IEEE Transactions on Smart Grid · 2015 · 161 citations · 17 references
EngineeringDecision SciencesDemand ForecastingElectric Vehicle EngineeringElectric Vehicle TechnologyCharging SystemsElectric Vehicle SimulationEnergy Management StrategiesParking ManagementState Of Charge EstimationState Of Charge ManagementApproximate Dynamic ProgrammingArrival Time PredictionCharging OptimizationCharging Strategy OptimizationCharging TimeEnergy Cost OptimizationPlug-in Electric Vehicle ChargingPoisson Process Models
This paper targets the day-time charging scenario for plug-in electric vehicles at parking-lots near commercial places, where most vehicles have extended parking time. Compared with night-time charge scenarios for residential buildings, commercial building parking-lot charging during day-time feature significant stochastic vehicle arrival and departure, as well as highly dynamic electricity price. A two-stage approximate dynamic programming framework is proposed to determine the optimal charging strategy, utilizing the predicted short-term future information and long-term estimation from historical data. All the vehicles are desired to be charged to full prior to the departure time specified under constrained total charging capacity. The uncharged amount is subject to a significant penalty cost. Simulation scenarios are created by modeling the vehicle arrival behavior as Poisson process, including arrival time, departure time, and arrival state of charge. The simulation results show that the proposed method can significantly decrease the energy cost.
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Sara Deilami, Amir S. Masoum, Paul Moses et al. · IEEE Transactions on Smart Grid · 2011 · 1.1K citations
Engineering, Infrastructure Planning, Electric Vehicle Engineering +16