This paper proposes an intelligent method for scheduling usage of available energy storage capacity from plugin hybrid electric vehicles (PHEV) and electric vehicles (EV). The batteries on these vehicles can either provide power to the grid when parked, known as vehicle- to-grid (V2G) concept or take power from the grid to charge the batteries on the vehicles. A scalable parking lot model is developed with different parameters assigned to fleets of vehicles. The size of the parking lot is assumed to be large enough to accommodate the number of vehicles performing grid transactions. In order to figure out the appropriate charge and discharge times throughout the day, binary particle swarm optimization is applied. Price curves from the California ISO database are used in this study to have realistic price fluctuations. Finding optimal solutions that maximize profits to vehicle owners while satisfying system and vehicle owners' constraints is the objective of this study. Different fleets of vehicles are used to approximate varying customer base and demonstrate the scalability of parking lots for V2G. The results are compared for consistency and scalability. Discussions on how this technique can be applied to other grid issues such as peaking power are included at the end.
C. Huston et al., "Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions," Proceedings of the IEEE Energy 2030 Conference, 2008 (2008, Atlanta, GA), pp. 1-8, Institute of Electrical and Electronics Engineers (IEEE), Nov 2008.
The definitive version is available at http://dx.doi.org/10.1109/ENERGY.2008.4781051
IEEE Energy 2030 Conference, 2008 (2008: Nov. 17-18, Atlanta, GA)
Electrical and Computer Engineering
National Science Foundation (U.S.)
United States. Department of Education
Keywords and Phrases
Energy Storage Capacity; Plug-In Hybrid Electric Vehicles; Vehicle-To-Grid; Electric vehicles
International Standard Book Number (ISBN)
Article - Conference proceedings
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