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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tina, G.M. Ventura, C. De Fiore, S. |
| Copyright Year | 2012 |
| Description | Author affiliation: Dipartimento di Ingegneria Elettrica, Elettronica e Informatica, University of Catania, Viale Andrea Doria n. 6, 95125, Italy (Tina, G.M.; Ventura, C.) || Softeco Sismat SpA Via De Marini, 1 - WTC Tower - 16149 Genoa, Italy (De Fiore, S.) |
| Abstract | The global irradiance on a horizontal surface has been measured in many meteorological stations around the world, but there are only a few stations that measure this solar component on inclined surfaces. However, in practice solar collectors (flat plate thermal or photovoltaic collectors) are tilted, since it allows to maximize the energy production of the system maximizing the direct irradiance that can be received. The target of this work consists in evaluating models that estimate the global solar radiation on the plane of the PV arrays based on that measured on horizontal surfaces, using data with time steps of 10 minutes, 30 minutes and one hour. Global solar radiation incident on a tilted plane is composed by three components: beam radiation, diffuse radiation and reflected radiation from the ground. A simple method, based on the beam radiation tilt factor, was used for estimating beam solar radiation incident on tilted surfaces, while an isotropic model was used for estimating the reflected solar component on a tilted plane. In contrast, different models can be used to evaluate the diffuse radiation component; in this paper the Perez and the Klucher models have been implemented. However, these models need to split the global solar radiation on a horizontal surface into beam and diffuse components. Therefore, a neural network that allows to evaluate the global solar radiation on a tilted surface directly from the horizontal global solar radiation, has been developed, it allows to obtain more accurate results. Referring to the French Mediterranean site of Ajaccio, experimental data are reported to demonstrate the potentiality of the adopted solutions. |
| Starting Page | 001321 |
| Ending Page | 001326 |
| File Size | 1019745 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467300643 |
| ISSN | 01608371 |
| e-ISBN | 9781467300667 |
| DOI | 10.1109/PVSC.2012.6317844 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-03 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Energy measurement Time measurement Artificial neural networks Neural network Irradiance models Radiation on inclined surface |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Control and Systems Engineering Electrical and Electronic Engineering |
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