Decoupling vector control and optimisation of PMSG-based wind energy system using adaptive type-1 and type-2 fuzzy logic control

• Autorzy: Mekki Mustapha , Tayeb Allaoui , Belabbas Belkacem , Mouloud Denai

Identyfikatory

DOI

10.15199/48.2020.08.22

Warianty tytułu

PL

Odsprzęgnięte sterowanie wektorowe systemu energii wiatrowej z generatorem MSG wykorzystujące logikę rozmytą

• Języki publikacji: EN

Abstrakty

EN

Variable-speed wind energy conversion systems based on permanent magnet synchronous generators (PMSG) are becoming increasingly popular over the recent years and PMSGs are being adopted by many wind turbine manufacturers especially due to several advantages such as high energy density, low maintenance, self-excitation and direct-drive operation. Vector control is currently the most widely used control strategyin PMSGs to achieve decoupling between the magnetic flux and torguqe via the direct and quadrature components of the current respectively.The major disadvantage of this method is the use of current sensors to ensure accurate decoupling. In this work, a decoupling vector control strategy based on Type-1 and Type-2 fuzzy logic is proposed eliminating the use of current sensors. In addition, a maximum power point tracking (MPPT) technique is proposed to optimise the power extracted from the wind turbine system. Two speed control methodes based on adaptive Type-1 and Type-2 fuzzy logic fractional proportional and integral (PI) controllers. Several simulations are presented to demonstrated the effectiveness of the proposed control schemes for the PMSG-based wind energy conversion system.

PL

Generator synchroniczny z magnesem trwałym PMSG odgrywa kluczową rolę w konwersji energii wiatru (WECS). Sterowanie wektorowe było najczęściej stosowane jako strategia sterowania dla tego generatora w celu zapewnienia oddzielenia prądu stałego od kwadratury. Wadą tej metody jest to, że potrzebuje czujników prądu, aby zapewnić oddzielenie. Artykuł koncentruje się na sterowaniu wektorem oddzielającym opartym na logice rozmytej typu 1 (DFLC1_VC) i logice rozmytej typu 2 (DFLC2_VC). Możemy zapewnić kontrolę systemu, a oddzielenie bez użycia czujników prądu zapewnia kontrolę i odsprzęgnięcie w tym samym czasie. Wyniki symulacji wykazały skuteczność proponowanych strategii kontroli WECS w oparciu o PMSG.

Słowa kluczowe

EN

WECS; PMSG; MPPT; vector control; decoupling vector control; FOPI; type 1 fuzzy logic; type-2 fuzzy logic

PL

WECS; PMSG; MPPT; kontrola wektorowa; FOPI; logika rozmyta typu 1; logika rozmyta typu 2

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 8
• Strony: 112--116
• Opis fizyczny: Bibliogr. 20 poz., rys., tab

