Flexible photovoltaic power station load distribution prediction method and system

By acquiring meteorological factor data and vibration response data, combining the structural characteristics of flexible photovoltaic power stations, and using neural networks to build a load distribution prediction model, the problem of insufficient prediction accuracy and reliability of flexible photovoltaic power stations is solved, and higher safety and power generation efficiency are achieved.

CN120105894APending Publication Date: 2025-06-06上海尤汶新能源有限公司
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Patent Information

Application Number
CN202510182466.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-19
Publication Date
2025-06-06

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Abstract

The invention discloses a load distribution prediction method and system for a flexible photovoltaic power station. The prediction method comprises the following steps: acquiring meteorological factor data of the flexible photovoltaic power station; according to the meteorological factor data, in combination with the deformation characteristics of the flexible base and the layout mode of the photovoltaic module, obtaining the spatial distribution characteristics of load distribution; obtaining vibration response data of the flexible photovoltaic power station, and obtaining a dynamic load in combination with the spatial distribution characteristics; historical load distribution data are obtained, the historical load distribution data are input into a load distribution prediction model, a current prediction result is obtained, the load distribution prediction model is obtained through training of a training set, the training set is the fused meteorological factor data, spatial distribution characteristics and dynamic loads, and the load distribution prediction model is constructed through a neural network; and comparing the current prediction result with real-time monitoring data to obtain a prediction deviation, and updating the load distribution prediction model through a feedback correction mechanism to obtain a final prediction result. The safety of the power station is improved.
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