Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults

doi:10.1007/s11465-017-0442-1

Frontiers of Mechanical Engineering

2017, Vol. 12

Issue (3): 281-302 https://doi.org/10.1007/s11465-017-0442-1

本期目录

Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults

Shoudao HUANG, Xuan WU(

), Xiao LIU, Jian GAO, Yunze HE

College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

全文: PDF(595 KB) HTML

Abstract：

Electric power conversion system (EPCS), which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine (DD-WT). However, this component accounts for the most failures (approximately 60% of the total number) in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring (CM) and fault diagnostics (FD). Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.

Key words： direct-drive wind turbine electric power conversion system condition monitoring fault diagnosis operation control under faults fault tolerance

收稿日期: 2016-09-22 出版日期: 2017-08-04

Corresponding Author(s): Xuan WU

引用本文:

. [J]. Frontiers of Mechanical Engineering, 2017, 12(3): 281-302.
Shoudao HUANG, Xuan WU, Xiao LIU, Jian GAO, Yunze HE. Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults. Front. Mech. Eng., 2017, 12(3): 281-302.

链接本文:

https://academic.hep.com.cn/fme/CN/10.1007/s11465-017-0442-1
https://academic.hep.com.cn/fme/CN/Y2017/V12/I3/281

Fig.1

Fig.2

Fig.3

Tab.1

Fig.4

Tab.2

Fig.5

Fig.6

Fig.7

Tab.3

Tab.4

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Tab.5

Fig.13

Fig.14

1	Qiao W, Lu D. A survey on wind turbine condition monitoring and fault diagnosis—Part I: Components and subsystems. IEEE Transactions on Industrial Electronics, 2015, 62(10): 6536–6545 https://doi.org/10.1109/TIE.2015.2422112
2	Qiao W, Lu D. A survey on wind turbine condition monitoring and fault diagnosis—Part II: Signals and signal processing methods. IEEE Transactions on Industrial Electronics, 2015, 62(10): 6546–6557 https://doi.org/10.1109/TIE.2015.2422394
3	Liu W, Tang B, Han J, et al. The structure healthy condition monitoring and fault diagnosis methods in wind turbines: A review. Renewable and Sustainable Energy Reviews, 2015, 44: 466–472 https://doi.org/10.1016/j.rser.2014.12.005
4	Mirafzal B. Survey of fault-tolerance techniques for three-phase voltage source inverters. IEEE Transactions on Industrial Electronics, 2014, 61(10): 5192–5202 https://doi.org/10.1109/TIE.2014.2301712
5	Machado de Azevedo H D, Araújo A M, Bouchonneau N. A review of wind turbine bearing condition monitoring: State of the art and challenges. Renewable and Sustainable Energy Reviews, 2016, 56: 368–379 https://doi.org/10.1016/j.rser.2015.11.032
6	Feng Y, Zhou J, Qiu Y, et al. Fault tolerance for wind turbine power converter. In: Proceedings of 2nd IET Renewable Power Generation Conference (RPG 2013). IET, 2013 https://doi.org/10.1049/cp.2013.1831
7	Qiu Y, Jiang H, Feng Y, et al. A new fault diagnosis algorithm for PMSG wind turbine power converters under variable wind speed conditions. Energies, 2016, 9(7): 548 https://doi.org/10.3390/en9070548
8	Tian Z, Jin T, Wu B, et al. Condition based maintenance optimization for wind power generation systems under continuous monitoring. Renewable Energy, 2011, 36(5): 1502–1509
9	Yang D, Li H, Hu Y, et al. Vibration condition monitoring system for wind turbine bearings based on noise suppression with multi-point data fusion. Renewable Energy, 2016, 92: 104–116 https://doi.org/10.1016/j.renene.2016.01.099
10	Cheng M, Zhu Y, The state of the art of wind energy conversion systems and technologies: A review. Energy Conversion and Management, 2014, 88: 332–347 https://doi.org/10.1016/j.enconman.2014.08.037
11	Nasiri M, Milimonfared J, Fathi S H. A review of low-voltage ride-through enhancement methods for permanent magnet synchronous generator based wind turbines. Renewable and Sustainable Energy Reviews, 2015, 47: 399–415 https://doi.org/10.1016/j.rser.2015.03.079
12	Thomson W T. On-line MCSA to diagnose shorted turns in low voltage stator windings of 3-phase induction motors prior to failure. In: Proceedings of the IEEE International Electric Machines and Drives Conference. IEEE, 2001, 891–898 https://doi.org/10.1109/IEMDC.2001.939425
13	Tallam R M, Habetler T G, Harley R G. Stator winding turn-fault detection for closed-loop induction motor drives. IEEE Transactions on Industry Applications, 2003, 39(3): 720–724 https://doi.org/10.1109/TIA.2003.811784
14	Nandi S, Toliyat H. Novel frequency-domain-based technique to detect stator interturn faults in induction machines using stator-induced voltages after switch-off. IEEE Transactions on Industry Applications, 2002, 38(1): 101–109 https://doi.org/10.1109/28.980363
15	Kliman G B, Premerlani W J, Koegl R A, et al.Sensitive on-line turn-to-turn fault detection in AC motors. Electric Machines and Power Systems, 2000, 28(10): 915–927 https://doi.org/10.1080/07313560050129800
