Photovoltaic safety early warning method based on Bayesian dynamic belief propagation
By constructing a dynamic Bayesian network model and using the BD-BP algorithm, the problem of dynamically tracking the spatiotemporal evolution of risks in photovoltaic power plant monitoring systems was solved, enabling early risk identification and accurate warning of photovoltaic power plants, and improving the system's anti-interference capability and the confidence level of the warning.
CN122089044APending Publication Date: 2026-05-26CHINA THREE GORGES GRP SICHUAN ENERGY INVESTMENT CO LTD +1
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA THREE GORGES GRP SICHUAN ENERGY INVESTMENT CO LTD
- Filing Date
- 2025-12-19
- Publication Date
- 2026-05-26
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Figure CN122089044A_ABST
Abstract
The invention discloses a photovoltaic safety early warning method based on Bayesian dynamic belief propagation, and relates to the field of photovoltaic safety early warning. According to the method, a dynamic Bayesian network model of which the risk evolves along with time is constructed, belief propagation reasoning is performed on multi-source heterogeneous data by using a BD-BP algorithm, and risk weighted convergence is performed in combination with network topology centrality. Therefore, false alarms caused by environmental noise are effectively suppressed, dynamic tracking and accurate positioning of the gradient risk of the photovoltaic equipment are realized, the early warning has the characteristics of strong anti-interference capability and accurate key node identification, and the crossing from single-point passive alarm to system-level active situation awareness is realized.
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