{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T09:02:55Z","timestamp":1777626175413,"version":"3.51.4"},"reference-count":36,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["PTDC\/EEI-EEE\/31711\/2017"],"award-info":[{"award-number":["PTDC\/EEI-EEE\/31711\/2017"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Operational Program for Sustainability and Efficiency in the Use of Resources (POSEUR), through Portugal 2020 and the Cohesion Fund","award":["POSEUR-01-1001-FC-000007"],"award-info":[{"award-number":["POSEUR-01-1001-FC-000007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>The identification of extreme wind events and their driving forces are crucial to better integrating wind generation into the power system. Recent work related the occurrence of extreme wind events with some weather circulation patterns, enabling the identification of (i) wind power ramps and (ii) low-generation events as well as their intrinsic features, such as the intensity and time duration. Using Portugal as a case study, this work focuses on the application of a weather classification-type methodology to link the weather conditions with wind power generation, namely, the different types of extreme events. A long-term period is used to assess and characterize the changes in the occurrence of extreme weather events and corresponding intensity on wind power production. High variability is expected under cyclonic regimes, whereas low-generation events are most common in anticyclonic regimes. The results of the work provide significant insights regarding wind power production in Portugal, enabling an increase in its predictability.<\/jats:p>","DOI":"10.3390\/en14133944","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T12:03:27Z","timestamp":1625141007000},"page":"3944","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Identification of Extreme Wind Events Using a Weather Type Classification"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7368-8817","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Couto","sequence":"first","affiliation":[{"name":"LNEG\u2014Laborat\u00f3rio Nacional de Energia e Geologia, 2610-999 Lisbon, Portugal"}]},{"given":"Paula","family":"Costa","sequence":"additional","affiliation":[{"name":"LNEG\u2014Laborat\u00f3rio Nacional de Energia e Geologia, 2610-999 Lisbon, Portugal"}]},{"given":"Teresa","family":"Sim\u00f5es","sequence":"additional","affiliation":[{"name":"LNEG\u2014Laborat\u00f3rio Nacional de Energia e Geologia, 2610-999 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.energy.2019.03.092","article-title":"Status and perspectives on 100% renewable energy systems","volume":"175","author":"Hansen","year":"2019","journal-title":"Energy"},{"key":"ref_2","unstructured":"European Comission (2021, May 04). National Energy and Climate Plans. Available online: https:\/\/ec.europa.eu\/info\/energy-climate-change-environment\/implementation-eu-countries\/energy-and-climate-governance-and-reporting\/national-energy-and-climate-plans_en."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/j.renene.2018.02.130","article-title":"Energy droughts from variable renewable energy sources in European climates","volume":"125","author":"Raynaud","year":"2018","journal-title":"Renew. Energy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1016\/j.rser.2017.07.062","article-title":"A review at the role of storage in energy systems with a focus on Power to Gas and long-term storage","volume":"81","author":"Blanco","year":"2018","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1016\/j.rser.2015.07.154","article-title":"A review on the recent history of wind power ramp forecasting","volume":"52","year":"2015","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1016\/j.renene.2020.10.102","article-title":"Climatological analysis of solar and wind energy in Germany using the Grosswetterlagen classification","volume":"164","author":"Borsche","year":"2021","journal-title":"Renew. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Liu, F., Li, R., and Dreglea, A. (2019). Wind Speed and Power Ultra Short-Term Robust Forecasting Based on Takagi\u2013Sugeno Fuzzy Model. Energies, 12.","DOI":"10.3390\/en12183551"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Han, L., Qiao, Y., Li, M., and Shi, L. (2020). Wind Power Ramp Event Forecasting Based on Feature Extraction and Deep Learning. Energies, 13.","DOI":"10.3390\/en13236449"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/978-3-319-52920-2_7","article-title":"Random Forest Based Approach for Concept Drift Handling","volume":"Volume 661","author":"Zhukov","year":"2017","journal-title":"Communications in Computer and Information Science"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.energy.2017.01.104","article-title":"Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales","volume":"122","author":"Zhang","year":"2017","journal-title":"Energy"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"934","DOI":"10.1109\/TSTE.2014.2334062","article-title":"Impact of Weather Regimes on the Wind Power Ramp Forecast in Portugal","volume":"6","author":"Couto","year":"2015","journal-title":"IEEE Trans. Sustain. Energy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.renene.2016.10.002","article-title":"The influence of the main large-scale circulation patterns on wind power production in Portugal","volume":"102","author":"Correia","year":"2017","journal-title":"Renew. Energy"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lacerda, M., Couto, A., and Estanqueiro, A. (2017). Wind Power Ramps Driven by Windstorms and Cyclones. Energies, 10.","DOI":"10.3390\/en10101475"},{"key":"ref_14","unstructured":"(2019, July 12). NCEP\/NCAR NCEP\/NCAR Global Reanalysis Products, 1948\u2013Continuing. Available online: https:\/\/data.ucar.edu\/dataset\/ncep-ncar-global-reanalysis-products-1948-continuing1."