Abstract
This article presents a standardized analysis of failures in wind turbines concerning the main technologies classified in the literature, as well as identifies critical components and trends for the most modern wind farm facilities, which seek greater efficiency, robustness and reliability to mitigate failures and reduce wind turbine downtime. Through the application of Pareto’s rule, a set of components has been identified; although these provide little in terms of fault contribution, they do account for almost all downtime when they occur. Wind turbines fail around twice every year with an average downtime of 150 h per failure. The gearbox is one of the most critical components in terms of downtime that represents generation losses, where the faults in the frequency converter are directly influenced by the thermal cycle of the semiconductor switches in normal operation and accentuated by transient load fluctuations during the generation process. In order to identify the optimum point for preventive interventions that do not impact the overall maintenance cost, at the end a maintenance cost of a 2 MW wind turbine is discussed.
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References
Abouel-seoud, S. A., & Khalil, M. I. (2013). Cost optimization of maintenance scheduling for wind turbine gearbox components with assured reliability. World Journal Control Science and Engineering, 1(1), 25–34.
Ackermann, T. (2005). Wind power in power systems. Wiley. https://doi.org/10.1002/0470012684.
Adumene, S., & Okoro, A. (2020). A Markovian reliability approach for offshore wind energy system analysis in harsh environments. Engineering Reports, 2(3), 1–13. https://doi.org/10.1002/eng2.12128.
Akay, B., Ragni, D., Ferreira, C. J. S., & van Bussel, G. J. W. (2014). Experimental investigation of the root flow in a horizontal axis wind turbine. Wind Energy, 17, 1093–1109. https://doi.org/10.1002/we.1620.
Akdaǧ, S. A., & Dinler, A. (2009). A new method to estimate Weibull parameters for wind energy applications. Energy Conversion and Management, 50(7), 1761–1766. https://doi.org/10.1016/j.enconman.2009.03.020.
Artigao, E., Martín-Martínez, S., Honrubia-Escribano, A., & Gómez-Lázaro, E. (2018). Wind turbine reliability: A comprehensive review towards effective condition monitoring development. Applied Energy, 228(February), 1569–1583. https://doi.org/10.1016/j.apenergy.2018.07.037.
Barahona, B., Sørensen, P., Member, S., Christensen, L., Sørensen, T., Nielsen, H. K., & Lars, X. G. (2011). Flicker from wind turbines. IEEE Transactions on Energy Conversion, 26(1), 373–378.
Bariša, T., Sumina, D., Pravica, L., & Čolović, I. (2017). Flying start and sensorless control of permanent magnet wind power generator using induced voltage measurement and phase-locked loop. Electric Power Systems Research, 152, 457–465. https://doi.org/10.1016/j.epsr.2017.08.002.
Bataglioli, R. P., Monaro, R. M., & Coury, D. V. (2019). Differential protection for stator ground faults in a full-converter wind turbine generator. Electric Power Systems Research, 169(March 2018), 195–205. https://doi.org/10.1016/j.epsr.2018.12.018.
Beainy, A., Maatouk, C., Moubayed, N., & Kaddah, F. (2016). Comparison of different types of generator for wind energy conversion system topologies. In 2016 3rd international conference on renewable energies for developing countries, REDEC 2016 (pp. 1–6). https://doi.org/10.1109/REDEC.2016.7577535
Besnard, F., & Bertling, L. (2010). An approach for condition-based maintenance optimization applied to wind turbine blades. IEEE Transactions on Sustainable Energy, 1(2), 77–83. https://doi.org/10.1109/TSTE.2010.2049452.
Bruce, T., Long, H., & Dwyer-Joyce, R. S. (2015). Dynamic modelling of wind turbine gearbox bearing loading during transient events. IET Renewable Power Generation, 9(7), 821–830. https://doi.org/10.1049/iet-rpg.2014.0194.
Cao, L., Qian, Z., Zareipour, H., Huang, Z., & Zhang, F. (2019). Fault diagnosis of wind turbine gearbox based on deep bi-directional long short-term memory under time-varying non-stationary operating conditions. IEEE Access, 7, 155,219-155,228. https://doi.org/10.1109/ACCESS.2019.2947501.
Carroll, J., McDonald, A., & McMillan, D. (2015). Reliability comparison of wind turbines with DFIG and PMG drive trains. IEEE Transactions on Energy Conversion, 30(2), 663–670. https://doi.org/10.1109/TEC.2014.2367243.
