In this paper, a commonly used global solar radiation (GSR) model is locally calibrated and tested for Kartepe, Kocaeli station. The coefficients of the model are calibrated for monthly and yearly by performing a regression analysis using the measured temperatures. Regression analysis results for both models provide that correlating the clearness index with the second degree of maximum temperature divided by minimum temperature gives the best accuracy for the selected location. Besides, the estimation results for each month indicate that the monthly calibrated coefficients provide very accurate results in terms of statistical errors. Moreover, yearly calibration of the model gives less accurate predictions. The simple and accurate results by monthly calibrated models using this approach can be used in designing and evaluating solar energy applications in the absence of accurate sunshine data.
maximum temperature minimum temperature global solar radiation regression calibration maximum temperature, minimum temperature, global solar radiation, regression, calibration
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | April 30, 2022 |
Submission Date | February 22, 2022 |
Acceptance Date | March 11, 2022 |
Published in Issue | Year 2022 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.