},{"key":"ref_15","unstructured":"Berrisford, P., Dee, D.P., Poli, P., Brugge, R., Fielding, K., Fuentes, M., Kallberg, P., Kobayashi, S., Uppala, S., and Simmons, A. (2011). The ERA-Interim Archive Version 2.0., ECMWF."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5419","DOI":"10.1175\/JCLI-D-16-0758.1","article-title":"The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)","volume":"30","author":"Gelaro","year":"2017","journal-title":"J. Clim."},{"key":"ref_17","unstructured":"(2019, July 12). NCEP\/DOE NCEP\/DOE Reanalysis 2 (R2), Available online: https:\/\/psl.noaa.gov\/data\/gridded\/data.ncep.reanalysis2.html."},{"key":"ref_18","first-page":"D61C1TXF","article-title":"NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products","volume":"10","author":"Saha","year":"2011","journal-title":"Res. Data Arch. Natl. Cent. Atmos. Res. Comput. Inf. Syst. Lab."},{"key":"ref_19","first-page":"14","article-title":"Towards a high-resolution offshore wind Atlas\u2014The Portuguese Case","volume":"1356","author":"Couto","year":"2019","journal-title":"IOP Conf. Ser. J. Phys. Conf. Ser."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Baumgartner, J., Gruber, K., Simoes, S.G., Saint-Drenan, Y.M., and Schmidt, J. (2020). Less information, similar performance: Comparing machine learning-based time series ofwind power generation to renewables.ninja. Energies, 13.","DOI":"10.3390\/en13092277"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1016\/j.energy.2016.08.068","article-title":"Using bias-corrected reanalysis to simulate current and future wind power output","volume":"114","author":"Staffell","year":"2016","journal-title":"Energy"},{"key":"ref_22","unstructured":"Gonz\u00e1lez-Aparicio, I., Zucker, A., Careri, F., Monforti, F., Huld, T., and Badger, J. (2016). EMHIRES Dataset. Part I: Wind Power Generation European Meteorological Derived HIgh Resolution RES Generation Time Series for Present and Future Scenarios, European Comission."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.apenergy.2017.04.066","article-title":"Simulating European wind power generation applying statistical downscaling to reanalysis data","volume":"199","author":"Monforti","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_24","unstructured":"Couto, A. (2020). Creating a Wind Power Long-Term Time Series for Portugal\u2014A MCP Approach, LNEG Internal Technical Report."},{"key":"ref_25","unstructured":"Freedman, J., Markus, M., and Penc, R. (2008). Analysis of West Texas Wind Plant Ramp-Up and Ramp-Down Events, AWS Truewind LLC. AWS Truewind Report."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1088\/1748-9326\/ab91e9","article-title":"Frequency and duration of low-wind-power events in Germany Environmental Research Letters Frequency and duration of low-wind-power events in Germany","volume":"15","author":"Ohlendorf","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.pce.2009.12.010","article-title":"Cost733cat\u2014A database of weather and circulation type classifications","volume":"35","author":"Philipp","year":"2010","journal-title":"Phys. Chem. Earth Parts A B C"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1196\/annals.1446.019","article-title":"Classifications of atmospheric circulation patterns: Recent advances and applications","volume":"1146","author":"Huth","year":"2008","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1002\/joc.3498","article-title":"Lamb weather types derived from reanalysis products","volume":"33","author":"Jones","year":"2013","journal-title":"Int. J. Climatol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"131","DOI":"10.5194\/asr-14-131-2017","article-title":"Weather dependent estimation of continent-wide wind power generation based on spatio-temporal clustering","volume":"14","author":"Schyska","year":"2017","journal-title":"Adv. Sci. Res."},{"key":"ref_31","first-page":"18","article-title":"An initial climatology of gales over the North Sea","volume":"62","author":"Jenkinson","year":"1977","journal-title":"Synop. Climatol. Branch Memo."},{"key":"ref_32","unstructured":"Costa, P., Estanqueiro, A., and Miranda, P. (March, January 27). Building a wind atlas for mainland Portugal using a weather type classification. Proceedings of the European Wind Energy Conference, Athens, Greece."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1002\/1097-0088(20001115)20:13<1559::AID-JOC555>3.0.CO;2-5","article-title":"Circulation weather types and their influence on the precipitation regime in Portugal","volume":"20","author":"Trigo","year":"2000","journal-title":"Int. J. Climatol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/feart.2014.00025","article-title":"Circulation weather types and spatial variability of daily precipitation in the Iberian Peninsula","volume":"2","author":"Ramos","year":"2014","journal-title":"Front. Earth Sci."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Couto, A., and Estanqueiro, A. (2020). Exploring Wind and Solar PV Generation Complementarity to Meet Electricity Demand. Energies, 13.","DOI":"10.3390\/en13164132"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1002\/met.1472","article-title":"Current issues in wind energy meteorology","volume":"21","author":"Emeis","year":"2014","journal-title":"Meteorol. Appl."}],"container-title":["Energies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1073\/14\/13\/3944\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:24:37Z","timestamp":1760163877000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1073\/14\/13\/3944"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":36,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["en14133944"],"URL":"https:\/\/doi.org\/10.3390\/en14133944","relation":{},"ISSN":["1996-1073"],"issn-type":[{"value":"1996-1073","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}