The validation applied real-world historical weather data, renewable energy production records and market data - including utility-scale datasets and market conditions representative of European energy markets - to evaluate the platform’s optimization recommendations and decision-support workflows across day-ahead and intraday scenarios under a range of operating conditions.

DeepSolar Predict combines weather intelligence, production forecasting and market analytics to support decision-making across day-ahead and intraday energy markets. The validation phase builds on platform milestones announced earlier this year, including DeepSolar’s participation in the NVIDIA Connect program and the Company’s patent application covering plant-level micro-climate modeling.

"Renewable energy operators are no longer managing only production — they are managing financial exposure in increasingly dynamic power markets," said Efi Cohen-Arazi, Chief Executive Officer of PRF Technologies. "Completing this validation using real-world datasets is an important step toward the planned commercial launch of DeepSolar Predict and supports our goal of bringing advanced revenue optimization capabilities to renewable energy operators."

As renewable energy penetration continues to increase globally, asset owners and energy traders face growing challenges in forecasting production, managing market exposure and maximizing revenue opportunities. PRF believes artificial intelligence and advanced analytics will play an increasingly important role in helping operators navigate these challenges.

"The renewable energy industry has made tremendous progress in operational monitoring over the past decade," added Efi Cohen-Arazi. "We believe the next opportunity lies in helping operators transform that information into optimized market decisions. This validation gives us additional confidence as we advance DeepSolar Predict toward commercial launch."