logo

SCIENCE CHINA Information Sciences, Volume 62 , Issue 11 : 212203(2019) https://doi.org/10.1007/s11432-018-9814-4

A Stackelberg game approach for demandresponse management of multi-microgrids with overlapping sales areas

More info
  • ReceivedDec 3, 2018
  • AcceptedJan 31, 2019
  • PublishedSep 24, 2019

Abstract

Microgrids are increasingly participating directly in the electricity market as sellers in order to fulfill the power demand in specific regions. In this study, we consider a demand response management model for multi-microgrids and multi-users, with overlapping sales areas. We construct a Stackelberg game model of microgrids and users, and then analyze the equilibrium strategies systematically. As such, we prove that there is a unique Stackelberg equilibrium solution for the game. In equilibrium, the electricity price strategies of the microgrids and the demand strategies of the users achieve a balance. Furthermore, we propose a numerical algorithm, supported by a simulation, to compute the equilibrium solution and give the proof of convergence.


References

[1] Lu Q, Mei S W. A review of modern power system. J Syst Sci Math Sci, 2012, 32: 1207--1225. Google Scholar

[2] Deng R, Yang Z, Chow M Y. A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches. IEEE Trans Ind Inf, 2015, 11: 570-582 CrossRef Google Scholar

[3] Saad W, Han Z, Poor H. Game-Theoretic Methods for the Smart Grid: An Overview of Microgrid Systems, Demand-Side Management, and Smart Grid Communications. IEEE Signal Process Mag, 2012, 29: 86-105 CrossRef ADS Google Scholar

[4] Yu M, Hong S H. A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach. IEEE Trans Smart Grid, 2016, 7: 879-888 CrossRef Google Scholar

[5] Ma L, Liu N, Zhang J. Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach. IEEE Trans Ind Inf, 2016, 12: 1930-1942 CrossRef Google Scholar

[6] Soliman H M, Leon-Garcia A. Game-Theoretic Demand-Side Management With Storage Devices for the Future Smart Grid. IEEE Trans Smart Grid, 2014, 5: 1475-1485 CrossRef Google Scholar

[7] Mohsenian-Rad A H, Wong V W S, Jatskevich J. Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid. IEEE Trans Smart Grid, 2010, 1: 320-331 CrossRef Google Scholar

[8] Park S, Lee J, Bae S. Contribution-Based Energy-Trading Mechanism in Microgrids for Future Smart Grid: A Game Theoretic Approach. IEEE Trans Ind Electron, 2016, 63: 4255-4265 CrossRef Google Scholar

[9] Wei W, Liu F, Mei S. Energy Pricing and Dispatch for Smart Grid Retailers Under Demand Response and Market Price Uncertainty. IEEE Trans Smart Grid, 2015, 6: 1364-1374 CrossRef Google Scholar

[10] Mei S W, Wei W. Hierarchal game and its applications in the smart grid. J Syst Sci Math Sci, 2015, 34: 1331--1344. Google Scholar

[11] Yu M, Hong S H. Supply-demand balancing for power management in smart grid: A Stackelberg game approach. Appl Energy, 2016, 164: 702-710 CrossRef Google Scholar

[12] Lee J H, Guo J, Choi J K. Distributed Energy Trading in Microgrids: A Game Theoretic Model and Its Equilibrium Analysis. IEEE Trans Ind Electron, 2015, 62: 3524-3533 CrossRef Google Scholar

[13] Maharjan S, Zhu Q, Zhang Y. Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach. IEEE Trans Smart Grid, 2013, 4: 120-132 CrossRef Google Scholar

[14] Chai B, Chen J, Yang Z. Demand Response Management With Multiple Utility Companies: A Two-Level Game Approach. IEEE Trans Smart Grid, 2014, 5: 722-731 CrossRef Google Scholar

[15] Ma G Q, Li J, Li T, et al. A demand response management model of multiple microgrids with different sales areas based on stackelberg game theory. In: Proceedings of the 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems, Groningen, 2018. 160--165. Google Scholar

[16] Zeng H, Yu J, Kang X. Countering JPEG anti-forensics based on noise level estimation. Sci China Inf Sci, 2018, 61: 032103 CrossRef Google Scholar

[17] Bolton P, Dewatripont M. Contract Theory. Cambridge: MIT Press, 2005. Google Scholar

[18] Lovász L, Plummer M. Matching Theory. New York: North-Holland Publishing, 1986. Google Scholar

[19] Klemperer P. Auction Theory: A Guide to the Literature. J Economic Surveys, 1999, 13: 227-286 CrossRef Google Scholar

[20] Bacsar T, Olsder G J. Dynamic Noncooperative Game Theory. 2nd ed. New York: Academic Press, 1995. Google Scholar

[21] Zhang W Y. Game Theory Information Economics (in Chinese). Shanghai: Shanghai People's Publishing House, 2012. Google Scholar

[22] Yates R D. A framework for uplink power control in cellular radio systems. IEEE J Sel Areas Commun, 1995, 13: 1341-1347 CrossRef Google Scholar

[23] Tang C, Li X, Wang Z. Cooperation and distributed optimization for the unreliable wireless game with indirect reciprocity. Sci China Inf Sci, 2017, 60: 110205 CrossRef Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备17057255号       京公网安备11010102003388号