Evaluation of Temperature-Based Empirical Models and Machine Learning Techniques to Estimate Daily Global Solar Radiation at Biratnagar Airport, Nepal
Joint Authors
Dhakal, Sandeep
Gautam, Yogesh
Bhattarai, Aayush
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Global solar radiation (GSR) is a critical variable for designing photovoltaic cells, solar furnaces, solar collectors, and other passive solar applications.
In Nepal, the high initial cost and subsequent maintenance cost required for the instrument to measure GSR have restricted its applicability all over the country.
The current study compares six different temperature-based empirical models, artificial neural network (ANN), and other five different machine learning (ML) models for estimating daily GSR utilizing readily available meteorological data at Biratnagar Airport.
Amongst the temperature-based models, the model developed by Fan et al.
performs better than the rest with an R2 of 0.7498 and RMSE of 2.0162 MJm−2d−1.
Feed-forward multilayer perceptron (MLP) is utilized to model daily GSR utilizing extraterrestrial solar radiation, sunshine duration, maximum and minimum ambient temperature, precipitation, and relative humidity as inputs.
ANN3 performs better than other ANN models with an R2 of 0.8446 and RMSE of 1.4595 MJm−2d−1.
Likewise, stepwise linear regression performs better than other ML models with an R2 of 0.8870 and RMSE of 1.5143 MJm−2d−1.
Thus, the model developed by Fan et al.
is recommended to estimate daily GSR in the region where only ambient temperature data are available.
Similarly, a more robust ANN3 and stepwise linear regression models are recommended to estimate daily GSR in the region where data about sunshine duration, maximum and minimum ambient temperature, precipitation, and relative humidity are available.
American Psychological Association (APA)
Dhakal, Sandeep& Gautam, Yogesh& Bhattarai, Aayush. 2020. Evaluation of Temperature-Based Empirical Models and Machine Learning Techniques to Estimate Daily Global Solar Radiation at Biratnagar Airport, Nepal. Advances in Meteorology،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1127210
Modern Language Association (MLA)
Dhakal, Sandeep…[et al.]. Evaluation of Temperature-Based Empirical Models and Machine Learning Techniques to Estimate Daily Global Solar Radiation at Biratnagar Airport, Nepal. Advances in Meteorology No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1127210
American Medical Association (AMA)
Dhakal, Sandeep& Gautam, Yogesh& Bhattarai, Aayush. Evaluation of Temperature-Based Empirical Models and Machine Learning Techniques to Estimate Daily Global Solar Radiation at Biratnagar Airport, Nepal. Advances in Meteorology. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1127210
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127210