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Power system simulations that extend over a time period of minutes, hours, or even longer are called extended-term simulations. As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales, extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energy integration, cascading failures), and there is an urgent need for efficient and robust extended-term simulation approaches. The conventional approaches are insufficient for dealing with the extended-term simulation of multi-timescale processes. This paper proposes an extended-term simulation approach based on the semi-analytical simulation (SAS) methodology. Its accuracy and computational efficiency are backed by SAS's high accuracy in event-driven simulation, larger and adaptive time steps, and flexible switching between full-dynamic and quasi-steady-state (QSS) models. We used this proposed extended-term simulation approach to evaluate bulk power system restoration plans, and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.


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Advanced extended-term simulation approach with flexible quasisteady-state and dynamic semi-analytical simulation engines

Show Author's information Rui Yao1( )Dongbo Zhao1A. P. Sakis Meliopoulos2Chanan Singh3Joydeep Mitra4Feng Qiu1
Division of Energy Systems, Argonne National Laboratory, Lemont, IL 60439, USA
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77843, USA
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA

Abstract

Power system simulations that extend over a time period of minutes, hours, or even longer are called extended-term simulations. As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales, extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energy integration, cascading failures), and there is an urgent need for efficient and robust extended-term simulation approaches. The conventional approaches are insufficient for dealing with the extended-term simulation of multi-timescale processes. This paper proposes an extended-term simulation approach based on the semi-analytical simulation (SAS) methodology. Its accuracy and computational efficiency are backed by SAS's high accuracy in event-driven simulation, larger and adaptive time steps, and flexible switching between full-dynamic and quasi-steady-state (QSS) models. We used this proposed extended-term simulation approach to evaluate bulk power system restoration plans, and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.

Keywords: dynamics, resilience, Extended-term simulation, multi-timescale simulation, event-driven simulation, quasi-steady-state (QSS), hybrid simulation, holomorphic embedding (HE), semi-analytical simulation (SAS)

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Publication history

Received: 06 December 2021
Revised: 27 January 2022
Accepted: 26 February 2022
Published: 25 March 2022
Issue date: March 2022

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© The author(s) 2022

Acknowledgements

Acknowledgements

This work was supported by the lab-directed research & development (LDRD) program of Argonne National Laboratory and U.S. DOE Advanced Grid Modeling Program grant DE-OE0000875. We also acknowledge the Laboratory Computing Resource Center of Argonne National Laboratory.

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The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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