Accuracy of energy prediction methodologies
In the current market, the specific annual energy yield (kWh/kWp) of a PV system is gaining in importance due to its direct link to the financial returns for possible investors who typically demand an accuracy of 5% in this prediction. This paper focuses on the energy prediction of photovoltaic modu...
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2006
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Online Access: | https://hdl.handle.net/2134/8204 |
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rr-article-95572432006-01-01T00:00:00Z Accuracy of energy prediction methodologies Sheryl Williams (1248759) Tom Betts (1258395) Ralph Gottschalg (1247661) David Infield (7183166) H. de Moor (7209833) N. van der Borg (7210256) A.R. Burgess (7210259) Gabi Friesen (7206953) D. Chianese (7209845) Antoine Guerin de Montgareuil (7205468) T. Zdanowicz (7209824) D. Stellbogen (7209839) W. Herrmann (7209848) untagged In the current market, the specific annual energy yield (kWh/kWp) of a PV system is gaining in importance due to its direct link to the financial returns for possible investors who typically demand an accuracy of 5% in this prediction. This paper focuses on the energy prediction of photovoltaic modules themselves, as there have been significant advances achieved with module technologies which affect the device physics in a way that might force the revisiting of device modelling. The paper reports the results of a round robin based evaluation of European modelling methodologies. The results indicate that the error in predicting energy yield for the same module at different locations was within 5% for most of the methodologies. However, this error increased significantly if the nominal nameplate rating is used in the characterization stage. For similar modules at the same location the uncertainties were much larger due to module-module variations. 2006-01-01T00:00:00Z Text Conference contribution 2134/8204 https://figshare.com/articles/conference_contribution/Accuracy_of_energy_prediction_methodologies/9557243 CC BY-NC-ND 4.0 |
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untagged Sheryl Williams Tom Betts Ralph Gottschalg David Infield H. de Moor N. van der Borg A.R. Burgess Gabi Friesen D. Chianese Antoine Guerin de Montgareuil T. Zdanowicz D. Stellbogen W. Herrmann Accuracy of energy prediction methodologies |
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In the current market, the specific annual energy yield (kWh/kWp) of a PV system is gaining in importance due to its direct link to the financial returns for possible investors who typically demand an accuracy of 5% in this prediction. This paper focuses on the energy prediction of photovoltaic modules themselves, as there have been significant advances achieved with module technologies which affect the device physics in a way that might force the revisiting of device modelling. The paper reports the results of a round robin based evaluation of European modelling methodologies. The results indicate that the error in predicting energy yield for the same module at different locations was within 5% for most of the methodologies. However, this error increased significantly if the nominal nameplate rating is used in the characterization stage. For similar modules at the same location the uncertainties were much larger due to module-module variations. |
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Default Conference proceeding |
author |
Sheryl Williams Tom Betts Ralph Gottschalg David Infield H. de Moor N. van der Borg A.R. Burgess Gabi Friesen D. Chianese Antoine Guerin de Montgareuil T. Zdanowicz D. Stellbogen W. Herrmann |
author_facet |
Sheryl Williams Tom Betts Ralph Gottschalg David Infield H. de Moor N. van der Borg A.R. Burgess Gabi Friesen D. Chianese Antoine Guerin de Montgareuil T. Zdanowicz D. Stellbogen W. Herrmann |
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Sheryl Williams (1248759) |
title |
Accuracy of energy prediction methodologies |
title_short |
Accuracy of energy prediction methodologies |
title_full |
Accuracy of energy prediction methodologies |
title_fullStr |
Accuracy of energy prediction methodologies |
title_full_unstemmed |
Accuracy of energy prediction methodologies |
title_sort |
accuracy of energy prediction methodologies |
publishDate |
2006 |
url |
https://hdl.handle.net/2134/8204 |
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1797287896833589248 |