Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Using artificial neural network (ANN) techniques for solar irradiation predictions
Download
index.pdf
Date
2019
Author
Akbaba, Erol Can
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
237
views
126
downloads
Cite This
Estimation of solar energy is a task with many benefits to a diverse group of people. This purpose is pursued with many different methodologies. Artificial Neural Networks (ANNs) are the novel methods of choice in the last decade. We compare the classical solar irradiation estimation methods with different ANN schemes including different inputs, data amount and estimation target. Our analyses show that the use of ANN to predict solar irradiation reaching the Earth’s surface gives similar results with that of the classical regression approaches. The small difference between these two approaches lies within the instrumentation accuracy of the measuring devices.
Subject Keywords
Solar energy.
,
Keywords: Solar energy
,
estimation
,
machine learning
,
deep learning
,
artificial neural network.
URI
http://etd.lib.metu.edu.tr/upload/12624006/index.pdf
https://hdl.handle.net/11511/44708
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Assessment of solar data estimation models for four cities in Iran
Jahani, Elham; Sadati, S. M. Sajed; Yousefzadeh, Moslem (2015-04-29)
The estimated solar resources are important for designing renewable energy systems since measured data are not always available. The estimation models have been introduced in several studies. These models are mainly dependent on local meteorological data and need to be assessed for different locations and times. The current study compares the results of Angstrom's model and a neural network (NN) model developed for this study with measured data for four cities in Iran. The time resolution for the estimated ...
Investigation of olive mill sludge treatment using a parabolic trough solar collector
Ben Othman, Fares; Eddhibi, Fathia; Bel Hadj Ali, Abdessalem; Fadhel, Abdelhamid; Bayer, Özgür; Tarı, İlker; Guizani, Amenallah; Balghouthi, Moncef (2022-01-15)
The olive mill sludge treatment system developed in this study is an indirect solar dryer driven by a solar parabolic trough collector (PTC). A heat exchanger is implemented to heat air with hot oil coming from the solar collector. The developed hot air dryer can treat up to 50 kg of olive mill sludge distributed over six trays at once. The designed system and its components are described, along with their experimental and simulated performance evaluations. With a mean direct normal irradiation (DNI) higher...
A Feasibility study for external control on self-organized production of plasmonic enhancement interfaces for solar cells
Zolfaghari Borra, Mona; Bek, Alpan; Ünalan, Hüsnü Emrah; Department of Micro and Nanotechnology (2013)
The present study is about the improvement of the energy conversion efficiency of solar cells in which plasmonic light-trapping approach has been investigated. In this study, metal nanoparticles are allowed to form in a self-organized fashion on both flat and textured full scale monocrystalline silicon solar cell. These metal nanoparticles with strong optical interaction cross-sections at localized plasmonic resonance energies, improve coupling of the incoming light into the active area of solar cells by wa...
A methodology to assess suitability of a site for small scale wet and dry CSP systems
Uzgoren, Eray; Timur, Eray (2015-06-25)
This study presents a methodology to assess suitability of a site for small scale concentrated solar power (CSP) systems for its energy conversion efficiency and make-up water requirement. Energy conversion efficiency of CSPs relies not only on the level of direct solar radiation but also on the performance of the cooling system. Regions with high solar potential have to deal with heat rejection at elevated temperatures which causes reduced energy conversion efficiencies due to high condenser temperatures. ...
Computational fluid dynamic analysis of wind loads acting on ground mounted solar panels /
Uslu, Veysel Emre; Sarıtaş, Afşin; Uzol, Oğuz; Department of Civil Engineering (2014)
Solar energy becomes more important day by day as a result of being part of renewable energy and increasing energy consumption. Although development of photovoltaic panels is enjoying the attention of many researchers, there has not been enough study towards determination of the loads acting on supporting structures of these systems yet. In this thesis, CFD analysis is mainly employed in order to model, analyze and understand the effects of the wind forces acting on solar panels. Also, different from previo...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. C. Akbaba, “Using artificial neural network (ANN) techniques for solar irradiation predictions,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Physics., Middle East Technical University, 2019.