Learn how digital twins can optimize electrical equipment diagnosis and condition assessment.
In this episode, we will learn about the concept of the digital twin and its application as a diagnostic and condition assessment tool in the electrical power industry.
Professor Michael Hartje, an expert for digital measurement and automation technology in power systems at the Bremen University of Applied Science in Germany, describes the connection between the digital twin and the monitoring, diagnosis and control of electrical equipment. He also highlights how the digital twin can be used as a single source of data about power equipment throughout its lifecycle, and how the digital twin supports decision making for the equipment’s continued operation.
Basically, a digital twin is a virtual representation of electrical equipment or systems, which spans their lifecycles. The digital twin is continuously updated with real-time data collected from multiple sensors to provide a complete overview of condition status and uses simulation and machine learning to identify developing problems and predict future performance. Professor Hartje explains how this will save time and greatly optimize the day-to-day work of equipment operators.
Specifically, Professor Hartje describes how digital twins are being currently used for the diagnosis and condition assessment of power transformers, which has been the focus of his work.
Lastly, he highlights the current work being done by various national and international committees to further the development and future use of digital twins in the electric power industry.
“The digital twin represents a further important development of conventional assessment methods for vital equipment in the electrical energy supply system.”
- Professor Michael Hartje, Bremen University of Applied Science
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