A profile-free non-parametric approach towards generation of synthetic hourly global solar irradiation data from daily totals

Muhammed A. Hassan, Mohamed Abubakr and Adel Khalil

Renewable Energy, 2021, vol. 167, issue C, 613-628

Abstract: Solar radiation is an essential input in the design and operation of many engineering systems. However, access to high-resolution data (hourly or sub-hourly) is usually limited, especially in developing countries, either due to its unavailability or expensive costs. A novel data-driven approach is proposed to predict the hourly global irradiation profiles from the cheaper and more likely available records of daily global irradiation. The proposed approach is based on a prior categorization of hourly observations using the K-means clustering algorithm, followed by non-parametric function approximation using the multi-layered perceptron artificial neural network. This approach is applied to measured data (130,000 data points) at six locations in the North African Sahara, and the developed models are benchmarked against all existing parametric models in the literature. The artificial neural network-based models outperformed all existing models, with maximum and minimum coefficients of determination of 0.960 and 0.930, respectively. The non-parametric models also captured the true asymmetric profiles of hourly irradiation with enhanced distributions of the residuals. Hence, the suggested models can be used to generate synthetic hourly data for multiple applications, most notably for building energy simulations and scheduling the operation of power generation systems.

Keywords: Solar radiation; Hourly global irradiation; Decomposition model; K-means clustering; Artificial neural network; North Africa (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148120318772
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:167:y:2021:i:c:p:613-628

DOI: 10.1016/j.renene.2020.11.125

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().