Chapter 09 · Sustainability & AISustainability & AI
Renewable energy forecasting
Definition
Predicting the output of variable renewable generation — wind, solar and hydro — from weather data, plant characteristics and operating history.
References
This source provides part of the technical or institutional basis for the definition.
This source supports the explanation of how the term is applied, measured or governed in practice.
Overview
What it means
Forecasting horizons run from minutes (grid balancing) to days (market trading and unit commitment). Machine learning has steadily improved accuracy by learning site-specific behaviour that physical models miss; the IEA identifies such digitalisation as central to integrating variable renewables.
How it is used
Grid operators, traders and plant owners use forecasts to schedule generation, storage and demand response, reducing curtailment and reliance on fossil backup. VPPs and flexibility markets are built on these predictions.
Why it matters
Every percentage point of forecast error costs backup capacity, fuel or spilled clean energy. As renewable shares rise, forecasting accuracy becomes a direct determinant of system emissions and cost.