A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 6 Issue 5
Sep.  2019

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 6.171, Top 11% (SCI Q1)
    CiteScore: 11.2, Top 5% (Q1)
    Google Scholar h5-index: 51, TOP 8
Turn off MathJax
Article Contents
J. S. Solís-Chaves, Lucas L. Rodrigues, C. M. Rocha-Osorio and Alfeu J. Sguarezi Filho, "A Long-Range Generalized Predictive Control Algorithm for a DFIG Based Wind Energy System," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1209-1219, Sept. 2019. doi: 10.1109/JAS.2019.1911699
Citation: J. S. Solís-Chaves, Lucas L. Rodrigues, C. M. Rocha-Osorio and Alfeu J. Sguarezi Filho, "A Long-Range Generalized Predictive Control Algorithm for a DFIG Based Wind Energy System," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1209-1219, Sept. 2019. doi: 10.1109/JAS.2019.1911699

A Long-Range Generalized Predictive Control Algorithm for a DFIG Based Wind Energy System

doi: 10.1109/JAS.2019.1911699
Funds:  This work was supported by UFABC, CNPQ and CAPES
More Information
  • This paper presents a new Long-range generalized predictive controller in the synchronous reference frame for a wind energy system doubly-fed induction generator based. This controller uses the state space equations that consider the rotor current and voltage as state and control variables, to execute the predictive control action. Therefore, the model of the plant must be transformed into two discrete transference functions, by means of an auto-regressive moving average model, in order to attain a discrete and decoupled controller, which makes it possible to treat it as two independent single-input single-output systems instead of a magnetic coupled multiple-input multiple-output system. For achieving that, a direct power control strategy is used, based on the past and future rotor currents and voltages estimation. The algorithm evaluates the rotor current predictors for a defined prediction horizon and computes the new rotor voltages that must be injected to controlling the stator active and reactive powers. To evaluate the controller performance, some simulations were made using Matlab/Simulink. Experimental tests were carried out with a small-scale prototype assuming normal operating conditions with constant and variable wind speed profiles. Finally, some conclusions respect to the dynamic performance of this new contro-ller are summarized.

     

