Diagnosis of Ideal Operation State of Reactive Power Compensation Equipment Based on Data Mining

In view of the shortcomings of the current management of reactive power compensation equipment in distribution network and the limitations of insufficient power data mining, this paper focuses on the operation state of reactive power compensation equipment, and proposes a diagnosis method of ideal operation state of reactive power compensation equipment based on data mining. Firstly, the nonlinear correlation between power factor and active power is analyzed. The operation data of distribution network is preprocessed and proceeds matrix approximated, and the regional equipment is clustered after dimension reduction according to the processed active load, then the definition of equipment health is proposed; Secondly, the actual and ideal switching action criterion of reactive power compensation equipment are proposed, as well as the definition of switching qualification rate; Finally, the TOPSIS method is used to comprehensively evaluate the operation status score of each reactive power compensation equipment, and the results are analyzed according to the statistical method. The example analysis proves that the proposed method has accurate identification results, strong applicability and easy implementation, and can be easily applied to the operation and maintenance of existing reactive power compensation equipment.