caa a22 4500 606159886 CHVBK 20210128100627.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s00521-014-1725-7 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1725-7 Improving waveform quality in direct power control of DFIG using fuzzy controller [Elektronische Daten] [H. Boroujeni, M. Othman, A. Shirdel, R. Rahmani, P. Movahedi, E. Toosi] This paper proposes a new direct power control (DPC) strategy of double-fed induction generator using fuzzy logic controller. The active and reactive power equations are expanded, and effects of voltage vectors on active and reactive power variations are investigated quantitatively. The selection of the voltage vectors is performed using fuzzy system which is used instead of optimal switching table. Four variables are used as inputs of the fuzzy system which are errors of active and reactive powers, real time value of the rotor speed and stator flux position. The defuzzified output is the optimal selected voltage vector. MATLAB/Simulink software is used for the purpose of simulation and the results reported show the effectiveness of the proposed method in improving the waveform quality. Compared with the conventional DPC, the proposed fuzzy technique can reduce the power out of band percentage by about 25% which is very impressive. The Natural Computing Applications Forum, 2014 Direct power control nationallicence Double-fed induction generator nationallicence Power quality nationallicence Fuzzy logic control nationallicence Boroujeni H. Department of Mechatronic and Automatic Control, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Johor, Malaysia aut Othman M. Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, Jalan Semarak, 54100, Kuala Lumpur, Malaysia aut Shirdel A. Department of Chemical Engineering, Åbo Akademi University, 20500, Turku, Finland aut Rahmani R. Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, Jalan Semarak, 54100, Kuala Lumpur, Malaysia aut Movahedi P. Department of Information Technology, University of Turku, 20014, Turku, Finland aut Toosi E. Faculty of Basic Science, Islamic Azad University, Neka Branch, Neka, Iran aut Neural Computing and Applications Springer London 26/4(2015-05-01), 949-955 0941-0643 26:4<949 2015 26 521 https://doi.org/10.1007/s00521-014-1725-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1725-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Boroujeni H. Department of Mechatronic and Automatic Control, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Johor, Malaysia aut NATIONALLICENCE 700 1- Othman M. Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, Jalan Semarak, 54100, Kuala Lumpur, Malaysia aut NATIONALLICENCE 700 1- Shirdel A. Department of Chemical Engineering, Åbo Akademi University, 20500, Turku, Finland aut NATIONALLICENCE 700 1- Rahmani R. Centre for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, Jalan Semarak, 54100, Kuala Lumpur, Malaysia aut NATIONALLICENCE 700 1- Movahedi P. Department of Information Technology, University of Turku, 20014, Turku, Finland aut NATIONALLICENCE 700 1- Toosi E. Faculty of Basic Science, Islamic Azad University, Neka Branch, Neka, Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/4(2015-05-01), 949-955 0941-0643 26:4<949 2015 26 521