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

Panagiotis N. Papadopoulos, Theofilos A. Papadopoulos, Andreas I. Chrysochos, Jovica V. Milanović

Research output: Contribution to journalArticle

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

This paper introduces a hybrid-methodology for online identification and clustering of generator oscillatory behavior, 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 operation of modern power systems, including Renewable Energy Sources (RES) are investigated, with emphasis on the impact of the dynamic behavior of power electronic interfaced RES.
Original languageEnglish
Number of pages10
JournalIEEE Transactions on Power Systems
Early online date27 Apr 2018
DOIs
Publication statusE-pub ahead of print - 27 Apr 2018

    Fingerprint

Keywords

  • clustering
  • online dynamic security assessment
  • renewable generation
  • unsupervised maching learning

Cite this