Empirical model development for the estimation of clearness index using meteorological parameters

Abstract

The clearness index is an indispensable parameter required for the design and analysis of solar energysystems. In the absence of measured values for a specific location, the clearness index can be estimated from othermeasured meteorological variables. In this study three meteorological parameters, sunshine hours, monthly mean valuesof the temperature difference (∆T), and cloudiness, are used to develop empirical models for the estimation of clearnessindex. The empirical models are developed for five major cities in Pakistan (Karachi, Multan, Lahore, Islamabad, andQuetta). For empirical model development, long-term data (1991 to 2010) of monthly average clearness index, sunshinehours, average daily minimum and maximum temperatures, and cloudiness have been used. The accuracy of the modelshas been tested by statistical indicators that include mean percentage error (MPE), coefficient of determination (R2),mean absolute relative error (MARE), mean bias error (MBE), and root mean square error (RMSE). The error analysisrevealed that the proposed models are suitable for the estimation of the clearness index. It is also concluded that multipleregression models give better estimates of clearness index for all the stations (0.80 ≤ R2 ≤ 0.86) compared to singleparameter model and therefore are recommended. The study indicated that clear sky conditions prevail throughoutthe months at all the investigated sites (0.58 ≤ KT ≤ 0.68), which is a good indicator for solar energy utilization.The statistical indicators also suggest that multilinear regression model M-3 gives a better representation of the climatesystem and using three parameters reduces the uncertainties in the developed model.