%0 Journal Article
%T Real-Time Error Analysis of Multi-Channel Capacitive Voltage Transformer Using Co-Prediction Matrix
%A Jiusong Hu
%A Ao Xiong
%A Yongqi Liu
%A Guaxuan Xiao
%A Yi Zhong
%J Journal of Power and Energy Engineering
%P 1-17
%@ 2327-5901
%D 2025
%I Scientific Research Publishing
%R 10.4236/jpee.2025.131001
%X Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage transformer errors, particularly minor variations in multi-channel setups, remains challenging. This paper proposes a method for online error tracking of multi-channel capacitive voltage transformers using a Co-Prediction Matrix. The approach leverages the strong correlation between in-phase channels, particularly the invariance of the signal proportions among them. By establishing a co-prediction matrix based on these proportional relationships, The influence of voltage changes on the primary measurements is mitigated. Analyzing the relationships between the co-prediction matrices over time allows for inferring true measurement errors. Experimental validation with real-world data confirms the effectiveness of the method, demonstrating its capability to continuously track capacitive voltage transformer measurement errors online with precision over extended durations.
%K Capacitive Voltage Transformers
%K Co-Prediction Matrix
%K High-Voltage
%K Measurement error
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=140173