Optimal scheduling strategy for orderly charging and discharging of electric vehicles based on spatio-temporal characteristics

With the development of vehicle-to-grid (V2G) technology, the disorderly access of a large number of electric vehicles (EVs) will impact the operation of the power system. Considering the uncertainty of EVs charging/discharging load on the spatio-temporal scale, this paper proposes an optimal scheduling strategy for EVs with spatio-temporal characteristics. The strategy integrates EVs into the microgrid, constructs the spatio-temporal distribution models of charging load and describes the uncertainty of electric vehicle owners’ (EVOs) charging behaviours by fuzzy theory. Considering the bounded rationality of EVOs, this paper takes the charging/discharging price of EVs as the decision variable, and the dynamic time-of-use price mechanism is used to guide EVOs to make charging/discharging decisions. Then, with the objective function of minimising the comprehensive operating cost (COC) and the peak-valley load difference (PVLD), an orderly charging/discharging scheduling model for EVs is established and the optimal scheduling strategy is given. Furthermore, the three scheduling scenarios are set up in the case study, and the maximum number of EVs to participate in scheduling is determined to be 4000. The numerical results show that the proposed scheduling strategy reduces the COC and PVLD by 17.96% and 5.21%, respectively, compared with the disorderly scheduling, and reduces the COC and PVLD by 13.35% and 5.21%, respectively, compared with the orderly scheduling without V2G, which verifies the effectiveness and superiority of the proposed scheduling strategy.