Power Demand Side Management Policy Incentive Process Dynamic Evolutionary Game Analysis

doi:10.11930/j.issn.1004-9649.201809029

Abstract

Abstract: Power demand side management(DSM) has many advantages, including the optimization of power resource allocation, promoting energy conservation and emission reduction, realizing peak load shifting and renewable energy development, etc. However, under the current electricity market environment, there exists sever nonidentity between the cost of DSM and its expected profit, which may weaken the enthusiasm of power grid companies and terminal users. At the same time, the foremost motivation among governments, power grid companies and power users are different, which will lead to intense game. In order to better analyze the game behavior of the main participants, this paper focus on the politic environment of power demand side, and applies an dynamic evolutionary game model to analyze the game between the government and power companies, as well as the government and users. In addition, some measures of power demand side management are proposed to eliminate the restraint among power grid company and power users that caused by DSM, which is the future direction of this field.

Key words: power demand side management, policy incentive mechanism, dynamic evolutionary game, DSM project, gear model

CLC Number:

TM73
F224.32

SONG Zongyun, ZHANG Jian, ZHENG Zedong, XIAO Xinli, HE Yuankang. Power Demand Side Management Policy Incentive Process Dynamic Evolutionary Game Analysis[J]. Electric Power, 2019, 52(10): 54-64.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201809029

https://www.electricpower.com.cn/EN/Y2019/V52/I10/54

References

[1] 王永利, 厉艳, 叶嘉雯, 等. 电力体制改革实施中电力需求侧管理发展模式[J]. 中国电力, 2016, 49(增刊1):75–81. WANG Yongli, LI Yan, YE Jiawen, et al. Research on development model of power demand side management during electric power system reform[J]. Electric Power, 2016, 49(S1):75–81.
[2] 国家发展改革委, 工业和信息化部, 等. 关于深入推进供给侧结构性改革做好新形势下电力需求侧管理工作的通知[EB/OL]. (2017-9-26)[2018-7-15]. http://www.gov.cn/xinwen/2017-09/26/content_5227721.htm.
[3] 施泉生. 面向智能电网的需求响应及其电价研究[M]. 上海:上海财经大学出版社, 2014.
[4] 张晨, 韩新阳, 白翠粉, 等. 基于合作博弈的电力市场模式下售电商购电策略模型[J]. 中国电力, 2017, 50(6):177-184 ZHANG Chen, HAN Xinyang, BAI Cuifen, et al. Purchasing strategy model for power supplier based on the cooperative game theory in an open electricity market[J]. Electric Power, 2017, 50(6):177-184
[5] 张艳馥. 需求侧管理(DSM)激励机制理论研究[D]. 北京:华北电力大学, 2006. ZHANG Yanfu. Research on demand side management incentive theories[D]. Beijing:North China Electric Power University, 2006.
[6] 谢翠菊, 孙新跃, 周志伟. 电力需求侧管理激励机制探讨[J]. 电力需求侧管理, 2005, 7(4):53-55 XIE Cuiju, SUN Xinyue, ZHOU Zhiwei. Encouragement mechanisms discussion of demand side management[J]. Power Demand Side Management, 2005, 7(4):53-55
[7] 张悦, 焦恒新. 我国电力需求侧管理的激励机制及政策研究分析建议[J]. 环球市场, 2017(22):40-40 ZHANG Yue, JIAO Hengxin. Research on demand side management incentive mechanism and policy analysis[J]. Global Market, 2017(22):40-40
[8] 孙毅, 贾孟扬, 陆俊, 等. 需求侧管理中面向居民用电的互动化评价模型[J]. 电力系统自动化, 2017, 41(13):62-69 SUN Yi, JIA Mengyang, LU Jun, et al. Interactive evaluation model for residential electricity in demand side management[J]. Automation of Electric Power Systems, 2017, 41(13):62-69
[9] NASH J. Non-cooperative games[J]. Annals of Mathematics, 1951, 54(2):286-295.
[10] 李军林, 崔琳, 姚东旻. 莱茵哈德·泽尔滕对有限理性与实验经济学的探索[J]. 经济学动态, 2017(2):148-158 LI Junlin, CUI Lin, YAO Dongmin. Reinhard selten exploration of bounded rationality and experimental economics[J]. Economic Perspectives, 2017(2):148-158
[11] PACHECO J M, SANTOS F C, DINGLI D. The ecology of cancer from an evolutionary game theory perspective[J]. Interface Focus, 2014, 4(4):1-9.
[12] 杨光, 刘新旺, 秦晋栋. 关于概率销售的动态演化博弈研究[J]. 系统工程理论与实践, 2017, 37(9):2231-2243 YANG Guang, LIU Xinwang, QIN Jindong. Probabilistic selling strategy study based on dynamic evolution game theory[J]. Systems Engineering-Theory & Practice, 2017, 37(9):2231-2243
[13] 李丹丹, 陶秋燕, 何勤, 等. 基于动态演化博弈视角的技术赶超研究[J]. 科技管理研究, 2018(3):30-36 LI Dandan, TAO Qiuyan, HE Qin, et al. Technological catching-up based on dynamic evolutionary game theory[J]. Science and Technology Management Research, 2018(3):30-36
[14] 罗朝晖, 李海波, 董鹏, 等. 装备合同履行管理的动态演化博弈研究[J]. 火力与指挥控制, 2017(9):140-145 LUO Zhaohui, LI Haibo, DONG Peng, et al. Equipment contract management based on dynamic evolutionary game theory[J]. Fire Control & Command Control, 2017(9):140-145
[15] 蒋金良, 沈彦君. 基于演化博弈的电力需求侧管理监管分析[J]. 华南理工大学学报(社会科学版), 2012, 14(5):50-56 JIANG Jinliang, SHEN Yanjun. Analysis on regulation of demand side management based on evolutionary game[J]. Journal of South China University of Technology (Social Science Edition), 2012, 14(5):50-56
[16] 牛文琪, 史安娜. 基于演化博弈理论的电力需求侧管理研究[J]. 经济问题, 2011(11):61-64 NIU Wenqi, SHI Anna. Study on DSM based on evolutionary game theory[J]. On Economic Problems, 2011(11):61-64
[17] VARGÜN A, DALKILIÇ ME. On the finite population evolutionary stable strategy equilibrium for perfect information extensive form games[C]//International conference on Game Theory for Networks, 2017.
[18] CHENG D, XU T, QI H. Evolutionarily stable strategy of networked evolutionary games[J]. IEEE Transactions on Neural Networks & Learning Systems, 2014, 25(7):1335-1345.
[19] WALLACE C, YOUNG H P. Chapter 6-Stochastic evolutionary game dynamics[J]. Handbook of Game Theory with Economic Applications, 2015, 4:327-380.
[20] FRIEDMAN D. Evolutionary games in economics[J]. Econometrica, 1991, 59(3):637-666.
[21] 梁文举, 刘华勇, 崔荣, 等. 考虑需求侧管理的输电网扩展规划方法研究[J]. 中国电力, 2015, 48(2):128-131 LIANG Wenju, LIU Huayong, CUI Rong, et al. Transmission expansion planning method with consideration of demand side management[J]. Electric Power, 2015, 48(2):128-131
[22] 陈明照, 毛坚, 杜宗林, 等. 基于聚类法的工业用户需求侧管理(DSM)方案分析与研究[J]. 电力系统保护与控制, 2017, 45(7):84-89 CHEN Mingzhao, MAO Jian, DU Zonglin, et al. Analysis on demand side management scheme of industrial enterprise based on clustering method[J]. Power System Protection and Control, 2017, 45(7):84-89