Regional new energy hierarchical diagnosis system based on big data cloud edge-end collaborative computing

CN122159496APending Publication Date: 2026-06-05YUNNAN HUADIAN FUXIN ENERGY POWER GENERATION CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
YUNNAN HUADIAN FUXIN ENERGY POWER GENERATION CO LTD
Filing Date
2026-02-11
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

The existing operation and maintenance management of new energy power plants lacks regional collaborative diagnostic capabilities, making it impossible to effectively detect local equipment anomalies and trace the root cause, thus hindering the implementation of precise preventive maintenance and operation strategy optimization.

Method used

A regional-level new energy hierarchical diagnostic system based on big data cloud-edge-device collaborative computing is adopted. Through data preprocessing, preliminary diagnosis, model building and solution, and strategy determination units, combined with adjoint theory and causal correlation analysis, global sensitivity analysis and causal inference of new energy field clusters are realized, and collaborative optimization strategies are generated.

Benefits of technology

It has enabled precise location of hidden faults at the equipment level in new energy power plants and proactive early warning of system-level operational risks, improving the overall operational efficiency and safety of regional new energy assets and forming a closed loop of diagnosis, decision-making, and optimization.

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Abstract

The application provides a regional new energy hierarchical diagnosis system based on big data cloud edge-end collaborative calculation, relates to the technical field of power diagnosis, and comprises the following: a data preprocessing unit for preprocessing multi-source state data; a preliminary diagnosis unit for determining a preliminary abnormal device; a model construction and solving unit for determining key abnormal devices and root causes affecting regional performance indexes based on adjoint theory; a strategy determination unit for determining an optimal operation strategy of the device; and a strategy evaluation unit for generating a strategy effect evaluation report and encrypting and uploading the report to the cloud to realize continuous optimization of cloud edge-end collaboration. The application realizes accurate positioning of equipment-level hidden faults of regional new energy field groups to active early warning of system-level operation risks, finally generates and executes a globally optimal collaborative control strategy, forms a closed loop of diagnosis, decision-making and optimization, and significantly improves the comprehensive operation efficiency of regional new energy assets.
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