Double-Layer Pricing Model of Power Grid Based on Rubinstein Game under the Influence of Source-Side and Load-Side Uncertainty
Li Lixing1, 2, Miao Shihong1, 2, Yu Jing3, Tu Qingyu1, 2, Duan Simo1, 2
1. State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China; 2. Hubei Electric Power Security and High Efficiency Key Laboratory School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China; 3. State Grid Jiangsu Electric Power Co. Ltd Nanjing 210000 China
Abstract:With the further opening of the electricity market and the increasing in the penetration rate of renewable energy sources, the complexity of power grid electricity transactions have brought challenges to the operation of power grids. This paper proposes a dual-tier pricing model based on Rubinstein game under the influence of source-side and load-side uncertainty. First, based on the current opening process of China's electricity market, a two-tiered pricing mechanism for scheduling game with consideration of maximizing social welfare is established. Secondly, considering the influence of uncertainties on both sides of source and load, a stochastic chance-constrained programming model for large power grid is established. Finally, based on Rubinstein's dynamic game model, the multi-agent bargaining mechanism under complete information is established, and the game subgame perfect Nash equilibrium is solved. Taking the PJM5 node system as an example, the simulation results verify the validity of the model. The results show that the proposed method satisfies the interests of all participants, reduces the cost of power generation, and realizes the improvement of total social benefits and wind power consumption.
李力行, 苗世洪, 余璟, 涂青宇, 段偲默. 源荷双侧不确定因素影响下基于Rubinstein博弈的电网双层定价模型[J]. 电工技术学报, 2019, 34(zk2): 729-741.
Li Lixing, Miao Shihong, Yu Jing, Tu Qingyu, Duan Simo. Double-Layer Pricing Model of Power Grid Based on Rubinstein Game under the Influence of Source-Side and Load-Side Uncertainty. Transactions of China Electrotechnical Society, 2019, 34(zk2): 729-741.
[1] 孔祥瑞, 李鹏, 严正, 等. 售电侧放开环境下的电力市场压力测试分析[J]. 电网技术, 2016, 40(11): 3279-3286. Kong Xiangrui, Li Peng, Yan Zheng, et al.Stress testing on electricity market with retail transactions opened[J]. Power System Technology, 2016, 40(11): 3279-3286. [2] 许洪强, 姚建国, 於益军, 等. 支撑一体化大电网的调度控制系统架构及关键技术[J]. 电力系统自动化, 2018, 42(6): 1-8. Xu Hongqiang, Yao Jianguo, Yu Yijun, et al.Architecture and key technologies of dispatch and control system supporting integrated Bulk power grids[J]. Automation of Electric Power Systems, 2018, 42(6): 1-8. [3] 薛禹胜, 雷兴, 薛峰, 等. 关于风电不确定性对电力系统影响的评述[J]. 中国电机工程学报, 2014, 34(29): 5029-5040. Xue Yusheng, Lei Xing, Xue Feng, et al.A review on impacts of wind power uncertainties on power systems[J]. Proceedings of the CSEE, 2014, 34(29): 5029-5040. [4] 卢强, 陈来军, 梅生伟. 博弈论在电力系统中典型应用及若干展望[J]. 中国电机工程学报, 2014, 34(29): 5009-5017. Lu Qiang, Chen Laijun, Mei Shengwei.Typical applications and prospects of game theory in power system[J]. Proceedings of the CSEE, 2014, 34(29): 5009-5017. [5] 张忠会, 赖飞屹, 谢义苗. 基于纳什均衡理论的电力市场三方博弈分析[J]. 电网技术, 2016, 40(12): 3671-3679. Zhang Zhonghui, Lai Feiyi, Xie Yimiao.Analysis of trilateral game in electricity market based on nash equilibrium theory[J]. Power System Technology, 2016, 40(12): 3671-3679. [6] 张忠会, 刘故帅, 谢义苗. 基于博弈论的电力系统供给侧多方交易决策[J]. 电网技术, 2017, 41(6): 1779-1785. Zhang Zhonghui, Liu Gushuai, Xie Yimiao.A game theory approach to analyzing multi-party electricity trading on supply side[J]. Power System Technology, 2017, 41(6): 1779-1785. [7] 代业明, 高岩. 基于智能电网需求侧管理的多零售商实时定价策略[J]. 