Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36
The demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organi...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/12/4/712 |
| _version_ | 1798003445305704448 |
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| author | Ines Würth Laura Valldecabres Elliot Simon Corinna Möhrlen Bahri Uzunoğlu Ciaran Gilbert Gregor Giebel David Schlipf Anton Kaifel |
| author_facet | Ines Würth Laura Valldecabres Elliot Simon Corinna Möhrlen Bahri Uzunoğlu Ciaran Gilbert Gregor Giebel David Schlipf Anton Kaifel |
| author_sort | Ines Würth |
| collection | DOAJ |
| description | The demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organized a workshop on “Very Short-Term Forecasting of Wind Power„ in 2018 to discuss different approaches for the implementation of minute-scale forecasts into the power industry. IEA Wind is an international platform for the research community and industry. Task 32 tries to identify and mitigate barriers to the use of lidars in wind energy applications, while IEA Wind Task 36 focuses on improving the value of wind energy forecasts to the wind energy industry. The workshop identified three applications that need minute-scale forecasts: (1) wind turbine and wind farm control, (2) power grid balancing, (3) energy trading and ancillary services. The forecasting horizons for these applications range from around 1 s for turbine control to 60 min for energy market and grid control applications. The methods that can be applied to generate minute-scale forecasts rely on upstream data from remote sensing devices such as scanning lidars or radars, or are based on point measurements from met masts, turbines or profiling remote sensing devices. Upstream data needs to be propagated with advection models and point measurements can either be used in statistical time series models or assimilated into physical models. All methods have advantages but also shortcomings. The workshop’s main conclusions were that there is a need for further investigations into the minute-scale forecasting methods for different use cases, and a cross-disciplinary exchange of different method experts should be established. Additionally, more efforts should be directed towards enhancing quality and reliability of the input measurement data. |
| first_indexed | 2024-04-11T12:08:53Z |
| format | Article |
| id | doaj.art-cc6b8b339f9f4e739b45806ce50072a1 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:08:53Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cc6b8b339f9f4e739b45806ce50072a12022-12-22T04:24:40ZengMDPI AGEnergies1996-10732019-02-0112471210.3390/en12040712en12040712Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36Ines Würth0Laura Valldecabres1Elliot Simon2Corinna Möhrlen3Bahri Uzunoğlu4Ciaran Gilbert5Gregor Giebel6David Schlipf7Anton Kaifel8Stuttgart Wind Energy, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, GermanyForWind-University of Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, GermanyDTU Wind Energy (Risø Campus), Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, DenmarkWEPROG, Willemoesgade 15B, 5610 Assens, DenmarkDepartment of Engineering Sciences, Division of Electricity, Uppsala University, The Ångström Laboratory, Box 534, 751 21 Uppsala, SwedenDepartment of Electronic and Electrical Engineering, University of Strathclyde, 204 George St, Glasgow G11XW, UKDTU Wind Energy (Risø Campus), Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, DenmarkWind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91–93, 24943 Flensburg, GermanyZentrum für Sonnenenergie- und Wasserstoff-Forschung Baden-Württemberg, Meitnerstraße 1, 70563 Stuttgart, GermanyThe demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organized a workshop on “Very Short-Term Forecasting of Wind Power„ in 2018 to discuss different approaches for the implementation of minute-scale forecasts into the power industry. IEA Wind is an international platform for the research community and industry. Task 32 tries to identify and mitigate barriers to the use of lidars in wind energy applications, while IEA Wind Task 36 focuses on improving the value of wind energy forecasts to the wind energy industry. The workshop identified three applications that need minute-scale forecasts: (1) wind turbine and wind farm control, (2) power grid balancing, (3) energy trading and ancillary services. The forecasting horizons for these applications range from around 1 s for turbine control to 60 min for energy market and grid control applications. The methods that can be applied to generate minute-scale forecasts rely on upstream data from remote sensing devices such as scanning lidars or radars, or are based on point measurements from met masts, turbines or profiling remote sensing devices. Upstream data needs to be propagated with advection models and point measurements can either be used in statistical time series models or assimilated into physical models. All methods have advantages but also shortcomings. The workshop’s main conclusions were that there is a need for further investigations into the minute-scale forecasting methods for different use cases, and a cross-disciplinary exchange of different method experts should be established. Additionally, more efforts should be directed towards enhancing quality and reliability of the input measurement data.https://www.mdpi.com/1996-1073/12/4/712wind energyminute-scale forecastingforecasting horizonDoppler lidarDoppler radarnumerical weather prediction models |
| spellingShingle | Ines Würth Laura Valldecabres Elliot Simon Corinna Möhrlen Bahri Uzunoğlu Ciaran Gilbert Gregor Giebel David Schlipf Anton Kaifel Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 Energies wind energy minute-scale forecasting forecasting horizon Doppler lidar Doppler radar numerical weather prediction models |
| title | Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 |
| title_full | Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 |
| title_fullStr | Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 |
| title_full_unstemmed | Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 |
| title_short | Minute-Scale Forecasting of Wind Power—Results from the Collaborative Workshop of IEA Wind Task 32 and 36 |
| title_sort | minute scale forecasting of wind power results from the collaborative workshop of iea wind task 32 and 36 |
| topic | wind energy minute-scale forecasting forecasting horizon Doppler lidar Doppler radar numerical weather prediction models |
| url | https://www.mdpi.com/1996-1073/12/4/712 |
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