A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines
Wind turbine aerodynamic interactions within wind farms lead to significant energy losses. Optimizing the flow between turbines presents a promising solution to mitigate these losses. While analytical models offer a fundamental approach to understanding aerodynamic interactions, further development...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/15/5710 |
| _version_ | 1797586830051246080 |
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| author | Esmail Mahmoodi Mohammad Khezri Arash Ebrahimi Uwe Ritschel Leonardo P. Chamorro Ali Khanjari |
| author_facet | Esmail Mahmoodi Mohammad Khezri Arash Ebrahimi Uwe Ritschel Leonardo P. Chamorro Ali Khanjari |
| author_sort | Esmail Mahmoodi |
| collection | DOAJ |
| description | Wind turbine aerodynamic interactions within wind farms lead to significant energy losses. Optimizing the flow between turbines presents a promising solution to mitigate these losses. While analytical models offer a fundamental approach to understanding aerodynamic interactions, further development and refinement of these models are imperative. We propose a simplified analytical model that combines the Gaussian wake model and the cylindrical vortex induction model to evaluate the interaction between wake and induction zones in 3.5 MW wind turbines with 328 m spacing. The model’s validation is conducted using field data from a nacelle-mounted LiDAR system on the downstream turbine. The ‘Direction to Hub’ parameter facilitates a comparison between the model predictions and LiDAR measurements at distances ranging from 50 m to 300 m along the rotor axis. Overall, the results exhibit reasonable agreement in flow trends, albeit with discrepancies of up to 15° in predicting peak interactions. These deviations are attributed to the single-hat Gaussian shape of the wake model and the absence of wake expansion consideration, which can be revisited to improve model fidelity. The ‘Direction to Hub’ parameter proves valuable for model validation and LiDAR calibration, enabling a detailed flow analysis between turbines. This analytical modeling approach holds promise for enhancing wind farm efficiency by advancing our understanding of turbine interactions. |
| first_indexed | 2024-03-11T00:28:43Z |
| format | Article |
| id | doaj.art-bbc64ce719184feca8c55acaa872cd81 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T00:28:43Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-bbc64ce719184feca8c55acaa872cd812023-11-18T22:51:49ZengMDPI AGEnergies1996-10732023-07-011615571010.3390/en16155710A Simple Model for Wake-Induced Aerodynamic Interaction of Wind TurbinesEsmail Mahmoodi0Mohammad Khezri1Arash Ebrahimi2Uwe Ritschel3Leonardo P. Chamorro4Ali Khanjari5Department of Mechanical Engineering of Biosystems, Shahrood University of Technology, Shahrood 3619995161, IranDepartment of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, IranChair of Wind Energy Technology, Faculty of Mechanical Engineering and Marine Technologies, University of Rostock, 18051 Rostock, GermanyChair of Wind Energy Technology, Faculty of Mechanical Engineering and Marine Technologies, University of Rostock, 18051 Rostock, GermanyDepartment of Mechanical Science and Engineering, University of Illinois, Urbana, IL 61801, USADepartment of Mechanical Engineering, University of Delaware, Newark, DE 19716, USAWind turbine aerodynamic interactions within wind farms lead to significant energy losses. Optimizing the flow between turbines presents a promising solution to mitigate these losses. While analytical models offer a fundamental approach to understanding aerodynamic interactions, further development and refinement of these models are imperative. We propose a simplified analytical model that combines the Gaussian wake model and the cylindrical vortex induction model to evaluate the interaction between wake and induction zones in 3.5 MW wind turbines with 328 m spacing. The model’s validation is conducted using field data from a nacelle-mounted LiDAR system on the downstream turbine. The ‘Direction to Hub’ parameter facilitates a comparison between the model predictions and LiDAR measurements at distances ranging from 50 m to 300 m along the rotor axis. Overall, the results exhibit reasonable agreement in flow trends, albeit with discrepancies of up to 15° in predicting peak interactions. These deviations are attributed to the single-hat Gaussian shape of the wake model and the absence of wake expansion consideration, which can be revisited to improve model fidelity. The ‘Direction to Hub’ parameter proves valuable for model validation and LiDAR calibration, enabling a detailed flow analysis between turbines. This analytical modeling approach holds promise for enhancing wind farm efficiency by advancing our understanding of turbine interactions.https://www.mdpi.com/1996-1073/16/15/5710wind energywake induced aerodynamicLiDARwind flow interaction |
| spellingShingle | Esmail Mahmoodi Mohammad Khezri Arash Ebrahimi Uwe Ritschel Leonardo P. Chamorro Ali Khanjari A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines Energies wind energy wake induced aerodynamic LiDAR wind flow interaction |
| title | A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines |
| title_full | A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines |
| title_fullStr | A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines |
| title_full_unstemmed | A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines |
| title_short | A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines |
| title_sort | simple model for wake induced aerodynamic interaction of wind turbines |
| topic | wind energy wake induced aerodynamic LiDAR wind flow interaction |
| url | https://www.mdpi.com/1996-1073/16/15/5710 |
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