Catelani, M., Ciani, L., Galar, D., & Patrizi, G. (2020a). Optimizing maintenance policies for a yaw system using reliability-centered maintenance and data-driven condition monitoring. IEEE Transactions on Instrumentation and Measurement, 69(9), 6241–6249. https://doi.org/10.1109/TIM.2020.2968160.
Catelani, M., Ciani, L., Galar, D., & Patrizi, G. (2020b). Risk assessment of a wind turbine: A new FMECA-based tool with RPN threshold estimation. IEEE Access, 8, 20181–20190. https://doi.org/10.1109/ACCESS.2020.2968812.
Cen, H., Zhang, T., Tian, W., & Zheng, Y. (2019). Fault analysis and adaptive design of wind turbine lubrication system. International Journal of Performability Engineering, 15(2), 431–440. https://doi.org/10.23940/ijpe.19.02.p8.431440.
Cevasco, D., Collu, M., & Lin, Z. (2018). O&M cost-based FMECA: Identification and ranking of the most critical components for 2–4 MW geared offshore wind turbines. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1102/1/012039.
Chatterjee, S., & Chatterjee, S. (2018). Review on the techno-commercial aspects of wind energy conversion system. IET Renewable Power Generation, 12(14), 1581–1608. https://doi.org/10.1049/iet-rpg.2018.5197.
Chen, G., & Cai, X. (2019). Reconfigurable control for fault-tolerant of parallel converters in PMSG wind energy conversion system. IEEE Transactions on Sustainable Energy, 10(2), 604–614. https://doi.org/10.1109/TSTE.2018.2841018.
Chen, Z., & Li, H. (2008). Overview of different wind generator systems and their comparisons. IET Renewable Power Generation, 2(2), 123–138. https://doi.org/10.1049/iet-rpg:20070044.
Chou, J. S., Chiu, C. K., Huang, I. K., & Chi, K. N. (2013). Failure analysis of wind turbine blade under critical wind loads. Engineering Failure Analysis, 27, 99–118. https://doi.org/10.1016/j.engfailanal.2012.08.002.
Dao, C., Kazemtabrizi, B., & Crabtree, C. (2019). Wind turbine reliability data review and impacts on levelised cost of energy. Wind Energy, 22(12), 1848–1871. https://doi.org/10.1002/we.2404.
De Freitas, T. R., Menegáz, P. J., & Simonetti, D. S. (2016). Rectifier topologies for permanent magnet synchronous generator on wind energy conversion systems: A review. Renewable and Sustainable Energy Reviews, 54, 1334–1344. https://doi.org/10.1016/j.rser.2015.10.112.
Diogo Spacek, A., Hideo Ando Junior, O., Mota Neto, J., Coelho, V., Oliveira, M., Shaeffer, L., & Gruber, V. (2013). Management of mechanical vibration and temperature in small wind turbines using zigbee wireless network. IEEE Latin America Transactions, 11(1), 512–517. https://doi.org/10.1109/TLA.2013.6502854.
Duong, M. Q., & Sava, G. N. (2017). Coordinated reactive power control of DFIG to Improve LVRT characteristics of FSIG in wind turbine generation. In 2017 11th international conference on electromechanical and power systems, SIELMEN 2017-proceedings (Vol. 2017-Janua, pp. 256–260). https://doi.org/10.1109/SIELMEN.2017.8123328
El-Metwally, M., El-Shimy, M., Mohamed, A., Elshahed, M., & Sayed, A. (2018). Reliability assessment of wind turbine operating concepts using reliability block diagrams (RBDs). In 2017 19th international middle-east power systems conference, MEPCON 2017-proceedings 2018-Febru(December), 430–436. https://doi.org/10.1109/MEPCON.2017.8301216
Ellis, A., Muljadi, E., Sanchez-Gasca, J., & Kazachkov, Y. (2011). Generic models for simulation of wind power plants in bulk system planning studies. IEEE Power and Energy Society General Meeting, pp. 1–8. https://doi.org/10.1109/PES.2011.6039844
Faiz, J., & Nejadi-Koti, H. (2016). Demagnetization fault indexes in permanent magnet synchronous motors—An overview. IEEE Transactions on Magnetics. https://doi.org/10.1109/TMAG.2015.2480379.
