network , control theory (sociology) , computer science , three phase , power (physics) , electronic engineering , voltage , engineering , physics , electrical engineering , artificial intelligence , acoustics , control (management) , quantum mechanics
Harmonics seriously affect the safety and economy of power system. In order to control harmonics effectively, harmonic current and harmonic power must be detected quickly. Based on the analysis of the components of three-phase nonlinear current, a neural network detection method of fundamental and harmonic current in three-phase circuit is proposed. The method uses a neural network instead of the low-pass filter in the instantaneous reactive power theory. The example results show that the proposed method has the advantages of less computation, better real-time performance and high detection accuracy. The method can be used to detect the positive-sequence (negative-sequence) fundamental active current, positive-sequence (negative-sequence) fundamental reactive current, harmonic, distortion current and harmonic power.