Research on Manufacturing Logistics with Applied Technology Based on Logistic Distribution Probability Function and Elman Neural Network of Wind Power

Abstract:

This article focuses on the probability distribution of wind power fluctuations and prediction problems, on this basis, putting forward new ideas for wind blade manufacturing process. Depending on that wind power has the characteristics of volatility, this article finds the probability distribution of wind power fluctuations in Logistic function is the best fit between the location - scale function, Logistic function, Extreme value function, and Normal function, Then, this article utilize the Elman neural network prediction model to forecast the wind power in the coming period of time, good results are obtained. Finally, we use new ideas in the manufacture of wind turbine blades with whole hollow, pitch type, carbon fiber as a reinforcing material.

• Periodical: Applied Mechanics and Materials (Volume 540)
• Pages: 537-540
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.540.537
• Online since: April 2014
• Authors: Yu Long Ma*
• Keywords: Elman Neural Network (ENN), Logistic Function, Turbine Blade Manufacturing, Wind Power

References

[1] X. X Wei: China's Wind Power Development Problems and Countermeasures[J]. Beijing: China Technical and Economic Power, 2009, 21（6）：23-26.

[2] W. X Lin, J. Y Wen: Research Based on Fluctuation Characteristics of Wind Power Probability Distribution. State Key Laboratory of Electromagnetic Engineering and New Technology.

[3] XuMing Han: Application of Elman neural network, (2009).

[4] W. B Tong: Manufacturing Technology of Rotor Blades for Large Wind Turbines, Harbin Institute of Large Electrical Machinery, Harbin 150040, China.