Feng, Y., Tavner, P. J., & Long, H. (2010). Early experiences with UK round 1 offshore wind farms. Proceedings of Institution of Civil Engineers: Energy, 163(4), 167–181. https://doi.org/10.1680/ener.2010.163.4.167.
Fischer, K., Besnard, F., & Bertling, L. (2012). Reliability-centered maintenance for wind turbines based on statistical analysis and practical experience. IEEE Transactions on Energy Conversion, 27(1), 184–195. https://doi.org/10.1109/TEC.2011.2176129.
Fischer, K., Pelka, K., Puls, S., Poech, M. H., Mertens, A., Bartschat, A., et al. (2019). Exploring the causes of power-converter failure in wind turbines based on comprehensive field-data and damage analysis. Energies. https://doi.org/10.3390/en12040593.
Franquet, E., Salvadó-Figueres, M., Lorenzo-Bosquet, C., Cuberas-Borrós, G., Rovira, A., Castell-Conesa, J., & Hernandez-Vara, J. (2012). Nigrostriatal pathway dysfunction in a methanol-induced delayed dystonia-parkinsonism. Movement Disorders, 27(10), 1220–1221. https://doi.org/10.1002/mds.25049.
Galani, P. A., Teixeira, J. C., & Guerra, S. M. G. (2015). Influence of failure rate and downtime in annual energy produced on a horizontal axis wind turbine. IEEE Latin America Transactions, 13(9), 2949–2954. https://doi.org/10.1109/TLA.2015.7350044.
Garabedian, N. T., Gould, B. J., Doll, G. L., & Burris, D. L. (2018). The cause of premature wind turbine bearing failures: Overloading or underloading? Tribology and Lubrication Technology, 74(7), 60–74.
Gonzalez, E., Reder, M., & Melero, J. J. (2016). SCADA alarms processing for wind turbine component failure detection. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/753/7/072019.
Gonzalez, E., Tautz-Weinert, J., Melero, J. J., & Watson, S. J. (2018). Statistical evaluation of SCADA data for wind turbine condition monitoring and farm assessment. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1037/3/032038.
Haddadi, A., Zhao, M., Kocar, I., Karaagac, U., Chan, K. W., & Farantatos, E. (2021). Impact of inverter-based resources on negative sequence quantities-based protection elements. IEEE Transactions on Power Delivery, 36(1), 289–298. https://doi.org/10.1109/TPWRD.2020.2978075.
Hatziargyriou, F. D., & Kanellos, N. D. (2009). Control of variable speed wind turbines equipped with synchronous or doubly fed induction generators supplying islanded power systems. IET Renewable Power Generation, 3(1), 96–108. https://doi.org/10.1049/iet-rpg.
Hernández, C. V., Telsnig, T., & Pradas, A. V. (2017). JRC wind energy status report 2016 edition. Technical report, Office of the European Union; 2017. JRC105720. Publications Office of the European. https://doi.org/10.2760/332535
Hsu, J. Y., Wang, Y. F., Lin, K. C., Chen, M. Y., & Hsu, J. H. Y. (2020). Wind turbine fault diagnosis and predictive maintenance through statistical process control and machine learning. IEEE Access, 8, 23427–23439. https://doi.org/10.1109/ACCESS.2020.2968615.
Hu, Y., Li, H., Shi, P., Chai, Z., Wang, K., Xie, X., & Chen, Z. (2018). A prediction method for the real-time remaining useful life of wind turbine bearings based on the Wiener process. Renewable Energy, 127, 452–460. https://doi.org/10.1016/j.renene.2018.04.033.
Huang, N., Chen, Q., Cai, G., Xu, D., Zhang, L., & Zhao, W. (2021). Fault diagnosis of bearing in wind turbine gearbox under actual operating conditions driven by limited data with noise labels. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2020.3025396.
Huenteler, J., Tang, T., Chan, G., & Anadon, L. D. (2018). Why is China’s wind power generation not living up to its potential? Environmental Research Letters. https://doi.org/10.1088/1748-9326/aaadeb.
IRENA. (2019). Future of wind: Deployment, investment, technology, grid integration and socio-economic aspects (A Global Energy Transformation paper). Technical report, International Renewable Energy Agency, Abu Dhabi.
IRENA. (2020). Renewable power generation costs in 2019. Abu Dhabi: International Renewable Energy Agency.
