Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Game Theory-based Bi-Level Pricing Scheme for Smart Grid Scheduling Control Algorithm

  • Park, Youngjae (Department of Computer Science, Sogang University) ;
  • Kim, Sungwook (Department of Computer Science, Sogang University)
  • Received : 2015.03.16
  • Accepted : 2015.07.30
  • Published : 2016.06.30
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Abstract

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

Keywords

Acknowledgement

Grant : 기본연구지원

Supported by : 서강대학교

References

  1. H. K. Nguyen, J. B. Song and, Z. Han, "Demand side management to reduce peak-to-average ratio using game theory in smart grid," in Proc. IEEE INFOCOM Workshops, pp. 91-96, 2012.
  2. T. Logenthiran, D. Srinivasan, and T. Z. Shun, "Demand side management in smart grid using heuristic optimization," IEEE Trans. Smart Grid, vol. 3, pp. 1244-1252, 2012. https://doi.org/10.1109/TSG.2012.2195686
  3. A. H. Mohsenian-Rad, V. W. S. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, "Autonomous demand-side management based on gametheoretic energy consumption scheduling for the future smart grid," IEEE Trans. Smart Grid, vol. 1, pp. 320-331, 2010. https://doi.org/10.1109/TSG.2010.2089069
  4. C. Joe-Wong, S. Sen, S. Ha and M. Chiang, "Optimized day-ahead pricing for smart grids with device-specific scheduling flexibility," IEEE J. Sel. Areas Commun., vol. 30, pp. 1075-1085, 2012. https://doi.org/10.1109/JSAC.2012.120706
  5. B. Kim, Y. Zhang, M. van der Chaar, and J. Lee, "Dynamic pricing for smart grid with reinforcement learning," in IEEE INFOCOM, 2014, pp. 640-645
  6. B. Xie, W. Zhou, C. Hao, X. Ai, and J. Song, "A novel bargaining based relay selection and power allocation scheme for distributed cooperative communication networks," in Proc. IEEE VTC, 2010.
  7. Y. Zhao and H. Zhao, "Study on negotiation strategy," in Proc. IEEE PowerCon, vol. 3, pp. 1335-1338, 2002.
  8. W. Zhou, B. Xie, and C. Hao, "A novel bargaining based power allocation for coordinated multiple point transmission/reception," in Proc. ICACT, 2011, pp. 458-462.
  9. H. Goudarzi, S. Hatami, and M. Pedram, "Demand-side load scheduling incentivized by dynamic energy prices," Proc. IEEE SmartGridComm, 2011, pp. 351-356.
  10. V. Radonjic and V. A. Raspopovic, "Local ISPs pricing strategies in the repeated game concepts," in Proc. TELSIKS, 2007.
  11. Y. Park and S. Kim, "Bargaining based smart grid pricing model demand side scheduling management," ETRI J., vol. 37, no. 1, pp. 197-202, Feb. 2015. https://doi.org/10.4218/etrij.15.0114.0007
  12. W. Y. Chiu, H. Sun, and H. V. Poor, "Energy imbalance management using a robust pricing scheme," IEEE Trans. Smart Grid, vol. 4, no. 2, pp. 896-904, 2013. https://doi.org/10.1109/TSG.2012.2216554
  13. W. Y. Chiu, H. Sun, and H. V. Poor, "A multiobjective approach to multimicrogrid system design," IEEE Trans. Smart Grid, vol. 6, no. 5, pp. 2263-2272, 2015. https://doi.org/10.1109/TSG.2015.2399497
  14. Y. Wu, B. Wang, R. Liu, and T. C. Clancy, "Repeated open spectrum sharing game with cheat-proof strategies," IEEE Trans. Wireless Commun., vol. 8, no. 4, 2009.
  15. S. Kim, Game Theory Applications in Network Design, IGI Global, 2014.