Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/214162
Title: Optimal Management for Parking-Lot Electric Vehicle Charging by Two-Stage Approximate Dynamic Programming
Authors: Lei Zhang;Yaoyu Li
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/214162
volume: 8
issue: 4
More Information: 1722,
1730
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7360236.pdf1.11 MBAdobe PDF
Title: Optimal Management for Parking-Lot Electric Vehicle Charging by Two-Stage Approximate Dynamic Programming
Authors: Lei Zhang;Yaoyu Li
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/214162
volume: 8
issue: 4
More Information: 1722,
1730
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7360236.pdf1.11 MBAdobe PDF
Title: Optimal Management for Parking-Lot Electric Vehicle Charging by Two-Stage Approximate Dynamic Programming
Authors: Lei Zhang;Yaoyu Li
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/214162
volume: 8
issue: 4
More Information: 1722,
1730
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7360236.pdf1.11 MBAdobe PDF