Jain, B., Jain, S., & Nema, R. K. (2015). Control strategies of grid interfaced wind energy conversion system: An overview. Renewable and Sustainable Energy Reviews, 47, 983–996. https://doi.org/10.1016/j.rser.2015.03.063.
Jia, X., Jin, C., Buzza, M., Wang, W., & Lee, J. (2016). Wind turbine performance degradation assessment based on a novel similarity metric for machine performance curves. Renewable Energy, 99, 1191–1201. https://doi.org/10.1016/j.renene.2016.08.018.
Jimmy, G., McDonald, A., & Carroll, J. (2020). Energy yield and operations and maintenance costs of parallel wind turbine powertrains. IEEE Transactions on Sustainable Energy, 11(2), 674–681. https://doi.org/10.1109/TSTE.2019.2902517.
Jin, X., Xu, Z., & Qiao, W. (2021). Condition monitoring of wind turbine generators using SCADA data analysis. IEEE Transactions on Sustainable Energy, 12(1), 202–210. https://doi.org/10.1109/TSTE.2020.2989220.
Kotsiopoulos, T., Sarigiannidis, P., Ioannidis, D., & Tzovaras, D. (2021). Machine learning and deep learning in smart manufacturing: The smart grid paradigm. Computer Science Review, 40, 100,341. https://doi.org/10.1016/j.cosrev.2020.100341.
Lau, B. C. P., Ma, E. W. M., & Pecht, M. (2012). Review of offshore wind turbine failures and fault prognostic methods. In Proceedings of IEEE 2012 prognostics and system health management conference, PHM-2012 (pp. 1–5). https://doi.org/10.1109/PHM.2012.6228954
Lee, J. S., & Lee, K. B. (2015). Open-switch fault tolerance control for a three-level NPC/T-type rectifier in wind turbine systems. IEEE Transactions on Industrial Electronics, 62(2), 1012–1021. https://doi.org/10.1109/TIE.2014.2347912.
Li, Y., Jiang, W., Zhang, G., & Shu, L. (2021). Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data. Renewable Energy, 171, 103–115. https://doi.org/10.1016/j.renene.2021.01.143.
Li, Z., Jiang, Y., Guo, Q., Hu, C., & Peng, Z. (2018). Multi-dimensional variational mode decomposition for bearing-crack detection in wind turbines with large driving-speed variations. Renewable Energy, 116, 55–73. https://doi.org/10.1016/j.renene.2016.12.013.
Lin, Y., Tu, L., Liu, H., & Li, W. (2016). Fault analysis of wind turbines in China. Renewable and Sustainable Energy Reviews, 55, 482–490. https://doi.org/10.1016/j.rser.2015.10.149.
Lishan, S. (2011). Technology roadmap: China wind energy development roadmap 2050. China National Energy Administration.
Liton Hossain, M., Abu-Siada, A., & Muyeen, S. M. (2018). Methods for advanced wind turbine condition monitoring and early diagnosis: A literature review. Energies. https://doi.org/10.3390/en11051309.
Liu, Y., Wu, Z., & Wang, X. (2020). Research on fault diagnosis of wind turbine based on SCADA data. IEEE Access, 8, 185,557-185,569. https://doi.org/10.1109/access.2020.3029435.
Liu, Z., & Zhang, L. (2020). Naturally damaged wind turbine blade bearing fault detection using novel iterative nonlinear filter and morphological analysis. IEEE Transactions on Industrial Electronics, 67(10), 8713–8722. https://doi.org/10.1109/TIE.2019.2949522.
Lu, B., Li, Y., Wu, X., & Yang, Z. (2009). A review of recent advances in wind turbine condition monitoring and fault diagnosis. In 2009 IEEE power electronics and machines in wind applications, PEMWA 2009 (November 2015). https://doi.org/10.1109/PEMWA.2009.5208325.
Lu, L., He, Y., Wang, T., Shi, T., & Li, B. (2019). Self-powered wireless sensor for fault diagnosis of wind turbine planetary gearbox. IEEE Access, 7, 87382–87395. https://doi.org/10.1109/ACCESS.2019.2925426.
Ma, K., Tutelea, L., Boldea, I., Ionel, D. M., & Blaabjerg, F. (2015). Power electronic drives, controls, and electric generators for large wind turbines—An overview. Electric Power Components and Systems, 43(12), 1406–1421. https://doi.org/10.1080/15325008.2015.1037470.
