Research background and significance
Against the backdrop of the growing global demand for renewable energy and the growing concern about fossil fuel depletion and environmental pollution, solar energy, as a clean and renewable energy source, has become an important alternative to fossil fuels. Photovoltaic power generation is an important way to utilize solar energy and plays a key role in achieving the strategic goal of "dual carbon". Therefore, it is necessary to continuously improve the efficiency and performance of photovoltaic power generation. Hyperspectral technology provides a new research method for it.
Equipment application introduction
In terms of photovoltaic power station operation and maintenance
Dust monitoring: Hyperspectral remote sensing can be used to monitor the dust coverage of photovoltaic panels in photovoltaic power stations. By analyzing the reflectivity of photovoltaic panels in different bands, evaluating dust coverage, accurately estimating cleaning time, and reasonably arranging cleaning tasks, the power generation efficiency of power stations can be improved and maintenance costs can be reduced.
Fault diagnosis: Hyperspectral imaging can obtain thermal images and spectral information of photovoltaic modules, which helps to detect problems such as hot spot effects and aging of modules, accurately locate module-level faults, detect potential faults in a timely manner, take maintenance measures in advance, and reduce power generation losses.
In terms of photovoltaic system design and optimization
Spectral matching research: Hyperspectral technology can accurately measure the spectral distribution of solar radiation and the spectral response characteristics of photovoltaic modules. Through comparative analysis, the design of photovoltaic systems can be optimized so that photovoltaic modules can better match the solar spectrum and improve the utilization of solar radiation, thereby improving photovoltaic power generation efficiency.
Environmental adaptability assessment: Combined with hyperspectral data and geographic information, the solar spectrum characteristics and environmental factors in different regions are analyzed to provide a scientific basis for the site selection, layout and inclination design of photovoltaic power stations, and improve the adaptability and stability of photovoltaic systems under different environmental conditions.
Training site
