Ultra-Short-Term Ahead Generating Power Forecasting for PV System Based on Markov Chain for Error Series

Abstract:

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This article presents a proper approach for the prediction of output power for photovoltaic generation system. Using the results of solar irradiation from the sunny-day-model as the base value, which are accurate when the sky is clear, and correcting the forecasting results with the assistance of Markov Chain in order to make them valid for other kinds of weathers. To be specific, by utilizing Markov Chain, the underlying stochastic effects of clouds coverage can be minimized and thus harvest more accurate results. The method is tested on the photovoltaic generation system of Electrical Engineering School, Wuhan University, P.R.China and rendered a satisfactory precision of forecasting. Finally, further measurements for enhancing accuracy are also discussed in this paper.

Info:

Periodical:

Advanced Materials Research (Volumes 347-353)

Edited by:

Weiguo Pan, Jianxing Ren and Yongguang Li

Pages:

1498-1505

DOI:

10.4028/www.scientific.net/AMR.347-353.1498

Citation:

X. Y. Zhang et al., "Ultra-Short-Term Ahead Generating Power Forecasting for PV System Based on Markov Chain for Error Series", Advanced Materials Research, Vols. 347-353, pp. 1498-1505, 2012

Online since:

October 2011

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Price:

$35.00

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