Deep learning algorithm applied to daily solar irradiation estimations

Date

2018-07-02

Author

Akbaba, Erol C.
Yüce, Emre
Akinoglu, Bulent G.

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

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Deep learning is applied in many research areas, and in many of them remarkable outcomes are attained compared to conventional methods. There are quite a number of studies also in the estimation of solar irradiation. Estimation of solar irradiation is vitally important for the design of solar energy systems. In this work, multi-layer perceptron (MLPs) method of deep learning is used to develop an estimation method for calculating horizontal daily solar irradiation and the results are compared with classical approaches. The results indicate that deep learning with little inputs can be used to estimate daily solar irradiation with a decent accuracy that is comparable to classical approaches.

Subject Keywords

ANN, Deep learning, Solar irradiation

URI

https://hdl.handle.net/11511/35905

DOI

https://doi.org/10.1109/irsec.2018.8702963

Collections

Department of Physics, Conference / Seminar

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Citation Formats

E. C. Akbaba, E. Yüce, and B. G. Akinoglu, “Deep learning algorithm applied to daily solar irradiation estimations,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35905.