16	Li H, Sun L, Xu B. Research on transient behaviors and detection methods of stator winding inter-turn short circuit fault in induction motors based on multi-loop mathematical model. In: Proceedings of International Conference on Electrical Machines and Systems. IEEE, 2005, 1951–1955 https://doi.org/10.1109/ICEMS.2005.202901
17	Joksimovic G M, Penman J. The detection of inter-turn short circuits in the stator windings of operating motors. IEEE Transactions on Industrial Electronics, 2000, 47(5): 1078–1084 https://doi.org/10.1109/41.873216
18	Cruz S M Z, Cardoso A J M. Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park’s vector approach. IEEE Transactions on Industry Applications, 2001, 37(5): 395–401 https://doi.org/10.1109/28.952496
19	Penman J, Sedding H G, Lloyd B A, et al. Detection and location of interturn short circuits in the stator windings of operating motors. IEEE Transactions on Energy Conversion, 1994, 9(4): 652–658 https://doi.org/10.1109/60.368345
20	Melero M G, Cabanas M F. Study of an induction motor working under stator winding inter-turn short circuit condition. In: Proceedings of 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives. Atlanta: IEEE, 2003, 423–429 https://doi.org/10.1109/DEMPED.2003.1234546
21	Henao H, Demian C, Capolino G A. A frequency-domain detection of stator winding faults in induction machines using an external flux sensor. IEEE Transactions on Industry Applications, 2003, 39(5): 1272–1279 https://doi.org/10.1109/TIA.2003.816531
22	Guo C, Zhang L, Wang Z. Fault diagnosis of AC motor on the vibrating spectral analysis. Oil Field Machinery, 2005, 34(4): 21–23 (in Chinese)
23	Cao C. Real-time detecting signal of motor vibration based on wavelet packet decomposition. Electric Machines and Control Applications, 2005, 32(8): 58–61 (in Chinese)
24	Amaral T G, Pires V F, Martins J F, et al. Statistic moment based method for the detection and diagnosis of induction motor stator fault. In: Proceedings of International Conference on Power Engineering. IEEE, 2007, 106–110 https://doi.org/10.1109/POWERENG.2007.4380151
25	Lee S B, Habetler T G, Harley R G, et al. An evaluation of model-based stator resistance estimation for induction motor stator winding temperature monitoring. IEEE Transactions on Energy Conversion, 1998, 4, 17(1): 7–15 https://doi.org/10.1109/60.986431
26	Lee S B, Habetler T G.An online stator winding resistance estimation technique for temperature monitoring of line-connected induction machines. IEEE Transactions on Industry Application, 2003, 4, 39(3): 685–694 https://doi.org/10.1109/TIA.2003.811789
27	Gao Z, Habetler T G, Harley R G, et al. A sensorless adaptive stator winding temperature estimator for mains-fed induction machines with continuous-operation periodic duty cycles. In: Proceedings of the IEEE Industry Applications Conference, 2006. 41st IAS Annual Meeting. IEEE, 2006, 448–455 https://doi.org/10.1109/IAS.2006.256559
28	Briz F, Degner M W, Guerrero J M, et al. Temperature estimation in inverter fed machines using high frequency carrier signal injection. IEEE Transactions on Industry Application, 2007, 799–808 https://doi.org/10.1109/TIA.2008.921380
29	Beguenane R,Benbouzid M E H.Induction motors thermal monitoring by means of rotor resistance identification. IEEE Transactions on Energy Conversion, 1999, 14(3): 566–570 https://doi.org/10.1109/60.790915
30	Grubic S, Aller J M, Lu B, et al. A survey on testing and monitoring methods for stator insulation systems of low-voltage induction machines focusing on turn insulation problems. IEEE Transactions on Industrial Electronics, 2008, 55(12): 4127–4136 https://doi.org/10.1109/TIE.2008.2004665
31	Stone G C. Advancements during the past quarter century in on-line monitoring of motor and generator winding insulation. IEEE Transactions on Dielectrics and Electrical Insulation, 2002, 9(5): 746–751 https://doi.org/10.1109/TDEI.2002.1038661
32	Stone G C, Boulter E A, Culbert I, et al. Electrical Insulation for Rotating Machines: Design, Evaluation, Aging, Testing, and Repair. New York: John Wiley & Sons, Inc., 2004
33	Tozzi M, Cavallini A, Montanari G C. Monitoring off-line and on-line PD under impulsive voltage on induction motors—Part 1: Standard procedure. IEEE Electrical Insulation Magazine, 2010, 26(4): 16–26 https://doi.org/10.1109/MEI.2010.5511185
34	Wang C, Wang Z, Li F, et al. Anti-interference techniques used for on-line partial discharge monitoring. In: Proceedings of International Conference on Properties and Application. 1994, 2: 582– 585 https://doi.org/10.1109/ICPADM.1994.414077
35	Li G, Yi K. Study on using thermal infrared imaging technology detecting the iron core faults of generator. Ningxia Electric Power, 2012, 12(6): 5–7
