Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions

Sunil Subedi, Nischal Guruwacharya, Robert Fourney, Hossein Moradi Rekabdarkolaee, Reinaldo Tonkoski, Timothy M. Hansen, Ujjwol Tamrakar, Phylicia Cicilio

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

6 Scopus citations

Abstract

With the advancement in power electronics technology and grid standards, traditional converters are being supplemented with the new IEEE 1547-2018 standard based grid support functions (GSFs) to support power system voltage and frequency. Inverter dynamics in power systems vary with different modes of operation, thus new modeling methods for proper system planning, operation, and dispatch are required. This work presents a data-driven approach for partitioned dynamic modeling of inverters to speed up simulation time and reduce computational complexity while ensuring acceptable accuracy. The proposed method was tested for a smart inverter with voltage support (Volt-VAr function) on a two-bus system considering dynamic residential loads, and the results showed a four-time speedup in simulation time compared to the use of the detailed model with acceptable levels of accuracy.

Original languageEnglish
Title of host publicationIECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9781665435543
DOIs
StatePublished - Oct 13 2021
Externally publishedYes
Event47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 - Toronto, Canada
Duration: Oct 13 2021Oct 16 2021

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2021-October

Conference

Conference47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021
Country/TerritoryCanada
CityToronto
Period10/13/2110/16/21

Funding

Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy National Nuclear Security Administration under contract DE-NA-0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. SAND2021-12105 C. This work is supported by the U.S. Department of Energy Office of Science, Office of Electricity Microgrid RD Program, and Office of Energy Efficiency and Renewable Energy Solar Energy Technology Office under the EPSCoR grant number DE-SC0020281. The work at Sandia (Ujjwol Tamrakar) is supported by the US Department of Energy, Office of Electricity, Energy Storage Program.

FundersFunder number
Office of Electricity Microgrid RD Program
Office of Energy Efficiency and Renewable Energy Solar Energy Technology Office
U.S. Department of Energy National Nuclear Security AdministrationDE-NA-0003525
U.S. Department of Energy
Office of Experimental Program to Stimulate Competitive ResearchDE-SC0020281
Sandia National Laboratories

    Keywords

    • Data-driven modeling
    • IEEE standard 1547-2018
    • grid support functions
    • partitioned dynamic modeling
    • simulation speedup
    • voltage support

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