Status Evaluation of Power Secondary Equipment Based on Big Data of Monitoring

The stability and reliability of Electric power secondary equipments operating is very important to the safety and stability of power grid. But nowadays, status evaluation of electric power operation equipments mainly concentrated in primary equipments. Electric power secondary equipments are lack of practical and feasible evaluation methods, can't comprehensive and scientific reflect the operating, all of these are the disadvantages of status evaluation. To solve these problems, in this paper, we build evaluation model based on mining the big data of monitoring signal and equipment ledger information, and then, the weights of each index value of evaluation model is got by Analytic Hierarchy Process(AHP) method, then, to modify the weights by relative entropy, the evaluation result is output by fuzzy algorithm. Electric power secondary equipment status evaluation method of calculation procedure is given in this paper, the effectiveness of the method is verified by numerical examples, the method is relatively simple and have good performance.