A Potential Game Based Distributed Optimization Strategy for the Electricity Retailer Considering Residential Demand Response

被引:0
作者
Tu J. [1 ]
Zhou M. [1 ]
Li G. [1 ]
Luan K. [2 ]
机构
[1] State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources, North China Electric Power University, Changping District, Beijing
[2] State Grid Jiangsu Electric Power Co. Ltd., Nanjing, 210024, Jiangsu Province
来源
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2020年 / 40卷 / 02期
基金
中国国家自然科学基金;
关键词
Demand response; Distributed optimization; Electricity retailer; Potential game; Residential load;
D O I
10.13334/j.0258-8013.pcsee.190093
中图分类号
学科分类号
摘要
With the opening of electricity market and the popularization of residential intelligent home, the design and implementation of demand response (DR) projects for large-scale residents to participate in grid interaction will be one of the key points for the operation optimization of electricity retailers. In view of decision-making of the electricity retailer considering residential DR, the characteristics of residential load were analyzed in detail, and then a decision model of the electricity retailer in day-ahead market was established based on potential game, aiming at maximizing its profits with the premise of no increasing of the residential electricity cost after DR. Thereafter, in order to solve the strategies iterative problems with the large-scale residential players, a distributed parallel iterative algorithm was put forward, which could coordinate strategies updating of residential players via their community agents. The simulation results show that the proposed model can protect the residential users' interests as well as effectively reduce the cost of purchasing electricity and the peak load of the residents. The proposed algorithm can converge to Nash equilibrium in a short time, and still keep a good convergence for the large-scale residential DR. © 2020 Chin. Soc. for Elec. Eng.
引用
收藏
页码:400 / 410
页数:10
相关论文
共 25 条
  • [11] Safdarian A., Fotuhi-Firuzabad M., Lehtonen M., Optimal residential load management in smart grids: a decentralized framework, IEEE Transactions on Smart Grid, 7, 4, pp. 1836-1845, (2016)
  • [12] Zhang J., Research on models and algorithms for distributed optimization based on the Non-cooperative games, (2014)
  • [13] Liang Y., Liu F., Mei S., A state-based potential game approach for distributed economic dispatch, Journal of Systems Science and Mathematical Sciences, 36, 3, pp. 413-425, (2016)
  • [14] Zeng J., Wang Q., Liu J., Et al., An operation optimization algorithm of microgrid based on potential game, Proceedings of the CSEE, 37, 24, pp. 7195-7204, (2017)
  • [15] Liang Y., Liu F., Mei S., Distributed real-time economic dispatch in smart grids: A state-based potential game approach, IEEE Transactions on Smart Grid, 9, 5, pp. 4194-4208, (2018)
  • [16] Wang X., Xiao Y., Wang X., Study and analysis on supply-demand interaction of power systems under new circumstances, Proceedings of the CSEE, 34, 29, pp. 5018-5028, (2014)
  • [17] Monderer D., Shapley L.S., Potential games, Games and Economic Behavior, 14, 1, pp. 124-143, (1996)
  • [18] Bao M., Ding Y., Shao C., Et al., Review of Nordic electricity market and its suggestions for China, Proceedings of the CSEE, 37, 17, pp. 4881-4892, (2017)
  • [19] Zhu Z., Zou B., Statistical analysis of day-ahead prices in PJM market, Automation of Electric Power Systems, 30, 23, pp. 53-57, (2006)
  • [20] Chen Z., Wu L., Fu Y., Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization, IEEE Transactions on Smart Grid, 3, 4, pp. 1822-1831, (2012)