Optimal Planning of Fast EV Charging Stations in a Coupled Transportation and Electrical Power Distribution Network

Electric Vehicles (EVs) can effectively mitigate global warming issues while ensuring energy security, when compared with conventional fuel-based vehicles. Therefore, proper planning and development of charging infrastructure are essential to promote EVs. This paper proposes a multi-objective formulation to determine fast charging stations’ optimal placement and sizing on intra-city corridors in a coupled transportation and Electrical Power Distribution Network (EPDN). The proposed formulation does a distance-based mapping between all transportation and EPDN nodes for precisely observing the impact of EV charging on EPDN. The proposed planning simultaneously considers the objectives and constraints of the transportation network and EPDN while satisfying the EV charging requirements. The EV charging demand, utilized in planning, is predicted using the Random Forest technique while considering the day type, hourly weather, and traffic flow that affect the forecasting accuracy. The improved Particle Swarm Optimization with Constriction Factor solves the proposed formulation for a 30-node EPDN coupled with a 25-node transportation network. The analysis of various cases, including varying initial State-Of-Charge of EVs and percentage growth of EVs per year, proves the efficacy and robustness of the proposed work.
Note to Practitioners
—The planned deployment of charging infrastructure is critical to facilitate EVs’ adoption and sustainable growth of EV industries. Since, EV charging stations couple transportation network and EPDN, the planning strategy should consider requirements of both networks. For satisfactory driving experience of EV users, the planning should also consider driving range constraints and charging requirements of EV users. Several works on charging infrastructure planning have been carried out. However, several aspects relevant to EV users, transportation networks, EPDN, and determining EV charging demand have been overlooked in existing literature (as evidenced through Table comparisonlitercomparisonliter). These aspects must be considered simultaneously while planning charging stations. Hence, this work proposes a planning strategy for optimal placement and sizing of fast EV charging stations in a metropolitan city connecting multiple suburbs while considering several aspects of transportation networks and EPDNs. The proposed strategy can be utilized by utilities for efficient deployment of charging infrastructure on metropolitan city intra-city corridors. It establishes a distance-based mapping between all transportation and EPDN nodes for observing the impact of EV charging on EPDN. The determination of EV charging demand is a crucial step in the planning, which is determined by forecasting hourly traffic flow while considering several key attributes. The proposed approach achieves the EPDN objectives of reducing power loss, voltage deviation, and total charging stations’ establishment cost, and transportation network objectives of maximising captured traffic flow while satisfying driving range constraints and charging requirements of EVs. Therefore, the focus is to utilize the existing grid infrastructure optimally while achieving the objectives and satisfying constraints of EV users, transportation network, and EPDN. Relevant case studies demonstrate the efficacy and robustness of proposed approach. The uncertainties in EVs’ injections and arrival/ departure times will be considered in our future work.