36	Posedel Z. Inspection of stator cores in large machines with a low yoke induction method-measurement and analysis of interlamination short-circuits. IEEE Transactions on Energy Conversion, 2001, 16(1): 81–86 https://doi.org/10.1109/60.911408
37	Sarikhani A, Mirafzal B, Mohammed O. Inter-turn fault diagnosis of PM synchronous generator for variable speed wind applications using floating-space-vector. In: Proceedings of IECON 2010— 36th Annual Conference on IEEE Industrial Electronics Society. IEEE, 2010, 2628–2633 https://doi.org/10.1109/IECON.2010.5675137
38	Ding F, Trutt F C. Calculation of frequency spectra of electromagnetic vibration for wound-rotor induction machines with winding faults. Electric Machines and Power Systems, 1988, 14(3–4): 137–150 https://doi.org/10.1080/07313568808909280
39	Hameed Z, Hong Y S, Cho Y M, et al. Condition monitoring and fault detection of wind turbines and related algorithms: A review. Renewable and Sustainable Energy Reviews, 2009, 13(1): 1–39 https://doi.org/10.1016/j.rser.2007.05.008
40	Zhang R, Wang X, Yang Y, et al. Based on the method of equivalent residual magnetism of permanent magnet motor rotor eccentricity magnetic field analytic calculation. Transactions of China Electrotechnical Society, 2009, 24(5): 7–12 (in Chinese)
41	Qiu Z, LiC, Zhou X, et al. Analytical calculation of no-load air-gap magnetic field in surface-mounted permanent magnet motors with rotor eccentricity. Transactions of China Electrotechnical Society, 2013, 28(3): 114–121 (in Chinese)
42	Tang R. Modern Permanent Magnet Machines Theory and Design. Beijing: China Machine Press, 2008, 18–21 (in Chinese)
43	Hao H, Chai J, Jiang Z, et al. Excitation loss in a Nd-Fe-B magnetic materials with alternating magnetic fields. Journal of Tsinghua University (Science and Technology), 2004, 44(6): 721–724 (in Chinese)
44	Xiao X, Zhang M, Li Y. On-line estimation of permanent-magnet flux linkage ripple for PMSM. Proceedings of the CSEE, 2007, 27(24): 142–146 (in Chinese)
45	Qi F. Magnetic stability of permanent magnet materials. Journal of magnetic Materials and Devices, 1998, 29(5): 26–31 (in Chinese)
46	von Staa F,Hempel K A, ArtzH. On the energy losses of hot worked Nd-Fe-B magnets and ferrites in a small alternating magnetic field perpendicular to a bias field. IEEE Transactions on Magnetics, 1995, 31(6): 3650–3652 https://doi.org/10.1109/20.489598
47	Xiao X, Zhang M, Li Y. Permanent magnet synchronous motor permanent magnet condition on-line monitoring. Proceedings of the CSEE, 2007, 27(24): 43–47 (in Chinese)
48	Shinnaka S. New “D-State-Observer”-based vector control for sensorless drive of permanent-magnet synchronous motors. IEEE Transactions on Industry Applications, 2005, 41(3): 825–833 https://doi.org/10.1109/TIA.2005.847282
49	Chen Z, Tomita M, Doki S, et al. An extended electromotive force model for sensorless control of Interior permanent-magnet synchronous motors. IEEE Transactions on Industrial Electronics, 2003, 50(2): 288–295 https://doi.org/10.1109/TIE.2003.809391
50	Eskola M, Tuusa H. Comparison of MRAS and novel simple method for position estimation in PMSM drives. In: Proceedings of IEEE 34th Annual Power Electronics Specialist Conference. Acapulco: IEEE, 2003 https://doi.org/10.1109/PESC.2003.1218115
51	Krishnan R, Vijayraghavan P. Fast estimation and compensation of rotor flux linkage in permanent magnet synchronous machines. In: Proceedings of the IEEE International Symposium on Industrial Electronics. IEEE, 1999 https://doi.org/10.1109/ISIE.1999.798691
52	Tchakoua P, Wamkeue R, Ouhrouche M, et al. Wind turbine condition monitoring: State-of-the-art review, new trends, and future challenges. Energies, 2014, 7(4): 2595–2630 https://doi.org/10.3390/en7042595
53	García Márquez F P, Tobias A M, Pinar Pérez J M, et al. Condition monitoring of wind turbines: Techniques and methods. Renewable Energy, 2012, 46(2): 169–178 https://doi.org/10.1016/j.renene.2012.03.003
54	Yang W, Tavner P J, Tian W. Wind turbine condition monitoring based on an improved spline-kernelled chirplet transform. IEEE Transactions on Industrial Electronics, 2015, 62(10): 6565–6574 https://doi.org/10.1109/TIE.2015.2458787
55	Astolfi D, Castellani F, Terzi L. Fault prevention and diagnosis through SCADA temperature data analysis of an onshore wind farm. Diagnostyka, 2014, 15(2): 71–78
56	Shahriar M R, Wang L, Kan M S, et al. Fault detection of wind turbine drivetrain utilizing power-speed characteristics. In: Amadi-Echendu J, Hoohlo C, Mathew J, eds. 9th WCEAM Research Papers. Lecture Notes in Mechanical Engineering. Cham: Springer, 2015, 143–155
57	Guo P, Infield D. Wind turbine tower vibration modeling and monitoring by the nonlinear state estimation technique (NSET). Energies, 2012, 5(12): 5279–5293 https://doi.org/10.3390/en5125279
