NDLI: Probability distribution characteristics at longitudinal time points of wind power

Content Provider	IEEE Xplore Digital Library
Author	Xiaolu, L.V. Jun Liang Feng Zhang Bohao Sun
Copyright Year	2013
Description	Author affiliation: Key Lab. of Power Syst. Intell. Dispatch & Control of Minist. of Educ., Shandong Univ., Jinan, China (Xiaolu, L.V.; Jun Liang; Feng Zhang; Bohao Sun)
Abstract	Fluctuation characteristic of wind power causes problems in many aspects like the stable and safe operation of the power grid. Thus it is important to analyze the fluctuation rules of wind power. The present research methods are all based on the continuous time axis and can be defined as lateral time series analysis. A new method called longitudinal time analysis is proposed in this paper, which analyzes the wind power output at the same time point of 365 days or longer. Based on the measured data, probability distributions at longitudinal time points of wind power are analyzed using statistical method, and probability distribution piecewise functions are proposed through function fitting. The data of other years are verified to validate the applicability of these functions. Example analysis shows that these functions are regular, general, invariable and applicative, which illustrates that they are the inherent properties of wind power. These functions can be used for the reliability analysis of wind power forecasting and the modification of scheduling plan.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	994
Ending Page	998
File Size	710902
Page Count	5
File Format	PDF
ISBN	9781467352536
DOI	10.1109/FSKD.2013.6816340
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fluctuations wind power longitudinal time Fitting function fitting Wind power generation Probability density function Wind farms probability distribution Probability distribution fluctuation characteristic Forecasting
Content Type	Text
Resource Type	Article

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