Abstract
Wind Energy Conversion System (WECS) using a Doubly Fed Induction Generator (DFIG) is popular due to its control flexibility and higher conversion efficiency, but maintaining the operational stability and optimal efficiency under dynamic wind conditions is still a control challenge. In this paper, a nonlinear mathematical model for a DFIG based WECS was developed from fundamentals and its characteristics near the operating point were studied. A Proportional Integral (PI) controller and a Linear Quadratic Regulator (LQR) controller were designed to control the system and the behavior of the closed-loop system with these controllers was studied. While the designed PI controller failed to ensure stability, the LQR controller was giving stability but an LQR controller is vulnerable to loss of stability under uncertainties due to parameter variations or changes in operating points. A suboptimal \(H_{\infty }\) controller was then synthesized to obtain robust control. The closed-loop system performance of the DFIG system with the proposed controller was found to be stable and superior to PI and LQR controllers in terms of performance.
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References
Song D, Yang Y, Zheng S et al (2020) New perspectives on maximum wind energy extraction of variable-speed wind turbines using previewed wind speeds. Energy Convers Manag 206:112496. https://doi.org/10.1016/j.enconman.2020.112496
Kushwaha A, Gopal M, Singh B (2020) Q-Learning based maximum power extraction for wind energy conversion system with variable wind speed. IEEE Trans Energy Convers 35:1160–1170. https://doi.org/10.1109/TEC.2020.2990937
Xia Y, Chen Y, Song Y, Strunz K (2020) Multi-scale modeling and simulation of DFIG-based wind energy conversion system. IEEE Trans Energy Convers 35:560–572. https://doi.org/10.1109/TEC.2019.2953893
Bu SQ, Zhang X, Xia SW et al (2017) Reducing model complexity of DFIG-based wind turbines to improve the efficiency of power system stability analysis. Energy Procedia 142:971–976. https://doi.org/10.1016/j.egypro.2017.12.155
Tiwari R, Babu NR (2016) Recent developments of control strategies for wind energy conversion system. Renew Sustain Energy Rev 66:268–285. https://doi.org/10.1016/j.rser.2016.08.005
Sadara W, Neammanee B (2018) Control technique of back-to-back converter for DFIG in wind energy conversion system under abnormal voltage conditions. IEEJ Trans Electr Electron Eng 13:1285–1295. https://doi.org/10.1002/tee.22694
Tang Y, Ju P, He H et al (2013) Optimized control of DFIG-based wind generation using sensitivity analysis and particle swarm optimization. IEEE Trans Smart Grid 4:509–520. https://doi.org/10.1109/TSG.2013.2237795
Bhushan R, Chatterjee K (2017) Mathematical modeling and control of DFIG-based wind energy system by using optimized linear quadratic regulator weight matrices. Int Trans Electr Energy Syst 27:1–23. https://doi.org/10.1002/etep.2416
Hu J, Huang Y, Wang D et al (2015) Modeling of grid-connected DFIG-based wind turbines for dc-link voltage stability analysis. IEEE Trans Sustain Energy 6:1325–1336. https://doi.org/10.1109/TSTE.2015.2432062
Borutzky W (ed) (2016) Bond graphs for modelling, control and fault diagnosis of engineering systems, Springer
Lei Y, Mullane A, Lightbody G, Yacamini R (2006) Modeling of the wind turbine with a doubly fed induction generator for grid integration studies. IEEE Trans Energy Convers 21:257–264. https://doi.org/10.1109/TEC.2005.847958
Bektache A, Boukhezzar B (2018) Nonlinear predictive control of a DFIG-based wind turbine for power capture optimization. Int J Electr Power Energy Syst 101:92–102. https://doi.org/10.1016/j.ijepes.2018.03.012
Nguyen-Thanh H (2014) Improved control of DFIG systems under unbalanced voltage dip for torque stability using PI-fuzzy controller. Int J Electr Energy 2:300–307. https://doi.org/10.12720/ijoee.2.4.300-307
Surinkaew T, Ngamroo I (2014) Coordinated robust control of DFIG wind turbine and Pss for stabilization of power oscillations considering system uncertainties. IEEE Trans Sustain Energy 5:823–833. https://doi.org/10.1109/TSTE.2014.2308358
Wu X, Ning W, Yin T et al (2018) Robust design method for the SSDC of a DFIG based on the practical small-signal stability region considering multiple uncertainties. IEEE Access 6:16696–16703. https://doi.org/10.1109/ACCESS.2018.2802698
Wang T, Nian H (2014) Small signal modeling and stability analysis of a DFIG based wind power system under unbalanced grid voltage condition. In: 2014 17th International conference on electrical machines and systems (ICEMS), Hangzhou, China, 2014, pp 2625–2630. https://doi.org/10.1109/ICEMS.2014.7013944
