Noise prediction of wind turbine based on regression analysis and BP neural network

被引：0

作者：

Cheng, Jing ^{[1
]}

Xie, Lirong ^{[2
]}

He, Shan ^{[1
]}

Wang, Weiqing ^{[2
]}

机构：

[1] College of Electric Engineering, Xinjiang University, Xinjiang

[2] Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Technology, Xinjiang

来源：

Journal of Computational Information Systems | 2015年 / 11卷 / 14期

关键词：

BP Neural Network; Noise Prediction; Regression Analysis; Wind Turbine Generation;

D O I：

10.12733/jcis14611

中图分类号：

学科分类号：

摘要：

Aiming at current situation of the energy problem and the complicated process of wind turbine noise detection, after studied IEC 61400-11 noise measurement technology standard, this paper put forward a kind of forecasting method combined regression analysis with BP neural network, forecast the A- weighted noise sound pressure level of wind turbine. The plural linear regression equation was established according to collected datum on wind farm, then calculated regression coefficient and simplified equation to train the BP neural network with less inputs. Finally, the noise prediction model was established. This model was applied to noise measurement on a wind farm in Xinjiang, and made good effect. So the feasibility and effectiveness of this method was verified. ©, 2015, Journal of Computational Information Systems. All right reserved.

引用

页码：5107 / 5116

页数：9

共 25 条

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