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Adaptacyjne sterowanie rozmyte typu 1 systemem konwersji energii wiatrowej w oparciu o dwustronnie zasilaną maszynę indukcyjną
Języki publikacji
Abstrakty
In this paper, we will develop an adaptive control algorithm applied to the wind energy conversion system (WECS) based on a double-fed induction machine (DFIM) driven by a turbine with variable blade pitch, and controlled through the rotor variables by two bidirectional converters. The main function of these converters in the considered system is the connection of the wind generator to the power grid in two different ways: one on the grid side converter which will allow continuous bus control and improve the power factor on the grid side; the other, on the converter on the rotor side, which will allow the control and optimization of the energy flow generated by the stator during the periods of operation of this system. In the first part we presented the individual modeling of the wind turbine chain, then we presented and developed the controls necessary to control the active and reactive powers produced by this system in order to ensure optimum performance and production quality.
W niniejszym artykule opracujemy algorytm sterowania adaptacyjnego zastosowany w systemie konwersji energii wiatru (SKEW) oparty na dwustronnie zasilanej maszynie indukcyjnej (DZMI) napędzanej turbiną o zmiennym skoku łopatek i sterowanej poprzez zmienne wirnika dwoma dwukierunkowymi konwertery. Główną funkcją tych przekształtników w rozpatrywanym systemie jest podłączenie generatora wiatrowego do sieci elektroenergetycznej na dwa różne sposoby: jeden po stronie przekształtnika sieciowego, który umożliwi ciągłą kontrolę magistrali i poprawi współczynnik mocy po stronie sieci; drugi, na przekształtniku po stronie wirnika, co pozwoli na sterowanie i optymalizację przepływu energii generowanej przez stojan w okresach pracy tego układu. W pierwszej części przedstawiliśmy indywidualne modelowanie łańcucha turbiny wiatrowej, następnie przedstawiliśmy i opracowaliśmy sterowanie niezbędne do sterowania mocą czynną i bierną wytwarzaną przez ten system w celu zapewnienia optymalnej wydajności i jakości produkcji.
Wydawca
Czasopismo
Rocznik
Tom
Strony
110--115
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
- Electrical Engineering Department, Mohamed Boudiaf University of M’sila, Algeria
- LGE Research Laboratory of M’sila
autor
- Electrical Engineering Department, Mohamed Boudiaf University of M’sila, Algeria
- LGE Research Laboratory of M’sila
autor
- Electrical Engineering Department, Mohamed Boudiaf University of M’sila, Algeria
- LGE Research Laboratory of M’sila
autor
- Electrical Engineering Department, Mohamed Boudiaf University of M’sila, Algeria
- LGE Research Laboratory of M’sila
Bibliografia
- [1] Rezaei MM., A nonlinear maximum power point tracking technique for DFIG-based wind energy conversion systems, Engi Science and Techn, Inter Jou.,21(2018),901-908
- [2] Darvish Falehi A., Rafiee M., Maximum efficiency of wind energy using novel Dynamic Voltage Restorer for DFIG based Wind Turbine, Energy Rep.,4(2018),308-322
- [3] Mekki M., Allaoui T., Belabbas B., Denai M., Decoupling Vector Control and Optimisation of PMSG-Based Wind Energy System Using Adaptive Type-1 and Type-2 Fuzzy Logic Control, Przegląd Elektrotechniczny, ISSN 0033-2097 96 (2020), nr 8, 123-128
- [4] Dahbi A., Nait-Said MS., Nait-Said N., A novel combined MPPT-pitch angle control for wide range variable speed wind turbine based on neural network, inter jour hydro ener , 41 (2016), n 22, 9427-9442
- [5] Ebin Cherian Mathew., Anandarup Das., Integration of renewable energy sources with MVDC network, IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) 2020 IEEE
- [6] Kenan Dösoglu M., Aysen Basa Arsoy., Transient modeling and analysis of a DFIG based wind farm with supercapacitor energy storage, Int J Electr Power Ener Syst.,78(2016),414- 441
- [7] Gajewski P., Improved control strategy of wind energy conversion system with PMSG during low voltage sags, Przegląd Elektrotechniczny, ISSN 0033-2097 96 (2020), nr 4,123-128
