Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules
The performance of five conventional turbulence models, commonly used in the wind industry, are examined in predicting the complex wake of an infinite span thin normal flat plate with large pressure gradients at Reynolds number of 1200. This body represents a large array of Photovoltaics modules, wh...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-08-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/12/17/3290 |
| _version_ | 1818035811307749376 |
|---|---|
| author | Mireille B. Tadie Fogaing Arman Hemmati Carlos F. Lange Brian A. Fleck |
| author_facet | Mireille B. Tadie Fogaing Arman Hemmati Carlos F. Lange Brian A. Fleck |
| author_sort | Mireille B. Tadie Fogaing |
| collection | DOAJ |
| description | The performance of five conventional turbulence models, commonly used in the wind industry, are examined in predicting the complex wake of an infinite span thin normal flat plate with large pressure gradients at Reynolds number of 1200. This body represents a large array of Photovoltaics modules, where two edges of the plate dominate the flow. This study provided a benchmark for capabilities of conventional turbulence models that are commonly used for wind forecasting in the wind energy industry. The results obtained from Reynolds Averaged Navier-Stokes (RANS) <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ε</mi> </mrow> </semantics> </math> </inline-formula>, Reynolds Normalization Group (RNG) <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ε</mi> </mrow> </semantics> </math> </inline-formula>, RANS <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ω</mi> </mrow> </semantics> </math> </inline-formula> Shear Stress Transport (SST) and Reynolds Stress Model (RSM) were compared with existing Direct Numerical Simulations (DNS). The mean flow features and unsteady wake characteristics were used as testing criteria amongst these models. All turbulence models over-predicted the mean recirculation length and under-predicted the mean drag coefficient. The major differences between numerical results in predicting the mean recirculation length, mean drag and velocity gradients, leading to deficits in turbulence kinetic energy production and diffusion, hint at major difficulties in modeling velocity gradients and thus turbulence energy transport terms, by traditional turbulence models. Unsteadiness of flow physics and nature of eddy viscosity approximations are potential reasons. This hints at the deficiencies of these models to predict complex flows with large pressure gradients, which are commonly observed in wind and solar farms. The under-prediction of wind loads on PV modules and over-estimation of the recirculation length behind them significantly affects the efficiency and operational feasibility of solar energy systems. |
| first_indexed | 2024-12-10T07:00:59Z |
| format | Article |
| id | doaj.art-2e7b10dd29cf46b18728281397b627f8 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-12-10T07:00:59Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2e7b10dd29cf46b18728281397b627f82022-12-22T01:58:19ZengMDPI AGEnergies1996-10732019-08-011217329010.3390/en12173290en12173290Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics ModulesMireille B. Tadie Fogaing0Arman Hemmati1Carlos F. Lange2Brian A. Fleck3Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaDepartment of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaDepartment of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaDepartment of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaThe performance of five conventional turbulence models, commonly used in the wind industry, are examined in predicting the complex wake of an infinite span thin normal flat plate with large pressure gradients at Reynolds number of 1200. This body represents a large array of Photovoltaics modules, where two edges of the plate dominate the flow. This study provided a benchmark for capabilities of conventional turbulence models that are commonly used for wind forecasting in the wind energy industry. The results obtained from Reynolds Averaged Navier-Stokes (RANS) <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ε</mi> </mrow> </semantics> </math> </inline-formula>, Reynolds Normalization Group (RNG) <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ε</mi> </mrow> </semantics> </math> </inline-formula>, RANS <inline-formula> <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>-</mo> <mi>ω</mi> </mrow> </semantics> </math> </inline-formula> Shear Stress Transport (SST) and Reynolds Stress Model (RSM) were compared with existing Direct Numerical Simulations (DNS). The mean flow features and unsteady wake characteristics were used as testing criteria amongst these models. All turbulence models over-predicted the mean recirculation length and under-predicted the mean drag coefficient. The major differences between numerical results in predicting the mean recirculation length, mean drag and velocity gradients, leading to deficits in turbulence kinetic energy production and diffusion, hint at major difficulties in modeling velocity gradients and thus turbulence energy transport terms, by traditional turbulence models. Unsteadiness of flow physics and nature of eddy viscosity approximations are potential reasons. This hints at the deficiencies of these models to predict complex flows with large pressure gradients, which are commonly observed in wind and solar farms. The under-prediction of wind loads on PV modules and over-estimation of the recirculation length behind them significantly affects the efficiency and operational feasibility of solar energy systems.https://www.mdpi.com/1996-1073/12/17/3290PV modulewind loadswind forecastingCFDRANSturbulencewake dynamics |
| spellingShingle | Mireille B. Tadie Fogaing Arman Hemmati Carlos F. Lange Brian A. Fleck Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules Energies PV module wind loads wind forecasting CFD RANS turbulence wake dynamics |
| title | Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules |
| title_full | Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules |
| title_fullStr | Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules |
| title_full_unstemmed | Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules |
| title_short | Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules |
| title_sort | performance of turbulence models in simulating wind loads on photovoltaics modules |
| topic | PV module wind loads wind forecasting CFD RANS turbulence wake dynamics |
| url | https://www.mdpi.com/1996-1073/12/17/3290 |
| work_keys_str_mv | AT mireillebtadiefogaing performanceofturbulencemodelsinsimulatingwindloadsonphotovoltaicsmodules AT armanhemmati performanceofturbulencemodelsinsimulatingwindloadsonphotovoltaicsmodules AT carlosflange performanceofturbulencemodelsinsimulatingwindloadsonphotovoltaicsmodules AT brianafleck performanceofturbulencemodelsinsimulatingwindloadsonphotovoltaicsmodules |