Details
Original language | English |
---|---|
Title of host publication | 2021 IEEE Madrid PowerTech |
Publisher | IEEE Computer Society |
Number of pages | 6 |
ISBN (electronic) | 978-1-6654-3597-0 |
ISBN (print) | 978-1-6654-1173-8 |
Publication status | Published - 2021 |
Event | IEEE PowerTech 2021 - Madrid, Spain Duration: 28 Jun 2021 → 2 Jul 2021 https://www.powertech2021.com/ |
Abstract
Keywords
- active distribution grid, Julia, probabilistic stability, short-circuits, survivability
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Energy(all)
- Energy Engineering and Power Technology
- Engineering(all)
- Electrical and Electronic Engineering
- Energy(all)
- Renewable Energy, Sustainability and the Environment
Sustainable Development Goals
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2021 IEEE Madrid PowerTech. IEEE Computer Society, 2021. 9494855.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Probabilistic Stability Assessment for Active Distribution Grids
AU - Liemann, Sebastian
AU - Strenge, Lia
AU - Schultz, Paul
AU - Hinners, Holm
AU - Porst, Johannis
AU - Sarstedt, Marcel
AU - Hellmann, Frank
N1 - Funding Information: Condynet2 FK. 03EK3055A. All authors gratefully acknowledge the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources on the high performance computer system at the Potsdam Institute for Climate Impact Research.
PY - 2021
Y1 - 2021
N2 - This paper demonstrates the concept of probabilistic stability assessment on large-signal stability in the use case of short circuits in an active distribution grid. Here, the concept of survivability is applied, which extends classical stability assessments by evaluating the stability and operational limits during transients for a wide range of operating points and failures. For this purpose, a free, open-source, and computationally efficient environment (Julia) for dynamic simulation of power grids is used to demonstrate its capabilities. The model implementation is validated against established commercial software and deviations are minimal with respect to power flow and dynamic simulations. The results of a large-scale survivability analysis reveal i) a broad field of application for probabilistic stability analysis and ii) that new non-intuitive stability correlations can be obtained. Hence, the proposed method shows strong potential to efficiently conduct power system stability analysis in active distribution grids.
AB - This paper demonstrates the concept of probabilistic stability assessment on large-signal stability in the use case of short circuits in an active distribution grid. Here, the concept of survivability is applied, which extends classical stability assessments by evaluating the stability and operational limits during transients for a wide range of operating points and failures. For this purpose, a free, open-source, and computationally efficient environment (Julia) for dynamic simulation of power grids is used to demonstrate its capabilities. The model implementation is validated against established commercial software and deviations are minimal with respect to power flow and dynamic simulations. The results of a large-scale survivability analysis reveal i) a broad field of application for probabilistic stability analysis and ii) that new non-intuitive stability correlations can be obtained. Hence, the proposed method shows strong potential to efficiently conduct power system stability analysis in active distribution grids.
KW - active distribution grid
KW - Julia
KW - probabilistic stability
KW - short-circuits
KW - survivability
KW - active distribution grid
KW - Julia
KW - probabilistic stability
KW - short-circuits
KW - survivability
UR - http://www.scopus.com/inward/record.url?scp=85112396601&partnerID=8YFLogxK
U2 - 10.1109/PowerTech46648.2021.9494855
DO - 10.1109/PowerTech46648.2021.9494855
M3 - Conference contribution
SN - 978-1-6654-1173-8
BT - 2021 IEEE Madrid PowerTech
PB - IEEE Computer Society
T2 - IEEE PowerTech 2021
Y2 - 28 June 2021 through 2 July 2021
ER -