The measurement error of capacitor voltage transformers (CVTs) has poor stability under the complex environment of substations. Con-ventionally, error detection is performed by regularly comparing the output of standard transformers, which lacks real-time performance. Moreover, CVTs are prone to operating in an out-of-tolerance state.
The measurement error of capacitor voltage transformers (CVTs) has poor stability under the complex environment of substations. Conventionally, error detection is performed by regularly comparing the output of standard transformers, which lacks real-time performance. Moreover, CVTs are prone to operating in an out-of-tolerance state.
Uncalibrated capacitive voltage transformers (CVTs) may significantly degrade measurement accuracy, because of the undetected excessive measurement error (ME). In this article, an online detection method is proposed which combines multi-source heterogeneous data composed of CVT measurements, acceptance test errors, and error limits.
Capacitor voltage transformer (CVT) is an electrical equipment composed of capacitor voltage divider and electromagnetic unit of medium voltage. It is characterized by simple structure and lower cost at higher voltage. At present, CVT is generally used in 500kV substations in China[1,2]. CVT monitors the operation of power grid.
As a key equipment for signal acquisition in power systems, capacitor voltage transformers (CVTs) are widely used in 110 kV and above power systems due to their excellent insulation perfor-mance and low cost. Moreover, their measurement error is easily affected by various factors during operation,1–7 resulting in lower stability.
The operating voltage as reference voltage, estimate feasibility analysis of CVT capacitor element of the state by the state of the secondary voltage, and through the field, find out more abnormal CVT can achieve CVT capacitor element of online monitoring function is proposed.