Computation of monthly average hourly and daily solar radiation incident on a flat tilted surface at Karachi, Pakistan

1986 ◽  
Vol 3 (4) ◽  
pp. 329-333 ◽  
Author(s):  
Firoz Ahmad ◽  
S.A. Husain
1983 ◽  
Vol 105 (3) ◽  
pp. 281-287 ◽  
Author(s):  
D. R. Clark ◽  
S. A. Klein ◽  
W. A. Beckman

A computationally simple algorithm is presented for evaluating the hourly utilizability function, φ, defined as the fraction of the long-term, monthly-average, hourly solar radiation incident on a surface which exceeds a specified threshold intensity. The algorithm was developed by correlating values of φ obtained by numerical integration of hourly radiation for three locations. The algorithm is shown to compare well both with a more complex analytical expression for φ developed recently and with results obtained numerically using many years of hourly horizontal radiation measurements in nine U.S. locations. In addition, the algorithm is shown to be applicable for surfaces of any orientation.


1996 ◽  
Vol 118 (3) ◽  
pp. 183-189 ◽  
Author(s):  
B. E. Psiloglou ◽  
C. A. Balaras ◽  
M. Santamouris ◽  
D. N. Asimakopoulos

The diffuse radiation incident on an inclined surface is composed of both the sky diffuse radiation and the ground-reflected radiation. Depending on the model used to calculate the sky diffuse radiation and the estimated albedo value, it is possible to introduce a significant error in the prediction of the total radiation incident on a tilted surface. Twelve sky diffuse submodels associated with four different albedo submodels are used to estimate the total radiation on the tilted surface from data on the horizontal plane. The predicted total solar radiation values are compared with measured data on a south facing vertical surface, from four representative south and north European locations. Root mean square error, mean bias error, and a t-test are used to determine the intrinsic performance of each combination of diffuse tilt and albedo submodel. Accordingly, the various model combinations do not exhibit a statistically significant difference between measured and calculated values.


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