Journal of Shandong University(Engineering Science) ›› 2026, Vol. 56 ›› Issue (3): 193-203.doi: 10.6040/j.issn.1672-3961.0.2024.197

• Mechanical, Energy and Power Engineering • Previous Articles     Next Articles

A game study on the evolution of carbon reduction behavior of energy- consuming enterprises considering dynamic rewards and penalties

CHEN Xi1, ZHANG Huan1*, TIAN Hongli1, DAI Chunyan2, JIANG Tianyan1, BI Maoqiang1   

  1. CHEN Xi1, ZHANG Huan1*, TIAN Hongli1, DAI Chunyan2, JIANG Tianyan1, BI Maoqiang1(1. School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China;
    2. School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing 400067, China
  • Published:2026-06-09

PDF (PC)

3

Abstract: In order to explore the impact of different factors on the carbon reduction behavior of high-energy-consuming enterprises, this paper researched the carbon reduction behavior of these enterprises under government regulation, considering their participation in both the electricity and carbon markets. A game theory model of the government's and high-energy-consuming enterprises' carbon reduction behavior in the joint electricity-carbon market was constructed. The evolutionarily stable strategies were examined under two scenarios: static rewards and penalties, and dynamic rewards and penalties. The effects of parameters such as the government's electricity price incentive coefficient, regulatory costs, regulatory intensity, and the upper and lower limits of penalties on the carbon reduction behavior of high-energy-consuming enterprises and the stability speed of the system under dynamic reward and penalty mechanisms were discussed. The analysis of numerical examples showed that: under a dynamic reward and penalty mechanism, there existed a unique evolved stable strategy for both parties; during different carbon reduction periods, the government should balance the upper limit of rewards and electricity price incentives to improve the probability of high-energy-consuming enterprises choosing carbon reduction behavior; the regulatory intensity of the government had a greater impact on the carbon reduction behavior of high-energy-consuming enterprises than regulatory costs, and it was recommended that the government strictly regulate these enterprises during carbon reduction periods.

Key words: high-energy-consuming enterprises, energy saving and carbon reduction, dynamic rewards and penalties, evolutionary game, joint electricity and carbon markets

CLC Number: 

