Optimal subinterval selection approach for power system transient stability simulation
Abstract
Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.
- Authors:
-
- Korea Electric Power Corporation (KEPCO), Daejeon (Korea)
- Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States)
- Publication Date:
- Research Org.:
- Univ. of Illinois at Urbana-Champaign, IL (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1239683
- Grant/Contract Number:
- OE0000097
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Energies
- Additional Journal Information:
- Journal Volume: 8; Journal Issue: 10; Journal ID: ISSN 1996-1073
- Publisher:
- MDPI AG
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 24 POWER TRANSMISSION AND DISTRIBUTION; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; transient stability simulation; numerical integration; time step; multi-rate method; subinterval; computational efficiency
Citation Formats
Kim, Soobae, and Overbye, Thomas J. Optimal subinterval selection approach for power system transient stability simulation. United States: N. p., 2015.
Web. doi:10.3390/en81011871.
Kim, Soobae, & Overbye, Thomas J. Optimal subinterval selection approach for power system transient stability simulation. United States. https://doi.org/10.3390/en81011871
Kim, Soobae, and Overbye, Thomas J. 2015.
"Optimal subinterval selection approach for power system transient stability simulation". United States. https://doi.org/10.3390/en81011871. https://www.osti.gov/servlets/purl/1239683.
@article{osti_1239683,
title = {Optimal subinterval selection approach for power system transient stability simulation},
author = {Kim, Soobae and Overbye, Thomas J.},
abstractNote = {Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.},
doi = {10.3390/en81011871},
url = {https://www.osti.gov/biblio/1239683},
journal = {Energies},
issn = {1996-1073},
number = 10,
volume = 8,
place = {United States},
year = {Wed Oct 21 00:00:00 EDT 2015},
month = {Wed Oct 21 00:00:00 EDT 2015}
}
Web of Science
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