DocumentCode :
3301279
Title :
Management of electric vehicle charging to mitigate renewable generation intermittency and distribution network congestion
Author :
Caramanis, Michael ; Foster, Justin M.
Author_Institution :
Coll. of Eng., Div. of Syst. Eng., Boston Univ., Boston, MA, USA
fYear :
2009
fDate :
15-18 Dec. 2009
Firstpage :
4717
Lastpage :
4722
Abstract :
We consider the management of electric vehicle (EV) loads within a market-based electric power system control area. EV load management achieves cost savings in both (i) EV battery charging and (ii) the provision of additional regulation service required by wind farm expansion. More specifically, we develop a decision support method for an EV load aggregator or energy service company (ESCo) that controls the battery charging for a fleet of EVs. A hierarchical decision making methodology is proposed for hedging in the day-ahead market and for playing the real-time market in a manner that yields regulation service revenues and allows for negotiated discounts on the use of distribution network payments. Amongst several potential solutions that are available, we employ a rolling horizon look-ahead stochastic dynamic programming algorithm and report some typical computational experience.
Keywords :
decision making; dynamic programming; electric vehicles; load management; power system control; stochastic programming; EV load aggregator; decision support method; distribution network congestion; distribution network payments; electric vehicle charging; electric vehicle load management; energy service company; hierarchical decision making; market-based electric power system control; renewable generation intermittency; rolling horizon look-ahead stochastic dynamic programming algorithm; wind farm expansion; Batteries; Control systems; Costs; Electric vehicles; Energy management; Load management; Power system control; Power system management; Wind energy generation; Wind farms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2009.5399955
Filename :
5399955
Link To Document :
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