Predicting the power grid frequency of European islands
Modelling, forecasting and overall understanding of the dynamics of the power grid and its frequency are essential for the safe operation of existing and future power grids. Much previous research was focused on large continental areas, while small systems, such as islands are less well-studied. The...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2023-01-01
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| Series: | Journal of Physics: Complexity |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-072X/acbd7f |
| _version_ | 1797844595255541760 |
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| author | Thorbjørn Lund Onsaker Heidi S Nygård Damiá Gomila Pere Colet Ralf Mikut Richard Jumar Heiko Maass Uwe Kühnapfel Veit Hagenmeyer Benjamin Schäfer |
| author_facet | Thorbjørn Lund Onsaker Heidi S Nygård Damiá Gomila Pere Colet Ralf Mikut Richard Jumar Heiko Maass Uwe Kühnapfel Veit Hagenmeyer Benjamin Schäfer |
| author_sort | Thorbjørn Lund Onsaker |
| collection | DOAJ |
| description | Modelling, forecasting and overall understanding of the dynamics of the power grid and its frequency are essential for the safe operation of existing and future power grids. Much previous research was focused on large continental areas, while small systems, such as islands are less well-studied. These natural island systems are ideal testing environments for microgrid proposals and artificially islanded grid operation. In the present paper, we utilise measurements of the power grid frequency obtained in European islands: the Faroe Islands, Ireland, the Balearic Islands and Iceland and investigate how their frequency can be predicted, compared to the Nordic power system, acting as a reference. The Balearic Islands are found to be particularly deterministic and easy to predict in contrast to hard-to-predict Iceland. Furthermore, we show that typically 2–4 weeks of data are needed to improve prediction performance beyond simple benchmarks. |
| first_indexed | 2024-04-09T17:24:49Z |
| format | Article |
| id | doaj.art-52c125afd1d046389873b72257af7070 |
| institution | Directory Open Access Journal |
| issn | 2632-072X |
| language | English |
| last_indexed | 2024-04-09T17:24:49Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Journal of Physics: Complexity |
| spelling | doaj.art-52c125afd1d046389873b72257af70702023-04-18T13:52:15ZengIOP PublishingJournal of Physics: Complexity2632-072X2023-01-014101501210.1088/2632-072X/acbd7fPredicting the power grid frequency of European islandsThorbjørn Lund Onsaker0Heidi S Nygård1https://orcid.org/0000-0002-1639-7634Damiá Gomila2https://orcid.org/0000-0002-3500-3434Pere Colet3https://orcid.org/0000-0002-5992-6292Ralf Mikut4https://orcid.org/0000-0001-9100-5496Richard Jumar5https://orcid.org/0000-0001-6854-4678Heiko Maass6https://orcid.org/0000-0002-8365-6042Uwe Kühnapfel7https://orcid.org/0000-0002-2218-3229Veit Hagenmeyer8https://orcid.org/0000-0002-3572-9083Benjamin Schäfer9https://orcid.org/0000-0003-1607-9748Faculty of Science and Technology, Norwegian University of Life Sciences , 1432 Ås, NorwayFaculty of Science and Technology, Norwegian University of Life Sciences , 1432 Ås, NorwayInstituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB),Campus Universitat Illes Balears, E-07122 Palma de Mallorca , SpainInstituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB),Campus Universitat Illes Balears, E-07122 Palma de Mallorca , SpainInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology , 76344 Eggenstein-Leopoldshafen, GermanyModelling, forecasting and overall understanding of the dynamics of the power grid and its frequency are essential for the safe operation of existing and future power grids. Much previous research was focused on large continental areas, while small systems, such as islands are less well-studied. These natural island systems are ideal testing environments for microgrid proposals and artificially islanded grid operation. In the present paper, we utilise measurements of the power grid frequency obtained in European islands: the Faroe Islands, Ireland, the Balearic Islands and Iceland and investigate how their frequency can be predicted, compared to the Nordic power system, acting as a reference. The Balearic Islands are found to be particularly deterministic and easy to predict in contrast to hard-to-predict Iceland. Furthermore, we show that typically 2–4 weeks of data are needed to improve prediction performance beyond simple benchmarks.https://doi.org/10.1088/2632-072X/acbd7fMachine learningforecastingpower gridtime series analysisEuropefrequency synchronisation |
| spellingShingle | Thorbjørn Lund Onsaker Heidi S Nygård Damiá Gomila Pere Colet Ralf Mikut Richard Jumar Heiko Maass Uwe Kühnapfel Veit Hagenmeyer Benjamin Schäfer Predicting the power grid frequency of European islands Journal of Physics: Complexity Machine learning forecasting power grid time series analysis Europe frequency synchronisation |
| title | Predicting the power grid frequency of European islands |
| title_full | Predicting the power grid frequency of European islands |
| title_fullStr | Predicting the power grid frequency of European islands |
| title_full_unstemmed | Predicting the power grid frequency of European islands |
| title_short | Predicting the power grid frequency of European islands |
| title_sort | predicting the power grid frequency of european islands |
| topic | Machine learning forecasting power grid time series analysis Europe frequency synchronisation |
| url | https://doi.org/10.1088/2632-072X/acbd7f |
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