Abstract

Solar radiation data are required for many applications and many areas of research. In order to achieve this, several empirical models have been suggested to predict the global solar radiation in Turkey and other countries. The different meteorological data as the global solar radiation, the sunshine duration, the temperature, the atmospheric pressure, the wind speed and the relative humidity were measured by Eskisehir Osmangazi University during the period between 01 January 2011 and 31 December 2014. These data were used to develop the empirical models in order to estimate the monthly average daily global solar radiation on the horizontal surface over Eskisehir City of Turkey. The developed empirical models were analyzed with the widely used nine statistical methods, namely; the relative percentage error (E), the mean percentage error (MPE), the mean absolute percentage error (MAPE), the sum of squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root mean square error (RMSE), the t-statistic method (t-stat) and coefficient of determination (R2). It is expected that the new model will be beneficial to everyone who is the solar engineers, architects, agriculturists, and hydrologists involved or interested in the design and study of solar energy applications such as solar furnaces, wood drying, stoves, concentrating collectors, interior illumination and thermal load analyzing of buildings, and photovoltaics, agricultural and meteorological forecasting.

Highlights

  • In this period, the increased decline of power supplies, growing power consumption, and lack of ecological values necessitate a direct response

  • This study indicated that artificial neural network (ANN) network gave good accuracy in terms of prediction error of less than 20%

  • Seventeen new temperature-based models were established, validated and compared with other three models proposed in the literature to estimate the monthly average daily global solar radiation on a horizontal surface

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Summary

INTRODUCTION

The increased decline of power supplies, growing power consumption, and lack of ecological values necessitate a direct response. Sahin et al [15] tested the estimation capacities of ANN techniques to predict monthly-average daily solar radiation over Turkey. Seventeen new temperature-based models were established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. Several empirical correlation models for estimating the monthly average daily global solar radiation on the horizontal surface were developed in connection with the measured solar radiation, sunshine duration and ambient temperature. These models were applied to Eskişehir City of Turkey. The results of empirical models were compared using the statistical evaluation methods as the relative percentage error (E), the mean percentage error (MPE),the mean absolute percentage error (MAPE), the sum of the squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root square error (RMSE), and correlation coefficient (R2)

Data set
Astronomical parameters
Global solar radiation models
STATISTICAL ANALYSIS METHODS
RESULTS AND DISCUSSION
CONCLUSIONS
Full Text
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