中国电力 ›› 2025, Vol. 58 ›› Issue (8): 109-117.DOI: 10.11930/j.issn.1004-9649.202410082

• 新型电网 • 上一篇    下一篇

绿证-碳-CCER市场交易主体协同效应

陈永权(), 杨万佳(), 王梦玉(), 李佳霖()   

  1. 华北电力大学 经济管理学院,北京 102206
  • 收稿日期:2024-10-25 发布日期:2025-08-26 出版日期:2025-08-28
  • 作者简介:
    陈永权(1971),男,副教授,硕士生导师,从事能源管理与决策支持研究,E-mail:yqc@ncepu.edu.cn
    杨万佳(1999),女,通信作者,硕士研究生,从事碳市场及碳交易决策研究,E-mail:miss_wjy@163.com
    王梦玉(1999),女,硕士研究生,从事绿证市场及碳市场交易研究,E-mail:wmy13821648836@163.com
    李佳霖(1994),女,博士研究生,从事多尺度电力市场机制优化,电碳耦合市场机制设计,新型电力系统仿真与建模研究,E-mail:tuziljl666@163.com
  • 基金资助:
    国家自然科学基金资助项目(2022BJ020)。

Synergistic Effect of Green Certificate-Carbon-CCER Market Trading Subjects

CHEN Yongquan(), YANG Wanjia(), WANG Mengyu(), LI Jialin()   

  1. Department of Economics and Management, North China Electric Power University, Beijing 102206, China
  • Received:2024-10-25 Online:2025-08-26 Published:2025-08-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.2022BJ020).

摘要:

为实现“双碳”目标,研究市场扩容背景下火力发电商在绿证市场、碳市场与中国核证自愿减排量(chinese certified emission reduction,CCER)市场下的多主体交易协同效应。构建火力发电商在多市场联合下的交易框架,并基于多主体非合作博弈模型分析市场扩容下的控排企业协同作用及减排影响,采用经验模态分解(empirical mode decomposition,EMD)结合支持向量机(support vector machine,SVM)模型预测碳排放权交易量,为博弈模型提供关键参数支持。研究结果表明,火电行业通过灵活策略占据主导地位,而钢铁和水泥行业则更多依赖碳排放权交易和CCER履约,不同行业在市场中的表现存在差异,碳市场的扩容、绿证与CCER的联合有效缓解了碳市场压力。

关键词: 碳市场扩容, 绿证-碳市场-CCER, 碳配额需求预测

Abstract:

In order to realize the goal of “double carbon”, we study the synergistic effect of thermal power generators in the green certificate market, carbon market and Chinese certified emission reduction (CCER) market under the background of market expansion. We construct a trading framework for thermal power generators under the multi-market association, and analyze the synergistic effect of emission control enterprises and emission reduction impacts under the market expansion based on the multi-subject non-cooperative game model, and adopt the empirical mode decomposition (EMD) combined with the support vector machine (SVM) model to predict the carbon emission right trading volume, and to estimate the carbon emission right trading volume, and to estimate the carbon emission right trading volume. Empirical mode decomposition (EMD) combined with support vector machine (SVM) model is used to predict the volume of carbon emissions trading and provide key parameter support for the game model. The results show that the thermal power industry dominates the market through flexible strategies, while the steel and cement industries rely more on carbon emissions trading and CCER compliance, and there are differences in the performance of different industries in the market, and the expansion of the carbon market, and the combination of green certificates and CCER effectively alleviate the pressure of the carbon market.

Key words: carbon market expansion, green certificates - carbon market - CCER, carbon allowance demand forecast


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