  • TM73
[1] LIAO X L, ZHANG Y, WANG X Y, et al. Digitalization level and green-oriented transition development of highly energy-intensive enterprises based on carbon reduction perspective[J]. Sustainability, 2023, 15(21): 15549.
[2] 何佳蒙, 谢海鹏, 孙啸天, 等. 考虑有限理性的钢铁生产企业电-碳市场交易决策方法[J]. 智慧电力, 2024, 52(8): 105-112. HE Jiameng, XIE Haipeng, SUN Xiaotian, et al. Bidding strategy for iron-and-steel enterprises in electricity and carbon market considering bounded rationality[J]. Smart Power, 2024, 52(8): 105-112.
[3] 孙啸天, 杨争林, 任涵钰, 等. 基于平均场博弈的钢铁生产企业电-碳市场非合作博弈均衡分析[J]. 电网技术, 2023, 47(8): 3058-3069. SUN Xiaotian, YANG Zhenglin, REN Hanyu, et al. Non-cooperative equilibrium for iron and steel enterprises in electricity and carbon emission permission market based on mean-field game theory[J]. Power System Technology, 2023, 47(8): 3058-3069.
[4] 杨博, 杨思雨, 王思齐. 碳中和标准体系建设现状、实践及展望[J]. 环境监测管理与技术, 2024, 36(1): 6-10. YANG Bo, YANG Siyu, WANG Siqi. Current situation, practice and prospect of carbon neutrality standard system[J]. The Administration andTechnique of Environmental Monitoring, 2024, 36(1): 6-10.
[5] 汤芳, 代红才, 张宁, 等. 能耗双控向碳排放双控转变影响分析及推进路径设计[J]. 中国电力, 2023, 56(12): 255-261. TANG Fang, DAI Hongcai, ZHANG Ning, et al. Effect analysis and promotion path design for transformation from energy consumption “dual control” to carbon “dual control”[J]. Electric Power, 2023, 56(12): 255-261.
[6] 龙小燕, 李明. “双碳”目标下我国碳减排税收体系构建: 机理、挑战与路径[J]. 经济纵横, 2024(2): 60-66. LONG Xiaoyan, LI Ming. Building China's carbon reduction tax system under “dual carbon” goals: mechanisms, challenges, and paths[J]. Economic Review Journal, 2024(2): 60-66.
[7] ZHANG C, ZHANG X X. Evolutionary game analysis of air pollution co-investment in emission reductions by steel enterprises under carbon quota trading mechanism[J]. Journalof Environmental Management, 2022, 317: 115376.
[8] 张婕, 王凯琪, 张云. 碳排放权交易机制的减排效果: 基于低碳技术创新的中介效应[J]. 软科学, 2022, 36(5): 102-108. ZHANG Jie, WANG Kaiqi, ZHANG Yun. Carbon emission abatement performance of carbon emissions trading scheme: based on the intermediary effect of low-carbon technology innovation[J]. Soft Science, 2022, 36(5): 102-108.
[9] 方国昌, 何宇, 田立新. 碳交易驱动下的政企碳减排演化博弈分析[J]. 中国管理科学, 2024, 32(5): 196-206. FANG Guochang, HE Yu, TIAN Lixin. Evolutionary game analysis of government and enterprises carbon-reduction under the driven of carbon trading[J]. Chinese Journal of Management Science, 2024, 32(5): 196-206.
[10] 焦建玲, 陈洁, 李兰兰, 等. 碳减排奖惩机制下地方政府和企业行为演化博弈分析[J]. 中国管理科学, 2017, 25(10): 140-150. JIAO Jianling, CHEN Jie, LI Lanlan, et al. A study of local governments' and enterprises' actions in the carbon emission mechanism of subsidy or punishment based on the evolutionary game[J]. Chinese Journal of Management Science, 2017, 25(10): 140-150.
[11] 程承, 安润飞, 董康银, 等. 碳交易机制引导下可再生能源发电企业创新策略研究: 基于演化博弈视角[J]. 中国管理科学, 2024, 32(3): 82-94. CHENG Cheng, AN Runfei, DONG Kangyin, et al. Research on innovation strategy for renewable power generation enterprises under the background of carbon trading mechanism: from the perspective of evolutionary game[J]. Chinese Journal of Management Science, 2024, 32(3): 82-94.
[12] 陈健, 唐志远, 谯傲, 等. 考虑高耗能企业车间柔性排程的低碳工业园区双层优化调度[J]. 电力工程技术, 2024, 43(5): 112-121. CHEN Jian, TANG Zhiyuan, QIAO Ao, et al. Bi-level optimal dispatching of low-carbon industrial park considering flexible shop scheduling in high-energy-consuming enterprise[J]. Electric Power Engineering Technology, 2024, 43(5): 112-121.
[13] 高艳艳, 周童, 王旭, 等. 地方政府和高速公路经营者低碳行为的演化博弈分析[J]. 山东大学学报(工学版), 2024, 54(4): 150-158. GAO Yanyan, ZHOU Tong, WANG Xu, et al. Evolutionary game analysis of low-carbon behavior between local government and expressway operator[J]. Journal of Shandong University(Engineering Science), 2024, 54(4): 150-158.
[14] 陈诗源, 任菲, 虞吉海. 生产网络视角下的碳税制度[J]. 经济管理学刊, 2024(3): 143-172. CHEN Shiyuan, REN Fei, YU Jihai. Carbon tax in China: a production network perspective[J]. Quarterly Journal of Economics and Management, 2024(3): 143-172.