58	Yang H, Mathew J, Ma L. Vibration feature extraction techniques for fault diagnosis of rotating machinery: A literature survey. In: Proceedings of Asia-Pacific Vibration Conference. Gold Coast, 2003
59	Hameed Z, Ahn S, Cho Y. Practical aspects of a condition monitoring system for a wind turbine with emphasis on its design, system architecture, testing and installation. Renewable Energy, 2010, 35(5): 879–894 https://doi.org/10.1016/j.renene.2009.10.031
60	Costinas S, Diaconescu I, Fagarasanu J. Wind power plant condition monitoring. In: Proceedings of the 3rd WSEAS International Conference on Energy Planning, Energy Saving, Environmental Education. Tenerife, 2009, 71–76
61	Rogers A L, Manwell J F, Wright S. Wind Turbine Acoustic Noise. White paper. 2002/2006
62	Salon S, Salem S, Sivasubramaniam K. Monitoring and diagnostic solutions for wind generators. In: Proceedings of IEEE Power and Energy Society General Meeting. IEEE, 2011 https://doi.org/10.1109/PES.2011.6039907
63	Niknam S A, Thomas T, Hines J W, et al. Analysis of acoustic emission data for bearings subject to unbalance. International Journal Prognostics and Health Management, 2013, 21(Suppl2): 1–10
64	Ma Y, He C, Feng X. Institutions function and failure statistic and analysis of wind turbine. Physics Procedia, 2012, 24(Part A): 25–30 https://doi.org/10.1016/j.phpro.2012.02.005
65	Yang W, Court R, Jiang J. Wind turbine condition monitoring by the approach of SCADA data. Renewable Energy. 2013, 53(9): 365–376 https://doi.org/10.1016/j.renene.2012.11.030
66	Patil N, Das D, Goebel K, et al. Identification of failure precursor parameters for insulated gate bipolar transistors (IGBTs). In: Proceedings of International Conference on Prognostics and Health Management. Denver: IEEE, 2008 https://doi.org/10.1109/PHM.2008.4711417
67	Yang L, Agyakwa P A, Johnson C M. A time-domain physics-of-failure model for the lifetime prediction of wire bond interconnects. Microelectronics and Reliability, 2011, 51(9–11): 1882–1886 https://doi.org/10.1016/j.microrel.2011.07.052
68	Li H, Liu S, Ran L, et al.Overview of condition monitoring technologies of power converter for high power grid-connected wind turbine generator system. Transactions of China Electrotechnical Society, 2016, 31(8): 1–10 (in Chinese)
69	Jabłoński A, Barszcz T, Bielecka M. Automatic validation of vibration signals in wind farm distributed monitoring systems. Measurement, 2011, 44(10): 1954–1967 https://doi.org/10.1016/j.measurement.2011.08.017
70	Liang Y, Fang R. An online wind turbine condition assessment method based on SCADA and support vector regression. Automation of Electric Power Systems, 2013, 37(14): 7–12 (in Chinese)
71	Guo P, Xu M, Bai N, et al. Wind turbine tower vibration modeling and monitoring driven by SCADA data. Proceedings of the CSEE, 2013, 33(5): 138–135 (in Chinese)
72	Dai J, Yuan X, Liu D, et al. Vibration analysis of large direct drive wind turbine nacelle based on SCADA system. Acta Energize Solaris Sinica, 2015, 36(12): 2895–2905
73	Isermann R. Model-based fault detection and diagnosis-status and applications. Annual Reviews in Control, 2004, 29(1): 71–85 https://doi.org/10.1016/j.arcontrol.2004.12.002
74	Mahyob P, Reghem P, Barakat G. Permeance network modeling of the stator winding faults in electrical machines. IEEE Transactions on Magnetics, 2009, 45(3): 1820–1823 https://doi.org/10.1109/TMAG.2009.2012780
75	Kim B W, Kim K T, Hur J. Simplified impedance modeling and analysis for inter-turn fault of IPM-type BLDC motor. Journal of Power Electronics, 2012, 12(1): 10–18
76	Yazidi A, Henao H, Capolino G. Double-fed three-phase induction machine model for simulation of inter-turn short circuit fault. In: Proceedings of IEEE International Electric Machines and Drives Conference. IEEE, 2009, 571–576 https://doi.org/10.1109/IEMDC.2009.5075263
77	Zhu D, Tan K. Present situation and prospects of condition monitoring and fault diagnosis technology for electrical equipments. Electrical Equipment, 2003, 4(6): 1–8 (in Chinese)
78	Widodo A, Yang B S, Gu D S, et al. Intelligent fault diagnosis system of induction motor based on transient current signal. Mechatronics, 2009, 19(5): 680–689 https://doi.org/10.1016/j.mechatronics.2009.02.002
79	Cusido J, Romeral L, Ortega J A,et al. Fault detection in induction machines using power spectral density in wavelet decomposition. IEEE Transactions on Industrial Electronics, 2008, 55(2): 633–643 https://doi.org/10.1109/TIE.2007.911960
80	Jung J H, Lee J J, Kwon B H. Online diagnosis of induction motors using MCSA. IEEE Transactions on Industrial Electronics, 2006, 53(6): 1842–1852 https://doi.org/10.1109/TIE.2006.885131
81	Cusido J, Rosero J A, Ortega J A, et al. Induction motor fault detection by using wavelet decomposition on dq0 components. In: Proceedings of IEEE International Symposiums on Industry Electronics. IEEE, 2006, 2406–2411 https://doi.org/10.1109/ISIE.2006.295949
