Kasper, L., Birkelbach, F., Schwarzmayr, P., Steindl, G., Ramsauer, D., & Hofmann, R. (2022). Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems. Applied Sciences, 12(14), Article 6981. https://doi.org/10.3390/app12146981
E302-03 - Forschungsbereich Industrielle Energiesysteme E191-03 - Forschungsbereich Automation Systems
Number of Pages:
digital twin platform; digital twin requirements; industrial energy systems; integrated energy systems; service engineering; service-oriented architecture
Digitalization and concepts such as digital twins (DT) are expected to have huge potential to improve efficiency in industry, in particular, in the energy sector. Although the number and maturity of DT concepts is increasing, there is still no standardized framework available for the implementation of DTs for industrial energy systems (IES). On the one hand, most proposals focus on the conceptual side of components and leave most implementation details unaddressed. Specific implementations, on the other hand, rarely follow recognized reference architectures and standards. Furthermore, most related work on DTs is done in manufacturing, which differs from DTs in energy systems in various aspects, regarding, for example, multiple time-scales, strong nonlinearities and uncertainties. In the present work, we identify the most important requirements for DTs of IES. We propose a DT platform based on the five-dimensional DT modeling concept with a low level of abstraction that is tailored to the identified requirements. We address current technical implementation barriers and provide practical solutions for them. Our work should pave the way to standardized DT platforms and the efficient encapsulation of DT service engineering by domain experts. Thus, DTs could be easy to implement in various IES-related use cases, host any desired models and services, and help get the most out of the individual applications. This ultimately helps bridge the interdisciplinary gap between the latest research on DTs in the domain of computer science and industrial automation and the actual implementation and value creation in the traditional energy sector.
5D Digital Twin für industrielle Energiesysteme: 881140 (FFG - Österr. Forschungsförderungs- gesellschaft mbH)
Information Systems Engineering: 20% Climate Neutral, Renewable and Conventional Energy Supply Systems: 80%