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Distributed Electric Vehicles Charging Management Considering Time Anxiety and Customer Behaviors

Amro Alsabbagh, Brian Wu, Chengbin Ma

2020IEEE Transactions on Industrial Informatics97 citationsDOI

Abstract

This article proposes a charging management of electric vehicles (EVs) that considers time anxieties and different behaviors of EV customers. The time anxiety concept is newly presented to address some uncertain events that may happen meanwhile charging of EVs, affect their charging patterns, and prevent them from meeting their energy demands. The working principle of the concept relies on prioritizing the charging before the event occurrences, and thus changing the EV charging patterns. Based on this concept, four different EV customer behaviors are proposed and their influences are investigated. The EV charging problem is formulated as a generalized nash equilibrium (NE) game, in which each EV minimizes its charging cost given its charging requirements and the charging facility constraints. The solution is developed on the basis of receding horizon optimization and reached iteratively in a distributed manner. Detailed simulation and comparison results are introduced to verify the effectiveness of the proposed charging management with the different time-anxiety-based EV customer behaviors.

Topics & Concepts

Electric vehicleComputer scienceCharging stationNash equilibriumEnergy managementGame theoryTime horizonEnergy (signal processing)SimulationAutomotive engineeringMathematical optimizationEngineeringPower (physics)MathematicsQuantum mechanicsStatisticsMathematical economicsPhysicsElectric Vehicles and InfrastructureAdvanced Battery Technologies ResearchSmart Grid Energy Management