82	Chetwani S H, Shah M K, Ramamoorty M. Online condition monitoring of induction motors through signal processing. In: Proceedings of 8th International Conference on Electrical Machines and Systems. IEEE, 2005, 2175–2179 https://doi.org/10.1109/ICEMS.2005.202952
83	Wu G. Theory and Practice of the State Monitoring of Motor Equipment. Beijing: Tsinghua University Press, 2005 (in Chinese)
84	Liu M, Cui S, GuoB. A method of failure recognition based on fuzzy C-means support vector machines for permanent magnetic DC motor. Micromotors, 2011, 44(10): 78–80 (in Chinese) https://doi.org/10.3969/j.issn.1001-6848.2011.10.020
85	Xu Y, Xu J, Guo X. Fuzzy diagnostic system for induction motor based on wavelet analysis and RBF neural network. Research and Exploration in Laboratory, 2012, 28(4): 282–301
86	Chen X. Fault diagnosis of electro-mechanical equipment based on noise signal processing. Machine Tool and Hydraulic, 2005, 65(12): 183–186 (in Chinese)
87	Tan Y, He Y, Cui C. A novel method for analog fault diagnosis based on neural networks and genetic algorithm. IEEE Transactions on Instrumentation and Measurement, 2008, 57(11): 2631–2639 https://doi.org/10.1109/TIM.2008.925009
88	Su H, Chong K T. Induction machine condition monitoring using neural network modeling. IEEE Transactions on Industrial Electronics, 2007, 54(1): 241–249 https://doi.org/10.1109/TIE.2006.888786
89	Valtierra-Rodriguez M, de Jesus Romero-Troncoso R, Osornio-Rios R A,et al. Detection and classification of single and combined power quality disturbances using neural networks. IEEE Transactions on Industrial Electronics, 2014, 61(5): 2473–2482 https://doi.org/10.1109/TIE.2013.2272276
90	Wang X, Kruger U, Irwin G W, et al. Nonlinear PCA with the local approach for diesel engine fault detection and diagnosis. IEEE Transactions on Control System Technology, 2008, 16(1): 122–129 https://doi.org/10.1109/TCST.2007.899744
91	Huang X, Wang J. The network generation technique of crack tracking. Journal of Shanghai Jiaotong University, 2001, 35(4): 493–495 (in Chinese)
92	Wang C, Zheng C. Semi-analytical finite element method for plane crack stress intensity factor. Engineering Mechanics, 2005, 22(1): 33–37 (in Chinese)
93	Yang T, Ren Y, Liu X, et al.Research on the modeling and simulation of wind turbine rotor imbalance fault. Journal of Mechanical Engineering, 2012, 48(6): 130–135 (in Chinese)
94	Jiang D. Huang Q, Hong L. Theoretical and experimental study on wind wheel unbalance for a wind turbine. In: Proceedings of World Non-Grid-Connected Wind Power and Energy Conference. IEEE, 2009 https://doi.org/10.1109/WNWEC.2009.5335787
95	Yuji T, Bouno T, Hamada T. Suggestion of temporarily for forecast diagnosis on blade of small wind turbine. IEEJ Transactions on Power and Energy, 2006, 126(7): 710–711 https://doi.org/10.1541/ieejpes.126.710
96	Bouno T, Yuji T, Hamada T, et al. Failure forecast diagnosis of small wind turbine using acoustic emission sensor. KIEE International Transaction on Electrical Machinery and Energy Conversion Systems, 2005, 5-B(1): 78–83
97	Qian Y, Ma H. A survey of fault diagnosis method for doubly-fed induction motor. Large electric Machine and Hydraulic Turbine, 2011, (5): 5–8 (in Chinese)
98	Le Roux W, Harley R G, Habetler T G. Detecting rotor faults in permanent magnet synchronous machines. In: Proceedings of 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronic Sand Drives. IEEE, 2003, 198–203 https://doi.org/10.1109/DEMPED.2003.1234573
99	Le Roux W, Harley R G, Habetler T G. Converter control effects on condition monitoring of rotor faults in permanent magnet synchronous machines. In: Proceedings of the Industry Applications Conference. 38th IAS Annual Meeting. IEEE, 2003, 1389–1396 https://doi.org/10.1109/IAS.2003.1257736
100	Rosero J, Romeral L, Ortega J A, et al.Demagnetization fault detection by means of Hilbert Huang transform of the stator current decomposition in PMSM. In: Proceedings of IEEE International Symposium on Industrial Electronics. IEEE, 2008, 172–177 https://doi.org/10.1109/ISIE.2008.4677217
101	Ruiz J R R, Rosero J A, Espinosa A G, et al. Detection of demagnetization faults in permanent-magnet synchronous motors under nonstationary conditions. IEEE Transactions on Magnetics, 2009, 45(7): 2961–2969 https://doi.org/10.1109/TMAG.2009.2015942
102	Rosero J A, Cusido J, Garcia A, et al. Study on the permanent magnet demagnetization fault in permanent magnet synchronous machines. In: Proceedings of 32nd Annual Conference of the IEEE Industrial Electronics. IEEE, 2006, 879–884 https://doi.org/10.1109/IECON.2006.347598
103	Farooq J, Srairi S, Djerdir A, et al. Use of permeance network method in the demagnetization phenomenon modeling in a permanent magnet. IEEE Transactions on Magnetics, 2006, 42(4): 1295–1298 https://doi.org/10.1109/TMAG.2006.870936
