Dynamic Double-Layer Energy Management Strategy for Park Power Grid Considering Vehicle-to-Grid

Abstract

This paper proposes a two-layer optimal control strategy for the park power grid, aiming at addressing the energy management challenges arising from the fluctuations in the output of clean energy sources and the random changes in the number of electric vehicles (EV) at the charging station. The upper layer establishes a dynamic optimization model of landscape storage based on the model predictive control technology, which comprehensively incorporates both the battery energy storage system of the park and the battery energy storage system of EVs, enabling them to participate in balancing the energy demand of the power grid, while the lower layer considers meeting the charging demand of EV owners and the vehicle-to-grid management demand of upper layer for energy dispatching simultaneously, and formulates an orderly charging and discharging strategy for EVs in the parking lot of the power grid. The simulation results show that the proposed strategy effectively can integrate scattered EV storage in the park into a unified virtual energy storage system, expand the energy storage capacity of the grid, and increase the consumption of renewable distributed generation supply, ultimately improving economic benefits for the park grid.

Keywords

• park power grid
• electric vehicle (ev) grid connection
• electric vehicle virtual energy storage
• model predictive control
• hybrid energy storage system