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SmartHelio Launches AI Solar Forecasting Tool with 98.5% Accuracy – pv magazine International

SmartHelio has developed an AI-based solar activity forecasting tool that is 98.5% accurate and uses socio-economic and climate data for predictive analytics.

SmartHelio, a Swiss solar software developer, is launching its AI-powered suite, offering up to 98.5% accuracy in forecasting global horizontal irradiance (GHI) and wind resources, as well as 95% accuracy in predicting failures, to reduce the risk of future PV investments and brownfield acquisitions.

The suite includes the predictive Autopilot solution and a Climate Risk Assessment (CRA) tool that uses meteorological data to guide investment decisions. It also offers component selection, ensuring flexibility, safety and cost-effectiveness of solar installations.

SmartHelio will showcase its AI-powered Suite at RE+ 2024, which will take place from September 9 to 12 in Anaheim, California.

“PV plant management is rife with inefficiencies, largely due to fragmented data and outdated reporting methods that delay decision-making and expose investors to significant financial risk. Addressing these challenges is key to improving the industry’s performance and profitability,” said SmartHelio CEO Govinda Upadhyay. “Many tools offer market-leading performance improvements, but plants using SmartHelio’s AI-based solution have seen up to a six-fold return on investment.”

The CRA tool combines socioeconomic data, including urbanization trends, deforestation, and aerosol concentrations, with microclimate factors. It predicts solar irradiance and wind speed by analyzing more than 100 variables, including historical and current weather data, local environmental factors such as proximity to lakes or mountains, global climate indicators such as El Niño/La Niña, and human impacts such as pollution and urbanization.

The Autopilot platform provides recommendations for future development and optimal plant operation, helping operators and owners maximize efficiency while minimizing costs. It enables them to prevent downtime and reduce operating and replacement costs by 80%.

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