Coordination of V2G and Distributed Wind Power Using the Storage-like Aggregate PEV Model

A plug-in electric vehicle (PEV) fleet utilizing vehicle-to-grid (V2G) technology, i.e., a V2G fleet, can behave as a storage system, e.g., promoting integration of distributed wind power resources. However, because the PEVs' behaviors are stochastic and a V2G fleet's population is large, three technical difficulties hinder the utilization of V2G: 1) charging demand forecasting; 2) ahead-of-time charge and discharge scheduling; 3) real-time charge and discharge power dispatching. This paper utilizes a storage-like aggregate model (SLAM) of a V2G fleet that employs aggregated parameters to represent energy and power constraints of the entire PEV population, and therefore reduces the difficulty of forecasting. Then, a stochastic joint power scheduling strategy for a distributed wind generation and a V2G fleet based on the SLAM is proposed aiming to promote the integration of distributed wind power by V2G technology, which has low computational burden. A real-time heuristic strategy is designed to efficiently dispatch the power schedules to PEVs and guarantee the modeling accuracy of SLAM and effectiveness of the proposed power scheduling strategy.