Measurement based method for online characterization of generator dynamic behaviour in systems with renewable generation

Panagiotis Papadopoulos, Theofilos Papadopoulos, Andreas Chrysochos, Jovica V. Milanovic

Research output: Contribution to journalArticlepeer-review

Abstract

This paper introduces a two-step methodology for online identification of the participation of generators in power system oscillatory modes, based on measured responses. The dominant modes in generator measured responses are initially identified using a mode identification technique and then introduced, in the next step, as input into a clustering algorithm. Critical groups of generators that exhibit poorly or negatively damped oscillations are identified, in order to enable corrective control actions and stabilize the system. The uncertainties associated with the operation of modern power systems with renewable energy sources (RESs) are investigated as well as the impact of the dynamic behavior of power electronic interfaced RESs.

Original languageEnglish
Pages (from-to)6466-6475
Number of pages10
JournalIEEE Transactions on Power Systems
Volume33
Issue number6
Early online date27 Apr 2018
DOIs
Publication statusPublished - Nov 2018

Keywords

  • clustering
  • online dynamic security assessment
  • renewable generation
  • uncertainties
  • unsupervised machine learning

Fingerprint

Dive into the research topics of 'Measurement based method for online characterization of generator dynamic behaviour in systems with renewable generation'. Together they form a unique fingerprint.

Cite this