Planning under uncertainty for aggregated electric vehicle charging with renewable energy supply
Authors: 
Erwin Walraven and Matthijs T. J. SpaanAuthors Info & Claims
Erwin Walraven and Matthijs T. J. SpaanAuthors Info & ClaimsAugust 2016
Pages 904 - 912
Abstract
Renewable energy sources introduce uncertainty regarding generated power in smart grids. For instance, power that is generated by wind turbines is time-varying and dependent on the weather. Electric vehicles will become increasingly important in the development of smart grids with a high penetration of renewables, because their flexibility makes it possible to charge their batteries when renewable supply is available. Charging of electric vehicles can be challenging, however, because of uncertainty in renewable supply and the potentially large number of vehicles involved. In this paper we propose a vehicle aggregation framework which uses Markov Decision Processes to control electric vehicles and deals with uncertainty in renewable supply. We present a grouping technique to address the scalability aspects of our framework. In experiments we show that the aggregation framework maximizes the profit of the aggregator, reduces cost of customers and reduces consumption of conventionally-generated power.
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Information & Contributors
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Published In
August 2016
1860 pages
ISBN:9781614996712
Sponsors
- ETINN: Essence ITN Network
- Vrije Universiteit Amsterdam: Vrije Universiteit Amsterdam, Netherlands
- PricewaterhouseCoopers: PricewaterhouseCoopers
- TANDFGROUP: Taylor & Francis Group
Publisher
IOS Press
Netherlands
Publication History
Published: 29 August 2016
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