Research on intelligent temperature prediction of wind turbine sensor based on BP neural network

Xiangkun Guo; Baogen Nie; Mo Su

doi:10.1117/12.2675465

25 May 2023 Research on intelligent temperature prediction of wind turbine sensor based on BP neural network

Xiangkun Guo, Baogen Nie, Mo Su

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126362H (2023) https://doi.org/10.1117/12.2675465
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

Intelligent control of wind turbine is an important part of intelligent wind farm construction, and the prediction of wind turbine operation status is the hot spot of wind turbine operation and maintenance. In this paper, the prediction research is conducted on the sensor values of wind turbine high speed brake disc temperature, stator cable temperature and high speed brake disc infrared temperature with respect to the active power, actual wind speed, generator speed and nacelle temperature of wind turbine and other status quantities. The paper compares the prediction results of multiple linear regression model and BP neural network, and proposes an optimized BP neural network prediction method based on genetic algorithm to overcome the shortcomings of lack of interaction effects and nonlinear causality in the linear regression model, and determines the optimal number of neurons in the hidden layer of BP neural network, which speeds up the training data and improves the accuracy of neural network model prediction is improved.

Citation Download Citation

Xiangkun Guo, Baogen Nie, and Mo Su "Research on intelligent temperature prediction of wind turbine sensor based on BP neural network", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126362H (25 May 2023); https://doi.org/10.1117/12.2675465

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