Optimal Control of Residents’ Controllable Load Resources Considering Different Demands of Users

Abstract

Optimizing the controllable load resources of residents on the demand side is a major aspect of virtual power plant (VPP). It is an important means to improve the utilization rate of new energy such as wind power and photovoltaic power, to achieve carbon neutrality. The key to control controllable load is to meet the basic power demand of users, and different users have different power demand. Therefore, an optimal control method of residents’ controllable load resources considering user demand was proposed. Considering the different demand of different users, as an intermediate link between the power grid and the load group, VPP manages the controllable load. Firstly, an improved K-means clustering algorithm for optimal k selection was proposed for clustering. Then, according to the demand difference function to quantify the deviation between the power consumption and the original demand of each group after load regulation, a priority division rule based on the demand difference was proposed. Finally, in the regulation, VPP compensated different costs for different priority groups to achieve the regulation goal of maximizing VPP revenue and minimizing changes in user electricity consumption behavior. The simulation results show that the proposed optimal control strategy can effectively cut the peak and fill the valley of the load curve, and ensure the VPP revenue with less impact on the power demand of users.

Keywords

• virtual power plant (vpp)
• controllable load
• load clustering
• user demand
• peak shaving and valley filling