An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System
Asynchronous generators; Electric fault currents; Energy conversion; Maximum power point trackers; Particle swarm optimization (PSO); Wind power; Wind speed; Doubly fed induction generators; Doubly feed induction generator and maximum power point tracking; Maximum Power Point Tracking; Optimization...
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2023
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my.uniten.dspace-271412023-05-29T17:40:08Z An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System Sai B.S.V. Chatterjee D. Mekhilef S. Wahyudie A. 57219283626 15623160900 57928298500 35306119500 Asynchronous generators; Electric fault currents; Energy conversion; Maximum power point trackers; Particle swarm optimization (PSO); Wind power; Wind speed; Doubly fed induction generators; Doubly feed induction generator and maximum power point tracking; Maximum Power Point Tracking; Optimization scheme; Particle swarm; Perturb and observe; Searching spaces; Space minimization; Swarm optimization; Tracking scheme; Wind turbines In this work, a searching space minimization-based particle swarm optimization (SSM-PSO) scheme has been proposed for maximum power point tracking (MPPT) in a doubly fed induction generator (DFIG) based wind energy conversion system (WECS). DFIG displays non-linearity in P-? characteristics. So different types of conventional and optimization-based schemes are developed for MPPT. The drawbacks in the conventional perturb and observe (P&O) scheme has been successfully abolished by the proposed SSM-PSO method. Because of its weather-insensitive nature, the conventional P&O MPP tracking scheme results in the fluctuation of DFIG output under a sudden change in wind speed. To avoid this problem, maximum and minimum limits for the optimal rotor speed have been determined in the proposed SSM-PSO scheme. Further, the obtained limits for rotor speed are employed to improve the searching space within the non-linear P-? curve. This initial confinement of particles to a limited searching space in SSM-PSO results in a faster response of the system. Since the proposed SSM-PSO is atmosphere sensitive, it avoids fluctuations under an abrupt variation in wind velocity. The improved initialization part of SSM-PSO leads to better dynamic characteristics compared to existing P&O and optimization-based schemes. The proposed SSM-PSO scheme is implemented for a 2MW DFIG system in MATLAB Simulink atmosphere and showed satisfactory results. � 2013 IEEE. Final 2023-05-29T09:40:07Z 2023-05-29T09:40:07Z 2022 Article 10.1109/ACCESS.2022.3193998 2-s2.0-85135584906 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135584906&doi=10.1109%2fACCESS.2022.3193998&partnerID=40&md5=f5949cc1d69a61092c4e0bc26fe3bceb https://irepository.uniten.edu.my/handle/123456789/27141 10 78306 78319 All Open Access, Gold Institute of Electrical and Electronics Engineers Inc. Scopus |
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Asynchronous generators; Electric fault currents; Energy conversion; Maximum power point trackers; Particle swarm optimization (PSO); Wind power; Wind speed; Doubly fed induction generators; Doubly feed induction generator and maximum power point tracking; Maximum Power Point Tracking; Optimization scheme; Particle swarm; Perturb and observe; Searching spaces; Space minimization; Swarm optimization; Tracking scheme; Wind turbines |
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57219283626 Sai B.S.V. Chatterjee D. Mekhilef S. Wahyudie A. |
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Sai B.S.V. Chatterjee D. Mekhilef S. Wahyudie A. |
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Sai B.S.V. Chatterjee D. Mekhilef S. Wahyudie A. An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
author_sort |
Sai B.S.V. |
title |
An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
title_short |
An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
title_full |
An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
title_fullStr |
An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
title_full_unstemmed |
An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System |
title_sort |
ssm-pso based mppt scheme for wind driven dfig system |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
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1806423550290034688 |
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13.222552 |