Optimal Management for Parking-Lot Electric Vehicle Charging by Two-Stage Approximate Dynamic Programming

• Published in: IEEE transactions on smart grid Vol. 8; no. 4; pp. 1722 - 1730
• Main Authors: Zhang, Lei, Li, Yaoyu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: approximate dynamic programming; Approximation methods; Batteries; Charge simulation; Charging management; Charging stations; Commercial buildings; Computer simulation; Constraints; demand response; Dynamic programming; electric vehicle; Electric vehicle charging; Electric vehicles; Electricity pricing; Modelling; Night; Optimization; Parking; Poisson density functions; Probability theory; Residential buildings; smart grid; State of charge; Stochastic processes; Vehicles
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2015.2505298

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.