Mehta B, Bhatt P, Pandya V (2014) Small signal stability analysis of power systems with DFIG based wind power penetration. Int J Electr Power Energy Syst 58:64–74. https://doi.org/10.1016/j.ijepes.2014.01.005
Parida SM, Kumar Rout P, Kar SK (2019) A novel self-tuning PI controller for a DFIG-based wind turbine system. Int J Syst Control Commun 10:176–190. https://doi.org/10.1504/IJSCC.2019.098979
Ali M, Joshi D (2019) Analysis of shunt active filter with PI, fractional Pi controller and ANN based controller. Int J Comput Appl 182:18–24. https://doi.org/10.5120/ijca2019918753
Tamaarat A, Benakcha A (2014) Performance of PI controller for control of active and reactive power in DFIG operating in a grid-connected variable speed wind energy conversion system. Front Energy 8:371–378. https://doi.org/10.1007/s11708-014-0318-6
Mesai Ahmed H, Bentaallah A, Djeriri Y, Mahmoudi A (2020) Comparative study between pi and fuzzy pi controllers for DFIG integrated in variable speed wind turbine. Int J Energ 4:8. https://doi.org/10.47238/ijeca.v4i2.102
Demirbas S (2017) Self-tuning fuzzy-PI-based current control algorithm for doubly fed induction generator. IET Renew Power Gener 11:1714–1722. https://doi.org/10.1049/iet-rpg.2016.0700
Salhi S, Salhi S (2019) LQR robust control for active and reactive power tracking of a DFIG based WECS: new LMI formulation based on time varying Lyapunov candidate function. Int J Adv Comput Sci Appl 10:565–579. https://doi.org/10.14569/IJACSA.2019.0100172
Bhushan R, Chatterjee K, Shankar R (2016) Comparison between GA-based LQR and conventional LQR control method of DFIG wind energy system. In: 2016 3rd International conference on recent advances in information technology (RAIT), Dhanbad, India, 2016, pp 214–219. https://doi.org/10.1109/RAIT.2016.7507904
El-Naggar A, Korai A, Erlich I (2015) Using MVMO for optimal tuning of linear quadratic regulators for DFIG-WT. IFAC PapersOnLine 48:479–484. https://doi.org/10.1016/j.ifacol.2015.12.425
Buduma P, Panda G (2018) LQR based control method for grid connected and islanded DG system. Int J Emerg Electr Power Syst 19:1–19. https://doi.org/10.1515/ijeeps-2018-0027
Debouza M, Al-Durra A (2019) Design of H-infinity controller for doubly fed induction generator based wind turbine. In: 2019 IEEE 28th international symposium on industrial electronics (ISIE), Vancouver, BC, Canada, pp 491–496. https://doi.org/10.1109/ISIE.2019.8781309
Wang Y, Wu Q, Gong W, Gryning MPS (2017) H∞ robust current control for DFIG-Based wind turbine subject to grid voltage distortions. IEEE Trans Sustain Energy 8(2):816--825. https://doi.org/10.1109/TSTE.2016.2621418
Louarem SLS, Belkhiat DEC, Bouktir T, Belkhiat S (2019) An efficient active and reactive power control of DFIG for a wind power generator. Eng Technol Appl Sci Res 9:4775–4782. https://doi.org/10.48084/etasr.3007
Zhao J, Mili L (2018) A decentralized H-infinity unscented Kalman filter for dynamic state estimation against uncertainties. IEEE Trans Smart Grid. https://doi.org/10.1109/TSG.2018.2870327
Tang W, Hu J, Chang Y, Liu F (2018) Modeling of DFIG-based wind turbine for power system transient response analysis in rotor speed control timescale. IEEE Trans Power Syst 33:6795–6805. https://doi.org/10.1109/TPWRS.2018.2827402
Mei F, Pal BC (2005) Modelling and small-signal analysis of a grid connected doubly-fed induction generator. In: 2005 IEEE power engineering society general meeting, San Francisco, CA, USA, vol 3, pp 2101–2108. https://doi.org/10.1109/pes.2005.1489386
Rigatos G, Siano P, Cecati C (2015) A nonlinear H-infinity feedback control approach for asynchronous generators. In: International conference on clean electrical power renewable energy resources impact, ICCEP, Taormina, Italy, 2015, vol 1, pp 460–465. https://doi.org/10.1109/ICCEP.2015.7177557
Phan DC, Trinh TH (2019) Application of linear quadratic regulator to control directly power for DFIG wind turbine. J Electr Syst 15:42–52
Mahapatro SR, Subudhi B, Ghosh S (2020) Design of a robust optimal decentralized PI controller based on nonlinear constraint optimization for level regulation: an experimental study. IEEE/CAA J Autom Sin 7:187–199. https://doi.org/10.1109/JAS.2019.1911516
Sedhom BE, Hatata AY, El-Saadawi MM, Abd-Raboh E-HE (2019) Robust adaptive H-infinity based controller for islanded microgrid supplying non-linear and unbalanced loads. IET Smart Grid 2:420–435. https://doi.org/10.1049/iet-stg.2019.0024
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Haneesh, K.M., Raghunathan, T. Robust Control of DFIG Based Wind Energy System Using an \(H_{\infty }\) Controller. J. Electr. Eng. Technol. 16, 1693–1707 (2021). https://doi.org/10.1007/s42835-021-00699-4
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DOI: https://doi.org/10.1007/s42835-021-00699-4