Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework
Large scale coherent structures in the atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In order to understand the dynamics of large scale structures, we perform proper orthogonal decomposition (POD) analysis of a finite sized wind turbine array canopy...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/7/1660 |
| _version_ | 1797571593779544064 |
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| author | Tanmoy Chatterjee Yulia T. Peet |
| author_facet | Tanmoy Chatterjee Yulia T. Peet |
| author_sort | Tanmoy Chatterjee |
| collection | DOAJ |
| description | Large scale coherent structures in the atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In order to understand the dynamics of large scale structures, we perform proper orthogonal decomposition (POD) analysis of a finite sized wind turbine array canopy in the current paper. The POD analysis sheds light on the dynamics of large scale coherent modes as well as on the scaling of the eigenspectra in the heterogeneous wind farm. We also propose adapting a novel Fourier-POD (FPOD) modal decomposition which performs POD analysis of spanwise Fourier-transformed velocity. The FPOD methodology helps us in decoupling the length scales in the spanwise and streamwise direction when studying the 3D energetic coherent modes. Additionally, the FPOD eigenspectra also provide deeper insights for understanding the scaling trends of the three-dimensional POD eigenspectra and its convergence, which is inherently tied to turbulent dynamics. Understanding the behaviour of large scale structures in wind farm flows would not only help better assess reduced order models (ROM) for forecasting the flow and power generation but would also play a vital role in improving the decision making abilities in wind farm optimization algorithms in future. Additionally, this study also provides guidance for better understanding of the POD analysis in the turbulence and wind farm community. |
| first_indexed | 2024-03-10T20:42:55Z |
| format | Article |
| id | doaj.art-6a8d471cae574d4aa364f5b039019f4d |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T20:42:55Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6a8d471cae574d4aa364f5b039019f4d2023-11-19T20:33:27ZengMDPI AGEnergies1996-10732020-04-01137166010.3390/en13071660Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD FrameworkTanmoy Chatterjee0Yulia T. Peet1General Electric Company (GE Global Research), Niskayuna, NY 12309, USAMechanical and Aerospace Engineering, Arizona State University, Tempe, AZ 85287, USALarge scale coherent structures in the atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In order to understand the dynamics of large scale structures, we perform proper orthogonal decomposition (POD) analysis of a finite sized wind turbine array canopy in the current paper. The POD analysis sheds light on the dynamics of large scale coherent modes as well as on the scaling of the eigenspectra in the heterogeneous wind farm. We also propose adapting a novel Fourier-POD (FPOD) modal decomposition which performs POD analysis of spanwise Fourier-transformed velocity. The FPOD methodology helps us in decoupling the length scales in the spanwise and streamwise direction when studying the 3D energetic coherent modes. Additionally, the FPOD eigenspectra also provide deeper insights for understanding the scaling trends of the three-dimensional POD eigenspectra and its convergence, which is inherently tied to turbulent dynamics. Understanding the behaviour of large scale structures in wind farm flows would not only help better assess reduced order models (ROM) for forecasting the flow and power generation but would also play a vital role in improving the decision making abilities in wind farm optimization algorithms in future. Additionally, this study also provides guidance for better understanding of the POD analysis in the turbulence and wind farm community.https://www.mdpi.com/1996-1073/13/7/1660proper orthogonal decompositionwind farmseigenspectracounter-rotating roll cells |
| spellingShingle | Tanmoy Chatterjee Yulia T. Peet Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework Energies proper orthogonal decomposition wind farms eigenspectra counter-rotating roll cells |
| title | Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework |
| title_full | Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework |
| title_fullStr | Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework |
| title_full_unstemmed | Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework |
| title_short | Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework |
| title_sort | dynamics of large scale turbulence in finite sized wind farm canopy using proper orthogonal decomposition and a novel fourier pod framework |
| topic | proper orthogonal decomposition wind farms eigenspectra counter-rotating roll cells |
| url | https://www.mdpi.com/1996-1073/13/7/1660 |
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