Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2021 IEEE Madrid PowerTech |
| Herausgeber (Verlag) | IEEE Computer Society |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 978-1-6654-3597-0 |
| ISBN (Print) | 978-1-6654-1173-8 |
| Publikationsstatus | Veröffentlicht - 2021 |
| Veranstaltung | IEEE PowerTech 2021 - Madrid, Spanien Dauer: 28 Juni 2021 → 2 Juli 2021 https://www.powertech2021.com/ |
Abstract
Schlagwörter
- active distribution grid, Julia, probabilistic stability, short-circuits, survivability
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Energie (insg.)
- Energieanlagenbau und Kraftwerkstechnik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Energie (insg.)
- Erneuerbare Energien, Nachhaltigkeit und Umwelt
Ziele für nachhaltige Entwicklung
Zitieren
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- BibTex
- RIS
2021 IEEE Madrid PowerTech. IEEE Computer Society, 2021. 9494855.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › 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 -