A new fuzzy logic approach for control system of wind turbine with Doubly Fed Induction Generator

Lee, Hong Hee; Dzung, Phan Quoc; Phương, Lê Minh; Khoa, Le Dinh; Nguyen, Huu-Nhan

doi:10.1109/ifost.2010.5667902

Cited by 14 publications

(1 citation statement)

References 10 publications

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“…Moreover, their costs are also falling at a sustainable rate, whereas the general cost trend for fossil fuels is in the opposite direction despite their present volatility. Wind energy is considered one of the most effective renewable sources [2][3][4][5][6][7][8]. It has many advantages as it is abundant and nondepletable.…”

Section: Introductionmentioning

confidence: 99%

Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator

et al. 2018

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This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, determined by the wind mechanical power, to supply the wind electrical power. The second cluster is the asymptotic non-linear control technique which proposes the reference signal tracking of the rotor direct and quadratic current, respectively. Thus, assigning specific zeros through feedback ensures the reproduction of an output that converges asymptotically to a required reference rotor current. For online operation, the Artificial Immunity Technique (AIT) is utilized to deal with the generated control reference signal. A proposal hardware implementation on Field Programmed Gate Array (FPGA) is also presented. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load. MATLAB program was used to simulate and test the performance of the proposed control methods. The results to show the effectiveness of the proposed technique. The reduction in CO 2 emission was calculated.

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Section: Introductionmentioning

confidence: 99%

Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator

et al. 2018

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Non linear control of a doubly fed induction generator in wind turbines

Doumi

Aissaoui²,

Tahour³

et al. 2015

2015 3rd International Conference on Control, Engineering &Amp; Information Technology (CEIT)

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In this paper, a decoupling control strategy has been applied to control the active and reactive powers generated by a Double Feed Induction Generator (DFIG). We propose new control strategies based on fuzzy sliding mode in order to control the power of the wind turbine transmitted to the grid and to make the wind turbine adaptable to different constraints. The use of this method provides very satisfactory performance for the DFIG control, and the chattering effect is also reduced by the fuzzy mode. Simulations results show interesting performances of the system in terms of the reference tracking stability and the robustness against parameters variations.

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