Optimization of Virtual Power Plant Aggregation Strategy Considering Adjustable Load Characteristics

As the proportion of clean energy connected to the grid gradually increases, virtual power plants (VPPs) that can help the grid to bridge the gap between supply and demand for electricity in the market have ushered in a boom. However, the overall economic benefits and regulation efficiency of VPPs are closely related to the response characteristics of the adjustable loads it aggregates. Still, the response characteristics of various adjustable loads vary greatly, and the existing research is minimal. In this paper, a revenue-cost analysis model is constructed based on the large electricity consumers with adjustable capacity in VPP scheduling, such as electric vehicle charging piles, oversized and heavy industry, and small and medium-sized industrial and commercial enterprises, which can quantitatively evaluate the impact of response methods, response capabilities and response costs on the overall revenue of different aggregate objects according to the characteristics of these target aggregates. Taking the trading situation of a spot market in Shanxi Province in August 2022 as an example, the impact of different response objects on the overall revenue of VPP is quantitatively analyzed by scenario, and the model’s effectiveness is verified. It provides good guiding significance and theoretical support for VPP operation decision-makers to improve the overall operating income by optimizing aggregation strategies.