An intelligent dynamic security assessment framework for power systems with wind power

Yan Xu, Zhao Yang Dong, Zhao Xu, Ke Meng, Kit Po Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

86 Citations (Scopus)


The increasing penetration of wind power can alter the dynamic security characteristic of a power system. To accommodate rapid and volatile wind power variations, dynamic security assessment (DSA) against foreseeable disturbances is required to be carried out online and provide security monitoring results within sufficiently small time frame. Based on soft computing (SC) technologies, this paper develops an intelligent framework for real-time DSA of power systems with large penetration of wind power. It consists of a DSA engine whose role is to perform real-time DSA of the power system, a wind power and load demand (W&LF) forecasting engine for offline and online predicting wind power generation and electricity load demand, a database generation (DBG) engine for generating instances to train the DSA engine, and a model updating (MU) engine for online updating the DSA engine. Case studies are conducted on two benchmark systems where high DSA efficiency and accuracy are obtained. This framework can be an ideal candidate for advanced security monitoring in the future SmartGrid control centres.
Original languageEnglish
Article number6227533
Pages (from-to)995-1003
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Issue number4
Publication statusPublished - 1 Nov 2012


  • Dynamic security assessment
  • extreme learning machine
  • intelligent system
  • soft computing
  • wind power

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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