  • loading
  • [1]
    GWEC, " Global wind report - annual market update 2017, ” Tech. Rep., Global Wind Energy Council, 2018.
    [2]
    GWEC, " Wind power is crucial for combating climate change., ” Tech. Rep., Global Wind Energy Council, 2008.
    [3]
    W. Cao, Y. Xie, and Z. Tan, Wind Turbine Generator Technologies. INTECH Open Access Publisher, 2012.
    [4]
    F. Blaabjerg and K. Ma, " Future on power electronics for wind turbine systems,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 1, no. 3, pp. 139–152, 2013. doi: 10.1109/JESTPE.2013.2275978
    [5]
    R. Datta and V. T. Ranganathan, " Variable-Speed wind power generation using a doubly fed wound rotor induction machine: a comparison with alternative schemes,” IEEE Power Engineering Review, vol. 22, pp. 52, July. 2002.
    [6]
    F. Blaabjerg and K. Ma, " Wind energy systems,” in Proc. of the IEEE , 2017. doi: 10.1109/J.PROC.2017.2695485
    [7]
    J. A. Baroudi, V. Dinavahi, and A. M. Knight, " A review of power converter topologies for wind generators,” Renewable Energy, vol. 32, no. 14, pp. 2369–2385, 2007. doi: 10.1016/j.renene.2006.12.002
    [8]
    D. W. Clarke, C. Mohtadi, and P. Tuffs, " Generalized predictive control part I. the basic algorithm,” Automatica, vol. 23, no. 2, pp. 137–148, 1987. doi: 10.1016/0005-1098(87)90087-2
    [9]
    D. Clarke, C. Mohtadi, and P. Tuffs, " Generalized predictive control part II. extension and interpretations,” Automatica, vol. 23, no. 2, pp. 149–160, 1987. doi: 10.1016/0005-1098(87)90088-4
    [10]
    D. W. Clarke and C. Mohtadi, " Properties of generalized predictive control,” Automatica, vol. 25, no. 6, pp. 859–875, 1989. doi: 10.1016/0005-1098(89)90053-8
    [11]
    L. Zhang, R. Norman, and W. Shepherd, " Long-Range predictive control of current regulated PWM for induction motor drives using the synchronous reference frame,” IEEE Transactions on Control Systems Technology, vol. 5, no. 1, pp. 119–126, 1996.
    [12]
    R. Kennel, A. Linder, and M. Linke, " Generalized predictive control (GPC)-ready for use in drive applications, ” in Proc. PESC. IEEE 32nd Annual Power Electronics Specialists Conf. , vol. 4, pp. 1839–1844, 2001.
    [13]
    S. Vazquez, J. Rodriguez, M. Rivera, L. G. Franquelo, and M. Norambuena, " Model predictive control for power converters and drives: advances and trends, ” IEEE Transactions on Industrial Electronics, vol. 64. pp. 935-947, Feb. 2017.
    [14]
    M. S. Mahmoud and M. O. Oyedeji, " Adaptive and predictive control strategies for wind turbine systems: a survey,” IEEE/CAA Journal of Automatica Sinica, vol. 6, pp. 364–378, March. 2019. doi: 10.1109/JAS.6570654
    [15]
    A. Linder, R. Kanchan, R. Kennel, and P. Stolze, Model-Based Predictive Control of Electric Drives. Cuvillier, 2010.
    [16]
    M. A. Bouzid, A. Massoum and S. Zine, " Generalized predictive control of standalone wind energy generation system,” International Journal of Renewable Energy Research, vol. 6, no. 1, pp. 220–228, Feb. 2016.
    [17]
    Z. Zhang, F. G. Hui Fang, J. Rodrguez, and R. Kennel, " Multiple-Vector model predictive power control for grid-tied wind turbine system with enhanced steady-state control performance, ” IEEE Transactions On Industrial Electronics, vol. 64, pp. 6287–6298, Aug. 2017.
    [18]
    D. D. Rú, M. Morandin, S. Bolognani, and M. Castiello, " Model predictive hysteresis current control for wide speed operation of a synchronous reluctance machine drive, ” Industrial Electronics Society, IEEE, pp. 2845–2850, Oct. 2016.
    [19]
    S. V. Dias, W. A. da Silva, L. L. dos Reis, and J. C. T. Campos, " Robust generalized predictive control applied to the rotor side converter of a wind power generator system based on DFIG, ” in Proc. 11th IEEE/IAS Int. Conf. on Industry Applications (INDUSCON), pp. 1-6, IEEE, 2014.
    [20]
    P. Kou, D. Liang, J. Li, L. Gao, and Q. Ze, " Finite-Control-Set model predictive control for DFIG wind turbines,” IEEE Transactions on Automation Science and Engineering, 2017.
    [21]
    S. Sui, C. L. P. Chen, and S. Tong, " Fuzzy adaptive finite-time control design for nontriangular stochastic nonlinear systems,” IEEE Transactions on Fuzzy Systems, vol. 27, pp. 172–184, Jan. 2019. doi: 10.1109/TFUZZ.2018.2882167
    [22]
    S. Sui, S. Tong, and C. L. P. Chen, " Finite-Time filter decentralized control for nonstrict-feedback nonlinear large-scale systems,” IEEE Transactions on Fuzzy Systems, vol. 26, pp. 3289–3300, Dec. 2018. doi: 10.1109/TFUZZ.2018.2821629
    [23]
    A. L. L. F. Murari, J. A. T. Altuna, R. V. Jacomini, C. M. Rocha-Osorio, J. S. Solís-Chaves, and A. J. S. Filho, " A proposal of project of PI controller gains used on the control of doubly-fed induction generators,” IEEE Latin America Transactions, vol. 15, pp. 173–180, Feb. 2017. doi: 10.1109/TLA.2017.7854609
    [24]
    C. Rocha-Osorio, J. S. Solís-Chaves, I. R. Casella, C. Capovilla, J. A. Puma, and A. S. Filho, " GPRS/EGPRS standards applied to DTC of a DFIG using fuzzy PI controllers,” International Journal of Electrical Power &Energy Systems, vol. 93, pp. 365–373, 2017.
    [25]
    C. M. Rocha-Osorio, J. S. Solís-Chaves, L. L. Rodrigues, J. A. Puma, and A. S. Filho, " Deadbeat fuzzy controller for the power control of a doubly fed induction generator based wind power system,” ISA Transactions, vol. 88, pp. 258–267, 2019. doi: 10.1016/j.isatra.2018.11.038
    [26]
    L. L. Rodrigues, O. A. C. Vilcanqui, A. L. L. F. Murari, and A. J. S. Filho, " Predictive power control for DFIG: a fare-based weighting matrices approach,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, pp. 967–975, June. 2019. doi: 10.1109/JESTPE.6245517
    [27]
    G. Abad, J. López, M. Rodríguez, L. Marroyo, and G. Iwanski, Dynamic Modeling of the Doubly Fed Induction Machine, pp. 209–239. Wiley IEEE Press, 2011.
    [28]
    A. J. S. Filho, A. L. L. F. Murari, a nd, et al, " A state feedback DFIG power control for wind generation,” Eletrônica de Potência - SOBRAEP, vol. 20, pp. 151–159, March. 2015. doi: 10.18618/REP
    [29]
    A. L. L. F. Murari, " Proposta de projeto de ganhos de controladores pi empregados no controle de geradores de indução com rotor bobinado aplicados a sistemas eólicos, ” M.S. thesis, UFABC, Santo André, SP, Brazil, 2015.
    [30]
    D. R. David, " Model predictive control with integral action: a simple mpc algorithm, ” Modeling, Identification and Control, vol. 34, pp. 119– 129, 2013.
    [31]
    I. Dogan., Microcontroller Based Applied Digital Control. John Wiley & Sons, Ltd., 2006.
    [32]
    " IEEE standard test procedure for polyphase induction motors and generators, ” IEEE Std 112-2017(Revision of IEEE Std 112-2004), pp. 1-115, Feb. 2018.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(17)  / Tables(1)

    Article Metrics

    Article views (1807) PDF downloads(71) Cited by()

    Highlights

    • A new DFIG model based on the CARIMA model is presented in this paper.
    • A new digital long-range controller based on the generalized predictive control (GPC) theory for the doubly-fed induction generator (DFIG) based Wind Energy System, is presented.
    • The new GPC developed here was compared via Simulink simulation, with a classical PI controller to evaluate its dynamic response and thus confirm its superior performance.
    • A remarkable advantage for this GPC is that a single weighting factor adjustment is needed for the algorithm in counter-position with other nonlinear controllers.
    • This new long-range GPC was tested under normal operating conditions in a small scale prototype considering constant and variable wind speed profiles with faster dynamic and performance results.
    • A DFIG’s parameter variation test was done to probe the better dynamic response for this GPC algorithm.

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return