一种光伏柔性支架结构参数自适应优化方法及系统
By classifying the structural parameters of the photovoltaic flexible support and constructing interval fields using a random field discretization algorithm, combined with sparse grid sampling and a multinomial surrogate model, the precise structural response optimization of the photovoltaic flexible support under extreme working conditions was achieved. This solved the problem of inaccurate mapping relationship description in existing technologies and improved control efficiency and stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- POWERCHINA JIANGXI ELECTRIC POWER ENGINEERING CO LTD
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing adaptive control methods for photovoltaic flexible supports cannot accurately describe their complex nonlinear mapping relationships, resulting in large structural response errors under extreme operating conditions, deviations between control actions and actual needs, and impacts power generation efficiency and structural stability.
The structural parameters of the photovoltaic flexible support are divided into geometric, material, and boundary condition parameters. A random field discretization algorithm is used to construct the interval field. Combined with sparse grid sampling, a parameter sample set is generated, and a multinomial surrogate model is constructed. The structural response parameters are detected in real time and optimized online through incremental sparse grid sampling.
Accurately characterize the nonlinear mapping relationship of photovoltaic flexible support, reduce structural response errors under extreme conditions, improve parameter optimization efficiency, and ensure the accuracy and stability of the support's operation and control under extreme conditions.
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Figure CN122413086A_ABST