A method and system for discovering key driving factors of offshore wind power fluctuation and evaluating intervention effects
By acquiring multi-source spatiotemporal data and performing multi-scale time-frequency preprocessing, combined with the construction of a spatiotemporal constraint structure causal graph and the decoupling calculation of causal effects, the key driving factors of offshore wind power fluctuations are identified. This solves the problems of causal relationship confusion and poor regulation effect in existing technologies, and achieves precise power fluctuation regulation and assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAIYIN INSTITUTE OF TECHNOLOGY
- Filing Date
- 2026-04-23
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to identify key driving factors and causal transmission paths of offshore wind power fluctuations, resulting in ineffective control measures and an inability to quantify the intervention's impact before implementation.
We employ a method that combines multi-source spatiotemporal data acquisition, multi-scale time-frequency joint preprocessing, spatiotemporal constraint structure causal graph construction, and causal effect decoupling calculation. By using conditional independence tests and triple constraint matrices to eliminate spurious associations, we identify key driving factors and quantify intervention effects.
It has enabled precise tracing of key driving factors of offshore wind power fluctuations and ex-ante quantification of their control effects, improving the accuracy of causal identification and assessment precision, effectively smoothing wind power output fluctuations, and reducing wind curtailment rates.
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