Research on Distributed Photovoltaic Day-ahead Scheduling and Consumption Strategy

Under the background that the proportion of distributed photovoltaic connected to the distribution network increases year by year, optimizing the photovoltaic absorption capacity of the distribution network is of great significance. Aiming at the problem that photovoltaic output cannot be absorbed locally, this paper proposes an optimization scheme for distributed photovoltaic systems that considers demand-side response and energy storage. In this paper, particle swarm optimization support vector machine (PSO-SVM) was used to predict photovoltaic output ahead of the day, and the kernel width function and penalty coefficient of SVM were optimized by particle swarm optimization algorithm to obtain the prediction data with high accuracy. Then, starting from the constraints of node voltage not exceeding the limit, line power flow not overloading, and energy storage system not exceeding the limit, and aiming at the maximum photovoltaic absorption capacity, a distributed photovoltaic absorption model is established. Taking IEEE14 node power distribution system as a simulation example, the influence of energy storage system and flexible load on photovoltaic consumption rate is analyzed. Finally, the ipopt solution toolbox is used to solve the model in MATLAB, and the power distribution scheme of the power distribution system is calculated with the goal of maximizing the photovoltaic absorption capacity. The simulation results show that the optimization scheme of the photovoltaic microgrid system considering the energy storage system and the demand-side response proposed in this paper can effectively reduce the photovoltaic power station's light abandonment rate, and realize the photovoltaic on-site consumption to meet the regional load supply, which is a good source of photovoltaic power in the region. The application provides feasibility guidance.