Optimization of Home Loads scheduling in Demand Response

수요 반응에서 가정용 전력기계의 최적화된 스케쥴링 기법

  • 김태완 (연세대학교 무선네트워크 연구실) ;
  • 이성진 (연세대학교 무선네트워크 연구실) ;
  • 이상훈 (연세대학교 무선네트워크 연구실)
  • Received : 2010.06.03
  • Accepted : 2010.09.02
  • Published : 2010.09.30

Abstract

In recent years, the smart grid technique for maximizing the energy efficiency of power networks has received a great deal of attentions. In particular, the Demand Response is a core technology differentiated from the present power network under the smart grid paradigm. To minimize the electric cost and maximize users' satisfaction, this paper proposes a unique scheduling algorithm derived by using optimization where the characteristics of various home appliances are taken into account. For this goal, we represent mathematical consumption patterns of the electric loads and propose the optimal scheduling scheme based on the importance factor of each device during one day. In the simulation results, we demonstrate the effectiveness of the proposed algorithm in the viewpoint of the minimal electric costs utilizing real statistical figures.

최근 전 세계적으로 많은 관심을 받고 있는 스마트 그리드는 기존 전력망의 에너지 효율을 최적화하고자 하는 차세대 전력망을 말한다. 그 중에서 수요 반응(Demand Response)은 현재 전력망과 차별화되는 핵심 기술이다. 가정에서 전력 요금의 최소화 및 사용자의 만족도를 최대화하기 위해, 본 논문은 가정에서 사용하고 있는 여러 종류의 전력 기계의 특성을 활용하여, 최적화 문제를 통한 스케쥴링 알고리듬을 제안한다. 여러 전력 기계의 소비패턴을 수학적 모델로 유도하였으며, 하루 동안 각 시간에서 전력 기계의 중요도에 따른 최적화된 스케쥴링 기법을 제안한다. 실제 통계 수치를 활용한 본 논문의 실험 결과에서는 제안하는 최적화 스케쥴링 알고리듬이 전력요금을 최소화하는 유틸리티에 매우 효과적인 것으로 나타났다.

Keywords

References

  1. Massoud Amin, S. and Wollenberg, B.F., "Toward a Smart Grid : Power Delivery for the 21st Century," Power and Energy Magazine IEEE}, Vol.3, Issue.5, pp.34-41, Sep. 2005.
  2. Ye Huang, Amos Brocco, Pierre Kuonen, Mich'ele Courant, and B'eat Hirsbrunner, "SmartGRID: A Fully Decentralized Grid Scheduling Framework Supported by Swarm Intelligence," Grid and Cooperative Computing), Oct. 2008.
  3. M. H. Albadi, and E. F. El-Saadany, "Demand Response in Electricity Markets: An Overview," Power Engineering Society General Meeting, 2007. IEEE}, June. 2007.
  4. US Department of Energy, "Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them," Report to the United States Congress, February 2006. Available online: http://eetd.lbl.gov
  5. Michael Angelo A. Pedrasa, Ted D. Spooner, and Iain F. MacGill, "Scheduling of Demand Side Resources Using Binary Particle Swarm Optimization," IEEE Trans. Power Systems}, Vol.24, No.3, pp.1173-1181, Aug. 2008.
  6. Tsair-Fwu Lee, Ming-Yuan Cho, Ying-Chang Hsiao, Pei-Ju Chao, and Fu-Min Fang, "Optimization and Implementation of a Load Control Scheduler Using Relaxed Dynamic Programming for Large Air Conditioner Loads," IEEE Trans. Power Systems}, Vol.23, No.2, pp.691-702, May. 2008. https://doi.org/10.1109/TPWRS.2008.919311
  7. Grayson C. Heffner, Charles A. Goldman, and Mithra M. Moezzi, "Innovative approaches to verifying demand response of water heater load control," IEEE Trans. Power Delivery), Vol.21, No.1, pp.388-397, Jan. 2006. https://doi.org/10.1109/TPWRD.2005.852374
  8. Badri Ramanathan, and Vijay Vittal, "A Framework for Evaluation of Advanced Direct Load Control With Minimum Disruption" IEEE Trans. Power Systems}, Vol.23, No.4, pp. 1681-1688, Nov. 2008. https://doi.org/10.1109/TPWRS.2008.2004732
  9. Zigbee Alliance, ZigBee Smart Energy Profile Specification, Document number 075356rl5, ZigBee Profile: 0x0109, Revision 15, 2400 Camino Ramon, Suite 375, San Ramon, CA 94583, USA 2008.