- [8] Nektarios E Karakasis., Christos A. Mademlis., High efficiency control strategy in a wind energy conversion system with doubly fed induction generator, Renewable Energy.,125(2018),974-984
- [9] Saihi L., Bakou Y., Ferroudji F., Berbaoui B., MPPTF & Pitch Fuzzy Controller of a Wind Turbine System Using DFIG, 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA) 2019 Algeria
- [10] Andreas Giannakis., Athanasios Karlis., Yannis L. Karnavas., A combined control strategy of a DFIG based on a sensorless power control through modified phase-locked loop and fuzzy logic controllers, Renewable Energy.,121(2018),489-501
- [11] Prosenjit Mondal., Praveen Tripathy., Ujjwal K. Saha., Second Order Sliding Mode Observer Design for the Speed Estimation of DFIG, IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) 2020 IEEE
- [12] Farshadnia M., V T., Current-based direct power control of a DFIG under unbalanced grid voltage, Int J Electr Power Ener Syst.,62(2014),571-582
- [13] Ayrir W., Ourahou M., El Hassouni B., Haddi A., Direct torque control improvement of a variable speed DFIG based on a fuzzy inference system, Mathematics and Computers in Simulation.,167(2020),308-324
- [14] Abdullah Asuhaimi B. Mohd Zin., Mahmoud Pesaran H.A.., Azhar B. Khairuddin., An overview on doubly fed induction generators′ controls and contributions to wind based electricity generation, Renewable and Sustainable Energy Reviews.,27(2013),692-708
- [15] Amrane F., Chaiba A., Francois B., Suitable Power Control based on Type-2 Fuzzy Logic for Wind-Turbine DFIG Under Hypo-Synchronous Mode Fed by Multi-Level Converter, The 5th International Conference on Electrical Engineering Boumerdes, Algeria. (ICEE-B) 2017 IEEE
- [16] Vall Hemeyine A., Abbou A., Bakouri B., Labbadi M., Power Control for Wind Turbine Driving a Doubly Fed Induction Generator using Type-2 Fuzzy Logic Controller, 2019 IEEE
- [17] Rouabhi R., Abdessemed R., Chouder A., Djerioui A., R.,Power Quality Enhancement of Grid Connected Doubly-Fed Induction Generator Using Sliding Mode Control, International Review of Electrical Engineering.,10(2010), nr 2,266-276
- [18] Kara R., Tlemcani A., Hassaoui N., Interval type-2 fuzzy logic controller based DPC-SVM algorithm for PWM rectifier, Przegląd Elektrotechniczny, ISSN 0033-2097 97 (2021), nr 7, 80-84
- [19] FENG Hao., PAN Lei., PENG Xiu-fang., Zhang Tian-wei., Coordinated Control Strategy of MPPT and Pitch angle of Wind Turbine Generator Based on Neural Network, 2019 IEEE, 99- 104
- [20] Afdhal A., Dhaoui M., Sbita L., Pitch Angle control of the variable speed wind turbine, The 17th international conference on Sciences and Techniques of Automatic control & computer engineering - STA'2016, Sousse, Tunisia 2016 IEEE, 582-587
- [21] Kang Qi., Research on Variable Pitch Wind Turbine Control System, 2014 IEEE
- [22] Rouabhi R., Control of the powers generated by a variable speed wind system based on a DFIG, PhD thesis, batna university 2, (2016)
- [23] Herizi J., Rouabhi R., Zemmit A., Comparative study of the performance of a sliding, sliding-fuzzy type 1 and a sliding fuzzy type 2 control of a permanent magnet synchronous machine, Przegląd Elektrotechniczny, ISSN 0033-2097 98 (2022), nr 11, 21-29
- [24] Fahrizal Auliansyah., Sutedjo., Ony Asrarul Qudsi., Indra Ferdiansyah., Controlling Speed Of Brushless DC Motor By Using Fuzzy Logic Controller, International Sem in ar on A pplication for Te ch n o lo gy of Inform ation and Com m unication (iSem antic) 2020 IEEE, 298-304
- [25] Khelifa S., Semmah A., Power quality enhancement in wind turbine based DFIG using fuzzy control and neural-RIP for harmonic mitigation, Przegląd Elektrotechniczny, ISSN 0033- 2097 98 (2022), nr 5, 140-147
- [26] Yongqing Fan., STongtong Kang., Type-2 Fuzzy Adaptive Control For Uncertain Robot Manipulator System With Time Varying Output Constraints, 2020 IEEE, 2430-2435
- [27] Ayad Al-Mahturi., Fendy Santoso., An Intelligent Control of an Inverted Pendulum Based on an Adaptive Interval Type-2 Fuzzy Inference System, 2019 IEEE
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2b713175-8afa-4fc2-8d53-b0fb458d7f2b