104	Wymore M L, Dam J E V, Ceylan H, et al. A survey of health monitoring systems for wind turbines. Renewable and Sustainable Energy Reviews, 2015, 52: 976–990 https://doi.org/10.1016/j.rser.2015.07.110
105	Jöckel S, Herrmann A, Rink J. High energy production plus built-in reliability—The VENSYS 70/77—New gearless wind turbines in the 1.5 MW class. Presentation in the Technical Track of the European Wind Energy Conference. 2006
106	Dubois M R, Polinder H, Ferreira J A. Generator topologies for direct-drive wind turbines, and adapted technology for turbines running in cold climate. In: Proceedings of Conference on Wind Energy in Cold Climates. Matane, 2001, 201–215
107	Dubois M R, Polinder H, Ferreira J A. Comparison of generator topologies for direct-drive wind turbines. In: Proceedings of Nordic Countries Power and Industrial Electronics Conference (NORPIE). Aalborg, 2000
108	Versteegh C J A. Design of the Zephyros Z72 wind turbine with emphasis on the direct drive PM generator. In: Proceedings of Nordic Countries Power and Industrial Electronics Conference (NORPIE). Trondheim, 2004
109	An X, Jiang D. Chaotic characteristics identification and trend prediction of running state for wind turbine. Electric Power Automation Equipment, 2010, 30(3): 15–19, 24 (in Chinese)
110	An X, Jiang D, Liu S, et al. Correlation analysis of oil temperature trend for wind turbine gearbox. In: Proceedings of the ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3. Montreal, 2010
111	ZhangY, WuW, Wu L.Motor mechanical fault diagnosis based on wavelet packet, Shannon entropy, SVM and GA. Electric Power Automation Equipment, 2010, 30(1): 87–91 (in Chinese)
112	Gu Y, Zhao W, Wu Z. Combustion optimization for utility boiler based on least square-support vector machine. Proceedings of the CSEE, 2010, 30(17): 91–97 (in Chinese)
113	Zhao M. Fault Feature Analysis and Experimental Investigation for Wind Turbine. Beijing: Tsinghua University Press, 2010 (in Chinese)
114	Barszcz T. Application of diagnostic algorithms for wind turbines. Diagnostyka, 2009, 50(2): 7–12
115	Wu Z, Huang N, Long S, et al. On the trend, trending, and variability of nonlinear and nonstationary time series. Proceedings of the National Academy of Sciences of the United States of America, 2007, 104(38): 14889–14894 https://doi.org/10.1073/pnas.0701020104
116	Pierre Tchakoua, René Wamkeue, Tommy Andy Tameghe, et al. A review of concepts and methods for wind turbines condition monitoring. In: Proceedings of 2013 World Congress on Computer and Information Technology (WCCIT). 2013 https://doi.org/10.1109/WCCIT.2013.6618706
117	Izelu C O, Oghenevwaire I S. A review on developments in the design and analysis wind turbine drive train. In: Proceedings of International Conference on Renewable Energy Research and Applications. IEEE, 2014, 589–594 https://doi.org/10.1109/ICRERA.2014.7016452
118	Estima J O, Cardoso A J M. Fast fault detection, isolation and reconfiguration in fault-tolerant permanent magnet synchronous motor drives. In: Proceedings of IEEE Energy Convers. 2012, 3617–3624
119	Lu B, Sharma S K. A literature review of IGBT fault diagnostic and protection methods for power inverters. IEEE Transactions on Industry Applications, 2009, 45(5): 1770–1777 https://doi.org/10.1109/TIA.2009.2027535
120	de Araujo Ribeiro R L, Jacobina C B, da Silva E R C, et al. Fault detection of open-switch damage in voltage-fed PWM motor drive systems. IEEE Transactions on Power Electronics, 2003, 18(2): 587–593 https://doi.org/10.1109/TPEL.2003.809351
121	Khomfoi S, Tolbert L M. Fault diagnostic system for a multilevel inverter using a neural network. IEEE Transactions on Power Electronics, 2007, 22(3): 1062–1069 https://doi.org/10.1109/TPEL.2007.897128
122	Tavnet P J, Van Bussel G J W, Spinato F. Machine and converter reliabilities in wind turbines. In: Proceedings of 3rd IET International Conference on Power electronics, Machines and Drives. Dublin: IET, 2006, 127–130
123	Jlassi I, Estima J O, Khojet El Khil S, et al. Multiple open-circuit faults diagnosis in back-to-back converters of PMSG drives for wind turbine systems. IEEE Transactions on Power Electronics, 2015, 30(5): 2689–2702 https://doi.org/10.1109/TPEL.2014.2342506
124	Choi U M, Jeong H G, Lee K B, et al. Method for detecting an open-switch fault in a grid-connected NPC inverter system. IEEE Transactions on Power Electronics, 2012, 27(6): 2726–2739 https://doi.org/10.1109/TPEL.2011.2178435
125	Freire N M A, Estima J O, Marques Cardoso A J. Open-circuit fault diagnosis in PMSG drives for wind turbine applications. IEEE Transactions on Industrial Electronics, 2013, 60(9): 3957–3967 https://doi.org/10.1109/TIE.2012.2207655
126	Fang Z P. Z-source inverter. IEEE Transactions on Industry Applications, 2003, 39(2): 504–510 https://doi.org/10.1109/TIA.2003.808920
