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A fault monitoring method for wind power generation system based on sliding mode observer

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, a rotor current fault monitoring method is proposed based on a sliding mode observer. Firstly, the state-space model of the Double-Fed Induction Generator (DFIG) is constructed by vector transformation. Meanwhile, the stator voltage orientation vector control method is applied to decouple a stator and rotor currents, so as to obtain the correlation between the stator and rotor current. Furthermore, the mathematical model of stator voltage orientation is obtained. Then a state sliding mode observer (SMO) is established for the output current of the rotor of the DFIG. The stability and reachability of the system in a limited time is proved. Finally, the system state is determined by the residuals of the measured and estimated rotor currents. The simulation results show that the method proposed in this paper can effectively monitor the status: a normal state, voltage drop faults, short-circuit faults between windings, and rotor current sensor faults which have the advantages of fast response, high stability.
Rocznik
Strony
625--643
Opis fizyczny
Bibliogr. 23 poz., rys., tab., wz.
Twórcy
autor
  • College of Electrical and Information Engineering, Hunan University Hunan Province, Changsha, 410082, China
  • School of Information and Electrical Engineering Hunan University of Science and Technology Hunan Province, Xiangtan, 411201, China
  • College of Electrical and Information Engineering, Hunan University Hunan Province, Changsha, 410082, China
autor
  • School of Information and Electrical Engineering Hunan University of Science and Technology Hunan Province, Xiangtan, 411201, China
Bibliografia
  • [1] Xue Z.Y., Xiahou K.S., Li M.S., Ji T.Y., Wu Q.H., Diagnosis of Multiple Open-Circuit Switch Faults Based on Long Short-Term Memory Network for DFIG-based Wind Turbine Systems, IEEE Journal of Emerging and Selected Topics in Power Electronics, p. 1 (2019).
  • [2] Lopez J., Sanchis P., Roboam X., Marroyo L., Dynamic Behavior of the Doubly Fed Induction Generator During Three-Phase Voltage Dips, IEEE Transactions on Energy Conversion, vol. 22, no. 3, pp. 709–717 (2007).
  • [3] Lopez J., GubÍa E., Sanchis P. et al., Wind Turbines Based on Doubly Fed Induction Generator Under Asymmetrical Voltage Dips, IEEE Transactions on Energy Conversion, vol. 23, no. 1, pp. 321–330 (2008).
  • [4] Ouyang J.X., Xiong X.F., Zhang H.Y., Characteristics of DFIG-based wind generation under grid short circuit, Proceedings of the CSEE, vol. 31, no. 22, pp. 17–25 (2011).
  • [5] Jiang S.D., Liu J., Passive control of doubly-fed wind turbines under grid voltage drop failure, Systems Engineering – Theory and Practice, vol. 34, no. 2, pp. 478–484 (2014).
  • [6] Ma J., Liu Q., Wu J.F., Sun F.Q., Wang Y. et al., Flexible power control of rotor-side converter for doubly-fed induction generator under unbalanced voltage, Electric Power Automation Equipment, vol. 39, no. 2, pp. 196–203 (2019).
  • [7] Shah D., Nandi S., Neti P., Stator Inter-Turn Fault Detection of Doubly-Fed Induction Generators Using Rotor Current and Search Coil Voltage Signature Analysis, IEEE Industry Applications Annual Meeting, vol. 34, no. 2, pp. 478–484 (2014).
  • [8] Ma H.Z., Zhang Z.D., Ju P. et al., Doubly-fed induction generator stator fault diagnosis based on rotor instantaneous power spectrum, IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) (2015), DOI: 10.1109/DEMPED.2015.7303685.
  • [9] Mohammad Yousefi Kia, Mostafa Khedri et al., Hybrid modelling of doubly fed induction generators with inter-turn stator fault and its detection method using wavelet analysis, IET Generation, Transmission and Distribution, vol. 9, no. 7, pp. 982–990 (2013).
  • [10] Xue Z.Y., Xiahou K.S., Li M.S., Ji T.Y., Wu Q.H., Diagnosis of Multiple Open-Circuit Switch Faults Based on Long Short-Term Memory Network for DFIG-based Wind Turbine Systems, IEEE Journal of Emerging and Selected Topics in Power Electronics (2019), DOI: 10.1109/JESTPE.2019.2908981.
  • [11] Wei Xiukun, Verhaegen M., Engelen T.V., Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques, International Journal of Adaptive Control and Signal Processing, vol. 24, no. 8, pp. 687–707 (2018).
  • [12] Wei X., Verhaegen M., Sensor and actuator fault diagnosis for wind turbine systems by using robust observer and filter, Wind Energy, vol. 14, no. 4, pp. 491–516 (2011).
  • [13] Ouyessaad H., Chafouk H., Lefebvre D., Fault sensor diagnosis with Takagi–Sugeno approach design applied for DFIG wind energy systems, International Conference on Systems and Control, IEEE (2013), DOI: 10.1109/ICoSC.2013.6750835.
  • [14] Shen Y.X., Yang X.F., Zhao Z.P., Sensor fault diagnosis for wind turbine system, Control Theory and Applications, vol. 31, no. 3, pp. 321–328 (2017).
  • [15] Wei S.R., Li Z.M., Fu Y. et al., Fault Diagnosis of Interturn Short Circuit in Stator Windings of Offshore Doubly-Fed Machines Considering the Difference of Current Estimation, Proceedings of the CSEE, vol. 38. no. 13, pp. 3169–3977 (2018).
  • [16] Lan Z.Y., Li L., Deng C., Zhang Y.Z., Yu W.X., Wong P., A Novel Stator Current Observer for Fault Tolerant Control of Stator Current Sensor in DFIG, 2018 IEEE Energy Conversion Congress and Exposition (ECCE) (2018), DOI: 10.1109/ECCE.2018.8557929.
  • [17] Drid S., Tadjine M., Nait-Said M.S., Robust backstepping vector control for the doubly fed induction motor, IET Control Theory and Applications, vol. 1, no. 4, pp. 861–868 (2007).
  • [18] Reigosa D.D., Guerrero J.M., Diez A.B., Briz F., Rotor Temperature Estimation in Doubly-Fed Induction Machines Using Rotating High-Frequency Signal Injection, IEEE Transactions on Industry Applications, vol. 53, no. 4, pp. 3652–3662 (2017).
  • [19] Mojallal A., Lotfifard S., DFIG Wind Generators Fault Diagnosis Considering Parameter and Measurement Uncertainties, IEEE Transactions on Sustainable Energy, vol. 9, no. 4, pp. 792–804 (2018).
  • [20] Abdelmalek S., Azar A.T., Dib D., A Novel Actuator Fault-tolerant Control Strategy of DFIG-based Wind Turbines Using Takagi–Sugeno Multiple Models, International Journal of Control Automation and Systems, pp. 1415–1424 (2018).
  • [21] Li Y., Ma L., Fault diagnosis of power transformer based on improved particle swarm optimization OS-ELM, Archives of Electrical Engineering, vol. 68, no. 1, pp. 161–172 (2019).
  • [22] Artigao E., Honrubia-Escribano A., Gomez E.,In-Service Wind Turbine DFIG Diagnosis using Current Signature Analysis, IEEE Transactions on Industrial Electronics, vol. 67, no. 3, pp. 2262–2271 (2020).
  • [23] Li W., Li Q., Sliding mode reaching laws for suppressing chattering, Proceeding of the 27th Chinese Control Conference, Kunming, China, pp. 154–158 (2008).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a91cff5b-e5f2-4e59-9377-590fde2e519d
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