Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

Yagang Zhang, Jingyun Yang, Kangcheng Wang and Zengping Wang
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Yagang Zhang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Jingyun Yang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Kangcheng Wang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Zengping Wang: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Energies, 2015, vol. 8, issue 1, 1-15

Abstract: This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

Keywords: wind energy; wind speed and power prediction; Lorenz system; atmospheric disturbance; artificial neural network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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