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Vol. 176, Issue 8, August 2014, pp. 237-243




Study on Parameters Modeling of Wind Turbines Using SCADA Data

Yonglong YAN, Jian LI, Peng SUN, Xiaomeng ZHANG

State Key Laboratory of Power Equipment & System Security and New Technology College of Electrical Engineering Chongqing University, Chongqing, 400030, China
Tel.: +86 23 65106880, fax: +86 23 65102442

E-mail: lijian@cqu.edu.cn



Received: 18 March 2014 /Accepted: 31 July 2014 /Published: 31 August 2014

Digital Sensors and Sensor Sysstems


Abstract: Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA) system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs). The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS) are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.


Keywords: Wind turbines, SCADA data, Parameter selection, Data modeling, Neural network.


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