Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems

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

“…A relatively low number of papers can be found in the literature addressing DTs in the energy domain [38]. In a current literature review by Kaiblinger et al [39], only 5 % of evaluated DT case studies could be attributed to the energy domain, which is inline with the findings of Yu et al [11] and Sleiti et al [37]. Regarding application scenarios, DTs are mostly represented in the area of prognostics and health management, while Tao et al [9] found that the areas of DTs in dispatching optimization and operational control are currently underexplored but very promising.…”

“…The estimation of stage of charge and aging state of storage devices as well as the cloud-based interconnection of multiple units to enhance computational abilities and overall operation management were highlighted. A recent summary of the modest amount of DT development in the area of power generation was given by Sleiti et al [37], including electricity generation, power distribution, the renewable and nuclear power industry, and the energy vehicle and storage sector. They concluded that while the energy industry is actively pursuing the tremendous opportunities of DT, most articles did not include details on the comprehensiveness of their DTs or details on the used models and enabling technologies.…”

“…Performance issues (B3) cannot be solved alone by large computational capacities but include aspects of standardization and scalability. Standardization will facilitate the interoperability of new and existing supporting software [37]. Only when standardization is achieved can DT really thrive in the energy sector due to the easy exchange of information and models.…”

“…Neto et al [73] summarized and identified four features of digital twins based on the literature, including digital modeling, analytical support, timeliness update and control. Sleiti et al [37] stated seven requirements for their DT architecture for power plants.…”

“…Other examples include DTs for decision making in energy system design [32] and, during operation, the application of DTs for wind turbines [33] and for scheduling [34] and state estimation [35], to name just a few. Only recently, the transfer of the DT concept to thermal IES has begun [36,37]. For a complete overview of existing DT research and industrial application, we refer interested readers to the current literature review by Liu et al [18].…”