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An integrated monitoring system for life-cycle management of wind turbines

  • Smarsly, Kay (Department of Civil and Environmental Engineering, Stanford University) ;
  • Hartmann, Dietrich (Department of Civil and Environmental Engineering, Ruhr-University Bochum) ;
  • Law, Kincho H. (Department of Civil and Environmental Engineering, Stanford University)
  • 투고 : 2012.08.16
  • 심사 : 2013.02.10
  • 발행 : 2013.08.25

초록

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

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참고문헌

  1. Adobe Systems Incorporated (2007), Datasheet Adobe Flex Builder 3 - Create engaging, cross-platform rich Internet applications, San Jose, CA, USA: Adobe Systems Incorporated.
  2. Allemang, R.J. (2003), "The Modal Assurance Criterion (MAC): twenty years of use and abuse", Sound Vib., 37(8), 14-21.
  3. Amirat, Y., Benbouzid, M.E.H., Bensaker, B. and Wamkeue, R. (2007), "Condition monitoring and fault diagnosis in wind energy conversion systems: a review", Proceedings of the IEEE International Electric Machines and Drives Conference. Antalya, Turkey, May 3-5.
  4. ANSYS Inc. (2011), Documentation for ANSYS, Documentation. Canonsburg, PA, USA: ANSYS Inc.
  5. Avendano-Valencia, L.D., Spiridonakos, M.D. and Fassois, S.D. (2011), "In-operation identification of a wind turbine structure via non-stationary parametric models", Proceedings of the 8th International Workshop on Structural Health Monitoring. Stanford, CA, USA, September 13-15.
  6. Back, T. (1996), Evolutionary algorithms in theory and practice, New York, NY, USA: Oxford University Press.
  7. Baumgart, A. (2001), Models for wind turbines - a collection, Riso-R-1352(EN), Roskilde, Denmark: Riso National Laboratory.
  8. Bellifemine, F., Caire, G., Pogg, A. and Rimassa, G. (2003), "JADE - a white paper", EXP Online, 3(3), 6-19.
  9. Bellifemine, F., Caire, G. and Greenwood, D. (2004), Developing Multi-Agent Systems with JADE, Hoboken, NJ, USA, John Wiley & Sons.
  10. Bellifemine, F., Caire, G., Trucco T. and Rimassa, G. (2007), Jade Programmer's Guide. [Online] Available at http://jade.tilab.com/doc/programmersguide.pdf.
  11. Besnard, F. (2009), On optimal maintenance management for wind power systems, Licentiate Thesis. Stockholm, Sweden: KTH Royal Institute of Technology.
  12. Bilek, J., Mittrup, I., Smarsly, K. and Hartmann, D. (2003), "Agent-based concepts for the holistic modeling of concurrent processes in structural engineering", Proceedings of the 10th ISPE International Conference on Concurrent Engineering: Research and Applications. Madeira, Portugal, June 26-30.
  13. Bittner, U. (2008), "Successive model-updating of the dynamic behavior of casing bodies on a practical example of an axial piston pump", Proceedings of the NAFEMS Seminar Interaction of Simulation and Testing: New Requirements and New Opportunities in Structural Dynamics. Wiesbaden, Germany, November 12-13.
  14. Castors, M. (2008), PDI Performance tuning check-list, Technical Report. Orlando, FL, USA, Pentaho Corporation.
  15. Ciang, C.C., Lee, J.R. and Bang, H.J. (2008), "Structural health monitoring for a wind turbine system: a review of damage detection methods", Meas. Sci. Technol., 19(12), 122001 (20 pages). https://doi.org/10.1088/0957-0233/19/12/122001
  16. Cooley, J.W. and Tukey, J.W. (1965), "An algorithm for the machine calculation of complex fourier series", Math. Comput., 19(90), 297-301. https://doi.org/10.1090/S0025-5718-1965-0178586-1
  17. Echavarria, E., Hahn, B., van Bussel, G.J.W. and Tomiyama, T. (2008), "Reliability of wind turbine technology through time", J. Sol. Energ.-T. ASME, 130(3), 031005 (8 pages). https://doi.org/10.1115/1.2936235
  18. EIA (U.S. Energy Information Administration) (2011), International Energy Outlook 2010 - Highlights. Report. Washington, DC, USA, U.S. EIA.
