Adaptive Model Reduction for Parareal in Time Method for Transient Stability Simulations

Denis Osipov, Nan Duan, Aleksandar Dimitrovski, Srikanth Allu, Srdjan Simunovic, Kai Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Real time or faster than real time simulation can enable system operators to foresee the effect of crucial contingencies on the power system dynamics and take timely actions to prevent system instability. Parareal in time method uses concurrent computations on different segments of the time domain of interest to speed up the dynamic simulations. This paper describes the application of an adaptive nonlinear model reduction method in improving computational speed of the Parareal solver. The proposed method adaptively switches between a hybrid system with selective linearization and a completely linear system based on the size of a disturbance. The functions in the hybrid system are linearized based on the electrical distance between specific generators and the area where disturbances originated. The proposed method is tested on the 327-machine 2383-bus Polish system.

Original languageEnglish
Title of host publication2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538677032
DOIs
StatePublished - Dec 21 2018
Event2018 IEEE Power and Energy Society General Meeting, PESGM 2018 - Portland, United States
Duration: Aug 5 2018Aug 10 2018

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2018-August
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Country/TerritoryUnited States
CityPortland
Period08/5/1808/10/18

Keywords

  • Adaptive model reduction
  • Parareal in time
  • Power system dynamics
  • Power system stability
  • Real time simulation

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