Short-term and regionalized photovoltaic power forecasting, enhanced by reference systems, on the example of Luxembourg

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A hybrid approach for PV-power forecasting, using metered PV-systems as references.

Demonstrating a comparably accurate forecast performance on our case study over a two years period.

Bottom-up model, able to reach high spatial resolutions if the data is available.


The authors developed a forecasting model for Luxembourg, able to predict the expected regional PV power up to 72 h ahead. The model works with solar irradiance forecasts, based on numerical weather predictions in hourly resolution. Using a set of physical equations, the algorithm is able to predict the expected hourly power production for PV systems in Luxembourg, as well as for a set of 23 chosen PV-systems which are used as reference systems. Comparing the calculated forecasts for the 23 reference systems to their measured power over a period of 2 years, revealed a comparably high accuracy of the forecast. The mean deviation (bias) of the forecast was 1.1% of the nominal power – a relatively low bias indicating low systemic error. The root mean square error (RMSE), lies around 7.4% – a low value for single site forecasts. Two approaches were tested in order to adapt the short-term forecast, based on the present forecast deviations for the reference systems. Thereby, it was possible to improve the very short term forecast on the time horizon of 1–3 h ahead, specifically for the remaining bias, but also systemic deviations can be identified and partially corrected (e.g. snow cover).


Photovoltaic forecasting

Forecasting performance


Photovoltaic integration

Solar forecasting

Solar energy integration

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