Optimal Scheduling Model Considering the Aggregation of Virtual Power Plant

With the increasing integration of asynchronous resources into the power system, the scheduling pressure on power systems is growing. As an aggregator of load-side resources, a virtual power plant can aggregate these resources to adjust the load curve and optimize the power system scheduling costs. This virtual power plant control is a demand-side response behavior. It can better utilize demand-side resources. To reduce scheduling costs by aggregating energy storage users through a virtual power plant, this paper proposes a model for optimizing power system scheduling costs. In this model, the electricity price curve for storage users is treated as a variable to optimize their electricity usage behavior. Thereby finding the optimal power system scheduling plan and electricity price curve. This approach ensures the benefits for storage users while achieving the lowest scheduling cost. Experimental results show that optimizing the load curve with the virtual power plant's control of energy storage price curves has led to improvements in the load curve. It also reduces both scheduling costs and scheduling pressure.