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
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;
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
DOI :
10.1109/CAMSAP.2013.6714109