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

Eleftherios O. Kontis, Georgios A. Barzegkar-Ntovom, Konstantinos A. Staios, Theofilos A. Papadopoulos and Grigoris K. Papagiannis
Additional contact information
Eleftherios O. Kontis: Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
Georgios A. Barzegkar-Ntovom: Power Systems Laboratory, Department of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi, Greece
Konstantinos A. Staios: Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
Theofilos A. Papadopoulos: Power Systems Laboratory, Department of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi, Greece
Grigoris K. Papagiannis: Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece

Energies, 2019, vol. 12, issue 13, 1-19

Abstract: 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.

Keywords: equivalent models; graphical user interface; load modelling; mode identification; multi-signal analysis; power system dynamics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/13/2606/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/13/2606/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:13:p:2606-:d:246283

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().