Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81635
Title: Construction of functional data analysis modeling strategy for global solar radiation prediction : application of cross-station paradigm
Authors: Beyaztas, U
Salih, SQ
Chau, KW 
AlAnsari, N
Yaseen, ZM
Keywords: Burkina Faso
energy harvesting
Functional data analysis
Global solar radiation
Regional investigation
Issue Date: 2019
Publisher: Hong Kong Polytechnic University, Department of Civil and Structural Engineering
Source: Engineering applications of computational fluid mechanics, 2019, v. 13, no. 1, p. 1165-1181 How to cite?
Journal: Mathematical problems in engineering 
Abstract: To support initiatives for global emissions targets set by the United Nations Framework Convention on climate change, sustainable extraction of usable power from freely-available global solar radiation as a renewable energy resource requires accurate estimation and forecasting models for solar energy. Understanding the Global Solar Radiation (GSR) pattern is highly significant for determining the solar energy in any particular environment. The current study develops a new mathematical model based on the concept of Functional Data Analysis (FDA) to predict daily-scale GSR in the Burkina Faso region of West Africa. Eight meteorological stations are adopted to examine the proposed predictive model. The modeling procedure of the regression FDA is performed using two different internal parameter tuning approaches including Generalized Cross-Validation (GCV) and Generalized Bayesian Information Criteria (GBIC). The modeling procedure is established based on a cross-station paradigm wherein the climatological variables of six stations are used to predict GSR at two targeted meteorological stations. The performance of the proposed method is compared with the panel data regression model. Based on various statistical metrics, the applied FDA model attained convincing absolute error measures and best goodness of fit compared with the observed measured GSR. In quantitative evaluation, the predictions of GSR at the Ouahigouya and Dori stations attained correlation coefficients of R = 0.84 and 0.90 using the FDA model, respectively. All in all, the FDA model introduced a reliable alternative modeling strategy for global solar radiation prediction over the Burkina Faso region with accurate line fit predictions.
URI: http://hdl.handle.net/10397/81635
ISSN: 1994-2060
EISSN: 1997-003X
DOI: 10.1080/19942060.2019.1676314
Rights: © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Ufuk Beyaztas, Sinan Q. Salih, Kwok-Wing Chau, Nadhir Al-Ansari & Zaher Mundher Yaseen (2019) Construction of functional data analysis modeling strategy for global solar radiation prediction: application of cross-station paradigm, Engineering Applications of Computational Fluid Mechanics, 13:1, 1165-1181, is available at https://doi.org/10.1080/19942060.2019.1676314
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