The transformation of the energy system is crucial to meet the challenges of the 21st century. A sustainable and efficient energy system is key to addressing environmental issues, resource scarcity, and the transition to renewable energy sources. However, transitioning to decentralized energy generation with an intelligent and interconnected energy infrastructure also presents many challenges.
Digital twins play a central role in the transformation phase and beyond. They enable precise modelling, monitoring, and control of the energy system. Technologically and in terms of the plurality and diversity of applications, they go beyond conventional approaches, offering a deeper understanding and better control over energy facilities and systems.
Digital twins are more than just models; they are "living" representations of physical assets in a virtual environment. By continuously capturing real-time data, digital twins enable a precise depiction of the current state of an asset or complex system. This opens up the possibility to analyse the behaviour of the asset or system, allowing for quick responses to changes.
To accomplish this, a digital twin possesses a digital object. The digital object serves as the digital representation of the physical object or system. It is a virtual entity created through comprehensive data and models, mimicking the real object in a digital environment.
It encompasses a wealth of information reflecting the state, characteristics, and behaviour of the physical object. This includes geometric data, physical parameters, operational data, sensor data, and other context-specific information. These data are continuously updated to reflect the current state of the physical object as accurately as possible. By integrating machine learning, artificial intelligence, and analytical algorithms, digital objects can comprehend complex relationships, make predictions, and respond to changes. This enables precise monitoring, control, and optimization of physical objects in real-time.
The digital object thus serves as the centrepiece of the digital twin and forms the basis for a variety of applications, which can be connected to the digital object in the form of services to utilize the information. These services are designed to perform specific tasks, functions, services, or interactions with the digital twin or the real object. The use case and purpose of the digital twin defines, which data must be available in the digital object and which services are to be used.
OFFIS defines digital twins independently of specific domains as follows:
A digital twin is the highest form of integration of the digital twin concept. It consists of a physical object and a digital object that accurately reflects the physical object to fulfil the purpose of the digital twin. The connection between the objects is bidirectional and in real-time. The digital object is updated by data from observers and reflects decisions back to the physical object, influencing it using manipulators.
Noteworthy characteristics include:
A significant advantage of this definition is the representation of passive physical objects (objects with inadequate sensors) through a digital twin. A schematic representation of a digital twin derived from the definition is shown in the following Figure.
The use case defines how a digital twin is deployed in a specific situation, what functions it performs, and what benefits it brings. Digital twins can be used, for example, for:
The ROC group is advancing the development of a reference architecture for digital twins for research and development, aiming to facilitate the creation of customized digital models, shadows, and twins. The reference architecture particularly focuses on the following properties:
Duration: 2024 - 2026
Michael Brand, Anand Narayan, Sebastian Lehnhoff; April / 2024
Anand Narayan, Michael Brand, Nils Huxoll, Batoul Hage Hassan, Sebastian Lehnhoff ; March / 2024
AMIT KUMAR SINGH, JELKE WIBBEKE, AMIN RAEISZADEH, NILS HUXOLL, MICHAEL BRAND; DACH+ Conference on Energy Informatics 2024; October / 2024
Anand Narayan; July / 2024
Michael Brand; December / 2023
Brand, Michael and Engel, Dominik and Lehnhoff, Sebastian; Energy Informatics; 2023
Payam Teimourzadeh Baboli, Amin Raeiszadeh, Michael Brand, and Sebastian Lehnhoff; DACH+ Conference on Energy Informatics, Vienna, Austria; 2023
Klaes, Marcel and Zwartscholten, Jannik and Narayan, Anand and Lehnhoff, Sebastian and Rehtanz, Christian; IEEE Access; 2023
Hage Hassan, Batoul and Brand, Michael and Lehnhoff, Sebastian; Abstracts of the 12th DACH+ Conference on Energy Informatics; 2023
Narayan, Anand and Brand, Michael and Lehnhoff, Sebastian; Energy Informatics; October / 2023