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Research on Data Sharing and Information Disclosure Mechanisms for Green Finance in the Power Sector
ZHANG Tian, GAO Jianwei, TAN Qinliang
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (5) : 31-38.
PDF(1181 KB)
PDF(1181 KB)
Research on Data Sharing and Information Disclosure Mechanisms for Green Finance in the Power Sector
[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.
electricity market / green finance / cross-departmental collaboration / data sharing / information disclosure
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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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