  19. Feinberg, S. (2011), Clean energy investment storms to new record in 2010, Press release. January 11, 2011. [Online] Available at http://bnef.com/PressReleases/view/134.
  20. Hameed, Z., Hong, Y.S., Cho, Y.M., Ahn, S.H. and Song, C.K. (2009), "Condition monitoring and fault detection of wind turbines and related algorithms: a review", Renew. Sust. Energ. Rev., 13(1), 1-39. https://doi.org/10.1016/j.rser.2007.05.008
  21. Hartmann, D. and Hoffer, R. (2010), Lifespan assessment of wind turbines through system identification (Lebensdauerabschatzung von Windenergieanlagen mit fortlaufend durch Systemidentifikation aktualisierten numerischen Modellen), Research project funded by the German Research Foundation (DFG) through the research grant HA 1463/20-1. Ruhr University Bochum, Bochum, Germany.
  22. Hartmann, D., Smarsly, K. and Law, K.H. (2011), "Coupling sensor-based structural health monitoring with finite element model updating for probabilistic lifetime estimation of wind energy converter structures", Proceedings of the 8th International Workshop on Structural Health Monitoring. Stanford, CA, USA, September 13-15.
  23. Hyers, R.W., McGowan, J.G., Sullivan, K.L., Manwell, J.F. and Syrett, B.C. (2006), "Condition monitoring and prognosis of utility scale wind turbines", Energy Mater., 1(3), 187-203. https://doi.org/10.1179/174892406X163397
  24. Jennings, N.R. and Wooldridge, M. (1998), "Applications of intelligent agents", (Eds., N.R. Jennings and M. Wooldridge), Agent technology: foundations, applications, and markets. Berlin, Germany, Springer.
  25. Lachmann, S., Baitsch, M., Hartmann, D. and Hoffer, R. (2009), "Structural lifetime prediction for wind energy converters based on health monitoring and system identification", Proceedings of the 5th European & African Conference on Wind Engineering. Florence, Italy, July 19.
  26. Lu, B., Li, Y., Wu, X. and Yang, Z. (2009), "A review of recent advances in wind turbine condition monitoring and fault diagnosis", Proceedings of the IEEE Power Electronics and Machines in Wind Application. Lincoln, NE, USA, June 24-26.
  27. Matsuishi, M. and Endo, T. (1968), "Fatigue of metals subjected to varying stress", Proceedings of the Kyushu District Meeting of the Japan Society of Mechanical Engineers. Fukuoka, Japan, March.
  28. Mittrup, I., Smarsly, K., Hartmann, D. and Bettzieche, V. (2003), "An agent-based approach to dam monitoring", Proceedings of the 20th CIB W78 Conference on Information Technology in Construction. Auckland, New Zealand, April 23-25.
  29. Nguyen, V.V., Hartmann, D., Baitsch, M. and Konig, M. (2010), "A distributed agent-based approach for robust optimization", Proceedings of the 2nd International Conference on Engineering Optimization. Lisbon, Portugal, September 6-9.
  30. Nilsson, J. and Bertling, L. (2007), "Maintenance management of wind power systems using condition monitoring systems - life cycle cost analysis for two case studies", IEEE T. Energy Conver., 22(1), 223-229. https://doi.org/10.1109/TEC.2006.889623
  31. Rai, R.K., Singh, M.J. and Naughton, J.W. (2011), "Investigation of wind turbine response to various wind inflow models", Proceedings of the 49th AAIA Aerospace Sciences Meeting. Orlando, FL, USA, January 4-7.
  32. Park, J., Smarsly, K., Law, K.H. and Hartmann, D. (2013), "Multivariate analysis and prediction of wind turbine response to varying wind field characteristics based on machine learning", Proceedings of the ASCE International Workshop on Computing in Civil Engineering. Los Angeles, CA, USA, June 23-25.
  33. Polanco, J. and Pedersen, A. (2009), Understanding the flex 3 component and framework lifecycle, San Francisco, CA, USA, DevelopmentArc LLC.
  34. Ribrant, J. and Bertling, L.R. (2007), "Survey of failures in wind power systems with focus on Swedish wind power plants during 1997-2005", Proceedings of the IEEE Power Engineering Society General Meeting 2007. Tampa, FL, USA, June 24-28.
