Placement of EV Charging Stations --- Balancing Benefits among Multiple Entities
TLDR
A nested logit model is employed to analyze the charging preference of the individual consumer and predict the aggregated charging demand at the charging stations and it is shown that the charging station placement is highly consistent with the heatmap of the traffic flow.Abstract:
This paper studies the problem of multi-stage placement of electric vehicle (EV) charging stations with incremental EV penetration rates. A nested logit model is employed to analyze the charging preference of the individual consumer (EV owner), and predict the aggregated charging demand at the charging stations. The EV charging industry is modeled as an oligopoly where the entire market is dominated by a few charging service providers (oligopolists). At the beginning of each planning stage, an optimal placement policy for each service provider is obtained through analyzing strategic interactions in a Bayesian game. To derive the optimal placement policy, we consider both the transportation network graph and the electric power network graph. A simulation software --- The EV Virtual City 1.0 --- is developed using Java to investigate the interactions among the consumers (EV owner), the transportation network graph, the electric power network graph, and the charging stations. Through a series of experiments using the geographic and demographic data from the city of San Pedro District of Los Angeles, we show that the charging station placement is highly consistent with the heatmap of the traffic flow. In addition, we observe a spatial economic phenomenon that service providers prefer clustering instead of separation in the EV charging market.read more
Citations
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Journal ArticleDOI
PEV Fast-Charging Station Siting and Sizing on Coupled Transportation and Power Networks
TL;DR: A mixed-integer linear programming model is formulated for PEV fast-charging station planning considering both transportation and electrical constraints based on CFRLM, which can be solved by deterministic branch-and-bound methods.
Journal ArticleDOI
Stochastic Dynamic Pricing for EV Charging Stations With Renewable Integration and Energy Storage
TL;DR: A new metric to assess the impact on power grid without solving complete power flow equations is proposed and a safeguard of profit is incorporated in the model to protect service providers from severe financial losses.
Journal ArticleDOI
Optimal Charging Scheduling by Pricing for EV Charging Station With Dual Charging Modes
TL;DR: This work forms a customer attrition minimization problem to minimize the number of EVs that leave the charging station without being charged and proposes an optimal pricing approach to guide and coordinate the charging processes of EVs in thecharging station.
Journal ArticleDOI
A Second-Order Cone Programming Model for Planning PEV Fast-Charging Stations
TL;DR: A stochastic mixed-integer second-order cone programming model for PEV fast-charging station planning that considers heterogeneous PEV driving ranges and charging demands and considers the transportation network constraints of CFRLM_SP and the power network constraints with ac power flow.
Journal ArticleDOI
Cooperative Management for PV/ESS-Enabled Electric Vehicle Charging Stations: A Multiagent Deep Reinforcement Learning Approach
TL;DR: This article proposes a method that can compute the scheduling solutions of multiple electric vehicle charging stations in a distributed manner while handling run-time time-varying dynamic data and achieves a desirable performance in terms of reducing the operation costs of electric vehiclecharging stations.
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