Non-invasive system identification of a tactical generator

Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 57-58). === Microgrids, small power distribution networks, are gaining traction as an approach to increasing the f...

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Main Author: Bell, John Harry, IV
Other Authors: Marija D. Ilic.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2019
Subjects:
Online Access:http://hdl.handle.net/1721.1/120255
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-1202552019-05-02T16:19:16Z Non-invasive system identification of a tactical generator Bell, John Harry, IV Marija D. Ilic. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 57-58). Microgrids, small power distribution networks, are gaining traction as an approach to increasing the fuel efficiency of tactical operations. In order to design controllers for microgrids, accurate models of the generators providing power are needed. In this thesis, non-invasive experimental methods for determining synchronous machine system parameters for a Tactical Quiet Generator (TQG), a generator commonly used by the US military, are explored. While the generator's rotor is at standstill, direct voltage excitation over a large range of excitation frequencies of a synchronous machine's stator is employed to determine electrical parameters for the synchronous machine. With the generator in running, the response of the frequency of generated AC power to a step in load is employed to determine the inertia of the generator's rotor. The stator excitation test is performed with the rotor positioned at a series of angles relative to the stator, so as to determine the location of the principal axes (d and q axes) of the rotor and impedances of the synchronous machine as seen in the d-q reference frame. Least-squares curve fitting is applied to the Bode plots of these impedances to fit the predictions of equivalent circuit models to the data, thus determining the model parameters represented by each equivalent circuit element. For the load step response test, the swing equation is used to calculate the system inertia from measured changes in frequency due to known steps in power. From execution of these techniques, it was determined that they are viable methods for estimating system parameters, though greater precision needs to be exercised in the stator excitation test in order to accurately estimate parameters. by John Harry Bell, IV. S.B. 2019-02-05T16:01:31Z 2019-02-05T16:01:31Z 2018 2018 Thesis http://hdl.handle.net/1721.1/120255 1083142010 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 58 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Mechanical Engineering.
spellingShingle Mechanical Engineering.
Bell, John Harry, IV
Non-invasive system identification of a tactical generator
description Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 57-58). === Microgrids, small power distribution networks, are gaining traction as an approach to increasing the fuel efficiency of tactical operations. In order to design controllers for microgrids, accurate models of the generators providing power are needed. In this thesis, non-invasive experimental methods for determining synchronous machine system parameters for a Tactical Quiet Generator (TQG), a generator commonly used by the US military, are explored. While the generator's rotor is at standstill, direct voltage excitation over a large range of excitation frequencies of a synchronous machine's stator is employed to determine electrical parameters for the synchronous machine. With the generator in running, the response of the frequency of generated AC power to a step in load is employed to determine the inertia of the generator's rotor. The stator excitation test is performed with the rotor positioned at a series of angles relative to the stator, so as to determine the location of the principal axes (d and q axes) of the rotor and impedances of the synchronous machine as seen in the d-q reference frame. Least-squares curve fitting is applied to the Bode plots of these impedances to fit the predictions of equivalent circuit models to the data, thus determining the model parameters represented by each equivalent circuit element. For the load step response test, the swing equation is used to calculate the system inertia from measured changes in frequency due to known steps in power. From execution of these techniques, it was determined that they are viable methods for estimating system parameters, though greater precision needs to be exercised in the stator excitation test in order to accurately estimate parameters. === by John Harry Bell, IV. === S.B.
author2 Marija D. Ilic.
author_facet Marija D. Ilic.
Bell, John Harry, IV
author Bell, John Harry, IV
author_sort Bell, John Harry, IV
title Non-invasive system identification of a tactical generator
title_short Non-invasive system identification of a tactical generator
title_full Non-invasive system identification of a tactical generator
title_fullStr Non-invasive system identification of a tactical generator
title_full_unstemmed Non-invasive system identification of a tactical generator
title_sort non-invasive system identification of a tactical generator
publisher Massachusetts Institute of Technology
publishDate 2019
url http://hdl.handle.net/1721.1/120255
work_keys_str_mv AT belljohnharryiv noninvasivesystemidentificationofatacticalgenerator
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