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  4. Working Principle of Self Adaptive Distributed Digital Twins in Power Systems
 
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2022
Conference Paper
Title

Working Principle of Self Adaptive Distributed Digital Twins in Power Systems

Abstract
Increasing the complexity of the power system architecture led to high complications in controlling and monitoring the modern power system. On the other hand, the growing accuracy in systems modeling and the ability to process huge amounts of data led to the invention of new methods that facilitate monitoring, controlling, and testing operations. One of the most prominent of these methods is what is known as the digital twin (DT), where it has become possible to build accurate and reliable models to conduct the analyzes and studies that are required for complex systems with high accuracy. This paper explains the concept of distributed DTs and their mechanism of operation. Additionally, more focus has been given to demonstrate the self-adaptation capability of these DTs using an online parameter estimation approach. In addition, this paper introduces the preliminary results for testing the concept of distributed DTs using real-time simulators. The results showed that integrating an online parameter optimizer in the distributed DTs improves their performance so that they behave like the physical component with high accuracy.
Author(s)
Alramlawi, Mansour  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Monsalve, Cristian  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Ruhe, Stephan  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Schäfer, Kevin
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Nicolai, Steffen  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Bretschneider, Peter  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Mainwork
IEEE Power & Energy Society General Meeting, PESGM 2022  
Conference
Institute of Electrical and Electronics Engineers, Power and Energy Society (IEEE PES General Meeting) 2022  
DOI
10.1109/pesgm48719.2022.9916753
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
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