DOI: https://doi.org/10.14710/ijred.2.2.69-74

A Reliability Based Model for Wind Turbine Selection

1Division of Electrical Engg, School of Engg., Cochin University of Science and Technology, (CUSAT), Cochin, Kerala, India

2Dept. of Mechanical Engg, Model Engineering College, Cochin, Kerala, India

Published: 17 Jun 2013.
Editor(s): H. Hadiyanto

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Abstract
A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbines commercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.
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Keywords: reliability; weibull distribution; wind power; wind speed; wind turbine selection

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Article Info
Section: Original Research Article
Language : EN
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  1. A Survey of Canadian Utilities.(1995) Isolated Systems Generating Planning Practices
  2. Abed,K.A. &El-Mallah,A.A.(1997) Capacity Factor of Wind Turbines. Energy, 22,487-91
  3. Albadi, M.H. &EI-Saadany, E.F.(2010) Optimum Turbine-Site Matching. Energy, 35, 3593-3602
  4. Bardi, U.(2009) Peak Oil: The Four Stages of A New Idea. Energy, 34, 323-6
  5. Billinton, R. &Allan, R.N.(1996) Reliability Evaluation of Power Systems. Plenum Press, 2nded. New York
  6. Charles,E.E.(2000) An Introduction to reliability and maintainability engineering, 1stedition , New Delhi; Tata McGraw –Hill Publishing company Ltd
  7. Dong Li, D. & Niu, L.Q.(2008) Reliability Analysis of Electric Distribution System Integrated with Wind Power, IEEE International Conference on Industrial Electronics and Applications ICIEA, Singapore pp 729-733
  8. Hirsch, R.L., Bezdec, R. & Wendling, R.(2005) Peaking of World Oil Production: Impacts, Mitigation and RiskManagement. DOE Report. Available from, http://www.netl.doe.gov/publications/others/pdf/Oil_Peaking_NETL.pdf
  9. Jangamshetti, S.H. &Rau, V.G.(1999) Site Matching of Wind Turbine Generators: A Case Study.IEEE Transactions on Energy Conversion, 14(4), 1537-1543
  10. Jangamshetti, S.H. &Rau, V.G.(2001a) Optimum Siting of Wind Turbine Generators.IEEE Transactions on Energy Conversion, 16(1), 8-13
  11. Jangamshetti, S.H. &Rau, V.G.(2001b) Normalized Power Curves as A Tool for Identification of Optimum Wind Turbine Generator Parameters.IEEE Transactions on Energy Conversion, 16(3), 283-288
  12. .Johnson & Gary,L.(1985) Wind Energy Systems, Prentice Hall Inc., Englewood Cliffs, NJ 07632
  13. Justus,C.G.(1978) Winds and System Performance, Franklin Institute Press, Philadelphia
  14. Karki, R. &Billinton, R.(2004) Cost-Effective Wind Energy Utilization for Reliable Power Supply.IEEE Transactions on Energy Conversion, 19(2), 435-440
  15. Karki. R.& Po,Hu.(2005) Wind Power Simulation Model for Reliability Evaluation, In Proc.IEEE Can. Con. Electr. Comput. Eng. Saskatoon, 541-544
  16. Manwell, J.F., McGowan, J.G. &Rogers, A.L.(2002) Wind Energy Explained –Theory, Design and Application. West Sussex: John Wiley & Sons Ltd
  17. Meng,Q.Y. & Bentley,R.W.(2008) Global Oil Peaking: Responding to The Case for Abundant Supplies of Oil. Energy, 33, 1179-84
  18. Salameh,Z.M. &Safari,I.(1992) Optimum Windmill-Site Matching. IEEE Transaction on Energy Conversion, 7, 669-76
  19. Srinath,L.S.(2005) Reliability Engineering,3rdedition, New Delhi. Affiliated East-West Press
  20. Suchitra, G. &Jangamshetti, S.H.(2008) Reliability Evaluation of Wind Power in North Karnataka, India-A Case Study.IEEE International Conference on Sustainable Energy Technologies ICSETSingapore, 24-27, 478-482

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