Measurement-based power system dynamic model reductions

Xuemeng Zhang, Yaosuo Xue, Shutang You, Yong Liu, Zhiyong Yuan, Jidong Chai, Yilu Liu

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

11 Scopus citations

Abstract

Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. Therefore, the model of the study system must be retained in detail while the external system can be reduced using system reduction techniques. This paper proposes a measurement-based dynamic equivalent in order to increase both model accuracy and simulation speed. The proposed method uses a set of measurements at the boundary nodes between the study area and external area for model parameter identification. Case studies demonstrate that the measurement-based technique can capture the main system behaviors accurately and improve computational efficiency.

Original languageEnglish
Title of host publication2017 North American Power Symposium, NAPS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538626993
DOIs
StatePublished - Nov 13 2017
Event2017 North American Power Symposium, NAPS 2017 - Morgantown, United States
Duration: Sep 17 2017Sep 19 2017

Publication series

Name2017 North American Power Symposium, NAPS 2017

Conference

Conference2017 North American Power Symposium, NAPS 2017
Country/TerritoryUnited States
CityMorgantown
Period09/17/1709/19/17

Funding

ACKNOWLEDGMENTS This material is based upon work supported by the U.S. Department of Energy, Grid Modernization Initiative, Grid Modernization Laboratory Consortium Extreme Event Modeling project, and partially supported by NSF under award number 1509624. This work also made use of the Engineering Research Center Shared Facilities supported by the Engineering Research Center Program of the National Science Foundation and DOE under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program.

FundersFunder number
National Science Foundation1509624
U.S. Department of EnergyEEC-1041877

    Keywords

    • Dynamic equivalent
    • model reduction
    • power system dynamic simulation
    • system identification
    • system transfer function

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