DocumentCode :
3665860
Title :
Coordinated optimization of PHEVs for frequency regulation capacity bids using hierarchical game
Author :
Jun Tan;Lingfeng Wang
Author_Institution :
Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, 53211, USA
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
This paper proposes a holistic framework for plug-in hybrid electric vehicles (PHEVs) to participate in frequency regulation in a deregulated electricity market. It is challenging to use PHEVs as frequency regulation units since conflicts of interests exist among PHEVs, aggregators and Transmission System Operator (TSO). PHEVs are also facing various uncertainties from power prices and the available regulation capacities. These challenges motivate us to model the system using a hierarchical game. At the upper level of the hierarchical game, the frequency regulation capacity bids of aggregators are formulated as a non-cooperative game. Based on the frequency regulation prices obtained from the non-cooperative game, we formulate a Markov game to coordinate the charging process of PHEVs at the lower level. The Markov game will optimize the regulation capacity of the aggregator and strengthen its ability in bidding a more favorable frequency regulation price in the upper level game. Thus, the benefits are well accommodated among PHEVs, aggregators and TSO in the proposed game-theoretic framework. Furthermore, the uncertainties from power prices and available regulation capacities are handled very well by the proposed non-cooperative game and Markov game respectively. Finally, various simulations are carried out to validate the effectiveness of the proposed hierarchical game approach.
Keywords :
"Markov processes","Hybrid electric vehicles"
Publisher :
ieee
Conference_Titel :
Power & Energy Society General Meeting, 2015 IEEE
ISSN :
1932-5517
Type :
conf
DOI :
10.1109/PESGM.2015.7286331
Filename :
7286331
Link To Document :
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