Design of substation risk early warning and control system based on edge calculation

Abstract

In order to realize real-time and multi-dimensional control of substation risk early warning, a substation risk early warning and control system based on edge computing is designed. The sensing layer collects the operation data of substation equipment through the Internet of Things equipment, and transmits the data to the edge layer through the communication between edge equipment and external equipment. After receiving data, edge layer parses the data through the communication protocol to complete data consistency, and packages cloud services downstream data sending to the cloud computing layer. The layer uses cloud computing to compute and analyze substation equipment data and transmit it to the application layer. The application layer adopts support vector machine (SVM) algorithm to establish a risk early warning mechanism, divide the risk data attribute, and obtain warning value. Based on this, the risk situation corresponding to the early warning value is predicted by the logistic regression risk prediction model, and the probability of failure is obtained to complete the substation risk warning. Meanwhile, the early warning results are presented on the visual interface, and the corresponding risk warning is controlled and controlled by the control channel. The test results show that the communication jitter results of the system are all below 15 ms, which can realize the calculation of risk probability, obtain the number of various risk warnings of the substation, have good work energy efficiency, and realize the multi-dimensional risk warning and control of the substation.

Keywords

• edge calculation
• substation
• risk warning and control
• risk warning mechanism
• data analysis
• the early warning value