Improved wind prediction based on the Lorenz system. (September 2015)

• Record Type: Journal Article
• Authors: Zhang, Yagang; Yang, Jingyun; Wang, Kangcheng; Wang, Zengping; Wang, Yinding
• Is Part Of: Renewable energy. Volume 81(2015)
• Page Start: 219
• Page End: 226
• Publication Date: 2015-09
• Subjects: Lorenz system -- Atmospheric disturbance -- Wavelet neural network -- Disturbance coefficient -- Disturbance intensity; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.03.039
• Languages: English
• ISSNs: 0960-1481

Abstract

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. Highlights: Introduce the Lorenz system as the atmospheric disturbance model. Define Lorenz comprehensive disturbance flow (LCDF). Establish a perturbation formula for wind speed forecasting. Propose a new short-term wind speed prediction model named LDWNN model. Wind forecasting precision is greatly improved by applying the Lorenz disturbance.