How AI Reads the Solar Market: From Raw Data to Signals

Solar and energy markets now produce huge volumes of data: prices, weather, forecasts, grid constraints and flexibility offers. On their own, these data streams are hard to read in real time.

AI models can be trained to detect patterns, seasonality and unusual situations. They help turn raw inputs into simple signals such as: expected price range, probability of volatility, or likely imbalance risk.

For decision makers, the key is not the complexity of the model but whether the signal is clear, explainable and aligned with real business questions.