Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms
A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/6/1964 |
| _version_ | 1797471882956505088 |
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| author | Bart Matthijs Doekemeijer Eric Simley Paul Fleming |
| author_facet | Bart Matthijs Doekemeijer Eric Simley Paul Fleming |
| author_sort | Bart Matthijs Doekemeijer |
| collection | DOAJ |
| description | A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model’s accuracy. We assume a fixed turbulence intensity of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>I</mi><mo>∞</mo></msub><mo>=</mo><mn>6</mn><mo>%</mo></mrow></semantics></math></inline-formula> and a standard deviation on the inflow wind direction of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>σ</mi><mrow><mi>w</mi><mi>d</mi></mrow></msub><mo>=</mo><mn>3</mn><mo>°</mo></mrow></semantics></math></inline-formula> in our Gaussian model. First, we demonstrate the non-uniqueness issue of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>I</mi><mo>∞</mo></msub></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>σ</mi><mrow><mi>w</mi><mi>d</mi></mrow></msub></semantics></math></inline-formula>, which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses. |
| first_indexed | 2024-03-09T19:54:23Z |
| format | Article |
| id | doaj.art-b276176dc623483a9a426fe54d927c0a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T19:54:23Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-b276176dc623483a9a426fe54d927c0a2023-11-24T01:02:31ZengMDPI AGEnergies1996-10732022-03-01156196410.3390/en15061964Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind FarmsBart Matthijs Doekemeijer0Eric Simley1Paul Fleming2National Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USANational Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USANational Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USAA recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model’s accuracy. We assume a fixed turbulence intensity of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>I</mi><mo>∞</mo></msub><mo>=</mo><mn>6</mn><mo>%</mo></mrow></semantics></math></inline-formula> and a standard deviation on the inflow wind direction of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>σ</mi><mrow><mi>w</mi><mi>d</mi></mrow></msub><mo>=</mo><mn>3</mn><mo>°</mo></mrow></semantics></math></inline-formula> in our Gaussian model. First, we demonstrate the non-uniqueness issue of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>I</mi><mo>∞</mo></msub></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>σ</mi><mrow><mi>w</mi><mi>d</mi></mrow></msub></semantics></math></inline-formula>, which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses.https://www.mdpi.com/1996-1073/15/6/1964FLORISmodel validationmodel comparisonoffshore windwake steeringSCADA |
| spellingShingle | Bart Matthijs Doekemeijer Eric Simley Paul Fleming Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms Energies FLORIS model validation model comparison offshore wind wake steering SCADA |
| title | Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms |
| title_full | Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms |
| title_fullStr | Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms |
| title_full_unstemmed | Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms |
| title_short | Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms |
| title_sort | comparison of the gaussian wind farm model with historical data of three offshore wind farms |
| topic | FLORIS model validation model comparison offshore wind wake steering SCADA |
| url | https://www.mdpi.com/1996-1073/15/6/1964 |
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