bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)

0.705

2013 Global Impact Factor

205.767

2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents

 

Best Articles 2011

 

 

 

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

 

Bullet

 

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.

 

Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format

 

 

Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)

 

 

 

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

 

 

Download <here> the Library Journal Recommendation Form

 

 

Read more about DAQ Systems

 

 

 

 

 


1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.


Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn