Research On Electric Vehicle Charging Load Monitoring System Based On Virtual Instrument Technology

As a solution to the energy crisis and environmental pollution, electric vehicle is classified as a strategic emerging industry. And its industrial application is vigorously promoted. As a new type of load, large-scale electric vehicle charging load is characteristic of temporal and spatial uncertainty. And its characteristic is closely related with the user’s habits. The access of large-scale is bound to bring new challenges for safe operation of the grid and power quality. So it is necessary to design a distributed monitoring system for electric vehicle charging load in order to obtain a regional electric vehicle charging load load characteristics and power quality conditions.Based on the characteristics of electric vehicle charging load, the detection indicators of monitoring system are determined. And their concept, detection algorithm, GB and impacts on the power system are introduced. For features of the monitoring system, LabVIEW is selected as the s development platform. Then the development platform characteristics and monitoring system development steps are introduced. The possible electric vehicle charging scenarios in future and charging scale electric vehicle charging load scheduling strategy are explored. The system can be divided into front-end system, server system and network communication system.Taking account of detection accuracy requirements and economic factor, hardware devices of front-end system is chosen and its acquisition parameters are set reasonably. The detection system and database are connected. And results of front-end system can be stored in the database. The report module is designed, which can generate electric vehicle charging load monitoring reports. Network communication system based on DataSocket technology is built, which accomplish data communication the between the front-end system and the server system.Projection Pursuit level evaluation model is used in evaluating the impact of electric vehicle charging load on power quality of grid. According to the characteristics of the electric vehicle charging load, the evaluation items and rating scale are determined. Multiple evaluation indexes are projected to the comprehensive single evaluation value using Projection Pursuit theory. The optimal projection direction is found through quantum particle swarm optimization algorithm. Based on the optimal projection values and their corresponding evaluation level, the linear interpolation charging load power quality evaluation model is established.