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2022•Unpublished venueRequires access

A Python-based Ringdown Analysis Toolbox for Electromechanical Modes Identification

R. D. Reyes, J.A. de la O, Mario R. Arrieta Paternina, Joe H. Chow, A. Zamora, J. Ortiz

Open publisher page 4 citations

Abstract

This paper presents a user-friendly graphical user interface (GUI) that is embedded in a Python toolbox to identify electromechanical modes emerging after large power system disturbances. This GUI is able to read xslx or csv files that contain the information of several phasor measurement units (PMUs) or a data file with a proper read format. Besides this GUI incorporates three well-known methods that stand out to perform ringdown analysis in power systems such as Prony’s method (PM), eigensystem realization algorithm (ERA), and matrix pencil (MP). A straightforward implementation is adopted to capture dynamic parameters by processing single or multiple channels. Numerical and graphical results demonstrate the usability of the GUI, even in real system events1.

About this research paper

What this paper is about

This paper presents a user-friendly graphical user interface (GUI) that is embedded in a Python toolbox to identify electromechanical modes emerging after large power system disturbances. This GUI is able to read xslx or csv files that contain the information of several phasor measurement units (PMUs) or a data file with a proper read format. Besides this GUI incorporates three well-known methods that stand out to perform ringdown analysis in power systems such as Prony’s method (PM), eigensystem realization algorithm (ERA), and matrix pencil (MP). A straightforward implementation is adopted to capture dynamic parameters by processing single or multiple channels. Numerical and graphical results demonstrate the usability of the GUI, even in real system events1.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents a user-friendly graphical user interface (GUI) that is embedded in a Python toolbox to identify electromechanical modes emerging after large power system disturbances. This GUI is able to read xslx or csv files that contain the information of several phasor measurement units (PMUs) or a data file with a proper read format. Besides this GUI incorporates three well-known methods that stand out to perform ringdown analysis in power systems such as Prony’s method (PM), eigensystem realization algorithm (ERA), and matrix pencil (MP). A straightforward implementation is adopted to capture dynamic parameters by processing single or multiple channels. Numerical and graphical results demonstrate the usability of the GUI, even in real system events1.

Key concepts: Toolbox, Python (programming language), Computer science, Identification (biology), Computational science, Physics, Programming language, Biology

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