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Design of a Power System Stabilizer Using Adaptive Neuro-Fuzzy Logic

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dc.contributor.advisor Roy, Dr. Naruttam Kumar
dc.contributor.author Ahmed, Moudud
dc.date.accessioned 2018-08-11T07:24:55Z
dc.date.available 2018-08-11T07:24:55Z
dc.date.copyright 2016
dc.date.issued 2016-05
dc.identifier.other ID 0000000
dc.identifier.uri http://hdl.handle.net/20.500.12228/314
dc.description This thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, May 2016. en_US
dc.description Cataloged from PDF Version of Thesis.
dc.description Includes bibliographical references (pages 63-67).
dc.description.abstract Power systems are large, complex and nonlinear systems, and often exhibit low-frequency power oscillations due to insufficient damping. PSSs are widely used to suppress the electromechanical oscillations of generators and thus, enhance the overall stability of power systems. The conventional PSS which uses lead-lag compensation and gain settings for particular operating conditions provides poor performance under different loading conditions. To mitigate the shortcomings of conventional PSS, Artificial Intelligence (AT) based techniques such as Fuzzy Logic Controller (FLC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been introduced. FLC based PSS does not require mathematical model, possess lesser computational time, and ensures good performance under all conditions. However, speed and robustness are the most significant properties in comparison to the other classical schemes, there are no practical systematic procedures for the FLPSS design, so the rules and the membership functions of the controller are tuned subjectively, making the design laborious and a time-consuming task. On the other hand, an ANFIS based techniques is a promising method, which adjusts membership functions and rules adaptively to improve a systems performance. In literature, ANFIS-PSS is implemented for multi-machine power system having constant impedance load. The main contribution of this thesis is to introduce a PSS for a multi-machine interconnected power system comprising a dynamic load grounded on adaptive-neuro fuzzy logic technique. Load dynamics is included because it has significant impact on power system dynamic analysis. Transient stability analysis is more concerned with dynamic behaviors of loads. The robustness of ANFIS-PSS is being tested by applying single line to ground faults and symmetrical three phase faults. Another contribution of this thesis is to analyze the performance of using various input signals to PSS. It is found that the performance of an ANFIS-PSS depends on the input signal to PSS and for speed deviation and accelerating power as an input signal, the performance is quite far better compared to the selection of other inputs utilized in this work. en_US
dc.description.statementofresponsibility Moudud Ahmed
dc.format.extent 72 pages
dc.language.iso en_US en_US
dc.publisher Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh. en_US
dc.rights Khulna University of Engineering & Technology (KUET) thesis/ dissertation/internship reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Power System Stabilizer en_US
dc.subject Neuro-Fuzzy Logic en_US
dc.subject Power en_US
dc.title Design of a Power System Stabilizer Using Adaptive Neuro-Fuzzy Logic en_US
dc.type Thesis en_US
dc.description.degree Master of Science in Electrical and Electronic Engineering
dc.contributor.department Department of Electrical and Electronic Engineering


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