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Cumulative Frequency Distributions for Daily Global Illuminance
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The present article describes the development of cumulative frequency distributions (similar to clearness index distributions) for daily global horizontal illuminance based on the modeled data of 56 US locations. Normalized variables have been employed to account for seasonal and location dependencies. The normalized variables contain the maximum and minimum illuminance values in the array of daily values in addition to the daily illuminance (the variable to be related to cumulative frequency) and the monthly average daily illuminance. The distributions thus developed discrete in terms of the normalized monthly average daily global illuminance have been presented in a convenient linear form which accommodates continuous values for the parameter. When data are not available, the maximum and minimum of the daily values needed in estimating the parameter first and eventually the daily illuminance values have been correlated to other more readily available predictors. Present distributions have been validated by comparing against the daily illuminance values available in the large data base employed. Daily global illuminance has been predicted with a standard deviation of 23.44 klux and rms difference of 4.64%. The present correlations can be conveniently applied to obtain the 30 or 31 daily illuminance values in a month from the monthly average value.
Title: Cumulative Frequency Distributions for Daily Global Illuminance
Description:
The present article describes the development of cumulative frequency distributions (similar to clearness index distributions) for daily global horizontal illuminance based on the modeled data of 56 US locations.
Normalized variables have been employed to account for seasonal and location dependencies.
The normalized variables contain the maximum and minimum illuminance values in the array of daily values in addition to the daily illuminance (the variable to be related to cumulative frequency) and the monthly average daily illuminance.
The distributions thus developed discrete in terms of the normalized monthly average daily global illuminance have been presented in a convenient linear form which accommodates continuous values for the parameter.
When data are not available, the maximum and minimum of the daily values needed in estimating the parameter first and eventually the daily illuminance values have been correlated to other more readily available predictors.
Present distributions have been validated by comparing against the daily illuminance values available in the large data base employed.
Daily global illuminance has been predicted with a standard deviation of 23.
44 klux and rms difference of 4.
64%.
The present correlations can be conveniently applied to obtain the 30 or 31 daily illuminance values in a month from the monthly average value.
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