
Forecast accuracy for wind and solar: MAE, RMSE and nRMSE explained
Learn what common forecast error metrics describe and what to check before comparing results.
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Read explainers on forecast evaluation, trading, solar generation and renewable energy operations.

Learn what common forecast error metrics describe and what to check before comparing results.
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See where wind and solar forecasts fit into portfolio planning for a virtual power plant.
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Understand how solar generation changes the shape of net demand and why timing matters.
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Learn how P50 and P90 describe different levels of confidence in an energy-yield estimate.
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Understand the radiation inputs behind a solar power forecast, their units and the checks that make comparisons meaningful.
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There is no single weather model that is best for every renewable asset, lead time and weather situation.
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Calculate capacity factor correctly and separate resource, availability and commercial constraints when interpreting it.
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An ensemble is a set of forecasts rather than a single forecast trajectory.
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Match solar forecasting methods to your decision horizon and design a fair asset-level evaluation.
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Explore how fresh observations support near-term production decisions and how to test latency, ramps and fallback behaviour.
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Separate available generation from delivered output and understand how curtailment changes data, scheduling and evaluation.
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Connect renewable forecasts with battery constraints and evaluate storage strategies without assuming a revenue guarantee.
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Understand the production profile behind a PPA and identify the quantity, timing and operational assumptions a forecast must support.
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Numerical weather prediction, usually shortened to NWP, estimates future atmospheric conditions from an analysed starting state and a model of atmospheric processes.
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Understand the conversion from wind speed to power and why a measured plant rarely follows one ideal curve exactly.
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Understand how production uncertainty enters grid planning and operations, and where forecasting complements physical flexibility.
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Connect forecast issue times and production revisions to electricity scheduling without confusing generation forecasts with price predictions.
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Calculate PV performance ratio with consistent boundaries and use it to investigate losses without treating it as a universal accuracy score.
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