Improved wind prediction based on the Lorenz system

Yagang Zhang, Jingyun Yang, Kangcheng Wang, Zengping Wang and Yinding Wang

Renewable Energy, 2015, vol. 81, issue C, 219-226

Abstract: Atmospheric disturbance is a complex nonlinear process. The Lorenz system was seen as a classical model to reveal essential characteristics of nonlinear systems. It has further improved people's understanding of the evolution of the climate system. Different from traditional studies working on improving the numerical methods for wind prediction, dynamic characteristics of the atmospheric system are fully considered here. This paper proposed the concept of the Lorenz Comprehensive Disturbance Flow (LCDF) and defined the perturbation formula for wind prediction. The Lorenz disturbance has significant influence on wind forecasting, which is proved by using wind data from the Sotavento wind farm. That is to say, the change process of atmospheric motion around the wind farm is more ideally described based on the Lorenz system. This research has important theoretical value in developing nonlinear systems and plays a great role on wind prediction and wind resource exploitation.

Keywords: Lorenz system; Atmospheric disturbance; Wavelet neural network; Disturbance coefficient; Disturbance intensity (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:81:y:2015:i:c:p:219-226

DOI: 10.1016/j.renene.2015.03.039

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