127	Faulstich S, Hahn B, Tavner P J. Wind turbine downtime and its importance for offshore deployment. Wind Energy (Chichester, England), 2011, 14(3): 327–337 https://doi.org/10.1002/we.421
128	Gao Z, Cecati C, Ding S X. A survey of fault diagnosis and fault-tolerant techniques—Part I: Fault diagnosis with model-based and signal-based approaches. IEEE Transactions on Industrial Electronics, 2015, 62(6): 3757–3767 https://doi.org/10.1109/TIE.2015.2417501
129	Gao Z, Cecati C, Ding S X. A survey of fault diagnosis and fault-tolerant techniques—Part II: Fault diagnosis with knowledge-based and hybrid/active approaches. IEEE Transactions on Industrial Electronics, 2015, 62(6): 3768–3774 https://doi.org/10.1109/TIE.2015.2417501
130	Schulte H, Gauterin E. Fault-tolerant control of wind turbines with hydrostatic trans-mission using Takagi-Sugeno and sliding mode techniques. Annual Reviews in Control, 2015, 40(17): 82–92 https://doi.org/10.1016/j.arcontrol.2015.08.003
131	Corradini M L, Ippoliti G, Orlando G. Sensorless efficient fault-tolerant control of wind turbines with geared generator. Automatica, 2015, 62(11): 161–167 https://doi.org/10.1016/j.automatica.2015.09.024
132	Guan H, Zhao H, Wang W, et al.LVRT capability of wind turbine generator and its application. Transactions of China Electrotechnical Society, 2007, 22(10): 173–177 (in Chinese)
133	Hu S, Li J, XuH. Modeling on converters of direct-driven wind power system and its performance during voltage sags. High Voltage Engineering, 2008, 34(5): 949–954 (in Chinese)
134	Freitas W, Morelato A, Xu W. Improvement of induction generator stability using braking resistors. IEEE Transactions on Power Systems, 2004, 19(2): 1247–1249 https://doi.org/10.1109/TPWRS.2004.825929
135	Causebrook A, Atkinson D J, Jack A G. Fault ride-through of large wind farms using series dynamic braking resistors. IEEE Transactions on Power Systems, 2007, 22(3): 966–975 https://doi.org/10.1109/TPWRS.2007.901658
136	Fatu M, Lascu C, Andreescu G D, et al. Voltage sags ride-through of motion sensorless controlled PMSG for wind turbines. In: Proceedings of IEEE Industry Applications Conference. 42nd IAS Annual Meeting. IEEE, 2007, 171–178 https://doi.org/10.1109/07IAS.2007.74
137	Li J, Hu S, Kong D, et al. Studies on the low voltage ride through capability of fully converted wind turbine with PMSG. Automation of Electric Power Systems, 2008, 32(19): 92–95 (in chinese)
138	Li H, Dong S, Wang Y, et al.Coordinated control of active and reactive power of PMSG-based wind turbines for low voltage ride through. Transactions of China Electrotechnical Society, 2013, 28(5): 73–81 (in Chinese)
139	Schulte H, Gauterin E. Fault-tolerant control of wind turbines with hydrostatic transmission using Takagi-Sugeno and sliding mode techniques. Annual Reviews in Control, 2015, 40: 82–92 https://doi.org/10.1016/j.arcontrol.2015.08.003
140	Zhang Z, Xu J, Liu X. Research on the high performance flux-weakening control strategy of permanent magnetic synchronous generator for wind turbine. High Power Converter Technology, 2013, 27(3): 62–65 (in Chinese)
141	Chai F, Bi Y. Research review of flux-weakening methods of axial flux permanent magnet synchronous machine. Micromotors, 2015, (2): 70–76 (in Chinese)
142	Li Z, Li Y, Li X. Flux-weakening control of consequent-pole permanent magnet machines. Proceedings of the CSEE, 2013, (21): 124–131 (in Chinese)
143	Parsa L, Toliyat H. Multi-phase permanent-magnet motor drives. IEEE Transactions on Industry Applications, 2005, 41(1): 30–37 https://doi.org/10.1109/TIA.2004.841021
144	Fu J R, Lipo T A. Disturbance-free operation of a multiphase current-regulated motor drive with an opened phase. IEEE Transactions on Industry Applications, 1994, 30(5): 1267–1274 https://doi.org/10.1109/28.315238
145	Toliyat H A. Analysis and simulation of five-phase variable speed induction motor drives under asymmetrical connections. IEEE Transactions on Power Electronics, 1998, 13(4): 748–756 https://doi.org/10.1109/63.704150
146	Dwari S, Parsa L. Fault-tolerant control of five-phase permanent-magnet motors with trapezoidal back EMF. IEEE Transactions on Industrial Electronics, 2011, 58(2): 476–485 https://doi.org/10.1109/TIE.2010.2045322
147	Liu T H, Fu J R, Lipo T A. A strategy for improving reliability of field oriented controlled induction motor drives. IEEE Transactions on Industry Applications, 1993, 29(5): 910–918 https://doi.org/10.1109/28.245714
148	Sinha G, Hochgraf C, Lasseter R H, et al. Fault protection in a multilevel inverter implementation of a static condenser. In: Proceedings of IEEE Industry Applications Conference. Thirtieth IAS Annual Meeting. IEEE, 1995, 2557–2564 https://doi.org/10.1109/IAS.1995.530628
