Understanding and mitigating the impact of data gaps on offshore wind resource estimates
<p>Like almost all measurement datasets, wind energy siting data are subject to data gaps that can for instance originate from a failure of the measurement devices or data loggers. This is in particular true for offshore wind energy sites where the harsh climate can restrict the accessibility...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2021-04-01
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| Series: | Wind Energy Science |
| Online Access: | https://wes.copernicus.org/articles/6/505/2021/wes-6-505-2021.pdf |
| _version_ | 1819138671321808896 |
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| author | J. Gottschall M. Dörenkämper |
| author_facet | J. Gottschall M. Dörenkämper |
| author_sort | J. Gottschall |
| collection | DOAJ |
| description | <p>Like almost all measurement datasets, wind energy siting data are subject to data gaps that can for instance originate from a failure of the measurement devices or data loggers. This is in particular true for offshore wind energy sites where the harsh climate can restrict the accessibility of the measurement platform, which can also lead to much longer gaps than onshore. In this study, we investigate the impact of data gaps, in terms of a bias in the estimation of siting parameters and its mitigation by correlation and filling with mesoscale model data. Investigations are performed for three offshore sites in Europe, considering 2 years of parallel measurement data at the sites, and based on typical wind energy siting statistics. We find a mitigation of the data gaps' impact, i.e. a reduction of the observed biases, by a factor of 10 on mean wind speed, direction and Weibull scale parameter and a factor of 3 on Weibull shape parameter. With increasing gap length, the gaps' impact increases linearly for the overall measurement period while this behaviour is more complex when investigated in terms of seasons. This considerable reduction of the impact of the gaps found for the statistics of the measurement time series almost vanishes when considering long-term corrected data, for which we refer to 30 years of reanalysis data.</p> |
| first_indexed | 2024-12-22T11:10:28Z |
| format | Article |
| id | doaj.art-fa8e17944dda4250802a244a7747f959 |
| institution | Directory Open Access Journal |
| issn | 2366-7443 2366-7451 |
| language | English |
| last_indexed | 2024-12-22T11:10:28Z |
| publishDate | 2021-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Wind Energy Science |
| spelling | doaj.art-fa8e17944dda4250802a244a7747f9592022-12-21T18:28:11ZengCopernicus PublicationsWind Energy Science2366-74432366-74512021-04-01650552010.5194/wes-6-505-2021Understanding and mitigating the impact of data gaps on offshore wind resource estimatesJ. Gottschall0M. Dörenkämper1Fraunhofer Institute for Wind Energy Systems IWES, Am Seedeich 45, 27572 Bremerhaven, GermanyFraunhofer Institute for Wind Energy Systems IWES, Küpkersweg 70, 26129 Oldenburg, Germany<p>Like almost all measurement datasets, wind energy siting data are subject to data gaps that can for instance originate from a failure of the measurement devices or data loggers. This is in particular true for offshore wind energy sites where the harsh climate can restrict the accessibility of the measurement platform, which can also lead to much longer gaps than onshore. In this study, we investigate the impact of data gaps, in terms of a bias in the estimation of siting parameters and its mitigation by correlation and filling with mesoscale model data. Investigations are performed for three offshore sites in Europe, considering 2 years of parallel measurement data at the sites, and based on typical wind energy siting statistics. We find a mitigation of the data gaps' impact, i.e. a reduction of the observed biases, by a factor of 10 on mean wind speed, direction and Weibull scale parameter and a factor of 3 on Weibull shape parameter. With increasing gap length, the gaps' impact increases linearly for the overall measurement period while this behaviour is more complex when investigated in terms of seasons. This considerable reduction of the impact of the gaps found for the statistics of the measurement time series almost vanishes when considering long-term corrected data, for which we refer to 30 years of reanalysis data.</p>https://wes.copernicus.org/articles/6/505/2021/wes-6-505-2021.pdf |
| spellingShingle | J. Gottschall M. Dörenkämper Understanding and mitigating the impact of data gaps on offshore wind resource estimates Wind Energy Science |
| title | Understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| title_full | Understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| title_fullStr | Understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| title_full_unstemmed | Understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| title_short | Understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| title_sort | understanding and mitigating the impact of data gaps on offshore wind resource estimates |
| url | https://wes.copernicus.org/articles/6/505/2021/wes-6-505-2021.pdf |
| work_keys_str_mv | AT jgottschall understandingandmitigatingtheimpactofdatagapsonoffshorewindresourceestimates AT mdorenkamper understandingandmitigatingtheimpactofdatagapsonoffshorewindresourceestimates |