The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles

With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs. • Electric vehicle traveling and charging behavior simulated by Monte Carlo algorithm. • Mixed-integer linear programming with digital description on interaction boundary. • Commuting to and from workplace causes more operational burden on distribution grid. • Orderly charging at valley period reduces 66.7% of load range when a EV per 10 people. • V2G with participation of 40% causes lower load range than that of 100% orderly charging.