Signal processing techniques for estimating power system modal parameters

D. Min, J. Heo, J. Yoo, K. Hur

Research output: Contribution to journalArticlepeer-review


Smart Grid is expected to provide a reliable power supply with fewer and briefer outages, cleaner power, and self-healing power systems through advanced Power Quality (PQ) monitoring, analysis and diagnosis of the PQ measurements and identification of the root cause, and timely automated controls. It is important to understand that signal processing has been an integral part of advancing and expanding the horizons of this PQ research significantly and the capabilities and applications of signal processing for PQ are continually evolving. This paper thus presents a survey on the proven and emerging signal applications for enhancing PQ, focusing on algorithms for estimating system modal parameters because resonant frequencies and their damping information are critical signatures in evaluating the PQ. In particular, we discuss the need for investigating time-varying and nonlinear characteristics of the modal parameters due to dynamic changes in system operating conditions and introduce promising signal processing techniques for this purpose.

Original languageEnglish
Article number1240019
JournalJournal of Circuits, Systems and Computers
Issue number6
Publication statusPublished - 2012 Oct

Bibliographical note

Funding Information:
This work was supported in part by a grant through the Human Resource Development Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) funded by the Korea government Ministry of Knowledge Economy (No. 20104010100590). This work was supported in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology (No. 20110014440).

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering


Dive into the research topics of 'Signal processing techniques for estimating power system modal parameters'. Together they form a unique fingerprint.

Cite this