Man, L. A. N., & Committee, S. (2008). IEEE Standard for,2008(November), 5–8. https://doi.org/10.1109/IEEESTD.2008.4610935.
Merizalde, Y., Hernández-Callejo, L., Duque-Pérez, O., & Alonso-Gómez, V. (2019). Diagnosis of wind turbine faults using generator current signature analysis: A review. Journal of Quality in Maintenance Engineering. https://doi.org/10.1108/JQME-02-2019-0020.
Muljadi, E., & Ellis, A. (2008). Validation of wind power plant models. IEEE power and energy society 2008 general meeting: Conversion and delivery of electrical energy in the 21st century. PES (pp. 1–7). https://doi.org/10.1109/PES.2008.4596053.
Nagpal, M., & Henville, C. (2018). Impact of power-electronic sources on transmission line ground fault protection. IEEE Transactions on Power Delivery, 33(1), 62–70. https://doi.org/10.1109/TPWRD.2017.2709279.
Navalkar, S. T., Van Solingen, E., & Van Wingerden, J. W. (2015). Wind tunnel testing of subspace predictive repetitive control for variable pitch wind turbines. IEEE Transactions on Control Systems Technology, 23(6), 2101–2116. https://doi.org/10.1109/TCST.2015.2399452.
Nguyen, T. T., & Kim, H. M. (2020). Cluster-based predictive PCC voltage control of large-scale offshore wind farm. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3048175.
Ozturk, S., Fthenakis, V., & Faulstich, S. (2018). Failure modes, effects and criticality analysis for wind turbines considering climatic regions and comparing geared and direct drive wind turbines. Energies. https://doi.org/10.3390/en11092317.
Pérez, E., Ntaimo, L., & Ding, Y. (2015). Multi-component wind turbine modeling and simulation for wind farm operations and maintenance. Simulation, 91(4), 360–382. https://doi.org/10.1177/0037549715572490.
Pfaffel, S., Faulstich, S., & Rohrig, K. (2017). Performance and reliability of wind turbines: A review. Energies. https://doi.org/10.3390/en10111904.
Pinar Pérez, J. M., García Márquez, F. P., Tobias, A., & Papaelias, M. (2013). Wind turbine reliability analysis. Renewable and Sustainable Energy Reviews, 23(2013), 463–472. https://doi.org/10.1016/j.rser.2013.03.018.
Polinder, H., Bang, D., Van Rooij, R. P., McDonald, A. S., & Mueller, M. A. (2007). 10 MW wind turbine direct-drive generator design with pitch or active speed stall control. Proceedings of IEEE international electric machines and drives conference, IEMDC, 2007(2), 1390–1395. https://doi.org/10.1109/IEMDC.2007.383632.
Polinder, H., Ferreira, J. A., Jensen, B. B., Abrahamsen, A. B., Atallah, K., & McMahon, R. A. (2013). Trends in wind turbine generator systems. IEEE Journal of Emerging and Selected Topics in Power Electronics, 1(3), 174–185. https://doi.org/10.1109/JESTPE.2013.2280428.
Qiao, W., & Lu, D. (2015). A survey on wind turbine condition monitoring and fault diagnosis—Part I: Components and subsystems. IEEE Transactions on Industrial Electronics, 62(10), 6536–6545. https://doi.org/10.1109/TIE.2015.2422112.
Qiu, Y., Jiang, H., Feng, Y., Cao, M., Zhao, Y., & Li, D. (2016). A new fault diagnosis algorithm for PMSG wind turbine power converters under variable wind speed conditions. Energies, 9(7), 548. https://doi.org/10.3390/en9070548.
Rademakers, L. W., Braam, H., Obdam, T. S., Frohböse, P., & Kruse, N. (2008). TOols for estimating operation and maintenance costs of offshore wind farms: State of the art. European Wind Energy Conference and Exhibition, 2008(5), 2531–2540.
Rahimi, M. (2014). Dynamic performance assessment of DFIG-based wind turbines: A review. Renewable and Sustainable Energy Reviews, 37, 852–866. https://doi.org/10.1016/j.rser.2014.05.072.
