A simplified seasonal forecasting strategy, applied to wind and solar power in Europe
We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector...
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ftenea:oai:iris.enea.it:20.500.12079/68492 2024-04-21T08:07:56+00:00 A simplified seasonal forecasting strategy, applied to wind and solar power in Europe Bett P. E. Thornton H. E. Troccoli A. De Felice M. Suckling E. Dubus L. Saint-Drenan Y. -M. Brayshaw D. J. Bett, P. E. Thornton, H. E. Troccoli, A. De Felice, M. Suckling, E. Dubus, L. Saint-Drenan, Y. -M. Brayshaw, D. J. 2022 https://hdl.handle.net/20.500.12079/68492 https://doi.org/10.1016/j.cliser.2022.100318 eng eng volume:27 firstpage:100318 journal:CLIMATE SERVICES https://hdl.handle.net/20.500.12079/68492 doi:10.1016/j.cliser.2022.100318 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85136115347 Climate services Renewable energy Seasonal forecasting Solar Wind info:eu-repo/semantics/article 2022 ftenea https://doi.org/20.500.12079/6849210.1016/j.cliser.2022.100318 2024-03-27T15:05:15Z We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector. Following previous studies, we show that, where there is skill, a simple linear regression-based method using the hindcast and forecast ensemble means provides a straightforward approach for producing calibrated probabilistic seasonal forecasts. This method extends naturally to using a larger-scale feature of the climate, such as the North Atlantic Oscillation, as the climate model predictor, and we show that this provides opportunities to improve the skill in some cases. We further demonstrate that, on seasonal-average and regional (e.g. national) average scales, wind and solar power generation are highly correlated with single climate variables (wind speed and irradiance). The detailed non-linear transformations from meteorological quantities to energy quantities, which are essential for detailed simulation of power system operations, are usually not necessary when forecasting gross wind or solar generation potential at seasonal-mean regional-mean scales. Together, our results demonstrate that where there is skill in seasonal forecasts of wind speed and irradiance, or a correlated larger-scale climate predictor, skilful forecasts of seasonal mean wind and solar power generation can be made based on the climate variable alone, without requiring complex transformations. This greatly simplifies the process of developing a useful seasonal climate service. Article in Journal/Newspaper North Atlantic North Atlantic oscillation ENEA-IRIS Open Archive (Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile) Climate Services 27 100318 |
institution |
Open Polar |
collection |
ENEA-IRIS Open Archive (Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile) |
op_collection_id |
ftenea |
language |
English |
topic |
Climate services Renewable energy Seasonal forecasting Solar Wind |
spellingShingle |
Climate services Renewable energy Seasonal forecasting Solar Wind Bett P. E. Thornton H. E. Troccoli A. De Felice M. Suckling E. Dubus L. Saint-Drenan Y. -M. Brayshaw D. J. A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
topic_facet |
Climate services Renewable energy Seasonal forecasting Solar Wind |
description |
We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector. Following previous studies, we show that, where there is skill, a simple linear regression-based method using the hindcast and forecast ensemble means provides a straightforward approach for producing calibrated probabilistic seasonal forecasts. This method extends naturally to using a larger-scale feature of the climate, such as the North Atlantic Oscillation, as the climate model predictor, and we show that this provides opportunities to improve the skill in some cases. We further demonstrate that, on seasonal-average and regional (e.g. national) average scales, wind and solar power generation are highly correlated with single climate variables (wind speed and irradiance). The detailed non-linear transformations from meteorological quantities to energy quantities, which are essential for detailed simulation of power system operations, are usually not necessary when forecasting gross wind or solar generation potential at seasonal-mean regional-mean scales. Together, our results demonstrate that where there is skill in seasonal forecasts of wind speed and irradiance, or a correlated larger-scale climate predictor, skilful forecasts of seasonal mean wind and solar power generation can be made based on the climate variable alone, without requiring complex transformations. This greatly simplifies the process of developing a useful seasonal climate service. |
author2 |
Bett, P. E. Thornton, H. E. Troccoli, A. De Felice, M. Suckling, E. Dubus, L. Saint-Drenan, Y. -M. Brayshaw, D. J. |
format |
Article in Journal/Newspaper |
author |
Bett P. E. Thornton H. E. Troccoli A. De Felice M. Suckling E. Dubus L. Saint-Drenan Y. -M. Brayshaw D. J. |
author_facet |
Bett P. E. Thornton H. E. Troccoli A. De Felice M. Suckling E. Dubus L. Saint-Drenan Y. -M. Brayshaw D. J. |
author_sort |
Bett P. E. |
title |
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
title_short |
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
title_full |
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
title_fullStr |
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
title_full_unstemmed |
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe |
title_sort |
simplified seasonal forecasting strategy, applied to wind and solar power in europe |
publishDate |
2022 |
url |
https://hdl.handle.net/20.500.12079/68492 https://doi.org/10.1016/j.cliser.2022.100318 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
volume:27 firstpage:100318 journal:CLIMATE SERVICES https://hdl.handle.net/20.500.12079/68492 doi:10.1016/j.cliser.2022.100318 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85136115347 |
op_doi |
https://doi.org/20.500.12079/6849210.1016/j.cliser.2022.100318 |
container_title |
Climate Services |
container_volume |
27 |
container_start_page |
100318 |
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1796948052739620864 |