A Dynamic Partition Model for Multi-Energy Power Grid Energy Balance Considering Electric Vehicle Response Willingness

Abstract

In multi-energy power grids in which electric vehicles (EVs) participate in response, there are significant differences in the power balance between multi-energy supply and load at different time scales and spatial scales. To optimize the energy balance demand of each region, this paper proposes a dynamic partition coordination model for power grid energy regulation demand that considers the willingness of electric vehicles to respond and the uncertainties related to sources, loads, and storage. Firstly, the charging and discharging characteristics of multi-energy conversion devices in power grids, as well as the response uncertainties of these devices, are studied, and a source, load, and storage uncertainty model is established. Then, based on the Markov random field theory and the energy prior model, the dynamic partition model and its solution algorithm for the multi-energy power grid are proposed. Finally, a simulation system is established based on the actual operating data of a multi-energy power grid, and the proposed method is simulated and analyzed. The results indicate that the energy balance partition optimization method proposed in this article is effective. The application of the method proposed in this article can fully leverage the regulatory potential of energy conversion equipment, effectively reduce the proportion of traditional energy supply and peak shaving capacity, and improve the utilization rate of renewable energy.