Energy Speaker Series - Module 2: Digital Twins for Digital Transformation

Overview

Session 2.2: Gas Turbine Digital Twin for Performance Diagnostics and Optimization,
Dr. Vili Panov, Advisory Key Expert at Siemens Energy and visiting professor of Health Monitoring and Diagnostics in College of Science at University of Lincoln

This talk will discuss development of a Gas Turbine Performance Digital Twin by use of tools such as Simulink Real-Time™ and Simulink PLC Coder™.  The developed Performance Digital Twin utilizes Real-Time high-speed computing and can be leveraged with various Enterprise and IOT Cloud Platforms. Proposed solutions are provided in a form of modular software architecture for a range of hardware platforms with corresponding functionalities to support model-based control strategies and advanced asset health management.

This project explored novel advanced techniques, which can meet the challenging requirements of increased reliability, improved efficiency and extended operational life of gas turbine assets. The Digital Twins based on real-time dynamic engine models has emerged as the most viable approach for solving challenging control and diagnostics requirements.

The developed real-time on-line Digital Twin technology has the ability to enhance current state-of -the-art offerings which are predominantly based on non-real time and off-line solutions. The devised solution highlights the next generation of Digital Twins that exploit modular functionalities distributed across the whole IoT chain consisting of Embedded, Edge and Cloud computational platforms. The gas turbine Performance Digital Twin has been deployed on the operational site and collected field data have been analyzed and presented in this study.

Session 2.3: Virtual commissioning for Wind Farms using Hybrid models: A digitization approach,
Prof. Diego Galar Pascual, Division of Operation and Maintenance Engineering at Luleå University of Technology and Principal researcher in Tecnalia (Spain), heading the Maintenance and Reliability research group within the Division of Industry and Transport

Digital twin is a virtual and digital representation of a physical entity or system. It involves connected “things” generating real-time data. That data is analyzed in the cloud and combined with other data related to the context around it. It can be then presented to operators and maintainers in a variety of roles, so they can remotely understand asset condition, history, etc.

Wind turbines are complex with respect to technology and operations that is why, a viable solution is to apply intelligent computerized systems, such as computerized control systems, or advanced monitoring and diagnostic systems. Indeed, the huge amount of information provided by wind farms convert this type of asset in the perfect candidates for digitization and deployment of digital twins.

However, the digital twin must be complemented besides the captured information in order to assess the overall condition of the whole fleet/system including the one from design and manufacturing which obviously contains the physical knowledge.

Therefore, the integration of asset information during the entire lifecycle is required to get an accurate health assessment of the whole system and determine the probability of a shutdown or slowdown avoiding black swans and other unexpected or unknown asset behaviors. Moreover, the lack of data on advanced degraded states due to early replacements makes the data-driven approach vulnerable to such situations. These hybrid models are expected to be shortly integrated as a part of the digitization in the digital twins created as digital mirrors of wind farms all over the world.

This talk will show the digital twins technologies for wind farms including hybrid models applying the maintenance analytics concept by the means of virtualization i.e. virtual commissioning of the assets through data fusion and integration from a systems perspective.

About the Presenters

Session 2.2

Dr. Vili Panov is a Chartered Engineer and Member of IMechE. Currently he is employed as an Advisory Key Expert by Siemens Energy Industrial Turbomachinery Ltd. He is appointed Visiting Professor of Health Monitoring and Diagnostics in College of Science at University of Lincoln. He received the Dipl.-Ing. degree in Mechanical Engineering in 1996 and the M.Sc. degree in Aeronautical Engineering in 2002, from University of Belgrade. Dr. Panov was awarded a Ph.D. in Engineering Mechanics form Cranfield University in 2006, and he has more than 20 years of experience in the turbomachinery sector. 

Session 2.3

Prof. Diego Galar is a Full Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology where he is coordinating several H2020 projects related to different aspects of cyber physical systems, Industry 4.0, IoT or Industrial AI and Big Data. He was also involved in the SKF UTC center located in Lulea focused on SMART bearings and also actively involved in national projects with the Swedish industry or funded by Swedish national agencies like Vinnova. He is also principal researcher in Tecnalia (Spain), heading the Maintenance and Reliability research group within the Division of Industry and Transport.

He has authored more than five hundred journal and conference papers, books and technical reports in the field of maintenance, working also as member of editorial boards, scientific committees and chairing international journals and conferences and actively participating in national and international committees for standardization and R&D in the topics of reliability and maintenance.