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Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations
Uncertainties in the calibration of PV devices affect the power rating of modules and thus their value. The expanded measurement uncertainty in Pmax of modules at state-of-art indoor calibration facilities is between 1.6- 3.85% based on conventional Si technologies. The uncertainties of TF technolog...
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| Main Authors: | , , , |
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| Format: | Default Conference proceeding |
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2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/13474 |
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| _version_ | 1818173783676026880 |
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| author | Blagovest Mihaylov Martin Bliss Tom Betts Ralph Gottschalg |
| author_facet | Blagovest Mihaylov Martin Bliss Tom Betts Ralph Gottschalg |
| author_sort | Blagovest Mihaylov (1258503) |
| collection | Figshare |
| description | Uncertainties in the calibration of PV devices affect the power rating of modules and thus their value. The expanded measurement uncertainty in Pmax of modules at state-of-art indoor calibration facilities is between 1.6- 3.85% based on conventional Si technologies. The uncertainties of TF technologies are agreed to be higher. The contributions from different uncertainty sources are combined according to the GUM Uncertainty Framework. The Framework has the limitation of considering only the mean and standard deviation of symmetric distributions. This paper advocates the use of the Monte Carlo (MC) method for calculating the overall uncertainty of module calibration that is specific to the device-under-test and the measuring setup. Since the MC method retains all the information from the input quantities, more comprehensive probability density functions can be assigned to the main contributors. Recognised systematic effects can be accounted for by assigning asymmetric distributions to given contributions eliminating the need for correction. The use of the MC method for the total uncertainty calculation allows for a more detailed estimation of the input influences and their understanding and minimisation. In the simulated case study this led to reduction in uncertainty from ±2.5% in Isc to [+1.93%:-1.97%] for a 95% coverage interval. |
| format | Default Conference proceeding |
| id | rr-article-9558869 |
| institution | Loughborough University |
| publishDate | 2013 |
| record_format | Figshare |
| spelling | rr-article-95588692013-01-01T00:00:00Z Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations Blagovest Mihaylov (1258503) Martin Bliss (1250019) Tom Betts (1258395) Ralph Gottschalg (1247661) Mechanical engineering not elsewhere classified Uncertainty Monte Carlo Modules Calibration Mechanical Engineering not elsewhere classified Uncertainties in the calibration of PV devices affect the power rating of modules and thus their value. The expanded measurement uncertainty in Pmax of modules at state-of-art indoor calibration facilities is between 1.6- 3.85% based on conventional Si technologies. The uncertainties of TF technologies are agreed to be higher. The contributions from different uncertainty sources are combined according to the GUM Uncertainty Framework. The Framework has the limitation of considering only the mean and standard deviation of symmetric distributions. This paper advocates the use of the Monte Carlo (MC) method for calculating the overall uncertainty of module calibration that is specific to the device-under-test and the measuring setup. Since the MC method retains all the information from the input quantities, more comprehensive probability density functions can be assigned to the main contributors. Recognised systematic effects can be accounted for by assigning asymmetric distributions to given contributions eliminating the need for correction. The use of the MC method for the total uncertainty calculation allows for a more detailed estimation of the input influences and their understanding and minimisation. In the simulated case study this led to reduction in uncertainty from ±2.5% in Isc to [+1.93%:-1.97%] for a 95% coverage interval. 2013-01-01T00:00:00Z Text Conference contribution 2134/13474 https://figshare.com/articles/conference_contribution/Uncertainty_considerations_of_indoor_PV_module_calibration_based_on_Monte_Carlo_simulations/9558869 CC BY-NC-ND 4.0 |
| spellingShingle | Mechanical engineering not elsewhere classified Uncertainty Monte Carlo Modules Calibration Mechanical Engineering not elsewhere classified Blagovest Mihaylov Martin Bliss Tom Betts Ralph Gottschalg Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title | Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title_full | Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title_fullStr | Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title_full_unstemmed | Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title_short | Uncertainty considerations of indoor PV module calibration based on Monte Carlo simulations |
| title_sort | uncertainty considerations of indoor pv module calibration based on monte carlo simulations |
| topic | Mechanical engineering not elsewhere classified Uncertainty Monte Carlo Modules Calibration Mechanical Engineering not elsewhere classified |
| url | https://hdl.handle.net/2134/13474 |