Ravikumar, K., Subbiah, R., Ranganathan, N., Bensingh, J., Kader, A., & Nayak, S. K. (2020). A review on fatigue damages in the wind turbines: Challenges in determining and reducing fatigue failures in wind turbine blades. Wind Engineering, 44(4), 434–451. https://doi.org/10.1177/0309524X19849851.
Reder, M. D., Gonzalez, E., & Melero, J. J. (2016). Wind turbine failures–Tackling current problems in failure data analysis. Journal of Physics: Conference Series, 753(7), 1. https://doi.org/10.1088/1742-6596/753/7/072027.
Rehman, S., Alam, M., & Alhems, L. M. (2018). A review of wind-turbine structural stability , failure and alleviation. The 2018 World Congress on Advances in Civil, Environmental, & Materials Research (ACEM18) Songdo Convensia, Incheon, Korea, August 27–31, 2018, Vol. 2017.
Rezamand, M., Carriveau, R., Ting, D. S., Davison, M., & Davis, J. J. (2019). Aggregate reliability analysis of wind turbine generators. IET Renewable Power Generation, 13(11), 1902–1910. https://doi.org/10.1049/iet-rpg.2018.5909.
Rezamand, M., Kordestani, M., Carriveau, R., Ting, D. S., Orchard, M. E., & Saif, M. (2020). Critical wind turbine components prognostics: A comprehensive review. IEEE Transactions on Instrumentation and Measurement, 69(12), 9306–9328. https://doi.org/10.1109/TIM.2020.3030165.
Ribrant, J. (2006). A survey of failures in wind power systems. Ph.D. thesis, KTH School of Electrical Engineering.
Ribrant, J., & Bertling, L. M. (2007). Survey of failures in wind power systems with focus on Swedish wind power plants during 1997–2005. IEEE Transactions on Energy Conversion, 22(1), 167–173. https://doi.org/10.1109/TEC.2006.889614.
Roth, S. (2018). Palm Springs is famous for its wind farms. They may look a lot different in the future: Palm Springs Desert Sun [Internet] [revised 2018 Oct 26; cited 2021 Sep]. Available from: https://www.desertsun.com/story/tech/science/energy/2018/10/24/palm-springs-iconic-windfarms-could-change-dramatically/1578515002/.
Salameh, J. P., Cauet, S., Etien, E., Sakout, A., & Rambault, L. (2018). Gearbox condition monitoring in wind turbines: A review. Mechanical Systems and Signal Processing, 111, 251–264. https://doi.org/10.1016/j.ymssp.2018.03.052.
Scheu, M. N., Tremps, L., Smolka, U., Kolios, A., & Brennan, F. (2019). A systematic Failure Mode Effects and Criticality Analysis for offshore wind turbine systems towards integrated condition based maintenance strategies. Ocean Engineering, 176(January), 118–133. https://doi.org/10.1016/j.oceaneng.2019.02.048.
Song, Y., & Wang, B. (2013). Survey on reliability of power electronic systems. IEEE Transactions on Power Electronics, 28(1), 591–604. https://doi.org/10.1109/TPEL.2012.2192503.
Spinato, F., Tavner, P. J., Van Bussel, G. J., & Koutoulakos, E. (2009). Reliability of wind turbine subassemblies. IET Renewable Power Generation, 3(4), 387–401. https://doi.org/10.1049/iet-rpg.2008.0060.
Tavner, P. (2011). How are we going to make offshore wind farms more reliable? SUPERGEN Wind 2011 General Assembly (March).
van Bussel, G. J. W., & Zaaijer, M. B. (2001). DOWEC concepts study, reliability, availability and maintenance aspects. In Proceedings of the 2001 European wind energy conference (Vol. 113, pp. 557–560).
Vasquez, S., Kinnaert, M., & Pintelon, R. (2019). Active fault diagnosis on a hydraulic pitch system based on frequency-domain identification. IEEE Transactions on Control Systems Technology, 27(2), 663–678. https://doi.org/10.1109/TCST.2017.2772890.
Wang, Y., & Hu, W. (2017). Investigation of the effects of receptors on the lightning strike protection of wind turbine blades. IEEE Transactions on Electromagnetic Compatibility, 59(4), 1180–1187. https://doi.org/10.1109/TEMC.2016.2647260.
Wang, Z., & Pan, R. (2021). Point and interval estimators of reliability indices for repairable systems using the Weibull generalized renewal process. IEEE Access, 9, 6981–6989. https://doi.org/10.1109/ACCESS.2021.3049438.
