Hierarchical Transactive Energy Scheduling of Electric Vehicle Charging Stations in Constrained Power Distribution and Transportation Networks

Abstract

There is a growing opportunity to explore transactive energy potentials among electric vehicle charging station (EVCS) systems as the ongoing trend is toward the deployment of more distributed energy resources such as solar PV and energy storage units at EVCS premises. In this paper, we propose a multi-agent hierarchical framework for energy scheduling and trading of EVCSs considering the mobility constraints in the transportation network (TN) and the operational constraints in the power distribution network (PDN). Modeled as independent profit-driven entities, each EVCS optimally schedules its operation based on a multi-period traffic assignment problem (TAP) solved by the traffic operator (TO) agent. A modified single-sided auction mechanism with limited shared information is used to clear the electricity market based on submitted EVCS bids and offers. The resulting trading operations are shared with the PDN operator to guarantee a reliable network operation. A trading adjustment signal is sent back to market participants (i.e., EVCSs) in case of any PDN violations. We use a realistic three-phase unbalanced representation formulated as a MISOCP problem to model the PDN operation. A four-stage solution method is proposed to solve the proposed EVCS energy scheduling and trading problem. Numerical simulations performed on a modified IEEE 33-bus test system and 12-node benchmark TN prove the effectiveness of the proposed multi-agent-based hierarchical transactive market model and its solution approach for EVCSs.