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Adaptive network-based fuzzy inferen...
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Singh, Mukhtiar.
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Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features .
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features ./
Author:
Singh, Mukhtiar.
Description:
220 p.
Notes:
Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6342.
Contained By:
Dissertation Abstracts International71-10B.
Subject:
Alternative Energy. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR62841
ISBN:
9780494628416
Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features .
Singh, Mukhtiar.
Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features .
- 220 p.
Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6342.
Thesis (Ph.D.)--Ecole de Technologie Superieure (Canada), 2010.
This thesis work presents an Adaptive Network-Based Fuzzy Inference System (ANFIS) for Sensor-less control of PMSG based wind turbine. The ANFIS tuned estimator is able to estimate the rotor position and speed accurately over a wide speed range with a great immunity against parameter variation. The proposed system consists of two back to back connected inverters, where one controls the PMSG, while another is used for grid synchronization. Moreover, in the proposed work, the grid side inverter is also utilized as harmonic, reactive power and unbalanced load compensator for a 3-phase 4-wire (3P4W) non-linear load, if any, at point of common coupling (PCC). This enables the grid to always supply/absorb a balanced set of fundamental currents at unity power factor. The proposed system is developed and simulated using MATLAB/SimPowerSystem (SPS) toolbox. Besides this, a scaled laboratory hardware prototype is also developed to validate the proposed control approach.
ISBN: 9780494628416Subjects--Topical Terms:
1035473
Alternative Energy.
Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features .
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Adaptive network-based fuzzy inference systems for sensorless control of PMSG based wind turbine with power quality improvement features .
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220 p.
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Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6342.
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Thesis (Ph.D.)--Ecole de Technologie Superieure (Canada), 2010.
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This thesis work presents an Adaptive Network-Based Fuzzy Inference System (ANFIS) for Sensor-less control of PMSG based wind turbine. The ANFIS tuned estimator is able to estimate the rotor position and speed accurately over a wide speed range with a great immunity against parameter variation. The proposed system consists of two back to back connected inverters, where one controls the PMSG, while another is used for grid synchronization. Moreover, in the proposed work, the grid side inverter is also utilized as harmonic, reactive power and unbalanced load compensator for a 3-phase 4-wire (3P4W) non-linear load, if any, at point of common coupling (PCC). This enables the grid to always supply/absorb a balanced set of fundamental currents at unity power factor. The proposed system is developed and simulated using MATLAB/SimPowerSystem (SPS) toolbox. Besides this, a scaled laboratory hardware prototype is also developed to validate the proposed control approach.
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Keywords: Wind Energy, Permanent Magnet Synchronous Generator, Adaptive Neuro-Fuzzy Systems, Sensorless control, Power Quality, Active Power Filter.
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School code: 1246.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR62841
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