EV Charging Station Placement Considering V2G and Human Factors in Multi-Energy Systems

Abstract

This paper proposes a new planning framework to determine the optimal location, capacity, and types of EV charging stations (EVCSs) in multi-energy systems (MESs). We propose a two-stage stochastic programming approach -with scenario-based algorithms- that explicitly considers vehicle-to-grid (V2G) peculiarities (four-quadrant operation and stochastic human factors influence: V2G willingness, walking distance, and charging patterns). Considering those factors together with MES uncertainties -RES generation, load demands, and electricity price- enables a comprehensive study of V2G and MES impact on EVCS planning. The proposed approach is applied to both a purely electric distribution network (EDN) and an MES to analyze the interplay of EVCSs in different energy domains, in consideration of different V2G contracts. The obtained results underline that the sole consideration of the EDN can lead to non-optimal results, while the more comprehensive analysis leads to optimal planning of all energy resources and cost savings. Finally, we analyse how each considered factor individually impacts EVCSs planning.