A methodology for the stochastic generation of hourly synthetic direct normal irradiation time series

Many of the available solar radiation databases only provide global horizontal irradiance (GHI) while there is a growing need of extensive databases of direct normal radiation (DNI) mainly for the development of concentrated solar power and concentrated photovoltaic technologies. In the present work...

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Bibliographic Details
Published in:Theoretical and applied climatology 2018-02, Vol.131 (3-4), p.1517-1527
Main Authors: Larrañeta, M., Moreno-Tejera, S., Lillo-Bravo, I., Silva-Pérez, M. A.
Format: Article
Language:English
Subjects:
Adaptation
Analysis
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Atmospheric Sciences
Climate models
Climate science
Climatology
Data
Data processing
Distribution
Dynamics
Earth and Environmental Science
Earth Sciences
Frequency distribution
Irradiance
Irradiation
Kolmogorov-Smirnov test
Methodology
Methods
Original Paper
Photovoltaics
Radiation
Radiation (Physics)
Solar energy
Solar power
Solar radiation
Statistical analysis
Statistical methods
Statistical tests
Stochasticity
Waste Water Technology
Water Management
Water Pollution Control
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Summary:Many of the available solar radiation databases only provide global horizontal irradiance (GHI) while there is a growing need of extensive databases of direct normal radiation (DNI) mainly for the development of concentrated solar power and concentrated photovoltaic technologies. In the present work, we propose a methodology for the generation of synthetic DNI hourly data from the hourly average GHI values by dividing the irradiance into a deterministic and stochastic component intending to emulate the dynamics of the solar radiation. The deterministic component is modeled through a simple classical model. The stochastic component is fitted to measured data in order to maintain the consistency of the synthetic data with the state of the sky, generating statistically significant DNI data with a cumulative frequency distribution very similar to the measured data. The adaptation and application of the model to the location of Seville shows significant improvements in terms of frequency distribution over the classical models. The proposed methodology applied to other locations with different climatological characteristics better results than the classical models in terms of frequency distribution reaching a reduction of the 50% in the Finkelstein-Schafer (FS) and Kolmogorov-Smirnov test integral (KSI) statistics.
ISSN:0177-798X
1434-4483
DOI:10.1007/s00704-017-2188-4