DocumentCode
2003352
Title
Auction-based Energy Management System of a large-scale PHEV municipal parking deck
Author
Rahimi-Eichi, Habiballah ; Chow, Mo-Yuen
Author_Institution
Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fYear
2012
fDate
15-20 Sept. 2012
Firstpage
1811
Lastpage
1818
Abstract
The Plug-in Hybrid Electric Vehicle (PHEV) is becoming the most significant component of the future advanced transportation system and an important part of the smart grid. The energy management issue of charging a large number of PHEVs parked in a municipal parking lot with a limited amount of power available from the grid can be formulated as an optimization problem. Since the problem is basically a scalable resource allocation problem, a proportional allocation mechanism in auction theory is used to address the issue as a market-based tool. Also, a decentralized algorithm based on auction theory is developed that furnishes an updating rule to the vehicles as bidders to make the optimal decision about their next bid. This decision considers their previous bids and the price they have received from the market manager as a feedback. In this paper, considering PHEVs as price-taker bidders, we apply the auction theory method to solve the PHEV parking lot optimization problem for 10 vehicles, as a small example, and then for a large number of vehicles. The results are presented for both cases and compared to the Particle Swarm Optimization (PSO) as a well-known population-based optimization method.
Keywords
energy management systems; hybrid electric vehicles; optimisation; power markets; pricing; resource allocation; smart power grids; transportation; PSO; advanced transportation system; auction theory method; decentralized algorithm; energy management system; large-scale PHEV municipal parking deck; market-based tool; parking lot optimization problem; particle swarm optimization; plug-in hybrid electric vehicle; population-based optimization method; price-taker bidders; proportional allocation mechanism; scalable resource allocation problem; smart grid; Abstracts; Radio frequency; Resource management;
fLanguage
English
Publisher
ieee
Conference_Titel
Energy Conversion Congress and Exposition (ECCE), 2012 IEEE
Conference_Location
Raleigh, NC
Print_ISBN
978-1-4673-0802-1
Electronic_ISBN
978-1-4673-0801-4
Type
conf
DOI
10.1109/ECCE.2012.6342592
Filename
6342592
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