State monitoring method of automation equipment in independent and controllable substation based on grey prediction model

In the independent and controllable intelligent substation, the reliable operation of the automation equipment is the premise and guarantee of the stable operation of the substation. Independent and controllable automation equipment uses a large number of domestic chip products to replace imported chips. Compared with imported chips, application time of domestic chip products is short, the operation experience is very insufficient. This paper first analyzes the data that can be monitored by the independent and controllable chip and the characteristics of the corresponding data. Then, the algorithm characteristics of gray-scale prediction model GM (1,1) and its applicability and superiority in chip monitoring are analyzed, so as to construct the chip-level state monitoring system of the independent and controllable automation equipment combining gray-scale model and expert system. Finally, combined with the actual operation data of the equipment, the accuracy of the gray model prediction data and the practicability of the equipment monitoring system are verified. The results show that this method is effective in equipment state monitoring.