This paper presents direct power control (DPC) strategies using the super-twisting sliding mode control (STSMC) applied to active and reactive power control of a doubly-fed induction generator (DFIG) supplied by a space vector modulation inverter for wind turbine system. Then, a control STSMC-DPC and SVM strategies are applied. The active and reactive powers that are generated by the DFIG will be decoupled by the orientation of the stator flux and controlled by super-twisting sliding mode control. Its simulated performance is then compared with conventional sliding mode control. The test of robustness of the controllers against machine parameters uncertainty will be tackled, and the simulations will be presented. Simulation results of the proposed controller (SMC-DPC) and (STSMC-DPC) scheme are compared for various step changes in the active and reactive power. This approach super-twisting sliding mode control is validated using the Matlab/Simulink software and the results of the simulation can prove the excellent performance of this control in terms of improving the quality of the energy supplied to the electricity grid.
This paper proposes a direct power control (DPC) strategy for the doubly-fed induction generator (DFIG) operating under variable wind speeds. Under this strategy, the active and reactive powers of the DFIG are directly controlled by the AC/DC converter, whose switching states were selected from a switch table. Besides, a two-level hysteresis corrector was selected to control the active and reactive powers, ensuring the dynamic performance of the DFIG. The effectiveness of the proposed DPC strategy was compared through MATLAB simulation with the field oriented control (FOC), a classical proportional-integral (PI) control strategy for wind turbines. The results show that the DPC strategy adjusted the instantaneous active and reactive powers in the grid perfectly with respect to their references, and realized the absorption of sinusoidal currents with a unity power factor. The proposed DPC strategy has a great application potential in wind power generation.
In this paper, a Direct Power Control (DPC) based on the switching table and Artificial Neural Network-based Maximum Power Point Tracking control for variable speed Wind Energy Conversion Systems (WECS) is proposed. In the context of wind energy exploitation, we are interested in this work to improve the performance of the wind generator by controlling the continuation of the Maximum Power Point Tracking (MPPT) using the Artificial Neural Network (ANN). The results obtained show the interest of such control in this system. The proposed Direct Power Control strategy produces a fast and robust power response, also the grid side is controlled by Direct Power Control based a grid voltage position to ensure a constant DC- link voltage. The THD of the current injected into the electric grid for the Wind Energy Conversion Systems with Direct Power Control is shown in this paper, the THD is lower than the 5 % limit imposed by IEEE STANDARDS ASSOCIATION. This approach Direct Power Control is validated using the Matlab/Simulink software and simulation results can prove the excellent performance of this control as improving power quality and stability of wind turbine.
This article presents a study on the use of the concept of direct power control (DPC) based on intelligent techniques in the control of a shunt active power filter (SAPF). In order to improve harmonic mitigation and reactive power compensation capabilities, the conventional switching table is replaced by a fuzzy inference system to generate the switching sequences of the shunt active power filter. To ensure an active power exchange stable and efficient, the DC voltage of the SAPF in controlled using an integrated proportional controller (PI) optimized by a heuristic optimization technique based on genetic algorithms (GA). The combination of two intelligent techniques in this proposed control strategy makes it possible to reduce ripples in different variables of the SAPF, to maintain the direct voltage at their reference value and to improve the THD of the grid current. The numerical simulation results obtained under Matlab / Simulink confirm the importance of the SAPF's proposed control technique. Streszczenie. W artykule opisano wykorzystanie metody DPC (direct power control) do poprawy parametrów bocznikowego filtru aktywnego SAPF. Konwencjonalna tabela przełączeń jest zastąpiona przez system logiki rozmytej. Do optymalizacji filtru wykorzystano też algorytm genetyczny. Optymalizacja aktywnego filtru bocznikowego SAPF z wykorzystaniem algorytmu genetycznego i logiki rozmytej
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