Determining the Responsibility of Three-Phase Unbalanced Sources Based on RICA
Yixuan Yang,
Ying Wang and
Xiaoyang Ma
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Yixuan Yang: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Ying Wang: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Xiaoyang Ma: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Energies, 2019, vol. 12, issue 15, 1-19
Abstract:
Voltage unbalance is one of the main power quality problems, and the source of many negative effects on utilities that are experienced by customers. In this paper, a method based on robust independent component analysis (RICA) for responsibility division of unbalanced sources is proposed for voltage unbalance. According to the weak correlation between negative-sequence voltage and upstream and downstream current fluctuation at the point of common coupling (PCC), the independent component of the negative-sequence voltage and current fluctuation at the point of common coupling is obtained by RICA. The blind source mixing coefficient matrix can be obtained according to the least squares method. The equivalent negative-sequence impedance on both sides of the PCC can be obtained using the linear correlation between the mixing coefficients. Finally, according to the principle of partial pressure, the unbalance contribution of the upstream and downstream at the PCC is calculated. The method is accurate for upstream and downstream impedance estimation compared with the traditional method, and has a strong anti-interference ability. When the background noise or system fluctuation is large, the responsibility division result is still accurate. The correctness and effectiveness of the proposed method are proven by the simulation of the experimental circuit.
Keywords: power quality; voltage unbalance; Robust Independent Component Analysis; division of responsibilities (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)
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