主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

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电力行业脱碳路径:企业层面的投资决策与转型策略分析

黄晓霞, 范栩侨, 洪权龙   

  1. 北京科技大学, 100083
  • 收稿日期:2024-08-13 修回日期:2026-01-07 接受日期:2026-01-23
  • 通讯作者: 黄晓霞
  • 基金资助:
    北京市社会科学基金重点项目(23GLA006)

Decarbonization Pathways in the Power Sector: An Analysis of Investment Decisions and Transformation Strategies at the Enterprise Level

Xiaoxia Huang   

  1. , 100083,
  • Received:2024-08-13 Revised:2026-01-07 Accepted:2026-01-23
  • Contact: Huang, Xiaoxia

摘要: 在“双碳”目标的驱动下,电力行业作为最大的碳排放来源,正面临着前所未有的脱碳挑战,这对电力企业的低碳转型战略规划提出了更高的要求。在这一背景下,投资组合优化成为电力企业实施转型策略的有效手段。如何选择与企业资源、市场趋势以及政策导向相匹配的电力项目组合,以及如何权衡低碳技术的应用,以平衡经济效益与环境责任,成为了转型成功与否的关键。为此,本研究从企业视角出发,提出了一种综合考虑低碳技术应用的电力项目组合选择优化模型。基于四种不同的企业低碳转型情景,选取实际的电力项目数据,通过改进的二进制Jaya算法,分析不同情景下各类发电技术的最优项目组合收益与碳排放变化,协助企业平衡低碳技术的应用与非化石能源项目的选择。研究结果表明,在碳排放预算较高的情景1与情景2中,企业转型方向倾向于选择非化石能源项目,而在碳排放预算较低的情景3与情景4中,CCS技术成为企业低碳转型的首要选择。随着CCS碳捕集率的提高,火电项目与CCS技术的结合获得更多的经济效益。同时,企业的投资预算对低碳转型路径的选择具有决定性影响,充足资金保障能够显著促进企业向非化石能源战略的转变。研究有助于帮助电力企业进行科学的项目组合投资决策,制定科学有效的低碳转型策略,同时为政策制定者提供了决策支持,也为电力行业的可持续发展和国家碳中和目标的实现提供了实践指导。

关键词: 电力企业项目选择, 投资决策, 低碳转型, 碳捕集与封存技术(CCS)

Abstract: Driven by the dual carbon goals, the power sector, as the largest source of carbon emissions, faces an urgent challenge in decarbonization. This study focuses on the strategic planning of low-carbon transitions within power companies, with a particular emphasis on optimizing power project portfolios. The central issue is how to select a portfolio of power projects that aligns with corporate resources, market trends, and policy directions, while balancing the application of low-carbon technologies to achieve both economic and environmental objectives. To address this, we introduce an optimization model for power project portfolio selection that comprehensively considers the application of low-carbon technologies. The model aims to maximize the total net present value (NPV) of a power project portfolio over a given period, while accounting for carbon emissions and potential carbon trading revenues or costs. The study uses real power project data from representative companies such as Huaneng Power International, Inc. and China National Nuclear Power Co.,Ltd., ensuring the model’s practical applicability and scientific validity. The data includes investment costs, operational and maintenance costs, fuel costs, and carbon emission intensities, which are crucial for the model’s accuracy. An improved Binary Jaya algorithm is employed to analyze the optimal combinations of various power generation technologies under four different low-carbon transition scenarios. The main findings indicate that in scenarios with higher carbon emission budgets (Scenarios 1 and 2), companies tend to prioritize non-fossil energy projects. Conversely, in scenarios with lower carbon emission budgets (Scenarios 3 and 4), Carbon Capture and Storage (CCS) technology emerges as the primary choice for low-carbon transitions. As the CCS carbon capture rate increases, the integration of coal-fired power projects with CCS technology becomes more economically efficient. Adequate investment budgets significantly promote the shift towards non-fossil energy strategies. This research provides power companies with a scientific framework for optimizing project portfolio investment decisions and formulating effective low-carbon transition strategies. It also offers decision support for policymakers and provides practical guidance for the sustainable development of the power sector and the achievement of national carbon neutrality goals. The findings contribute to helping companies navigate the complex transformation of the power market and make informed investment decisions in line with carbon emission constraints and policy directives.

Key words: power enterprise project selection, investment decision, low-carbon transformation, carbon capture and storage (ccs) technology