Snow identification method and system for photovoltaic power station based on multi-source fusion and hierarchical lag
By using a time-series state machine with multi-source data fusion and a hierarchical lag-holding mechanism, the snow accumulation status of photovoltaic power plants is identified, solving the problems of high false alarm rate and hardware dependence in existing technologies, and achieving efficient and accurate snow accumulation monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING HUANENG XINRUI CONTROL TECH
- Filing Date
- 2026-03-18
- Publication Date
- 2026-07-03
AI Technical Summary
Existing methods for monitoring snow accumulation in photovoltaic power plants rely on a single threshold, resulting in a high false alarm rate. They cannot accurately determine the end time of snow accumulation events and require additional hardware or manual intervention, while ignoring the lag effect of snow melting.
By fusing multi-source data, the gain attenuation index and voltage deviation are calculated. Combined with a time-series state machine with a graded hysteresis hold mechanism, the inefficient state of the inverter is identified, the inefficiency ratio coefficient at the site level is generated, the snow accumulation status is determined by combining the ambient temperature, and time-domain filtering is performed to verify and generate a snow accumulation event report.
It improves the accuracy of snow accumulation identification, avoids misjudgment due to single device failure, reduces hardware costs, is suitable for promotion in existing power plants, and solves the problem of judgment jitter in critical states of traditional methods.
Smart Images

Figure CN122332771A_ABST