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

doi:10.1109/IECON48115.2021.9589066

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 proceeding › Conference contribution › peer-review

9 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 language	English
Title of host publication	IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665435543
DOIs	https://doi.org/10.1109/IECON48115.2021.9589066
State	Published - Oct 13 2021
Externally published	Yes
Event	47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 - Toronto, Canada Duration: Oct 13 2021 → Oct 16 2021

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2021-October

Conference

Conference	47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021
Country/Territory	Canada
City	Toronto
Period	10/13/21 → 10/16/21

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.

Keywords

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

Access to Document

10.1109/IECON48115.2021.9589066

Cite this

Subedi, S., Guruwacharya, N., Fourney, R., Rekabdarkolaee, H. M., Tonkoski, R., Hansen, T. M., Tamrakar, U., & Cicilio, P. (2021). Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions. In IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October). IEEE Computer Society. https://doi.org/10.1109/IECON48115.2021.9589066

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title = "Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions",

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.",

keywords = "Data-driven modeling, IEEE standard 1547-2018, grid support functions, partitioned dynamic modeling, simulation speedup, voltage support",

author = "Sunil Subedi and Nischal Guruwacharya and Robert Fourney and Rekabdarkolaee, {Hossein Moradi} and Reinaldo Tonkoski and Hansen, {Timothy M.} and Ujjwol Tamrakar and Phylicia Cicilio",

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month = oct,

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doi = "10.1109/IECON48115.2021.9589066",

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Subedi, S, Guruwacharya, N, Fourney, R, Rekabdarkolaee, HM, Tonkoski, R, Hansen, TM, Tamrakar, U & Cicilio, P 2021, Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions. in IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), vol. 2021-October, IEEE Computer Society, 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021, Toronto, Canada, 10/13/21. https://doi.org/10.1109/IECON48115.2021.9589066

Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions. / Subedi, Sunil; Guruwacharya, Nischal; Fourney, Robert et al.
IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2021. (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October).

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

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AU - Subedi, Sunil

AU - Guruwacharya, Nischal

AU - Fourney, Robert

AU - Rekabdarkolaee, Hossein Moradi

AU - Tonkoski, Reinaldo

AU - Hansen, Timothy M.

AU - Tamrakar, Ujjwol

AU - Cicilio, Phylicia

PY - 2021/10/13

Y1 - 2021/10/13

N2 - 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.

AB - 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.

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Subedi S, Guruwacharya N, Fourney R, Rekabdarkolaee HM, Tonkoski R, Hansen TM et al. Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions. In IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society. 2021. (IECON Proceedings (Industrial Electronics Conference)). doi: 10.1109/IECON48115.2021.9589066

Computationally Efficient Partitioned Modeling of Inverter Dynamics with Grid Support Functions

Abstract

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Keywords

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