A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models

During the last decade the dynamic properties of power systems have been altered drastically, due to the emerge of new non-conventional types of loads as well as to the increasing penetration of distributed generation. To analyze the power system dynamics and develop accurate models, measurement-bas...

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Main Authors: Eleftherios O. Kontis, Georgios A. Barzegkar-Ntovom, Konstantinos A. Staios, Theofilos A. Papadopoulos, Grigoris K. Papagiannis
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/13/2606
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spelling doaj-690286613f6349a0b7af1e8938931df32020-11-25T00:42:41ZengMDPI AGEnergies1996-10732019-07-011213260610.3390/en12132606en12132606A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent ModelsEleftherios O. Kontis0Georgios A. Barzegkar-Ntovom1Konstantinos A. Staios2Theofilos A. Papadopoulos3Grigoris K. Papagiannis4Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, GreecePower Systems Laboratory, Department of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi, GreecePower Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, GreecePower Systems Laboratory, Department of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi, GreecePower Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, GreeceDuring the last decade the dynamic properties of power systems have been altered drastically, due to the emerge of new non-conventional types of loads as well as to the increasing penetration of distributed generation. To analyze the power system dynamics and develop accurate models, measurement-based techniques are usually employed by academia and power system operators. In this regard, in this paper an identification toolbox is developed for the derivation of measurement-based equivalent models and the analysis of dynamic responses. The toolbox incorporates eight of the most widely used mode identification techniques as well as several static and dynamic network equivalencing models. First, the theoretical background of the mode identification techniques as well as the mathematical formulation of the examined equivalent models is presented and analyzed. Additionally, multi-signal analysis methods are incorporated in the toolbox to facilitate the development of robust equivalent models. Additionally, an iterative procedure is adopted to automatically determine the optimal order of the derived models. The capabilities of the toolbox are demonstrated using simulation responses, acquired from large-scale benchmark power systems, as well as using measurements recorded at a laboratory-scale active distribution network.https://www.mdpi.com/1996-1073/12/13/2606equivalent modelsgraphical user interfaceload modellingmode identificationmulti-signal analysispower system dynamics
collection DOAJ
language English
format Article
sources DOAJ
author Eleftherios O. Kontis
Georgios A. Barzegkar-Ntovom
Konstantinos A. Staios
Theofilos A. Papadopoulos
Grigoris K. Papagiannis
spellingShingle Eleftherios O. Kontis
Georgios A. Barzegkar-Ntovom
Konstantinos A. Staios
Theofilos A. Papadopoulos
Grigoris K. Papagiannis
A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
Energies
equivalent models
graphical user interface
load modelling
mode identification
multi-signal analysis
power system dynamics
author_facet Eleftherios O. Kontis
Georgios A. Barzegkar-Ntovom
Konstantinos A. Staios
Theofilos A. Papadopoulos
Grigoris K. Papagiannis
author_sort Eleftherios O. Kontis
title A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
title_short A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
title_full A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
title_fullStr A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
title_full_unstemmed A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models
title_sort toolbox for analyzing and testing mode identification techniques and network equivalent models
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-07-01
description During the last decade the dynamic properties of power systems have been altered drastically, due to the emerge of new non-conventional types of loads as well as to the increasing penetration of distributed generation. To analyze the power system dynamics and develop accurate models, measurement-based techniques are usually employed by academia and power system operators. In this regard, in this paper an identification toolbox is developed for the derivation of measurement-based equivalent models and the analysis of dynamic responses. The toolbox incorporates eight of the most widely used mode identification techniques as well as several static and dynamic network equivalencing models. First, the theoretical background of the mode identification techniques as well as the mathematical formulation of the examined equivalent models is presented and analyzed. Additionally, multi-signal analysis methods are incorporated in the toolbox to facilitate the development of robust equivalent models. Additionally, an iterative procedure is adopted to automatically determine the optimal order of the derived models. The capabilities of the toolbox are demonstrated using simulation responses, acquired from large-scale benchmark power systems, as well as using measurements recorded at a laboratory-scale active distribution network.
topic equivalent models
graphical user interface
load modelling
mode identification
multi-signal analysis
power system dynamics
url https://www.mdpi.com/1996-1073/12/13/2606
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