售电公司串谋定价行为随机演化博弈分析

doi:10.11930/j.issn.1004-9649.202208044

中国电力 ›› 2023, Vol. 56 ›› Issue (9): 27-34,133.DOI: 10.11930/j.issn.1004-9649.202208044

• 全国统一电力市场发展路径设计与关键技术 • 上一篇下一篇

售电公司串谋定价行为随机演化博弈分析

陈曦^1,2,3, 陈万露¹, 田洪莉¹, 林健怡⁴, 江天炎^1,2, 毕茂强^1,2

1. 重庆理工大学电气与电子工程学院，重庆 400054;
2. 重庆市能源互联网工程技术研究中心，重庆 400054;
3. 重庆市配售电行业协会，重庆 401147;
4. 重庆大学经济与工商管理学院，重庆 400044

收稿日期:2022-08-11 修回日期:2023-03-13 出版日期:2023-09-28 发布日期:2023-09-20
作者简介:陈曦(1986-),男,博士,讲师,硕士生导师,从事能源经济与能源互联网等研究,E-mail:chenxi1986@cqut.edu.cn;陈万露(1997-),男,硕士研究生,从事电力市场交易策略、演化博弈论研究,E-mail:10022803@2020.cqut.edu.cn
基金资助:
重庆理工大学研究生创新项目（gzlcx20223051）。

Stochastic Evolutionary Game Analysis on Collusion Pricing Behavior of Electricity Retailers

CHEN Xi^1,2,3, CHEN Wanlu¹, TIAN Hongli¹, LIN Jianyi⁴, JIANG Tianyan^1,2, BI Maoqiang^1,2

1. School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China;
2. Chongqing Energy Internet Engineering Technology Research Center, Chongqing 400054, China;
3. Chongqing Electricity Distribution Industry Association, Chongqing 401147, China;
4. School of Economics and Business Administration, Chongqing University, Chongqing 400044, China

Received:2022-08-11 Revised:2023-03-13 Online:2023-09-28 Published:2023-09-20
Supported by:
This work is supported by Graduate Innovation Program of Chongqing University of Technology (No.gzlcx20223051).

摘要/Abstract

摘要： 电力零售侧市场建设初期，容易出现集中度较高的情况，对售电公司的串谋定价行为开展研究可以为规范市场运行的政策制定提供参考。先将串谋定价行为视为有限的售电公司主体在“有限理性”前提下的协同行动策略问题，进而将具有选择差异的Moran过程引入售电公司串谋定价随机演化博弈模型的构建和分析中，最后结合算例分析了串谋系数、供需比等关键参数对售电公司串谋定价策略的影响。研究结果表明：在寡占市场尤其是极高寡占市场中售电公司串谋定价的成功率会更高；在不同类型的市场中，串谋系数对串谋定价策略的影响不同，市场内外部环境随机因素对串谋定价行为的影响随市场集中度增高而愈加显著；市场管理机构应加强对电能零售价格的分析研判并加强对竞争有效性的监管以及与反垄断执法部门、征信部门等单位的信息互通和协同联动。

关键词: 售电公司, 串谋定价, Moran过程, 随机演化博弈, 吸收概率

Abstract: At the early stage of electricity retail market construction, high concentration of ownership is likely to take place and hence the research on collusive pricing behavior of electricity retailers could provide reference for the establishment of reasonable policies. In this paper, the collusive pricing behavior is considered as the strategy choice problem of a “finite population” of electricity retailers under the context of “finite rationality”. The Moran process is introduced into the stochastic evolutionary game model of collusive pricing. Then the effects of key parameters such as collusion coefficient and supply/demand ratio on the collusive pricing strategy of power sales companies are analyzed by virtue of detailed case studies. The results has shown that the success rate of collusive pricing is higher in oligopolistic markets, especially in highly oligopolistic markets; for different types of markets, the collusion coefficient demonstrates different effects on collusive pricing strategies, and furthermore, the impact of random factors in the internal and external market environment on collusive pricing behavior becomes more significant as the market concentration increases; market management agencies should enhance the analysis and research of retail electricity prices and strengthen the supervision of competition effectiveness as well as the information sharing and coordination with anti-monopoly enforcement departments, credit departments and other units.

Key words: electricity retailers, collusive pricing, Moran process, stochastic evolutionary game, absorption probability

陈曦, 陈万露, 田洪莉, 林健怡, 江天炎, 毕茂强. 售电公司串谋定价行为随机演化博弈分析[J]. 中国电力, 2023, 56(9): 27-34,133.

CHEN Xi, CHEN Wanlu, TIAN Hongli, LIN Jianyi, JIANG Tianyan, BI Maoqiang. Stochastic Evolutionary Game Analysis on Collusion Pricing Behavior of Electricity Retailers[J]. Electric Power, 2023, 56(9): 27-34,133.

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售电公司串谋定价行为随机演化博弈分析

Stochastic Evolutionary Game Analysis on Collusion Pricing Behavior of Electricity Retailers

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Stochastic Evolutionary Game Analysis on Collusion Pricing Behavior of Electricity Retailers

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