Performance and Condition Monitoring of Tidal Stream Turbines
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Research within the Cardiff Marine Energy Research Group (CMERG) has considered the integrated mathematical modelling of Tidal Stream Turbines (TST). The modelling studies are briefly reviewed. This paper concentrates on the experimental validation testing of small TST models in a water flume facility. The dataset of results, and in particular the measured axial thrust signals are analysed via time-frequency methods. For the 0.5 m diameter TST the recorded angular velocity typically varies by ± 2.5% during the 90 second test durations. Modelling results confirm the expectations for the thrust signal spectrums, for both optimum and deliberately offset blade results. A discussion of the need to consider operating conditions, condition monitoring sub-system refinements and the direction of prognostic methods development, is provided.
How to Cite
##plugins.themes.bootstrap3.article.details##
condition monitoring, renewable energy, Tidal Stream Turbines
Bechhoefer, E., Wadham-Gagnon, M. & Boucher, B. (2012). Initial condition monitoring experience on a wind turbine. Annual Conference of Prognostics and Health Management Society (pp 1 – 8), September 23-27, Minneapolis.
Grosvenor, R.I. & Prickett, P.W. (2011). A discussion of the prognostics and health management aspects of embedded condition monitoring systems. Annual Conference of Prognostics and Health Management Society (pp 1 – 8), September 25-25, Montreal.
Hameed, Z., Ahn, S.H. & Cho, Y. M. (2010). Practical aspects of a condition monitoring system for a wind turbine with emphasis on its design, system architecture, testing and installation, Renewable Energy, vol. 35, no. 5, pp. 879–894.
Iatsenko, D., McClintock, P.V.E. & Stefanovska, A. (2013). Linear and synchrosqueezed time-frequency representations revisited. Digital Signal Processing, arXiv:1310.7215v2 [math.NA] pp1-45.
Li, C. & Liang, M. (2012). Time-frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform. Mechanical Systems and Signal Processing, vol 26, pp. 205 – 217. Doi:10.1016/j.ymssp2011.07.001.
Mason-Jones, A., O’Doherty, D.M., Morris, C.E., O’Doherty, T., Byrne, C.B., Prickett, P.W., Grosvenor, R.I., Owen, I., Tedds, S. & Poole, R.J. (2012). Non-dimensional scaling of tidal stream turbines. Energy, vol 44 pp. 820 – 829. doi: 10.1016/ j.energy.2012.05.010.
Mason-Jones, A., O’Doherty, D.M., Morris, C.E., & O’Doherty, T. (2013). Influence of a velocity profile and support structure on tidal stream turbine performance. Renewable Energy. Vol 52, pp. 23 – 30. Doi:10.1016/j.renene.2012.10.022.
Myers, L.E. & Bahaj, A.S. (2012). An experimental investigation simulating flow effects in first generation marine current energy converter arrays. Renewable Energy. Vol 37, pp. 28 – 36. Doi:10.1016/j.renene.2011.03.043.
Ng, K-W., Lam, W-H. & Ng, K-C. (2013). 2002-2013: 10 years of research progress in horizontal-axis marine current turbines. Energies. Vol 6, pp. 1497 – 1526. Doi:10.3390/en6031497.
O’Doherty, T., Mason-Jones, A., O’Doherty, D.M., Evans, P.S., Woolridge, C.F. & Fryett, I. (2009), Considerations of a horizontal axis tidal turbine. Energy, vol 163 (issue EN3), pp. 119 – 130.
Tian, Z. & Jin, T. (2011). Maintenance of wind turbine systems under continuous monitoring, Reliability and Maintainability Symposium (RAMS), pp. 1 –6.
Uluyol, O. & Parthasarathy, G. (2012). Multi-turbine associative model for wind tunnel performance monitoring. Annual Conference of Prognostics and Health Management Society (pp 1 – 8), September 23-27, Minneapolis.
Yang, W., Tavner, P. J., Crabtree, C. J. & Wilkinson, M. (2010). Cost-effective condition monitoring for wind turbines, Industrial Electronics, IEEE Transactions on, vol. 57, no. 1, pp. 263 –271.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.