149	Bianchi N, Bolognani S, Zigliotto M, et al. Innovative remedial strategies for inverter faults in IPM synchronous motor drives. IEEE Transactions on Energy Conversion, 2003, 18(2): 306–314 https://doi.org/10.1109/TEC.2002.808334
150	Athulya Justin, Reshma S. Fault tolerant control of wind energy conversion system—Fuzzy approach. In: Proceedings of the Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT). Acapulco: IEEE, 2013 https://doi.org/10.1109/ICCCNT.2013.6726761
151	de Araujo Ribeiro R L, Jacobina C B, da Silva E R C, et al. Fault-tolerant voltage-fed PWM inverter AC motor drive systems. IEEE Transactions on Industrial Electronics, 2004, 51(2): 439–446 https://doi.org/10.1109/TIE.2004.825284
152	Welchko B A, Lipo T A, Jahns T M, et al. Fault tolerant three-phase AC motor drive topologies: A comparison of features, cost, limitations. IEEE Transactions on Power Electronics, 2004, 19(4): 1108–1116 https://doi.org/10.1109/TPEL.2004.830074
153	Tiegna H, Amara Y, Barakat G, et al. Overview of high power wind turbine generators. In: Proceedings of International Conference on Renewable Energy Research and Applications (ICRERA). IEEE, 2012 https://doi.org/10.1109/ICRERA.2012.6477341
154	Chowdhury M M, Haque M E, Aktarujjaman M, et al. Grid integration impacts and energy storage systems for wind energy applications—A review. In: Proceedings of IEEE Power and Energy Society General Meeting. IEEE, 2011 https://doi.org/10.1109/PES.2011.6039798
155	Polinder H, Ferreira J A, Jensen B B, et al. Trends in wind turbine generator systems. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2013, 1(3): 174–185 https://doi.org/10.1109/JESTPE.2013.2280428
156	Huang S, Gao J. The Design and Grid-Connected Control of Direct-Drive Permanent Magnet Wind Turbine. Beijing: Publishing House of Electronics Industry, 2015, 15–19 (in Chinese)
157	Alepuz S, Calle A, Busquets-Monge S, et al. Use of stored energy in PMSG rotor inertia for low-voltage ride-through in back-to-back NPC converter-based wind power systems. IEEE Transactions on Industrial Electronics, 2013, 60(5): 1787–1796
158	Scarcella G, Scelba G, Pulvirenti M, et al. A fault-tolerant power conversion topology for PMSG based wind power systems. In: Proceedings of International Conference on Electrical Machines (ICEM). IEEE, 2014 https://doi.org/10.1109/ICELMACH.2014.6960410
159	YangZ, Chai Y. A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems. Renewable and Sustainable Energy Reviews, 2016, 66: 345–359 https://doi.org/10.1016/j.rser.2016.08.006
160	Huang S, Wang H, Liao W, et al. The coordinated control strategy based on VSC-HVDC series-parallel topology in wind farm. Transactions of China Electrotechnical Society, 2015, 30(23): 155–162 (in Chinese)
161	Huang S, Wang H, Liao W, et al. Control strategy based on VSC-HVDC series topology offshore wind farm for low voltage ride through. Transactions of China Electrotechnical Society, 2015, 30(14): 362–369 (in Chinese)
162	Arani M F M, Mohamed Y A R I. Assessment and enhancement of a full-scale PMSG-based wind power generator performance under faults. IEEE Transactions on Energy Conversion, 2016, 31(2): 728–739 https://doi.org/10.1109/TEC.2016.2526618
163	Zmood D N, Holmes D G. Stationary frame current regulation of PWM inverters with zero steady-state error. IEEE Transactions on Power Electronics, 2003, 18(3): 814–822 https://doi.org/10.1109/TPEL.2003.810852
164	Nian H, Cheng P. Resonant based direct power control strategy for PWM rectifier under unbalanced grid voltage condition. Transactions of China Electrotechnical Society, 2013, 28(11): 86–94 (in Chinese)
165	Huang S, Xiao L, Huang K, et al.DC voltage stability of directly-driven wind turbine with PM synchronous generator during the asymmetrical faults. Transactions of China Electrotechnical Society, 2010, 25(7): 123–129 (in Chinese)
166	Huang S, Xiao L, Huang K, et al.Operation and control on the grid-side converter of the directly-driven wind turbine with PM synchronous generator during asymmetrical faults. Transactions of China Electrotechnical Society, 2011, 26(2): 173–180 (in Chinese)
167	Xiao L, Huang S, Lu K. DC-bus voltage control of grid-connected voltage source converter by using space vector modulated direct power control under unbalanced network conditions. IET Power Electronics, 2013, 6(5): 925–934 https://doi.org/10.1049/iet-pel.2012.0576
168	Hasegawa N, Kumano T. Low voltage ride-through capability improvement of wind power generation using dynamic voltage restorer. In: Proceedings of the 5th IASME/WSEAS International Conference on Energy and Environment. 2010, 166–171
169	Wang L, Truong D N. Dynamic stability improvement of four parallel-operated PMSG-based off shore wind turbine generators fed to a power system using a STATCOM. IEEE Transactions on Power Delivery, 2013, 28(1): 111–119 https://doi.org/10.1109/TPWRD.2012.2222937

Viewed

Full text

Abstract

Cited

Shared

Discussed