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Adaptive type-1 fuzzy control of a wind energy conversion system based on a double-fed induction machine

Bensaadia Labib, Rouabhi Riyadh, Khodja Djalaleddine, Herizi Abdelghafour

Przegląd Elektrotechniczny

2023

R. 99, nr 8

110--115

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.

Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS

Nazir Awais, Khan Safdar Abbas, Khan Malak Adnan, Alam Zaheer, Khan Imran, Irfan Muhammad, Rehman Saifur, Nowakowski Grzegorz

Bulletin of the Polish Academy of Sciences. Technical Sciences

2023

Vol. 71, nr 5

art. no. e147063

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.

High performances of grid-connected DFIG based on direct power control with fixed switching frequency via MPPT strategy using MRAC and neuro-fuzzy control

Amrane F., Chaiba A., Mekhilef S.

Journal of Power Technologies

2016

Vol. 96, nr 1

27--39

This paper presents high performance improved direct power control (DPC) based on model reference adaptive control (MRAC) and neuro-fuzzy control (NFC) for grid connected doubly fed induction generator (DFIG), to overcome the drawbacks of conventional DPC which was based only on PID controllers, namely the speed/efficiency trade-off and divergence from peak power under fast variation of wind speed. A mathematical model of DFIG implemented in the d-q reference frame is achieved. Then, a direct power control algorithm for controlling rotor currents of DFIG is incorporated using PID controllers, and space-vector modulation (SVM) is used to determine a fixed switching frequency. The condition of the stator side power factor is controlled at unity level via MPPT strategy. The MRAC which is based on DPC is investigated instead of PID regulators. Also, the performances of NFC based on DPC are tested and compared to those achieved using MRAC controller. The results obtained in the Matlab/Simulink environment using robustness tests show that the NFC is efficient, has superior dynamic performance and is more robust during parameter variations.