TITLE:
Real-Time Error Analysis of Multi-Channel Capacitive Voltage Transformer Using Co-Prediction Matrix
AUTHORS:
Jiusong Hu, Ao Xiong, Yongqi Liu, Guaxuan Xiao, Yi Zhong
KEYWORDS:
Capacitive Voltage Transformers, Co-Prediction Matrix, High-Voltage, Measurement error
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.13 No.1,
January
24,
2025
ABSTRACT: 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.