Presentation Details
Improved Global Irradiance Decomposition by Sky Condition Classification from Measured Spectral Clearness Indices (Student Award Finalist)

Viktar Tatsiankou1, 2, Karin Hinzer1, Henry Schriemer1, Richard Beal2.

1University of Ottawa, Ottawa, ON, Canada.2Spectrafy, Ottawa, ON, Canada

Abstract


This paper describes a decomposition algorithm for deriving the broadband direct normal (DNI) and diffuse horizontal (DHI) irradiances from one-minute spectral global horizontal irradiance measurements performed by the SolarSIM-G. The algorithm was calibrated and validated at four stations across Canada (Ottawa, Varennes, Egbert, and Devon) and at one station in China (Xianghe), which cumulatively represent a seven-year data set. For the DNI estimation, the root mean squared error (RMSE) ranged from 26 W/m2 to 48 W/m2, while the largest mean bias error (MBE) was 4 W/m2. For the DHI estimation, the RMSE ranged from 14 W/m2 to 27 W/m2, while the largest MBE was 3 W/m2. In addition, the integrated DNI and DHI errors for each station were less than 1% and 2%, respectively. The described method is an alternative to other measurement techniques for obtaining all three irradiance components.
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