Amperon unveils probabilistic forecasting tools for solar and wind assets

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A Better Energy solar-plus-wind project.
Amperon’s new short-term forecasting tool is designed to help market and operational decision-making in a renewables-heavy grid. Image: Better Energy.

US-based energy forecasting company Amperon has launched a new AI-based short-term probabilistic forecasting tool for solar and wind generation assets.

The company said its Asset Solar and Wind Short-Term Forecasts would enable renewable energy operators, independent power producers, utilities and others to make better market and operational decisions by offering a new way to quantify generation uncertainty.

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As power markets grow more volatile with increased solar and wind penetration, energy companies face greater pressure to forecast generation accurately and plan for a wider range of possible outcomes. 

Amperon said the new tool addresses this by providing short-term forecasts of solar and wind generation, offering energy companies a clearer picture of potential output fluctuations. The forecasts provide hourly and sub-hourly visibility up to 15 days ahead, with 19 percentile bands from P5 through P95 delivered via API.

Unlike traditional deterministic forecasts, which provide a single predicted value, probabilistic forecasting delivers a range of possible outcomes along with their likelihood. This approach enables operators to quantify uncertainty and make more informed decisions in real-time.

“By moving beyond a single-point forecast, the product helps renewable energy operators and IPPs better manage market exposure, while also giving gentailers and utilities a stronger basis for net load planning, supply stack decisions, and renewable portfolio optimisation,” Amperon said in a statement marking the launch.

For example, an independent power producer bidding into the day-ahead market can use probabilistic forecasting to see when weather uncertainty materially increases the risk of underperformance during a key interval, then adjust its bid accordingly to reduce imbalance exposure and protect margins.

Amperon’s platform leverages advanced machine learning algorithms and real-time data inputs, including weather conditions, historical generation patterns, and grid dynamics. By incorporating probabilistic models, the company aims to improve the accuracy of renewable energy forecasts, which are often subject to variability due to changing weather conditions and other external factors.

“Our focus at Amperon is simple: keep pushing forecasting forward so customers have the insight they need to make smarter decisions,” said Sean Kelly, CEO of Amperon. “We recently expanded our weather-informed, probabilistic Grid Mid-Term Forecast into Europe after launching it in the US, and now we are bringing that same commitment to innovation to probabilistic Asset Short-Term Forecasts—giving customers a clearer view of uncertainty and more confidence in how they plan, bid and operate.”

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