Optimal Power Flow Research of Smart Park Distribution Network Control Technique Based on Source-Charge Interaction

The disorder of EV charging and the randomness of Distributed Generation (DG) power generation are first investigated in this work. The probability models are built based on the charging characteristics of electric vehicles (EV) and the power generation characteristics of distributed energy under various conditions, and the daily power curves of electric vehicles and distributed energy are drawn based on the models. The radial physical model of the distribution network is next developed, followed by the mathematical model of the distribution network, which includes electric vehicles and distributed energy. Finally, a mathematical model of the best power flow is created, and the revised particle swarm optimization technique is utilized to optimize the scheduling in terms of both time and space, with the viability of the particle swarm optimization algorithm confirmed by MATLAB simulation. This paper has less network loss than research that only uses one Angle for optimization, and the improved particle swarm optimization algorithm used in this paper outperforms the standard particle swarm optimization algorithm, and the experimental results obtained through simulation are better in some ways.