Twórcy

autor

Mekki Mustapha

• Laboratory at the Ibn Khaldoun University of Tiaret, Algeria

autor

Tayeb Allaoui

• Laboratory at the Ibn Khaldoun University of Tiaret, Algeria

autor

Belabbas Belkacem

• Laboratory at the Ibn Khaldoun University of Tiaret, Algeria

autor

Mouloud Denai

• School of Engineering & Technology, University of Hertfordshire, UK

Bibliografia

• [1] Huenteler, J.; Niebuhr, C.; Schmidt, T.S. The effect of local and global learning on the cost of renewable energy in developing countries. J. Clean. Prod. 2016, 128, 6–21.
• [2] Singaravel, M.M.R.; Daniel, S.A. MPPT with Single DC-DC Converter and Inverter for Grid Connected Hybrid Wind-Driven PMSG-PV System. IEEE Trans. Ind. Electron 2015, 62, 4849– 4857.
• [3] Abdelrahem, M.; Hackl, M.C.; Kennel, R. Simplified model predictive current control without mechanical sensors for variable-speed wind energy conversion systems. Electr. Eng. 2017, 99, 367–377.
• [4] Gencer, A. Analysis and control of low-voltage ride-through capability improvement for PMSG based on an NPC converter using an interval type-2 fuzzy logic system. Elektron. Elektrotech. 2019, 25, 63–70.
• [5] Putri R.I., Jasa L., Pujiantara M., Priyadi A., Hery M., “Tuning PI controller based on multiobjective optimization approaches for speed control of PMSG wind turbine”, International Review of Automatic Control, Vol.8, No.4, pp.315-321, July 2015.
• [6] Y. Zhao, C. Wei, Z. Zhang, W. Qiao, “A review on position/speed sensorless control for permanent-magnet synchronous machine-based wind energy conversion systems”, IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol.1, No.4, pp.203–216, Dec. 2013.
• [7] J. Ivanqui, H. Voltolini, R. Carlson and E. H. Watanabe, “pq theory” control applied to wind turbine trapezoidal PMSG under symmetrical fault,IEEE International Electric Machines & Drives Conference (IEMDC):534-540, 2013.
• [8] A.G. Sanchez, M.G. Molina, A.M. Rizzato Lede, “Dynamic model of wind energy conversion systems with PMSG-based variable-speed wind turbines for power system studies”, International Journal of Hydrogen Energy, Vol.37, 2012, pp.10064-10069.
• [9] S. Li ., T.A. Haskew, L. Xu, “Conventional and novel control designs for direct driven PMSG wind turbines”, Electric Power Systems Research, Vol.80, 2010, pp.328–338.
• [10] S. Chekkal, N. A. Lahaçani, D. Aouzellag, K. Ghedamsi, Fuzzy logic control strategy of wind generator based on the dualstator induction generator, International Journal of Electrical Power & Energy Systems, vol. 59:166-175, July. 2014.
• [11] Baroudi JA, Dinavahi V, Knight AM. A review of power converter topologies for wind generators. Renew Energy 2007;32:2369–85
• [12] Abdin ES, Xu W. Control design and dynamic performance analysis of a wind turbine-induction generator unit. IEEE Trans Energy Convers 2000;15(1):5–8
• [13] M. Singh, A. Chandra, Power maximization and voltage sag/swell ride-through capability of PMSG based variable speed wind energy conversion system, Industrial Electronics, 34th Annual Conference of IEEE:2206-2211, 2008.
• [14] Poitiers F. Study and control of induction generators for wind energy conversion systems. PhD thesis, University of Nantes; 2003.
• [15] Kumar, R.; Daya, M.L. A novel self-tuning fuzzy based PID controller for speed control of induction motor drive. In Proceedings of the International Conference on Control Communication.
• [16] Gopala-Rao, K.A.; Amarendra-Reddy, B.; Durga-Bhavani, P. Fuzzy Pi and integrating type fuzzy PID controllers of linear, nonlinear and time-delay systems. IJCA 2010, 1, 41–47.
• [17] Gnanavadivel, J., Senthil Kumar, N., Yogalakshmi, P.: Comparative study of PI, fuzzy and fuzzy tuned PI controllers for single-Phase AC–DC three-level converter. J Electr. Eng. Technol. 12, 78–90 (2017)
• [18] El-Bardini, M., El-Nagar, A.M.: Direct adaptive interval type- 2fuzzy logic controller for the multivariable anaesthesia system.Ain Shams Eng. J. 2, 149–160 (2011)
• [19] Mendel, J.M., John, R.I., Liu, F.: Interval type-2 fuzzy logic systems made simple. IEEE Trans. Fuzzy Syst. 14,808–821 (2006).
• [20] Ibrahim BENGUERGOUR , Tayeb ALLAOUI, Abdeldjabbar Mohamed KOUADRIA , Mouloud DENAI, Optimization and Adaptive Control of Wind water Pumping System based on fuzzy RST and genetic RST, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 2/2020.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).