Hollow coil current transformer error compensation method based on elastic network

Abstract

The invention provides a hollow coil current transformer error compensation method based on an elastic network. The method comprises the steps that of collecting the influence quantity influencing three-phase error compensation of a hollow coil current transformer, wherein the influence quantity comprises environmental parameters and electrical parameters; collecting an error compensation quantity; normalizing the influence quantity and the error compensation quantity, calculating Pearson correlation coefficients of the influence quantity and the error compensation quantity, and performing feature selection on the main influence quantity by using a factor screening method based on an elastic network algorithm; taking dominant influence quantity of the hollow coil current transformer as aninput quantity, using an elastic network algorithm based on cross validation to carry out modeling prediction on error compensation, calculating a difference value between an actual compensation valueand a prediction compensation value, and taking an average absolute error and a root-mean-square error as prediction evaluation. According to the method, the error compensation trend of the hollow coil current transformer can be effectively predicted, and the measurement precision of the hollow coil current transformer can be effectively improved.

Description

technical field [0001] The invention relates to the technical field of current transformer error compensation, in particular to an elastic network-based air-core coil current transformer error compensation method. Background technique [0002] As an ideal substitute for traditional electromagnetic current transformers, air-core coil current transformers are currently widely used in smart substations to provide accurate current measurement data for metering and protection equipment. Due to immature technology development, its digital processing unit and sensing unit are susceptible to interference from the working environment, and there is a problem of accuracy degradation after long-term operation. This requires finding a method to compensate the error of the air-core coil current transformer to improve The accuracy of air-core coil current transformers, and the rapid development of artificial intelligence and machine learning in recent years, provide a new idea for error co...

AI Technical Summary

Problems solved by technology

Due to immature technology development, its digital processing unit and sensing unit are susceptible to interference from the working environment, and there is a problem of accuracy degradation after long-term operation. This requires finding a method to compensate the error of the air-core coil current transformer to improve The accuracy of air-core coil current transformers, and the rapid development of artificial intelligence and machine learning in recent years, provides a new idea for error compensation of air-core coil current transformers

[0003] The literature in the prior art "Luo Sunan, Tian Chaobo, Zhao Xicai. Performance analysis of air-core coil current transformers [J]. Chinese Journal of Electrical Engineering, 2004, 24(3): 108-114." After a lot of research, we have studied the interference mechanism of air-core coil current transformers by factors such as temperature and magnetic field, and proposed improvements to its hardware to achieve the measurement accuracy of air-core coil current transformers. However, it is more expensive to replace new transformers and cannot Large-scale popularization, there may also be a problem that the accuracy of transformers will degrade after long-term grid-connected operation

[0004] The literature in the prior art "Yin Shiyu, Zhang Shichang, Wu Tian. Temperature error analysis and temperature error compensation of all-fiber current transformers [J]. Electrical Measurement and Instrumentation, 2017, 54(7): 16-21." only analyzed The influence of temperature on some hardware and its error compensation, while the transformer is affected by the cross influence of multiple factors, and the error compensation of the transformer cannot be fully realized

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