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电力绿色金融数据共享与信息披露机制研究
Research on Data Sharing and Information Disclosure Mechanisms for Green Finance in the Power Sector
【目的】 为改善中国电力与绿色金融领域数据壁垒显著、信息披露失范、标准不统一、采集受限等突出问题，破解由此引发的能源低碳转型受阻困境，提出一套兼具理论性与实践性的跨部门数据共享及信息披露协同解决方案。【方法】 基于制度经济学与技术创新理论，结合重庆等地电力与绿色金融融合发展的实践案例，从非完全数据采集实际场景与信息高效使用视角切入，系统剖析跨部门数据共享和信息披露的现状、核心堵点及深层矛盾，明确各参与主体的权责边界。构建“组织架构、运行规则、技术支撑”三位一体的协同机制框架，提出“顶层统筹+分层执行”的跨部门数据共享体系与“强制披露+自愿补充”的信息披露模式，细化成本分摊、利益分配、风险防控等关键操作路径，开展多场景技术方案适配性验证，并配套全维度保障措施。【结果】 所提方案有效提升了数据共享效率与信息披露质量。【结论】 所提协同机制及实施路径能够有效打通“电-碳-金融”数据传导链条，显著提升绿色金融服务电力行业的精准度，为推动能源低碳转型提供兼具理论价值与实践可行性的支撑路径，对破解行业发展困境、完善相关领域治理体系具有重要意义。
[Objective] To address the practical challenges confronting China’s power and green finance sectors， which are characterized by prominent data barriers， irregular information disclosure， inconsistent standards and data collection constraints， and to resolve the resulting obstacles to low-carbon energy transition， this study proposes a cross-sectoral data sharing and information disclosure collaborative solution that is both theoretically grounded and practically applicable. [Methods] Based on institutional economics and technological innovation theory， and by integrating case studies regarding integrated development of power and green finance sectors from Chongqing and other regions， this study systematically analyzes the current status， core bottlenecks and underlying contradictions of cross-sectoral data sharing and information disclosure from the perspectives of incomplete data collection scenarios and inefficient information utilization， while clarifying the rights and responsibilities of participating entities. A trinity collaborative mechanism framework integrating "organizational structure， operational rules and technical support" is established. Specifically， it proposes a “top-level coordination + tiered implementation” cross-sectoral data sharing system and a “mandatory disclosure + voluntary supplementation” information disclosure model. Furthermore， the operational pathways for cost allocation and benefit distribution are elaborated in detail， the compatibility verification of multi-scenario technical solutions is implemented， and a comprehensive set of safeguarding measures is provided to ensure the mechanism’s operability. [Results] The proposed solution effectively improves the efficiency of data sharing and the quality of information disclosure. [Conclusions] The proposed collaborative mechanism and operational pathway effectively unblock the data transmission chain connecting electricity， carbon and finance. This provides a supporting pathway with both theoretical value and practical feasibility for promoting the low-carbon energy transition， and holds significant importance for addressing industry development challenges and improving the governance system in related fields.
电力市场 / 绿色金融 / 跨部门协同 / 数据共享 / 信息披露
electricity market / green finance / cross-departmental collaboration / data sharing / information disclosure
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Green power trading policy is an important tool in the field of energy emission reduction. This study proposes a system dynamics model for green power participation in power market trading to address the effect of green power trading policy on the electricity market. First, we analyzed the operational status of green power trading policies at home and abroad and the problems of green power trading in China. Next, we constructed a system dynamics model of green power participation in electricity market trading to analyze the effect of the green power trading policy on the electricity market. Finally, we considered the Beijing-Tianjin-Hebei region as an example to analyze and verify the accuracy and rationality of the proposed model. The obtained results forecasted that, during 2026-2030, the price of green power will rise with a linear upward trend, and the installed capacity of green power will increase substantially. Under this growth scenario of the share of green power generation, the installed capacity and power generation of traditional energy sources is expected to grow moderately to ensure the stable operation of the power system. Moreover, we concluded that the implementation of the green power trading policy can effectively adjust the power supply structure. |
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Addressing the lack of efficient online detection schemes for ledger tampering attacks in the current power industry consortium blockchain, we propose a ledger tampering attack detection method based on endorsement features. First, an attack on the state data of specific nodes in a power industry consortium blockchain was proposed and implemented in a green power-trading simulation environment. Accordingly, endorsement features related to the attack were collected and extracted from the chain-operation data to construct the required dataset for detection. Finally, the boosting random forest algorithm was used to train the detection model, and the model was noninvasively deployed on the blockchain for online detection of ledger tampering attacks. The test results indicate that the proposed method has a smaller operating burden on the power consortium blockchain than rule-based detection methods and excels in terms of identification time and blockchain performance loss, incurring only a 4.03% performance burden. Compared with other machine learning-based detection methods, this method can be adapted to multiple consensus algorithms and has a high accuracy of 95.75%. |
利益冲突声明（Conflict of Interests）： 所有作者声明不存在利益冲突。
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