中国电机工程学报, 2014, 34(25): 4244-4249. Dai Yeming, Gao Yan.Real-time pricing strategy with multi-retailers based on demand-side manage- ment for the smart grid[J]. Proceedings of the CSEE, 2014, 34(25): 4244-4249. [8] 代业明, 高岩, 高红伟, 等. 基于需求响应的智能电网实时电价谈判模型[J]. 中国管理科学, 2017, 25(3): 102-110. Dai Yeming, Gao Yan, Gao Hongwei, et al.Real-time pricing strategy with multi-retailers based on demand- side management for the smart grid[J]. Chinese Journal of Management Science, 2017, 25(3): 102-110. [9] 陈晓明. 电力市场中投标策略纳什均衡计算及安全成本分摊[D]. 天津: 天津大学, 2005. [10] 余贻鑫, 陈晓明. 考虑输电约束的古诺均衡求解方法[J]. 中国电机工程学报, 2005, 25(13): 68-72. Yu Yixin, Chen Xiaoming.An algorithm for calcu- lating cournot equilibrium with transmission con- straints[J]. Proceedings of the CSEE, 2005, 25(13): 68-72. [11] Belgana A, Rimal B P, Maier M.Open energy market strategies in microgrids: a stackelberg game approach based on a hybrid multiobjective evolutionary algo- rithm[J]. IEEE Transactions on Smart Grid, 2015, 6(3): 1243-1252. [12] 蒋国华. 基于博弈模型的智能电网需求响应管理及定价策略[D]. 杭州: 浙江工业大学, 2013. [13] 罗纯坚, 李姚旺, 许汉平, 等. 需求响应不确定性对日前优化调度的影响分析[J]. 电力系统自动化, 2017, 41(5): 22-29. Luo Chunjian, Li Yaowang, Xu Hanping, et al.Influence of demand response uncertainty on day- ahead optimization dispatching[J]. Automation of Electric Power Systems, 2017, 41(5): 22-29. [14] 牛文娟. 计及不确定性的需求响应机理模型及应用研究[D]. 南京: 东南大学, 2015. [15] 杨胜春, 刘建涛, 姚建国, 等. 多时间尺度协调的柔性负荷互动响应调度模型与策略[J]. 中国电机工程学报, 2014, 34(22): 3664-3673. Yang Shengchun, Liu Jiantao, Yao Jianguo, et al.Model and strategy for multi-time scale coordinated flexible load interactive scheduling[J]. Proceedings of the CSEE, 2014, 34(22): 3664-3673. [16] Yang Shengchun, Zeng Dan, Ding Hongfa, et al.Multi-objective demand response model considering the probabilistic characteristic of price elastic load[J]. Energies, 2016, 9(2): 80. [17] 赵冬梅, 殷加玞. 考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J]. 电工技术学报, 2018, 33(5): 1076-1085. Zhao Dongmei, Yin Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering source-side and load-side uncer- tainty[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1076-1085. [18] Zhao Chaoyue, Wang Jianhui, Watson J P, et al.Multi-stage robust unit commitment considering wind and demand response uncertainties[J]. IEEE Transa- ctions on Power Systems, 2013, 28(3): 2708-2717. [19] 言茂松, 李玉平, 辛洁晴, 等. 从加州电力危机看稳健的当量电价体系[J]. 电网技术, 2001, 25(6): 8-17. Yan Maosong, Li Yuping, Xin Jieqing, et al.From California power crisis to review robust electricity value equivalent systems for restructuring and pricing[J]. Power System Technology, 2001, 25(6): 8-17. [20] 于琳娜. 电价持续飙升困扰澳大利亚[N]. 中国电力报, 2017-04-29(011). [21] Nguyen D T, Nguyen H T, Le Longbao.Dynamic pricing design for demand response integration in power distribution networks[J]. IEEE Transactions on Power Systems, 2016, 31(5): 3457-3472. [22] Rahimiyan M, Baringo L, Conejo A J.Energy management of a cluster of interconnected price- responsive demands[J]. IEEE Transactions on Power Systems, 2014, 29(2): 645-655. [23] 刘宝碇, 赵瑞清, 王纲. 不确定规划及应用[M]. 北京: 清华大学出版社, 2003 [24] Rubinstein A.Perfect equilibrium in a bargaining model[J]. Econometrica, 1982, 50(1): 97-109. [25] Gibbons R.Game theory for applied economists[M]. Princeton: Princeton University Press, 1992. [26] Shaked A, Sutton J.Involuntary unemployment as a perfect equilibrium in a bargaining model[J]. Econo- metrica, 1984, 52(6): 1351-1364. [27] Li Fangxing, Rui Bo.DCOPF-based LMP simulation: algorithm, comparison with ACOPF, and sensiti- vity[J]. IEEE Transactions on Power Systems, 2007, 22(4): 1475-1485.