Optimal spatio-temporal scheduling for Electric Vehicles and Load Aggregators considering response reliability

The increasing power in the demand side, the large-scale Electric Vehicles' (EVs) randomness in charging/discharging modes and uncertainty in demand response are posing a threat to the stable operation and security of power systems. A spatio-temporal bi-layers scheduling model for EVs and Load Aggregators (LAs) considering response reliability is proposed in the paper. In the upper layer, the indices of charging urgency and discharging adequacy are established to describe the controllability of EVs. Further, the EVs are sequenced, and the upper and lower boundaries of controllable power domain are determined. Then, the optimal nodal schedulable load is obtained through an improved optimal power flow model considering the spatial characteristics. In the lower layer, pricing strategies for charging/discharging considering the response reliability of LAs and EVs are developed, and the optimal scheduling strategies are built. Finally, the effectiveness of the proposed model is verified through a modified IEEE 33 system, in addition, impacts of response reliability on the energy allocation and economic benefits are analyzed in the case study.