Research on The Accuracy of New Energy Station Monitoring Data Based on Data Anomaly Identification
Zhiyuan Sun, Mosi Liu, Changfu Wei · 2024
New energy station monitoring data is becoming more and more important. This paper studies the accuracy evaluation method of new energy station monitoring data based on data anomaly identification. Firstly, real-time monitoring data collected by each monitoring node in the new energy station is obtained. Execute the pre-processing and cluster analysis of monitoring data in turn, define data monitoring standards, and preliminarily verify abnormal data in the monitoring process; Extract sample data from monitoring data, build anomaly identification model, comprehensively identify abnormal data in monitoring data, and dynamically optimize model identification performance based on incremental learning; Integrate all abnormal data in the monitoring process, and evaluate the accuracy of real-time monitoring data collected by new energy stations based on anomaly location and composition analysis. By integrating abnormal data for positioning and composition analysis, the accuracy of monitoring data of each monitoring node and station is comprehensively and accurately evaluated, to improve the reliability of data.