DocumentCode
3590
Title
Preprocessing Uncertain Photovoltaic Data
Author
Miao Fan ; Vittal, Vijay ; Heydt, Gerald T. ; Ayyanar, Raja
Author_Institution
Dept. of Electr., Comput., & Energy Eng., Arizona State Univ., Tempe, AZ, USA
Volume
5
Issue
1
fYear
2014
fDate
Jan. 2014
Firstpage
351
Lastpage
352
Abstract
This letter suggests a method to manage the uncertainty of photovoltaic (PV) data by removing the periodic effect of the annual position of the sun in the sky. The least squares method is applied to determine the low-frequency (annual) periodic component which is predictable in the system operation. This method can be applied to estimate the probabilistic characteristics of PV generation at various locations on the earth with differing insolation due to changing solar position.
Keywords
least squares approximations; photovoltaic power systems; probability; PV generation; least square method; low-frequency periodic component; periodic effect; probabilistic characteristic estimation; solar position; system operation; uncertain photovoltaic data preprocessing; Photovoltaic systems; Probabilistic logic; Probability density function; Production; Sun; Uncertainty; Least squares method; photovoltaic (PV) generation; probability density function (pdf); renewable energy; uncertainty;
fLanguage
English
Journal_Title
Sustainable Energy, IEEE Transactions on
Publisher
ieee
ISSN
1949-3029
Type
jour
DOI
10.1109/TSTE.2013.2287992
Filename
6677516
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