Solar power is using AI and machine learning for better efficiency

Solar-energy experts are working together to utilize artificial intelligence (AI) diagnostic ability to increase performance in solar power systems.

Solar-energy experts are working together to utilize artificial intelligence (AI) diagnostic ability to increase performance in solar power systems.

Photovoltaic (PV) modular solar technology is used to create sustainable and green energy using sunlight. The industry and the customers, researchers say, would benefit from more effective solar power plants.

"Solar is currently the cheapest form of electricity in the world, but the efficiency of actual power plants is being evaluated one by one, and it is just not tractable, especially for a fast-growing industry," said Roger French, Director of the Research Center for Solar Durability and Expansion, Kyocera, Professor of Ceramics, Department of Materials. "This project will help us learn how to improve the efficiency of solar energy."

The work, financed by a US $750,000 US$ 3-year grant. DOE, consisting of a large solar-technology program proposed by the DOE in 2020, included $7.3 million primarily for engine learning and other solar-powered AI solutions. The Department of Energy is part of the DOE.

The project is currently headed by French and research associate professor Laura Bruckman of Materials Science and Engineering.

In short, the project led by Case Western Reserve attempts to use computers to improve and analyze data from a variety of nearby photovoltaic systems to measure their short and long-term performance.
These machine learning methods are employed to resolve the quality of data problems impacting each factory. In doing so, researchers are going to use a "neural network spatiotemporal graph model."
The team member Mehmet Koyutürk, Computer Science Professor: "Since we have no robot inspecting all photovoltaic plants who are testing their information for similar patterns between their behaviors, but instead use all collected data to act as we did."

"In their area of the country, various companies have data on their technology," said Mehmet Koyutürk, "but we had no chance to collect and analyze data from various companies and regions so far."
Financing for projects that "improve the affordability, reliability, and value of solar technology in the national grid and address emerging challenges in solar energy" was set up at Solar Energy Developments Office for the Fiscal Year 2020 (SETO 2020).

It funds projects from early-stage photovoltaic to solar thermal, highlights convergence of diverse technologies, and lowers costs in building solar power systems.

Article from Syed Mohammed
Fourth Partner Energy Pvt. Ltd.

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