[15] 曹柬, 卞兆龙, 陆佳雯, 等. 基于碳税的EPR规制设计: 制造-再制造竞争视角[J]. 系统工程理论与实践, 2025, 45(6): 1960-1979. CAO Jian, BIAN Zhaolong, LU Jiawen, et al. Design of EPR regulations based on carbon tax: from the perspective of manufacturing-remanufacturing competition[J]. Systems Engineering-Theory & Practice, 2025, 45(6): 1960-1979.
[16] 王薇蓉, 陈杨波, 梁中豪. 关于“双碳”背景下电力市场化改革的思路和探索[J]. 电气时代, 2023(12): 24-26.
[17] 张海静, 周颖, 王为帅, 等. 典型高耗能工业用户发用电经济优化建模及调节潜力研究[J]. 电力需求侧管理, 2021, 23(2): 16-21. ZHANG Haijing, ZHOU Ying, WANG Weishuai, et al. Study on economic optimization modeling and regulation potential of power generation and consumption for typical high energy consumption industrial users[J]. Power Demand Side Management, 2021, 23(2): 16-21.
[18] 赵琳, 林立国. 电力价格政策对企业全要素生产率的影响[J]. 经济学动态, 2021(10): 64-81. ZHAO Lin, LIN Liguo. The impact of electricity pricing policy on total factor productivity[J]. Economic Perspectives, 2021(10): 64-81.
[19] 张玉敏, 李竞锐, 吉兴全, 等. 考虑电-碳市场决策协同的园区综合能源系统双层博弈调度[J]. 电力系统自动化, 2025, 49(12): 45-59. ZHANG Yumin, LI Jingrui, JI Xingquan, et al. Bi-level game dispatch of park integrated energy system considering decision-making synergy of electricity-carbon markets[J]. Automation of Electric Power Systems, 2025, 49(12): 45-59.
[20] 王晛, 张梓彦, 张少华, 等. 考虑新能源发电商租赁共享储能的电力市场博弈分析[J]. 电网技术, 2024, 48(8): 3269-3277. WANG Xian, ZHANG Ziyan, ZHANG Shaohua, et al. Game analysis of electricity market with considerations of leasing-based energy storage sharing for renewable generators[J]. Power System Technology, 2024, 48(8): 3269-3277.
[21] 窦迅, 王俊, 王湘艳, 等. 基于演化博弈的区域电-气互联综合能源系统用户需求侧响应行为分析[J]. 中国电机工程学报, 2020, 40(12): 3775-3786. DOU Xun, WANG Jun, WANG Xiangyan, et al. Analysis of user demand side response behavior of regional integrated power and gas energy systems based on evolutionary game[J]. Proceedings of the CSEE, 2020, 40(12): 3775-3786.
[22] 何鑫雨, 董萍, 刘明波, 等. 基于双层演化博弈模型的多区域点对点能源共享机制[J]. 电网技术, 2023, 47(1): 163-174. HE Xinyu, DONG Ping, LIU Mingbo, et al. Multi-region P2P energy sharing mechanism based on two-stage evolutionary game model[J]. Power System Technology, 2023, 47(1): 163-174.
[23] 蒋学海, 郑婉琼, 马本江. 不同奖惩机制下数字平台反垄断演化博弈与仿真研究[J]. 系统科学与数学, 2024, 44(8): 2213-2235. JIANG Xuehai, ZHENG Wanqiong, MA Benjiang. Evolutionary game and simulation research on digital platform anti monopoly under different reward & punishment mechanisms[J]. Journal of Systems Science and Mathematical Sciences, 2024, 44(8): 2213-2235.
[24] 郭一航, 邹凯, 罗思敏, 等. 不同奖惩机制下智慧城市信息安全服务质量监管的演化博弈分析[J]. 运筹与管理, 2024, 33(6): 64-70. GUO Yihang, ZOU Kai, LUO Simin, et al. Evolutionary game analysis of smart city information security service quality supervision under different reward and punishment mechanisms[J]. Operations Research and Management Science, 2024, 33(6): 64-70.
[25] 潘峰, 刘月, 王琳. 公众参与视角下的央地环境规制博弈分析[J]. 运筹与管理, 2020, 29(6): 113-123. PAN Feng, LIU Yue, WANG Lin. Game analysis of environmental regulation between central government and local government under the perspective of public participation[J]. Operations Research and Management Science, 2020, 29(6): 113-123.
[26] 高攀, 杜汪苗, 赵旭. 大中型水电工程库区漂浮物协同治理的多元主体博弈研究[J]. 水资源与水工程学报, 2023, 34(5): 32-42. GAO Pan, DU Wangmiao, ZHAO Xu. Multi-subject game research of synergistic governance of floating debris in large and medium hydropower project reservoir areas[J]. Journal of Water Resources and Water Engineering, 2023, 34(5): 32-42.
[27] 曹霞, 邢泽宇, 张路蓬. 政府规制下新能源汽车产业发展的演化博弈分析[J]. 管理评论, 2018, 30(9): 82-96. CAO Xia, XING Zeyu, ZHANG Lupeng. An evolutionary game analysis of new energy vehicle industry development under government regulations[J]. Management Review, 2018, 30(9): 82-96.
[28] TAYLOR C, FUDENBERG D, SASAKI A, et al. Evolutionary game dynamics in finite populations[J]. Bulletin of Mathematical Biology, 2004, 66(6): 1621-1644.
[29] LI S, CAI J N, FENG Z, et al. Government contracting with monopoly in infrastructure provision: regulation or deregulation?[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 122: 506-523.
