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An Optimal and Distributed Demand Response Strategy With Electric Vehicles in the Smart Grid
被引:191
作者:
Tan, Zhao
[1
]
Yang, Peng
[1
]
Nehorai, Arye
[1
]
机构:
[1] Washington Univ, Preston M Green Dept Elect & Syst Engn Dept, St Louis, MO 63130 USA
关键词:
Alternating direction method of multipliers;
demand response;
distributed optimization;
electric vehicle;
fluctuation cost;
smart grid;
SIDE MANAGEMENT;
INTEGRATION;
GENERATION;
SYSTEMS;
D O I:
10.1109/TSG.2013.2291330
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
In this paper, we propose a new model of demand response management for the future smart grid that integrates plug-in electric vehicles and renewable distributed generators. 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 loads only to the utility company, thus ensuring their privacy. Consumers can update their loads scheduling simultaneously and locally to speed up the optimization computing. Using numerical examples, we show that the demand curve is flattened after the optimization, even though there are uncertainties in the model, thus reducing the cost paid by the utility company. The distributed algorithms are also shown to reduce the users' daily bills.
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页码:861 / 869
页数:9
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