A transformer operation safety evaluation method based on multi-source power data fusion
By using a multi-source data fusion method, a transformer operation safety assessment model was established to identify load fluctuation segments and analyze changes in characteristic gases at oil temperature. This solved the problem of insufficient prediction using single data, enabled accurate determination of transformer insulation aging and dynamic load control, and improved the safety and economy of power grid operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BAODING YUANCHUANG POWER TECH CO LTD
- Filing Date
- 2026-03-05
- Publication Date
- 2026-06-09
AI Technical Summary
Existing transformer operation safety prediction technologies rely on single-dimensional data, which makes it difficult to fully reflect the actual state of the equipment, resulting in insufficient accuracy of prediction results. Furthermore, they lack analysis of repetitive load fluctuation events and cannot meet the needs of dynamic load management of the power grid.
By synchronously collecting historical load data, oil temperature data, and oil chromatography data of transformers, a time-series correlation is established, repetitive load fluctuation segments are identified, the variation patterns of oil temperature and characteristic gases are analyzed, the correlation between the degree of thermal response delay and the growth rate of characteristic gases is established, the insulation aging stage is determined, and dynamic load control suggestions are generated.
It enables accurate determination of transformer insulation aging stages, generates standardized load capacity boundaries and dynamic load control suggestions, improves equipment operation safety and economy, and supports stable power grid operation.
Smart Images
Figure CN122178562A_ABST