Wei, L., Qian, Z., & Zareipour, H. (2020). Wind turbine pitch system condition monitoring and fault detection based on optimized relevance vector machine regression. IEEE Transactions on Sustainable Energy, 11(4), 2326–2336. https://doi.org/10.1109/TSTE.2019.2954834.
Xu, J., Li, L., & Zheng, B. (2016). Wind energy generation technological paradigm diffusion. Renewable and Sustainable Energy Reviews, 59, 436–449. https://doi.org/10.1016/j.rser.2015.12.271.
Yang, L., Li, G., Zhang, Z., Ma, X., & Zhao, Y. (2021). Operations & maintenance optimization of wind turbines integrating wind and aging information. IEEE Transactions on Sustainable Energy, 12(1), 211–221. https://doi.org/10.1109/TSTE.2020.2986586.
Yang, Z., & Chai, Y. (2016). A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems. Renewable and Sustainable Energy Reviews, 66, 345–359. https://doi.org/10.1016/j.rser.2016.08.006.
Yaramasu, V., Dekka, A., Durán, M. J., Kouro, S., & Wu, B. (2017). PMSG-based wind energy conversion systems: Survey on power converters and controls. IET Electric Power Applications, 11(6), 956–968. https://doi.org/10.1049/iet-epa.2016.0799.
Yaramasu, V., Wu, B., Sen, P. C., Kouro, S., & Narimani, M. (2015). High-power wind energy conversion systems: State-of-the-art and emerging technologies. Proceedings of the IEEE, 103(5), 740–788. https://doi.org/10.1109/JPROC.2014.2378692.
Yu, X., Tang, B., & Zhang, K. (2021). Fault diagnosis of wind turbine gearbox using a novel method of fast deep graph convolutional networks. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2020.3048799.
Yun, W., & Xin, H. (2021). Fault diagnosis of wind turbine pitch system based on multiblock KPCA algorithm. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3054729.
Zhang, J., Sun, H., Sun, Z., Dong, W., & Dong, Y. (2019). Fault diagnosis of wind turbine power converter considering wavelet transform, feature analysis, judgment and BP neural network. IEEE Access, 7, 179,799-179,809. https://doi.org/10.1109/ACCESS.2019.2958409.
Zhang, S., Franek, O., Eggers, P. C., Byskov, C., & Pedersen, G. F. (2017). Multipath suppression with an absorber for UWB wind turbine blade deflection sensing systems. IEEE Transactions on Microwave Theory and Techniques, 65(7), 2583–2595. https://doi.org/10.1109/TMTT.2017.2649499.
Zhang, T., Chen, J., Xie, J., & Pan, T. (2021). SASLN: Signals augmented self-taught learning networks for mechanical fault diagnosis under small sample condition. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2020.3043098.
Zhang, X., Han, P., Xu, L., Zhang, F., Wang, Y., & Gao, L. (2020). Research on bearing fault diagnosis of wind turbine gearbox based on 1DCNN-PSO-SVM. IEEE Access, 8, 192,248-192,258. https://doi.org/10.1109/ACCESS.2020.3032719.
Zhou, D., Zhang, G., & Blaabjerg, F. (2018). Optimal selection of power converter in DFIG wind turbine with enhanced system-level reliability. IEEE Transactions on Industry Applications, 54(4), 3637–3644. https://doi.org/10.1109/TIA.2018.2822239.
Zhu, M., Hu, W., & Kar, N. C. (2017). Torque-ripple-based interior permanent-magnet synchronous machine rotor demagnetization fault detection and current regulation. IEEE Transactions on Industry Applications, 53(3), 2795–2804. https://doi.org/10.1109/TIA.2016.2634518.
Zhu, Y. M., Gong, Y., & Yang, Z. G. (2019). Failure analysis on over-temperature combustion of transformers in 4 MW offshore wind turbines. Engineering Failure Analysis, 96(August 2018), 211–222. https://doi.org/10.1016/j.engfailanal.2018.10.005.
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Santelo, T.N., de Oliveira, C.M.R., Maciel, C.D. et al. Wind Turbine Failures Review and Trends. J Control Autom Electr Syst 33, 505–521 (2022). https://doi.org/10.1007/s40313-021-00789-8
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DOI: https://doi.org/10.1007/s40313-021-00789-8