Carbon emission abnormity tracing method and device, medium and equipment

By combining blockchain technology and Merkle tree signature verification with hash consistency verification, along with the isolated forest algorithm and group signature verification, the efficiency and accuracy issues of tracing anomalies in renewable energy carbon emissions have been resolved, achieving data authenticity, integrity, and privacy protection.

CN121998668AActive Publication Date: 2026-05-08STATE GRID ZHEJIANG ELECTRIC POWER CO LTD
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Patent Information

Application Number
CN202610458943.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-09
Publication Date
2026-05-08
Estimated Expiration
2046-04-09

AI Technical Summary

Technical Problem

Existing technologies cannot accurately and efficiently trace the sources of carbon emission anomalies in renewable energy sources. They also present problems such as data tampering risks, chaotic data formats, delayed anomaly detection, insufficient identity tracing, and lack of data change history tracing.

Method used

By obtaining traceability requests, using blockchain signature verification and hash consistency verification, combined with Merkle tree and isolated forest algorithms, data integrity is verified layer by layer. Using group signature verification methods and private key derivation processes, accurate traceability of carbon emission anomalies is achieved.

Benefits of technology

It improves the efficiency and accuracy of carbon emission anomaly tracing, ensures the authenticity and consistency of data, achieves a balance between anonymity and regulatory needs, protects the privacy of participants, and provides reliable support for carbon emission management.

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Abstract

The invention discloses a carbon emission abnormity traceability method and device, a medium and equipment, and belongs to the field of carbon emission, and the method comprises the steps: receiving a traceability request containing a to-be-verified data identifier, positioning target link data from a block chain storage, and executing signature verification and Hash consistency verification, thereby guaranteeing the authenticity and consistency of the data. And if the verification of the target link data is passed, verifying the inclusion relation of Merkle tree root hash of each link upwards layer by layer to confirm the integrity of the full-chain data. And if verification failure of any level is found, the feature data of the level is combined with an anomaly detection model based on an isolated forest algorithm, and an abnormal data node is positioned. And then, according to the signature information of the abnormal data node and the preset tracking secret key, a group signature verification and private key derivation process is applied, the responsibility participant is traced, and the tracing process of the carbon emission abnormity is completed, so that the problem that the carbon emission abnormal point cannot be accurately and efficiently traced in the prior art is effectively solved.
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