Centralized bi-level spatial-temporal coordination charging strategy for area electric vehicles

Abstract

Increased penetration of electric vehicles (EVs) is expected to impact power system performance in adverse ways, e.g., overloading, uncertain power quality, and increased voltage fluctuation, particularly at the distribution level. Most EV charging control strategies that have been proposed only benefit the grid or EV users. A centralized EV charging strategy based on bilevel optimization is proposed in this paper with the objectives of deriving benefits for the grid and EV users simultaneously. The proposed strategy involves distributing the EV charging load more beneficially across both spatial and temporal levels. In the spatial problem, the whole fleet of EVs is controlled to minimize load variance as spatial coordination, with total charging rate and energy needed as the constraint. While in the temporal problem, EVs in each aggregator are controlled to minimize the charging cost or maximize the EV user's degree of satisfaction with each aggregator's charging rate and energy needed as the constraint. The proposed bi-level charging strategy is transformed to a single-stage optimization problem and solved using the classical optimization method. The impacts of uncontrolled charging on the grid and EV users are studied using the Monte Carlo Simulation (MCS) method. Then, the effectiveness of the proposed charging strategy is demonstrated via results obtained in the MCS.