DocumentCode
2924742
Title
Distributed demand response for plug-in electrical vehicles in the smart grid
Author
Zhao Tan ; Peng Yang ; Nehorai, Arye
Author_Institution
Preston M. Green Dept. of Electr. & Syst. Eng., Washington Univ. in St. Louis, St. Louis, MO, USA
fYear
2013
fDate
15-18 Dec. 2013
Firstpage
468
Lastpage
471
Abstract
In this paper, we propose a new model of demand response management for the future smart grid that integrates plug-in electric vehicles. A price scheme considering fluctuation cost is developed. We consider a market where users have the flexibility to sell back the energy generated from their distributed generators or the energy stored in their plug-in electric vehicles. A distributed optimization algorithm based on the alternating direction method of multipliers is developed to solve the optimization problem, in which consumers need to report their aggregated load only to the utility company, thus ensuring their privacy. Consumers can update their load scheduling simultaneously and locally to speed up the optimization computing. Using numerical examples, we show the demand curve is flattened after the optimization, thus reducing the cost paid by the utility company. The distributed algorithm is also shown to reduce the users´ daily bills.
Keywords
demand side management; electric vehicles; optimisation; power markets; pricing; scheduling; smart power grids; demand curve; distributed demand response; distributed generators; distributed optimization algorithm; fluctuation cost; load scheduling; plug-in electrical vehicles; power market; price scheme; smart grid; Batteries; Companies; Electric vehicles; Electricity; Load management; Optimization; Smart grids;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 IEEE 5th International Workshop on
Conference_Location
St. Martin
Print_ISBN
978-1-4673-3144-9
Type
conf
DOI
10.1109/CAMSAP.2013.6714109
Filename
6714109
Link To Document