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The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model

Year 2014, Volume: 4 Issue: 2, 401 - 412, 01.06.2014

Abstract

This paperpresents an application of acondition-monitoring system (CMS) based on a polynomial regression model (PRM)to study the influence of heat loss on a wind generator’s temperatures.Monitoring the wind generator temperatures is a significant for efficientoperation, and plays a key role in an effective CMS. Many techniques, includingprediction models can be utilized to reliably forecast a wind generator’stemperature during operation and avoid the occurrence of a failure. PRMs arewidely used in situations when therelationship between the response and the independent variables are curve-linear.Thesetechniques can be used to construct a normal behavior model of an electricalgenerator’s temperatures based on recorded data. Many independent variables affect agenerator’s temperature; however, the degree of influence of each independent variable on the response is dissimilar. In manysituations, adding a new independent variableto the model may cause unsatisfactory results; therefore,the selection of the variables should be veryaccurate. A generator’s heatloss can be considered a significant independent variable that greatlyinfluences the wind generator with respect to the other variables. A generator’s heat loss can be estimated in intervals by analyzing theexchange in the heat between the hot and cold fluid throughthe heat exchangers of wind generators. Acase study built on data collected from actual measurements demonstrates theadequacy of the proposed model.

References

  • Lu, Bin, et al, A review of recent advances in wind turbine condition monitoring and fault diagnosis, Power Electronics and Machines in Wind Applications, 2009. PEMWA 2009, IEEE, 2009
  • Avelino J. Gonzalez, M. Stanley Balowin, J. Stein, and N. E. Nilsson, Monitoring and Diagnosis of Turbine- Driven Generator, Electric Power Research Institute, Prentice ,1995. Cliffs, New Jersey SPSS software, analytics/products/statistics/ ibm.com/software/ index.html.
  • Minitab 16 software, http://www.minitab.com. F. P. Incropera, A. S. Lavine, and D. P. DeWitt, Fundamentals of heat and mass transfer, John Wiley & Sons Incorporated, 2011.
  • J. H. Lienhard. A heat transfer textbook, Courier Dover Publications, 2011.
  • R. K. Shah, D. P. Sekulić. Fundamental of Heat Exchanger Design, Published online, 2007.
  • Data of a variable speed wind turbine 5 MW rated power, three phase permanent magnetic type 440/660 V Hz. Provided by Dr. Kathryn, Colorado School of Mines, 2013. Nomenclature GT GP OT NT CT y Dependent value).
Year 2014, Volume: 4 Issue: 2, 401 - 412, 01.06.2014

Abstract

References

  • Lu, Bin, et al, A review of recent advances in wind turbine condition monitoring and fault diagnosis, Power Electronics and Machines in Wind Applications, 2009. PEMWA 2009, IEEE, 2009
  • Avelino J. Gonzalez, M. Stanley Balowin, J. Stein, and N. E. Nilsson, Monitoring and Diagnosis of Turbine- Driven Generator, Electric Power Research Institute, Prentice ,1995. Cliffs, New Jersey SPSS software, analytics/products/statistics/ ibm.com/software/ index.html.
  • Minitab 16 software, http://www.minitab.com. F. P. Incropera, A. S. Lavine, and D. P. DeWitt, Fundamentals of heat and mass transfer, John Wiley & Sons Incorporated, 2011.
  • J. H. Lienhard. A heat transfer textbook, Courier Dover Publications, 2011.
  • R. K. Shah, D. P. Sekulić. Fundamental of Heat Exchanger Design, Published online, 2007.
  • Data of a variable speed wind turbine 5 MW rated power, three phase permanent magnetic type 440/660 V Hz. Provided by Dr. Kathryn, Colorado School of Mines, 2013. Nomenclature GT GP OT NT CT y Dependent value).
There are 6 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Khaled Bubaker Abdusamad This is me

David Wenzhong Gao This is me

Eduard Muljadi This is me

Publication Date June 1, 2014
Published in Issue Year 2014 Volume: 4 Issue: 2

Cite

APA Abdusamad, K. B., Gao, D. W., & Muljadi, E. (2014). The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model. International Journal Of Renewable Energy Research, 4(2), 401-412.
AMA Abdusamad KB, Gao DW, Muljadi E. The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model. International Journal Of Renewable Energy Research. June 2014;4(2):401-412.
Chicago Abdusamad, Khaled Bubaker, David Wenzhong Gao, and Eduard Muljadi. “The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model”. International Journal Of Renewable Energy Research 4, no. 2 (June 2014): 401-12.
EndNote Abdusamad KB, Gao DW, Muljadi E (June 1, 2014) The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model. International Journal Of Renewable Energy Research 4 2 401–412.
IEEE K. B. Abdusamad, D. W. Gao, and E. Muljadi, “The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model”, International Journal Of Renewable Energy Research, vol. 4, no. 2, pp. 401–412, 2014.
ISNAD Abdusamad, Khaled Bubaker et al. “The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model”. International Journal Of Renewable Energy Research 4/2 (June 2014), 401-412.
JAMA Abdusamad KB, Gao DW, Muljadi E. The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model. International Journal Of Renewable Energy Research. 2014;4:401–412.
MLA Abdusamad, Khaled Bubaker et al. “The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model”. International Journal Of Renewable Energy Research, vol. 4, no. 2, 2014, pp. 401-12.
Vancouver Abdusamad KB, Gao DW, Muljadi E. The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model. International Journal Of Renewable Energy Research. 2014;4(2):401-12.