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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
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ROMANIA

Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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 HIGH-IMPACT PAPER 

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance

ZHANG, Y. See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on IEEExplore See more information about ZHANG, Y. on Web of Science, WANG, P. See more information about  WANG, P. on SCOPUS See more information about  WANG, P. on SCOPUS See more information about WANG, P. on Web of Science, CHENG, P. See more information about  CHENG, P. on SCOPUS See more information about  CHENG, P. on SCOPUS See more information about CHENG, P. on Web of Science, LEI, S. See more information about LEI, S. on SCOPUS See more information about LEI, S. on SCOPUS See more information about LEI, S. on Web of Science
 
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Download PDF pdficon (1,200 KB) | Citation | Downloads: 1,147 | Views: 3,884

Author keywords
ARMA model, Lorenz system, renewable energy, wavelet decomposition, wind speed prediction

References keywords
wind(14), energy(10), speed(8), prediction(8), time(6), power(6), systems(5), series(5), forecasting(5), models(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 107 - 114
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03014
Web of Science Accession Number: 000410369500014
SCOPUS ID: 85030118150

Abstract
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Due to the sustainable and pollution-free characteristics, wind energy has been one of the fastest growing renewable energy sources. However, the intermittent and random fluctuation of wind speed presents many challenges for reliable wind power integration and normal operation of wind farm. Accurate wind speed prediction is the key to ensure the safe operation of power system and to develop wind energy resources. Therefore, this paper has presented a wavelet time series wind speed prediction model based on Lorenz disturbance. Therefore, in this paper, combined with the atmospheric dynamical system, a wavelet-time series improved wind speed prediction model based on Lorenz disturbance is proposed and the wind turbines of different climate types in Spain and China are used to simulate the disturbances of Lorenz equations with different initial values. The prediction results show that the improved model can effectively correct the preliminary prediction of wind speed, improving the prediction. In a word, the research work in this paper will be helpful to arrange the electric power dispatching plan and ensure the normal operation of the wind farm.


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Cited-By SCOPUS

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[1] Multi-sensors based condition monitoring of rotary machines: An approach of multidimensional time-series analysis, Wang, Teng, Lu, Guoliang, Yan, Peng, Measurement, ISSN 0263-2241, Issue , 2019.
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[CrossRef]

[2] Wind speed prediction research with EMD-BP based on Lorenz disturbance, Zhang, Yagang, Pan, Guifang, Zhang, Chenhong, Zhao, Yuan, Journal of Electrical Engineering, ISSN 1339-309X, Issue 3, Volume 70, 2019.
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[4] A Novel Hybrid Model for Wind Speed Prediction Based on VMD and Neural Network Considering Atmospheric Uncertainties, Zhang, Yagang, Zhao, Yuan, Gao, Shuang, IEEE Access, ISSN 2169-3536, Issue , 2019.
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[17] A Method Based on Lorenz Disturbance and Variational Mode Decomposition for Wind Speed Prediction, ZHANG, Y., GAO, S., BAN, M., SUN, Y., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 19, 2019.
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