A Load Optimization Scheduling Method of Community Energy Platform Based on Community Power Demand

With the rise of electric vehicles and the increase of electric vehicle charging pile equipment in the community, the community is prone to the problems of large peak-to-valley difference and high electricity cost during the peak period of the power load. Aiming at this problem, this paper established a community energy platform model according to the different electricity load characteristics in the community. Taking the minimum difference between the peak and valley of the community electricity load and the minimum total electricity cost as the objective function, the improved constrained multi-objective particle swarm algorithm was used to optimize the scheduling of the community power system, and it was verified by an example. The results showed that by effectively regulating the output of electric vehicle charging, residential air conditioning, commercial air conditioning, and energy storage, the load peak in the community during the peak period of electricity consumption could be greatly reduced. It could effectively realize peak shaving and valley filling, reduce the cost of electricity consumption in the community, and improve economic benefits.