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Modeling Adequacy of Droop-Controlled Grid-Forming Converters for Transient Studies: Singular Perturbation Analysis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The converter-interfaced generation (CIGs) are expected to dominate the grid of the future. These CIGs will cohabit with a small percentage of synchronous generators (SGs) producing power from hydro, solar thermal or even nuclear resources. It appears that the literature lacks comprehensive modeling adequacy studies on such grids with SGs and CIGs. This paper takes the first step in that direction. To that end, a nonlinear averaged phasor model of the system with detailed model of the converters including grid-forming converters (GFCs) and their control is developed. Then a singular perturbation analysis based model reduction approach for such system is proposed. Based on the proposed method, two levels of reduced order models for the GFCs are derived. Finally, the adequacy of these reduced-order models are presented via time-domain simulations on two test system models using MATLAB/Simulink.

Original languageEnglish (US)
Title of host publication2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665453554
DOIs
StatePublished - 2023
Event2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023 - Washington, United States
Duration: Jan 16 2023 → Jan 19 2023

Publication series

Name2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023

Conference

Conference2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023
Country/TerritoryUnited States
CityWashington
Period1/16/23 → 1/19/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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