Research on Online Monitoring Method of Low Voltage User Electric Energy Meter Operation Error Based on Multi-model Fusion
In order to address the practical issues of low anomaly detection accuracy and large operation error deviation of low-voltage electric energy meters in operation,combined with the actual situation that low-voltage user meters only collect daily frozen meter code data,this paper proposes an online monitoring method of low voltage user electric energy meter operation error based on multi-model fusion.Firstly,the correlation analysis model is improved based on the outlier detection algorithm to enhance the anomaly detection capability.Secondly,variable losses of distribution areas are estimated by ridge regression,and the operation error analysis model is improved to overcome the adverse effects of variable correlation and nonlinear factors on the calculation of the operation error values of the electric energy meters.Then,a review model is proposed to deeply explore the correlation between the user daily electricity consumption and the distribution area line loss.Finally,the proposed models are fused and comprehensively evaluated to achieve precise detection of abnormal low-voltage electricity meters.The case study,based on real data from a province,demonstrates that the method presented herein exhibits high accuracy and superior robustness in anomaly detection and error estimation.
operational errorsubstation line lossloss predictioncorrelationreview model
万方数据
维普
