G. Ibarra-Berastegi, S. J. González-Rojí, Alain Ulazia, Sheila Carreno-Madinabeitia, J. Sáenz
{"title":"利用ERA5再分析计算黎巴嫩海上风能潜力:季节性空气密度变化的影响","authors":"G. Ibarra-Berastegi, S. J. González-Rojí, Alain Ulazia, Sheila Carreno-Madinabeitia, J. Sáenz","doi":"10.1109/ACTEA.2019.8851092","DOIUrl":null,"url":null,"abstract":"In this work, data from the ERA5 reanalysis (2010–2017) have been used to estimate the seasonal offshore wind energy potential for the Lebanese coast. Additionally, for this estimation, the effect of seasonal changes of air density has been incorporated. As a reference, the SIEMENS 160/6 turbine has been adopted and wind energy potential has been expressed as the capacity factor (CF) associated to this turbine. The spatial distribution of CF provides an idea of available wind energy potential in the Lebanese coast. The impact of seasonal air density changes has been assessed as percentage reduction in this indicator. In summer, the CF reduction due to high temperatures and lower air density, reaches in some Southern regions of the Lebanese coast to values around 5.5%. The use of such reanalyses is likely to increase in the future, thus making consultancy work easier since a lot of computational work with state-of-the-art meteorological models like WRF or MC2 (used to draw the National Wind Atlas of Lebanon) may not be necessary. Therefore, most likely in the future, for wind potential estimations, rather than heavy calculation efforts, the know-how for consultancy companies will focus into deeper analysis and interpretation of readily-available data from reanalyses.","PeriodicalId":432120,"journal":{"name":"2019 Fourth International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)","volume":"99 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Calculation of Lebanon offshore wind energy potential using ERA5 reanalysis: impact of seasonal air density changes\",\"authors\":\"G. Ibarra-Berastegi, S. J. González-Rojí, Alain Ulazia, Sheila Carreno-Madinabeitia, J. Sáenz\",\"doi\":\"10.1109/ACTEA.2019.8851092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, data from the ERA5 reanalysis (2010–2017) have been used to estimate the seasonal offshore wind energy potential for the Lebanese coast. Additionally, for this estimation, the effect of seasonal changes of air density has been incorporated. As a reference, the SIEMENS 160/6 turbine has been adopted and wind energy potential has been expressed as the capacity factor (CF) associated to this turbine. The spatial distribution of CF provides an idea of available wind energy potential in the Lebanese coast. The impact of seasonal air density changes has been assessed as percentage reduction in this indicator. In summer, the CF reduction due to high temperatures and lower air density, reaches in some Southern regions of the Lebanese coast to values around 5.5%. The use of such reanalyses is likely to increase in the future, thus making consultancy work easier since a lot of computational work with state-of-the-art meteorological models like WRF or MC2 (used to draw the National Wind Atlas of Lebanon) may not be necessary. Therefore, most likely in the future, for wind potential estimations, rather than heavy calculation efforts, the know-how for consultancy companies will focus into deeper analysis and interpretation of readily-available data from reanalyses.\",\"PeriodicalId\":432120,\"journal\":{\"name\":\"2019 Fourth International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)\",\"volume\":\"99 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Fourth International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACTEA.2019.8851092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Fourth International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACTEA.2019.8851092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Calculation of Lebanon offshore wind energy potential using ERA5 reanalysis: impact of seasonal air density changes
In this work, data from the ERA5 reanalysis (2010–2017) have been used to estimate the seasonal offshore wind energy potential for the Lebanese coast. Additionally, for this estimation, the effect of seasonal changes of air density has been incorporated. As a reference, the SIEMENS 160/6 turbine has been adopted and wind energy potential has been expressed as the capacity factor (CF) associated to this turbine. The spatial distribution of CF provides an idea of available wind energy potential in the Lebanese coast. The impact of seasonal air density changes has been assessed as percentage reduction in this indicator. In summer, the CF reduction due to high temperatures and lower air density, reaches in some Southern regions of the Lebanese coast to values around 5.5%. The use of such reanalyses is likely to increase in the future, thus making consultancy work easier since a lot of computational work with state-of-the-art meteorological models like WRF or MC2 (used to draw the National Wind Atlas of Lebanon) may not be necessary. Therefore, most likely in the future, for wind potential estimations, rather than heavy calculation efforts, the know-how for consultancy companies will focus into deeper analysis and interpretation of readily-available data from reanalyses.