Chinese Researchers Claim That Their Ai Model Can Pinpoint The Excellent Places For Double-Faced Solar Panels


A group of Chinese researchers has created an artificial intelligence tool to determine the desirable spot to put in double-sided solar panels, thus closing a significant information need in green energy.

Dual-sided panels can produce more power than their single-faced counterparts. The researchers claimed that installing them in areas east of the Tibetan Plateau and other locations in northern China could increase the solar energy output.

Power Generating Capability

The power-generating capability of the double-sided photovoltaic (PV) panel largely depends on how much diffuse solar radiation gets to its rear, as the team outlined in an article published in the peer-reviewed Journal of Remote Sensing last month.

If the conditions are suitable for sunlight, Two-sided solar panels generate more power than standard ones. However, they can be challenging to move and maintain; therefore, selecting the right place for them is essential to ensure the desirable utilization of the resources.

Largest Solar PV Module Manufacturer

China is the largest solar PV module manufacturer modules. The figure is around 80 percent of the total global population.

However, it must have the data to determine the accurate places to install two-sided solar panels.

Only 17 radiation stations gather data on the quantity and the type of “solar power” available in a particular area. This includes information on direct radiation – which is beaming directly from the sun and directed to the front face of the solar panel and diffuse radiation that can be scattered through the atmosphere and is most likely to get detected on the panels’ rear surface.

AI Model

The equipment used at these stations requires adjustments each year and routine maintenance, which results in a significant cost of operation.

To address the need for ground-based data, researchers at Tsinghua University in Beijing and the National Tibetan Plateau Data Centre have developed an AI model based on sunlight information from more than 2,500 meteorological stations in China.

The AI was based on solar radiation data collected through satellite remote sensing meteorological data from the surface to estimate the amount of indirect and direct radiation in any particular spot.

“In principle, the model can be used on a global scale with no more training in locally sourced data,” researchers wrote.

China Requires Ten Times the Wind and Solar Power

Author senior Yang Kun, a professor of the earth system science department at Tsinghua, said that the lack of a comprehensive radiation database resulted in a lack of information available to benefit the authorities and the solar industry in determining the desirable locations for panels.

“Now the results from the AI model, which is supported by satellite data will inform the decision-making process on the best type of solar panels to put in place to maximize the benefits of the solar energy,” Yang said.

Solar power will account for around 5 percent of China’s electricity generation in 2022.

Yang claimed that the AI system also revealed the solar power potential of the remote areas of China that do not have power line infrastructure. This may influence future research and development.

China Produces Electric Energy In Its Deserts 

The first author, Shao Chongkun Shao Chongkun, Ph.D. student at Tsinghua Shao Chongkun, stated that the region around and encompassing the Taklamakan Desert in the southwestern region of Xinjiang autonomous region, as well as the eastern part of the Tibetan Plateau was ideal spot for panels with two sides.

“Direct sunlight is extremely high in the high-altitude plateau, where the air is drier and diffuse solar radiation is significant because of its diverse terrain and extensive cloud coverage.” Shao said.

“Both side of the solar panel will be receiving large amounts of radiation within these areas.”

The team evaluated their calculations with data on radiation around the globe and discovered that their AI model was highly accurate, Shao said, adding that combining their models with other meteorological information from nations can benefit the system to be utilized to calculate solar radiation projections worldwide.

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