In this paper, several models to forecast the hourly solar irradiance with a day in advance using artificial neural network techniques have been developed and analyzed. The forecast irradiance is the one incident on the plane of the modules array of a photovoltaic plant. Pure statistical (ST) models that use only local measured data and model output statistics (MOS) approaches to refine numerical weather prediction data are tested for the University of Rome “Tor Vergata” site. The performance of ST and MOS, together with the persistence model (PM), is compared. The ST models improve the performance of the PM of around 20%. The combination of ST and NWP in the MOS approach gives the best performance, improving the forecast of approximately 39% with respect to the PM.
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June 2015
Research-Article
Twenty-Four Hour Solar Irradiance Forecast Based on Neural Networks and Numerical Weather Prediction
C. Cornaro,
C. Cornaro
1
Department of Enterprise Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
CHOSE,
e-mail: cornaro@uniroma2.it
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: cornaro@uniroma2.it
1Corresponding author.
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F. Bucci,
F. Bucci
Department of Enterprise Engineering,
e-mail: frabucci@gmail.com
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: frabucci@gmail.com
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M. Pierro,
M. Pierro
Department of Enterprise Engineering,
e-mail: marco.pierro@gmail.com
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: marco.pierro@gmail.com
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F. Del Frate,
F. Del Frate
Department of Civil Engineering and
Computer Science Engineering,
e-mail: fabio.delfrate@disp.uniroma2.it
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: fabio.delfrate@disp.uniroma2.it
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S. Peronaci,
S. Peronaci
Department of Civil Engineering and
Computer Science Engineering,
e-mail: simone.peronaci@hotmail.it
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: simone.peronaci@hotmail.it
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A. Taravat
A. Taravat
Department of Civil Engineering and
Computer Science Engineering,
e-mail: art23130@gmail.com
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: art23130@gmail.com
Search for other works by this author on:
C. Cornaro
Department of Enterprise Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
CHOSE,
e-mail: cornaro@uniroma2.it
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: cornaro@uniroma2.it
F. Bucci
Department of Enterprise Engineering,
e-mail: frabucci@gmail.com
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: frabucci@gmail.com
M. Pierro
Department of Enterprise Engineering,
e-mail: marco.pierro@gmail.com
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: marco.pierro@gmail.com
F. Del Frate
Department of Civil Engineering and
Computer Science Engineering,
e-mail: fabio.delfrate@disp.uniroma2.it
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: fabio.delfrate@disp.uniroma2.it
S. Peronaci
Department of Civil Engineering and
Computer Science Engineering,
e-mail: simone.peronaci@hotmail.it
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: simone.peronaci@hotmail.it
A. Taravat
Department of Civil Engineering and
Computer Science Engineering,
e-mail: art23130@gmail.com
Computer Science Engineering,
University of Rome “Tor Vergata”
,Via del Politecnico 1, Rome 00133
, Italy
e-mail: art23130@gmail.com
1Corresponding author.
Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received March 28, 2014; final manuscript received December 18, 2014; published online January 8, 2015. Assoc. Editor: Philippe Blanc.
J. Sol. Energy Eng. Jun 2015, 137(3): 031011 (9 pages)
Published Online: June 1, 2015
Article history
Received:
March 28, 2014
Revision Received:
December 18, 2014
Online:
January 8, 2015
Citation
Cornaro, C., Bucci, F., Pierro, M., Del Frate, F., Peronaci, S., and Taravat, A. (June 1, 2015). "Twenty-Four Hour Solar Irradiance Forecast Based on Neural Networks and Numerical Weather Prediction." ASME. J. Sol. Energy Eng. June 2015; 137(3): 031011. https://doi.org/10.1115/1.4029452
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