Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm
<p>Models used in wind resource assessment (WRA) range from engineering wake models and computational fluid dynamics models to mesoscale weather models with wind farm parameterizations and, more recently, large-eddy simulation (LES). The latter two produce time series of wind farm power of a c...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
|
| Series: | Wind Energy Science |
| Online Access: | https://wes.copernicus.org/articles/10/1471/2025/wes-10-1471-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849245522039144448 |
|---|---|
| author | B. Postema B. Postema R. A. Verzijlbergh R. A. Verzijlbergh P. van Dorp P. Baas H. J. J. Jonker H. J. J. Jonker |
| author_facet | B. Postema B. Postema R. A. Verzijlbergh R. A. Verzijlbergh P. van Dorp P. Baas H. J. J. Jonker H. J. J. Jonker |
| author_sort | B. Postema |
| collection | DOAJ |
| description | <p>Models used in wind resource assessment (WRA) range from engineering wake models and computational fluid dynamics models to mesoscale weather models with wind farm parameterizations and, more recently, large-eddy simulation (LES). The latter two produce time series of wind farm power of a certain period. This simulation period is, in the case of LES, mostly limited to <span class="inline-formula">≤</span> 1 year due to the computational costs. However, estimates of long-term (O(10 years)) power production are of high value to many parties involved in WRA. To address the need to calculate long-term annual energy production from <span class="inline-formula">≤</span> 1-year model runs, therefore, this paper presents methods to estimate the long-term (O(10 years)) power production of a wind farm using a <span class="inline-formula">≤</span> 1-year simulation. To validate the methods, a 10-year LES of a hypothetical large offshore wind farm is performed.</p>
<p>The methods work by estimating the conditional probability densities between wind farm power from the LES and wind speed from reanalysis data (ERA5) from a short (<span class="inline-formula">≤</span> 1 year) LES run. The conditional probability densities are then integrated over 10 years of ERA5 wind speed, yielding an estimate of the long-term mean power production.</p>
<p>This “long-term correction” method is validated on varying simulation periods, selected with four different day-selection techniques. When applied to a simulation period of 365 consecutive days, the methods can estimate the 10-year mean power production with a mean absolute error of around 0.35 % of the long-term mean. When choosing the simulation period with day-selection techniques that represent the long-term climate, only roughly 200 simulation days are needed to achieve the same accuracy.</p>
<p>Finally, a method to also include wind observations in the long-term correction is presented and tested. This requires an additional “free stream” LES run without active turbines and gives estimates of long-term power and wind that are corrected for a potential LES bias. Although validation of this final approach is difficult in the employed modeling strategy, it gives valuable insights and fits within the common WRA practice of combining models and observations.</p>
<p>The presented techniques are based on physical arguments, computationally cheap, and simple to implement. Furthermore, they are not limited to LES but can be applied to other time-series-based models. As such, they<span id="page1472"/> could be a useful extension for the diverse set of modeling, observational, and statistical techniques used in WRA.</p> |
| format | Article |
| id | doaj-art-9312293cd97643f4a0543a7c7b92dffb |
| institution | Kabale University |
| issn | 2366-7443 2366-7451 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Wind Energy Science |
| spelling | doaj-art-9312293cd97643f4a0543a7c7b92dffb2025-08-20T03:58:48ZengCopernicus PublicationsWind Energy Science2366-74432366-74512025-07-01101471148410.5194/wes-10-1471-2025Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farmB. Postema0B. Postema1R. A. Verzijlbergh2R. A. Verzijlbergh3P. van Dorp4P. Baas5H. J. J. Jonker6H. J. J. Jonker7Whiffle BV, Molengraaffsingel 8, 2629 JD Delft, the NetherlandsMeteorology and Air Quality Group, Wageningen University & Research, Droevendaalsesteeg 3a, 6708 PB Wageningen, the NetherlandsWhiffle BV, Molengraaffsingel 8, 2629 JD Delft, the NetherlandsDepartment of Engineering Systems and Services, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, the NetherlandsWhiffle BV, Molengraaffsingel 8, 2629 JD Delft, the NetherlandsWhiffle BV, Molengraaffsingel 8, 2629 JD Delft, the NetherlandsWhiffle BV, Molengraaffsingel 8, 2629 JD Delft, the NetherlandsDepartment of Geoscience and Remote Sensing, Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands<p>Models used in wind resource assessment (WRA) range from engineering wake models and computational fluid dynamics models to mesoscale weather models with wind farm parameterizations and, more recently, large-eddy simulation (LES). The latter two produce time series of wind farm power of a certain period. This simulation period is, in the case of LES, mostly limited to <span class="inline-formula">≤</span> 1 year due to the computational costs. However, estimates of long-term (O(10 years)) power production are of high value to many parties involved in WRA. To address the need to calculate long-term annual energy production from <span class="inline-formula">≤</span> 1-year model runs, therefore, this paper presents methods to estimate the long-term (O(10 years)) power production of a wind farm using a <span class="inline-formula">≤</span> 1-year simulation. To validate the methods, a 10-year LES of a hypothetical large offshore wind farm is performed.</p> <p>The methods work by estimating the conditional probability densities between wind farm power from the LES and wind speed from reanalysis data (ERA5) from a short (<span class="inline-formula">≤</span> 1 year) LES run. The conditional probability densities are then integrated over 10 years of ERA5 wind speed, yielding an estimate of the long-term mean power production.</p> <p>This “long-term correction” method is validated on varying simulation periods, selected with four different day-selection techniques. When applied to a simulation period of 365 consecutive days, the methods can estimate the 10-year mean power production with a mean absolute error of around 0.35 % of the long-term mean. When choosing the simulation period with day-selection techniques that represent the long-term climate, only roughly 200 simulation days are needed to achieve the same accuracy.</p> <p>Finally, a method to also include wind observations in the long-term correction is presented and tested. This requires an additional “free stream” LES run without active turbines and gives estimates of long-term power and wind that are corrected for a potential LES bias. Although validation of this final approach is difficult in the employed modeling strategy, it gives valuable insights and fits within the common WRA practice of combining models and observations.</p> <p>The presented techniques are based on physical arguments, computationally cheap, and simple to implement. Furthermore, they are not limited to LES but can be applied to other time-series-based models. As such, they<span id="page1472"/> could be a useful extension for the diverse set of modeling, observational, and statistical techniques used in WRA.</p>https://wes.copernicus.org/articles/10/1471/2025/wes-10-1471-2025.pdf |
| spellingShingle | B. Postema B. Postema R. A. Verzijlbergh R. A. Verzijlbergh P. van Dorp P. Baas H. J. J. Jonker H. J. J. Jonker Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm Wind Energy Science |
| title | Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm |
| title_full | Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm |
| title_fullStr | Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm |
| title_full_unstemmed | Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm |
| title_short | Estimating long-term annual energy production from shorter-time-series data: methods and verification with a 10-year large-eddy simulation of a large offshore wind farm |
| title_sort | estimating long term annual energy production from shorter time series data methods and verification with a 10 year large eddy simulation of a large offshore wind farm |
| url | https://wes.copernicus.org/articles/10/1471/2025/wes-10-1471-2025.pdf |
| work_keys_str_mv | AT bpostema estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT bpostema estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT raverzijlbergh estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT raverzijlbergh estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT pvandorp estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT pbaas estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT hjjjonker estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm AT hjjjonker estimatinglongtermannualenergyproductionfromshortertimeseriesdatamethodsandverificationwitha10yearlargeeddysimulationofalargeoffshorewindfarm |