Optimal Planning of Distribution Systems and Charging Stations Considering PV-Grid-EV Transactions
Haotian Yao, Yue Xiang, Chenghong Gu, Junyong Liu
Abstract
Uncertainties associated with large-scale deployment of electric vehicles (EVs) and photovoltaic (PV) pose challenges to distribution network expansion planning (DNEP). This paper proposes an optimal planning method for EV charging stations (EVCS) and distribution systems to accommodate the ever-increasing uncertainties. It is achieved by entailing PV-grid-EV transactions, which enables EVCS and PV prosumers to trade energy to make profits while complying with grid securities. It offers a cost-effective operational alternative to long-term planning, which would otherwise result in PV curtailment or unnecessary DNEP. The transactive market operates on a peer-to-peer (P2P) basis and is cleared via a decentralized algorithm to protect privacy and enable autonomous decision-making. EVCS is incentivized by a designed network charge, quantifying its impact on adhering to security constraints from both long-term and short-term perspectives. Considering EV users’ charging decisions, we derive optimal EV charging prices to regulate EV charging flow. We employ multiple linearization techniques to ensure the convergence of the non-convex model. Results demonstrate that the proposed method enables the distribution networks to accommodate the large-scale integration of EV and PV more effectively.