考虑多因素的电子式电压互感器误差组合预测方法研究

Research on combined error prediction method of electronic voltage transformer considering multiple features

电子式电压互感器的测量准确度与电网的安全性和经济性有着紧密的联系。为准确地预测EVT长期运行过程中的误差,提出一种考虑多种因素的组合预测方法。该方法通过相关性分析选取与EVT误差相关性较强的参量作为特征量,分别使用融合注意力机制的LSTM模型与SVR模型对互感器的误差进行预测,随后将所得的各预测结果进行组合以得到最终的预测结果。对某变电站实时运行数据进行仿真分析,结果表明所提出的方法能够有效预测EVT在未来一段时间内的误差变化信息,对变电站及时预知EVT误差问题并安排进行计量性能检修具有一定的参考价值。

The measurement accuracy of electronic voltage transformer(EVT)is closely related to the security and economy of the power grid.In order to accurately predict the error of EVT during the long⁃term operation,a combined error prediction method considering multiple features is proposed.This method selects parameters with strong correlation to EVT errors through correlation analysis as feature quantities.It utilizes a fused attention mechanism LSTM model and an SVR model to predict the errors of the transformer separately.The obtained prediction results are then combined to generate the final prediction result.The real⁃time operational data of a certain substation is simulated and analyzed.The results indicate that the proposed method can effectively predict the error variation information of the EVT over a certain period of time and has certain reference value for the timely prediction of EVT errors in substations and scheduling of measurement performance maintenance.