Scalable design methods for online data‐driven wide‐area control of power systems

Abstract A novel online system‐identification‐based control design for damping inter‐area oscillations in power systems using supplementary wide‐area excitation control is presented. The identification is based on a partly reduced‐order and a partly full‐order model of the grid. Assuming the grid to...

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Main Authors: Jishnudeep Kar, Aranya Chakrabortty
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:IET Generation, Transmission & Distribution
Online Access:https://doi.org/10.1049/gtd2.12159
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spelling doaj-8109a612ac0647178856e3441d3379e22021-07-14T13:25:33ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952021-07-0115142085210010.1049/gtd2.12159Scalable design methods for online data‐driven wide‐area control of power systemsJishnudeep Kar0Aranya Chakrabortty1FREEDM Systems Center North Carolina State University 2816 Avent Ferry Road, Raleigh, NC 27606 USAFREEDM Systems Center North Carolina State University 2816 Avent Ferry Road, Raleigh, NC 27606 USAAbstract A novel online system‐identification‐based control design for damping inter‐area oscillations in power systems using supplementary wide‐area excitation control is presented. The identification is based on a partly reduced‐order and a partly full‐order model of the grid. Assuming the grid to be divided into coherent areas with phasor measurement units located across the grid, the coherent states of the generators are averaged while the non‐coherent states, such as the internal states of each power system stabilizer, are not. A hybrid state vector consisting of these averaged and non‐averaged states is computed, and used for identifying a hybrid linear time‐invariant state‐space model. A linear quadratic regulator based on this hybrid model is, thereafter, designed. The reduced‐order part of the model is found to save significant amount of online time for both learning and control, while the full‐order part serves to enhance closed‐loop stability. N4SID with randomized singular value decomposition (rSVD) is used for making the identification loop fast. The reduced‐dimensional controller is finally implemented using a broadcast control strategy. The design is extended to non‐linear models of power systems using Carleman bilinearization. Results for linear and bilinear control designs are validated using the IEEE 68‐bus power system model.https://doi.org/10.1049/gtd2.12159
collection DOAJ
language English
format Article
sources DOAJ
author Jishnudeep Kar
Aranya Chakrabortty
spellingShingle Jishnudeep Kar
Aranya Chakrabortty
Scalable design methods for online data‐driven wide‐area control of power systems
IET Generation, Transmission & Distribution
author_facet Jishnudeep Kar
Aranya Chakrabortty
author_sort Jishnudeep Kar
title Scalable design methods for online data‐driven wide‐area control of power systems
title_short Scalable design methods for online data‐driven wide‐area control of power systems
title_full Scalable design methods for online data‐driven wide‐area control of power systems
title_fullStr Scalable design methods for online data‐driven wide‐area control of power systems
title_full_unstemmed Scalable design methods for online data‐driven wide‐area control of power systems
title_sort scalable design methods for online data‐driven wide‐area control of power systems
publisher Wiley
series IET Generation, Transmission & Distribution
issn 1751-8687
1751-8695
publishDate 2021-07-01
description Abstract A novel online system‐identification‐based control design for damping inter‐area oscillations in power systems using supplementary wide‐area excitation control is presented. The identification is based on a partly reduced‐order and a partly full‐order model of the grid. Assuming the grid to be divided into coherent areas with phasor measurement units located across the grid, the coherent states of the generators are averaged while the non‐coherent states, such as the internal states of each power system stabilizer, are not. A hybrid state vector consisting of these averaged and non‐averaged states is computed, and used for identifying a hybrid linear time‐invariant state‐space model. A linear quadratic regulator based on this hybrid model is, thereafter, designed. The reduced‐order part of the model is found to save significant amount of online time for both learning and control, while the full‐order part serves to enhance closed‐loop stability. N4SID with randomized singular value decomposition (rSVD) is used for making the identification loop fast. The reduced‐dimensional controller is finally implemented using a broadcast control strategy. The design is extended to non‐linear models of power systems using Carleman bilinearization. Results for linear and bilinear control designs are validated using the IEEE 68‐bus power system model.
url https://doi.org/10.1049/gtd2.12159
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AT aranyachakrabortty scalabledesignmethodsforonlinedatadrivenwideareacontrolofpowersystems
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