Expansion Details of AI Renewable Energy
PRF Technologies (Nasdaq: PRFX) announced on July 15, 2026, in Tel Aviv, Israel, an expansion of its DeepSolar Predictâ„¢ AI platform with a new feature called Battery-to-Revenue Intelligence. This capability aims to enhance revenue optimization from both solar and battery energy storage assets.
New Capabilities in AI Renewable Energy
The Battery-to-Revenue Intelligence feature incorporates various data points, including storage availability, operational constraints, and market conditions into its decision-support workflows. This enhancement allows operators to move beyond basic battery monitoring to a comprehensive evaluation of battery operating conditions. Key factors assessed include state of charge, availability, charging/discharging behavior, and operational readiness.
Decision Support Functionality for AI Renewable Energy
With this new capability, operators can determine optimal times for storage, discharging, and capacity preservation. The system evaluates market opportunities, production forecasts, and grid variability to guide decision-making.
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Future Developments in AI Renewable Energy
PRF Technologies plans to introduce a “What-if Battery Scenario” feature that will enable asset owners to assess the potential revenue impacts of integrating battery storage within their renewable energy portfolios.
Platform Integration for AI Renewable Energy
This expansion signifies a shift in the DeepSolar Predictâ„¢ platform from solely focusing on asset analytics and forecasting to a complete AI-driven revenue optimization model. These new features are expected to play a vital role in PRF’s forthcoming commercial platform, GridFeedâ„¢, which will facilitate renewable energy trading and market participation.
Company Overview of AI Renewable Energy
While PRF Technologies has a diverse portfolio that includes reformulating therapeutics, it has prioritized the development of AI-driven energy optimization technologies through its DeepSolar platform. The recent enhancements were validated using data from European markets.
Sources for AI Renewable Energy
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