Eigenvalue Estimation of Dominant Electromechanical Modes Based on Synchronous Measurement and Generator Grouping Technique

Hisayuki Hiraiwa, Hiroumi Saitoh, Eiichi Tsukada, Kazuo Minazawa, Junichi Toyoda

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The authors have been studying a new approach for modal analysis of large power systems that utilizes GPS-based synchronous measurement technology. The approach is based on the identification of a linearized Multi-Input Multi-Output model of power system. Since the identified model expresses approximately the electromechanical dynamics of actual power system, modal frequencies, dampings and mode shapes corresponding to electromechanical modes can be estimated as eigenvalues and eigenvectors of the identified model. In the paper, in order to advance our approach to a practical technique, it is mainly discussed how to select a small number of machines suitable for measurement locations to estimate eigenvalues associated with dominant slow modes. Such machines can be detected by identifying coherent groups related to the slow modes. The reference generators that behave representatively in each coherent group are the optimal ones to be measured. Therefore, the slow modes can be obtained by observing one generator from each group. The verification of the new modal analysis and coherency-based machine selection is done through simulation studies using IEEJ EAST 10-machine system model.

Original languageEnglish
Pages (from-to)1047-1054
Number of pages8
JournalIEEJ Transactions on Power and Energy
Volume125
Issue number11
DOIs
Publication statusPublished - 2005

Keywords

  • GPS
  • coherency
  • eigenvalue
  • stability monitoring
  • synchronous measurement
  • system identification

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Eigenvalue Estimation of Dominant Electromechanical Modes Based on Synchronous Measurement and Generator Grouping Technique'. Together they form a unique fingerprint.

Cite this