Stochastic Charging Coordination Method for Electric Vehicle (EV) Aggregator Considering Uncertainty in EV Departures

Abstract

-This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks

“…In an incentive and regulatory structure, the suggested strategy maximizes the aggregator's daily profit by participating in day-ahead and realtime markets and supplying power quality services to the distribution system operator. In [82], the stochastic scheduling of EVAs is presented, considering the uncertainties of power price and EV drivers' collective behavior. The Latin hypercube sampling (LHS) approach and a scenario-reduction methodology are used to create the suggested model.…”

Goal Programming Application for Contract Pricing of Electric Vehicle Aggregator in Join Day-Ahead Market

“…The scheduling problems of EVAs have been assessed in a number of recent papers that evaluate the impact of EVAs on various problems, including: the effects of a high EV penetration in the electricity market [16][17][18][19], modeling driving behaviors and fluctuation of electricity prices [20,21], and applying risk-based strategies [22,23].…”

Risk-based Cooperative Scheduling of Demand Response and Electric Vehicle Aggregators

“…In recent years, many studies in the area of EVs have focused on the scheduling problem of EVs' aggregation from di erent points of view including the impacts of EVs' high penetration in the market [26][27][28], investigation of uncertainty-based models to simulate EV owners' behavior and market prices [29,30], and risk-based approach [31,32]. Carpinelli et al [33] proposed a multi-objective function to optimize the operation of micro grids in the presence of a large number of EVs and renewable resources.…”