Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7935098 | Solar Energy | 2018 | 8 Pages |
Abstract
The National Solar Radiation Database (NSRDB) has provided solar resource data for over 25â¯years. Its most recent update, namely, physical solar model (PSM) version 3, generates half-hourly, gridded, satellite-derived irradiance data with a spatial resolution of 4â¯km à 4â¯km, covering most of America. The total volume of the data is over 40â¯TB. Since the main method to access the data is using API with a daily limit of 2000 requests, it would require 1000â¯days to obtain one year of PSM data from approximately 2â¯million pixels. Furthermore, such a big dataset is difficult to store and manipulate. In this regard, this paper empirically investigates the accuracies of various kriging methods, so that a suitable, dimension-reduced (in space) dataset can be opted during various spatio-temporal analyses, such as forecasting or monitoring network design.
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Authors
Dazhi Yang,