[30] 沈满洪, 贺震川. 低碳经济视角下国外财税政策经验借鉴[J]. 生态经济, 2011, 27(3): 83-89. SHEN Manhong, HE Zhenchuan. The experience of foreign fiscal policy on low-carbon economy[J]. Ecological Economy, 2011, 27(3): 83-89.
[31] LIU Z, SUN W Z. Study on low-carbon technology investment strategies for high energy-consuming enterprises under the health co-benefits of carbon emission reduction[J]. Sustainability, 2023, 15(11): 8872.
[1] ZHANG Yumin, LI Jingrui, YANG Ming, JI Xingquan, SUN Donglei, XU Bo, WU Fucheng. Robust unit commitment model with multi-energy coupled system considering gas-heat network dynamics [J]. Journal of Shandong University(Engineering Science), 2025, 55(5): 18-29.
[2] HAN Xueshan, LI Keqiang. Theoretical study on synergistic dispatch for development of new power system [J]. Journal of Shandong University(Engineering Science), 2022, 52(5): 14-23.
[3] Qingfa CHAI,Shoujing SUN,Jifu QIU,Ming CHEN,Zhen WEI,Wei CONG. Prediction method of power grid emergency supplies under meteorological disasters [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 76-83.
[4] Shizhan SONG,Haoyu CHEN,Jian ZHANG,Kun WANG,Qingshui HAO. Voltage control method of urban distribution network considering street light charging pile access [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 104-110.
[5] Zhiyuan PAN, Chaonan LIU, Hongwei LI, Jing WANG, Wei WANG, Jing LIU, Xin ZHENG. Energy scheduling method of smart home integrated with photovoltaic units based on time-of-use pricing [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 111-116.
[6] Meng LIU,Dingyi CHENG,Wen ZHANG,Hengxu ZHANG,Kuan LI,Guohui ZHANG,Jianjun SU. Discussion on emergency control of central air conditioner at large receiving-end grid to cope with HVDC blocking fault [J]. Journal of Shandong University(Engineering Science), 2020, 50(1): 72-81.
[7] Yutian LIU, Runjia SUN, Hongtao WANG, Xueping GU. Review on application of artificial intelligence in power system restoration [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 1-8.
[8] Runjia SUN,Hainan ZHU,Yutian LIU. Transmission network reconfiguration strategy based on preference multiobjective optimization and genetic algorithm [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 17-23.
[9] Fei WANG, Chunyi WANG, Chuanyong WANG, Guangfeng ZHAO, Mu LI, Xiaohan SHI. Restrictions and countermeasures of distributed PV integration based on secondary battery energy storage system [J]. Journal of Shandong University(Engineering Science), 2018, 48(6): 109-115.
[10] LIU Xiaoming, XU Naiyuan, YANG Bin, WEI Xin, ZHANG Lina, CAO Yongji. Bi-stage optimization method for receiving-end ultra-high voltage network planning under global energy interconnection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 1-6.
[11] CHE Changming, ZHANG Huadong, LI Jianxiang, YUAN Hong, LIU Haibo. Optimization dispatch control strategy for charging load of large-scale electric vehicle on demand side [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 108-114.
[12] XU Wei, JI Xiaotong, LIU Haibo, HAN Yuankai, CHEN Fang, ZHANG Chenglin. Location and resource allocation of emergency charging station for expressway electric vehicle [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 115-120.
[13] WANG Shibo, DU Heng, WU Yong, LIU Hongzheng, CHENG Yan. Economic dispatch of microgrid under two-level market operating environment [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 32-38.
[14] MA Hanjie, LIN Xia, XU Xiaohui, ZHANG Jian, ZHANG Zhisheng. Load optimization model of smart home management system based on adaptive particle swarm optimization [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 57-62.
[15] CHU Xiaodong, TANG Maosen, GAO Xu, LIU Weisheng, JIA Shanjie, LI Sun. Robust optimal dispatch of active distribution networks based on centralized information system [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 20-25.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd