Abstract
Present paper shows a new procedure to obtain control algorithms based on weather conditions to fault forecast in a real wind farm during a year. In an initial study, results showed a correlation between central hydraulic level and gearbox level and asymmetric currents and the emergency stop. A second statistical study of one-way analysis of variance was selected to define groups of errors under the same weather conditions. In consequence, a clear relationship between groups of maintenance problems and weather conditions under which they happens was obtained. It was obtained that the more important weather variables for maintenance were the mean outdoor temperature and the wind velocity. Mean outdoor temperature was related with freezing of anemometers and excessive orienting time faults. On the other hand, brake shoe temperature, emergency stop, low voltage and asymmetric currents were related with wind velocity and wind direction faults. Finally, relative humidity resulted as the worst weather parameter to predict maintenance problems. Furthermore, the average values of each weather condition at which faults are expected were defined due to these values can be employed in future research works about fault forecast based on local weather forecast.
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Entezami, M.; Hillmansen, S.; Weston, P.; Papaelias, M.Ph.: Fault detection and diagnosis within a wind turbine mechanical braking system using condition monitoring. Renew. Energy 47, 175–182 (2012)
Hameed, Z.; Hong, Y.S.; Cho, Y.M.; Ahn, S.H.; Song, C.K.: Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renew. Sustain. Energy Rev. 13, 1–39 (2009)
Orosa, J.A.; García-Bustelo, E.J.; Pérez, J.A.: Galician climatic change effect on wind power production. POWERENG2009. 978-1-4244-2291-3/09/$25.00 ©2009 IEEE. (2009) 180–184 (2009)
Caselitz, P.; Giebhardt, J.;Mevenkamp, M.: On-line fault detection and prediction in wind energy converters. EWEC’94 Thessaloniki 623–627 (1994)
Sen, Z.: Statistical investigation of wind energy reliability and its application. Renew. Energy 10, 71–79 (1997)
Kusiak, A.; Zhen, H.; Song, Z.: Models for monitoring wind farm power. Renew. Energy 34, 583–590 (2009)
Siam, R.: Environmental information system of Galicia. http://www.meteogalicia.es. Accessed May 2012
Apt, J.: The spectrum of power from wind turbines. J. Power Sources 169, 369–374 (2007)
Concetti, M.; Cuccioletta, R.; Fedele, L.; Mercuri, G.: Tele-maintenance “intelligent” system for technical plants result management. Reliab. Eng. Syst. Saf. 94, 63–77 (2009)
García, M.C.; Sanz-Bobi, M.A.; del Pico, J.: SIMAP: intelligent system for predictive maintenance application to the health condition monitoring of a wind turbine gearbox. Comput. Ind. 57, 552–568 (2006)
Orosa, J.A.; Oliveira, A.C.; Costa, A.M.: New procedure for wind farm maintenance. Ind. Manag. Data Syst. 110, 861–882 (2010)
Davim, J.P.: Statistical and computational techniques in manufacturing. Springer, Heidelberg (2012)
Byon, E.; Ding, Y.: Season-dependent condition-based maintenance for a wind turbine using a partially observed markov decision process. IEEE Trans. Power Syst. 25, 1823–1834 (2010)
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Costa, Á.M., Roshan, G., Orosa, J.A. et al. Case Study of Weather Maintenance in Wind Power Generation. Arab J Sci Eng 39, 5615–5624 (2014). https://doi.org/10.1007/s13369-014-1115-6
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DOI: https://doi.org/10.1007/s13369-014-1115-6