Robust Expansion Planning of Electric Vehicle Charging System and Distribution Networks

Abstract

Large integration of electric vehicles (EVs) brings uncertainties and challenges for distribution networks. Reliability and allocation of charging systems (charging stations and piles) need strong support from the distribution network, whose expansion planning would be also greatly impacted by the incremental load from the charging system. To address this issue, a collaborative planning scheme of the EV charging system and distribution networks that combines economic and reliability benefits is proposed, which is formulated as a two-stage distributionally robust optimization model considering source-load uncertainties. First, a candidate EVCS planning scheme is obtained using queuing theory. Then, system reliability is quantified by adopting the average energy not supplied index and correlated integrated into the two-stage mixed-integer linear programming model. Finally, it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm. Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies. Results indicate the planning scheme that considers economic and reliability benefit can perform better than traditional optimization methods.