A Game-Theoretical Scheme in the Smart Grid With Demand-Side Management: Towards a Smart Cyber-Physical Power Infrastructure

被引:77
作者
Bu, Shengrong [1 ]
Yu, F. Richard [1 ]
机构
[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
关键词
Cyber-physical systems; smart grid; demand-side management; real-time pricing; LOAD CONTROL; ELECTRICITY; PRICE; MODEL;
D O I
10.1109/TETC.2013.2273457
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The smart grid is becoming one of the fundamental cyber-physical systems due to the employment of information and communication technology. In the smart grid, demand-side management (DSM) based on real-time pricing is an important mechanism for improving the reliability of the grid. Electricity retailers in the smart grid can procure electricity from various supply sources, and then sell it to the customers. Therefore, it is critical for retailers to make effective procurement and price decisions. In this paper, we propose a novel game-theoretical decision-making scheme for electricity retailers in the smart grid using real-time pricing DSM. We model and analyze the interactions between the retailer and electricity customers as a four-stage Stackelberg game. In the first three stages, the electricity retailer, as the Stackelberg leader, makes decisions on which electricity sources to procure electricity from, how much electricity to procure, and the optimal retail price to offer to the customers, to maximize its profit. In the fourth stage, the customers, who are the followers in the Stackelberg game, adjust their individual electricity demand to maximize their individual utility. Simulation results show that the retailer and customers can achieve a higher profit and higher utility using our proposed decision-making scheme. We also analyze how the system parameters affect the procurement and price decisions in the proposed decision-making scheme.
引用
收藏
页码:22 / 32
页数:11
相关论文
共 34 条
[21]   A Stochastic-Based Decision-Making Framework for an Electricity Retailer: Time-of-Use Pricing and Electricity Portfolio Optimization [J].
Hatami, Alireza ;
Seifi, Hossein ;
Sheikh-El-Eslami, Mohammad Kazem .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (04) :1808-1816
[22]   Ordering Electricity via Internet and its Potentials for Smart Grid Systems [J].
Jin, Tongdan ;
Mechehoul, Mahmoud .
IEEE TRANSACTIONS ON SMART GRID, 2010, 1 (03) :302-310
[23]   Quantifying price risk of electricity retailer based on CAPM and RAROC methodology [J].
Karandikar, R. G. ;
Khaparde, S. A. ;
Kulkarni, S. V. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2007, 29 (10) :803-809
[24]  
Mas-Colell A., 1995, MICROECONOMIC THEORY
[25]  
Moholkar A, 2004, 2004 IEEE PES POWER SYSTEMS CONFERENCE & EXPOSITION, VOLS 1 - 3, P1030
[26]   Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments [J].
Mohsenian-Rad, Amir-Hamed ;
Leon-Garcia, Alberto .
IEEE TRANSACTIONS ON SMART GRID, 2010, 1 (02) :120-133
[27]   Demand Response Scheduling by Stochastic SCUC [J].
Parvania, Masood ;
Fotuhi-Firuzabad, Mahmud .
IEEE TRANSACTIONS ON SMART GRID, 2010, 1 (01) :89-98
[28]  
Rajkumar R, 2010, DES AUT CON, P731
[29]   A Framework for Evaluation of Advanced Direct Load Control With Minimum Disruption [J].
Ramanathan, Badri ;
Vittal, Vijay .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (04) :1681-1688
[30]  
Rasmusen E., 2007, Games and Information: an Introduction to Game Theory