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

Marwa Hassan, Alsnosy Balbaa, Hanady H. Issa and Noha H. El-Amary
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Marwa Hassan: Computer, Control and Operation Research Department, Piazzale Aldo Moro, Sapienza University, 00185 Rome, Italy
Alsnosy Balbaa: Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 2033, Egypt
Hanady H. Issa: Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 2033, Egypt
Noha H. El-Amary: Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 2033, Egypt

Energies, 2018, vol. 11, issue 10, 1-25

Abstract: 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.

Keywords: artificial Immunity eco-maximum power point tracking (AI EMPPT); artificial immunity system estimator (AISE); asymptotic output tracking; doubly fed induction generator (DFIG); field programmed gate array (FPGA); non-linear control (NLC); renewable energy; rotor side converter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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