Using artificial neural network (ANN) techniques for solar irradiation predictions

Date

2019

Author

Akbaba, Erol Can

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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

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Graduate School of Natural and Applied Sciences, Thesis