DocumentCode :
2789562
Title :
Photovoltaic array power forecasting model based on energy storage
Author :
Jun Tian ; Yong-qiang Zhu ; Jia-neng Tang
Author_Institution :
North China Power Univ., Beijing, China
fYear :
2010
fDate :
20-22 Sept. 2010
Firstpage :
1
Lastpage :
4
Abstract :
With the rapid increase of the capacity in photovoltaic (PV) generated systems, how to deal with the problem caused by the random output in the system becomes more significant. One possible solution could be the use of energy storage. The forecasting output can be obtained by the support vector regression model (SVR) introduced in this article, then the capacity of energy storage can be optimized by the difference between actual and predicting outputs. That is to say, energy storage devices are taken to compensate the difference, so that the deviation between predictions and actual values can be decreased. The results show that the proposed algorithm ELSSVR is effective and the installed capacity of energy storage is reduced significantly.
Keywords :
forecasting theory; photovoltaic power systems; regression analysis; energy storage; photovoltaic array; power forecasting; support vector regression model; Analytical models; Arrays; Energy storage; Forecasting; Mathematical model; Predictive models; Solar radiation; Photovoltaic array; SVR; optimization of energy storage capacity; power forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Critical Infrastructure (CRIS), 2010 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8080-7
Type :
conf
DOI :
10.1109/CRIS.2010.5617510
Filename :
5617510
Link To Document :
بازگشت