Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

被引:1974
作者
Mohsenian-Rad, Amir-Hamed [1 ,2 ]
Wong, Vincent W. S. [1 ]
Jatskevich, Juri [1 ]
Schober, Robert [1 ]
Leon-Garcia, Alberto [2 ]
机构
[1] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada
[2] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 2E4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Demand-side management; distributed algorithms; energy consumption scheduling; energy pricing; game theory; market incentives; smart grid; smart meter; DIRECT LOAD CONTROL; ELECTRICITY;
D O I
10.1109/TSG.2010.2089069
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
Most of the existing demand-side management programs focus primarily on the interactions between a utility company and its customers/users. In this paper, we present an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid. We use game theory and formulate an energy consumption scheduling game, where the players are the users and their strategies are the daily schedules of their household appliances and loads. It is assumed that the utility company can adopt adequate pricing tariffs that differentiate the energy usage in time and level. We show that for a common scenario, with a single utility company serving multiple customers, the global optimal performance in terms of minimizing the energy costs is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. The proposed distributed demand-side energy management strategy requires each user to simply apply its best response strategy to the current total load and tariffs in the power distribution system. The users can maintain privacy and do not need to reveal the details on their energy consumption schedules to other users. We also show that users will have the incentives to participate in the energy consumption scheduling game and subscribing to such services. Simulation results confirm that the proposed approach can reduce the peak-to-average ratio of the total energy demand, the total energy costs, as well as each user's individual daily electricity charges.
引用
收藏
页码:320 / 331
页数:12
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