Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems

Abstract

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.

Design, Modeling and Implementation of Digital Twins

“…The objective is to create a manufacturing process capable of reducing, reusing, recycling, recovering, redesigning and remanufacturing the product level. At the production level, the objective is to reduce energy, resource consumption, toxic waste and occupational hazards [ 53 ]. Liu et al [ 47 ] address the problem of the traceability and unpredictability of quality in manufacturing processes using a DT.…”

Review of Industry 4.0 from the Perspective of Automation and Supervision Systems: Definitions, Architectures and Recent Trends

“…In a similar sense, there are examples of DT that are fed with data provided by supervision systems, for instance, to represent industrial energy facilities [134]. In fact, a very interesting application of DT, still underexploited in the literature, is derived from the visualization of data of the physical facility.…”

“…In fact, a very interesting application of DT, still underexploited in the literature, is derived from the visualization of data of the physical facility. In other words, the DT can be used to monitor the physical process or facility [11,[134][135][136][137]. On the one hand, the operator must be informed about the current state of both the physical and digital systems in order to interact with the DT [138].…”

“…On the one hand, the operator must be informed about the current state of both the physical and digital systems in order to interact with the DT [138]. Therefore, simple and efficient interaction must be achieved through the HMI of the DT [134,139]. On the other hand, a step further can be performed since the DT provides the ability to monitor the physical counterpart due to the fact that DT is fed with real information via a communication linkage [11].…”

Development of a Digital Twin Platform for Industrial Energy Systems

“…The 5D digital twin platform proposed by Kasper et al [5] builds the foundation for the modeling of the digital twin for the PBTES test rig. Kasper et al designed their platform to be implemented for industrial energy systems and divided it into five dimensions (compare Fig.…”