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Re-modeling the solar diffuse fraction in Taiwan on basis of a typical-meteorological-year data.
- Source :
-
Renewable Energy: An International Journal . Mar2023, Vol. 204, p823-835. 13p. - Publication Year :
- 2023
-
Abstract
- An objective approach to determine a dataset from which a correlation model of solar diffuse fraction is fitted and tested is proposed. A typical meteorological year (TMY) of global radiation data that is measured in Tainan, Taiwan over 10 years (2011–2020) is used to construct the training dataset and the remaining data (90% data base) is used as a test dataset. Two multiple-predictor and one single-predictor correlation models for the hourly diffuse fraction are developed by using more theoretically rigorous techniques for determining the breaking points for segmentation (excluding the modified Boland-Ridley-Lauret (BRL) model) and how many significant predictors required in each segmented interval for the regression model with piece-wise linear multiple-predictor correlation. The performance of each developed correlation model is superior to that of the existing same-type model using a part (one year or two years) of the same data base. The re-modeled piece-wise linear multiple-predictor correlation model has the best long-term performance of the three developed correlation models. The modified BRL model on basis of the TMY data is second. The re-modeled Liu-Jordan-type (single predictor) model allows real time prediction and has a simpler form than the other two models but prediction accuracy is inferior. [ABSTRACT FROM AUTHOR]
- Subjects :
- *GLOBAL radiation
*FRACTIONS
*PREDICTION models
*REGRESSION analysis
Subjects
Details
- Language :
- English
- ISSN :
- 09601481
- Volume :
- 204
- Database :
- Academic Search Index
- Journal :
- Renewable Energy: An International Journal
- Publication Type :
- Academic Journal
- Accession number :
- 161628617
- Full Text :
- https://doi.org/10.1016/j.renene.2023.01.054