Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks

Publikationstyp
Conference Paper
Publikationsdatum
2019
Sprache
English
Author
Hotz, Christian Daniel 
Becker, Christian orcid-logo
Institut
Elektrische Energietechnik E-6 
TORE-URI
http://hdl.handle.net/11420/5044
Citation
Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2019)
Contribution to Conference
Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2019) 
Publisher Link
https://ieeexplore.ieee.org/document/9000480
Scopus ID
2-s2.0-85091864344
Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the current state of the power system to be able to detect critical situations immediately. This paper proposes a method based on artificial neural networks that is capable of providing an online supervision service, which works in real-time due to its low demand for computational resources. Additionally, the requirements regarding system state information of such a monitoring system are investigated to assess the measurement and communication setup necessary for its proper functionality and thus its applicability to real power systems.
Schlagworte
MLE@TUHH