A stochastic planning method for energy storage capacity in distribution networks based on source load interaction

A stochastic planning method for energy storage capacity in distribution networks based on source load interaction is proposed. By utilizing source load interaction, a stochastic programming model architecture is constructed to optimize the scheduling of energy storage systems. In the event of imbalanced supply and demand in the power grid or significant fluctuations in electricity prices, energy storage resources are allocated reasonably to implement scheduling strategies such as peak shaving and load smoothing, thereby improving the utilization efficiency of energy storage systems. Construct a multi-objective stochastic programming model for composite energy storage, constrained by power balance, state of charge of energy storage batteries, and maximum power. Using improved PSO algorithm to solve the stochastic planning model of energy storage capacity. The experimental results show that the planning results of the energy storage system obtained by the proposed method are: 5 wind turbines, 25 photovoltaic array units, 18 lithium batteries and 3 supercapacitors.