  35. Roldan, M.C. (2009), Pentaho data integration (Kettle) tutorial, Technical Report. Orlando, FL, USA, Pentaho Corporation.
  36. Rolfes, R., Gerasch, G., Haake, G., Reetz, J. and Zerbst, S. (2006), "Early damage detection system for tower and rotor blades of offshore wind turbines", Proceedings of the 3rd European Workshop on Structural Health Monitoring. Granada, Spain, July 5-7.
  37. Rolfes R., Zerbst S., Haake G., Reetz J. and Lynch J.P. (2007), "Integral SHM-System for Offshore Wind Turbines Using Smart Wireless Sensors", Proceedings of the 6th International Workshop on Structural Health Monitoring. Stanford, CA, USA, September 11-13.
  38. Russell, S. and Norvig, P. (1995), Artificial intelligence: a modern approach, Englewood Cliffs, NJ, USA, Prentice-Hall.
  39. Sathe, A and Bierbooms, W (2007), "Influence of different wind profiles due to varying atmospheric stability on the fatigue life of wind turbines", J. Phys. Conf. Ser., 75 (1), 012056. https://doi.org/10.1088/1742-6596/75/1/012056
  40. Schneider, M., Froggatt, A. and Thomas, S. (2011), The world nuclear industry status report 2010-2011, Nuclear Power in a Post-Fukushima World - 25 Years After the Chernobyl Accident. Washington, DC, USA, Worldwatch Institute. [Online] Available at: http://www.worldwatch.org/system/files/pdf/WorldNuclearIndustryStatusReport2011_%20FINAL.pdf.
  41. Smarasly, K. and Hartmann, D. (2009a), "Real-time monitoring of wind turbines based on software agents", Proceedings of the 18th International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering. Weimar, Germany, July 7-9.
  42. Smarsly, K. and Hartmann, D. (2009b), "Multi-scale monitoring of wind energy plants based on agent technology", Proceedings of the 7th International Workshop on Structural Health Monitoring. Stanford, CA, USA, September 9-11.
  43. Smarsly, K. and Hartmann, D. (2010), "Agent-oriented development of hybrid wind turbine monitoring systems", Proceedings of the 2010 EG-ICE Workshop on Intelligent Computing in Engineering. Nottingham, UK, June 30 - July 2.
  44. Smarsly, K., Law, K.H. and Hartmann, D. (2012), "Multi-agent-based collaborative framework for a self-managing structural health monitoring system", J. Comput. Civil Eng., 26(1), 76-89. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000107
  45. Smarsly, K., Law, K.H. and Konig, M. (2011), "Resource-efficient wireless monitoring based on mobile agent migration", Proceedings of the SPIE (Vol. 7984): Health Monitoring of Structural and Biological Systems 2011. San Diego, CA, USA, March 6-10.
  46. Stangenberg, F., Breitenbucher, R., Bruhns, O.T., Hartmann, D., Hoffer, R., Kuhl, D. and Meschke, G. (Eds.) (2009), Lifetime-oriented structural design concepts, Berlin, Germany, Springer.
  47. SVS (Structural Vibration Solutions) (2011), ARTeMIS software - version 5.3, Aalborg East, Denmark: Structural Vibration Solutions A/S.
  48. Swartz, R.A., Lynch, J.P., Sweetman, B., Rolfes, R. and Zerbst, S. (2010), "Structural monitoring of wind turbines using wireless sensor networks", Smart Struct. Syst., 6 (3), 183-196. https://doi.org/10.12989/sss.2010.6.3.183
  49. Wooldridge, M. and Jennings, N.R. (1995), "Intelligent agents: theory and practice", Knowl. Eng. Rev., 10(2), 115-152. https://doi.org/10.1017/S0269888900008122
  50. Wooldridge, M. (2009), An introduction to multiagent systems, 2nd Ed., Hoboken, NJ, USA, John Wiley & Sons.
  51. WWEA (World Wind Energy Association) (2012), Report 2011, Report. Bonn, Germany, WWEA.
  52. Zhang, X. Y., Sim, S. H. and Spencer Jr., B.F. (2007), "Finite element model updating of a truss model using incomplete modal data", Proceedings of the World Forum on Smart Materials and Smart Structures Technology. Chongqing, China, May 22-27.

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