Influence of various irradiance models and their combination on simulation results of photovoltaic systems

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Hofmann, M.; Seckmeyer, G.: Influence of various irradiance models and their combination on simulation results of photovoltaic systems. In: Energies 10 (2017), Nr. 10, 1495. DOI: https://doi.org/10.3390/en10101495

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/3352

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Sum total of downloads: 172




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Abstract: 
We analyze the output of various state-of-The-Art irradiance models for photovoltaic systems. The models include two sun position algorithms, three types of input data time series, nine diffuse fraction models and five transposition models (for tilted surfaces), resulting in 270 different model chains for the photovoltaic (PV) system simulation. These model chains are applied to 30 locations worldwide and three different module tracking types, totaling in 24,300 simulations. We show that the simulated PV yearly energy output varies between 5% and +8% for fixed mounted PV modules and between 26% and +14% for modules with two-Axis tracking. Model quality varies strongly between locations; sun position algorithms have negligible influence on the simulation results; diffuse fraction models add a lot of variability; and transposition models feature the strongest influence on the simulation results. To highlight the importance of irradiance with high temporal resolution, we present an analysis of the influence of input temporal resolution and simulation models on the inverter clipping losses at varying PV system sizing factors for Lindenberg, Germany. Irradiance in one-minute resolution is essential for accurately calculating inverter clipping losses. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2017
Appears in Collections:Fakultät für Mathematik und Physik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 100 58.14%
2 image of flag of United States United States 23 13.37%
3 image of flag of China China 15 8.72%
4 image of flag of Russian Federation Russian Federation 4 2.33%
5 image of flag of Switzerland Switzerland 4 2.33%
6 image of flag of India India 3 1.74%
7 image of flag of Hungary Hungary 3 1.74%
8 image of flag of Greece Greece 2 1.16%
9 image of flag of Finland Finland 2 1.16%
10 image of flag of Spain Spain 2 1.16%
    other countries 14 8.14%

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