Digital Twins How can digital twins be integrated into the operational routine of an energy system to ensure a resource-efficient and resilient energy supply in the future?
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.
What are Digital Twins?
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.
Definition
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:
- Purposefulness: The goal of every digital twin is to fulfil a predefined purpose. The functional scope of the digital twin is sufficient once the purpose is achieved. While a higher level of detail is possible, it is not necessary.
- Real-time: The digital twin's functionalities are bound to real-time, i.e., within a specified time frame, requirements. The size of this time frame depends on the digital twin's purpose.
- Observers and manipulators: The digital object receives data from the physical object through observers and, in turn, influences the physical object using manipulators. These may include sensors and actuators that automatically transmit data and perform tasks. However, the broader concepts of observers and manipulators also allow for broader possibilities for data acquisition and task execution. For example, external systems not associated with the physical object and humans (human-in-the-loop) can contribute to data acquisition as long as the real-time requirements are satisfied.
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.
Overview of Use Cases
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:
- Optimized plant performance: Digital twins enable precise plant modelling for optimal performance.
- Prediction and planning: Precise predictions and simulations allow for the analysis of future scenarios and the development of strategies.
- Effective maintenance: Real-time monitoring enables early problem identification and preventive maintenance.
- Resilient control and monitoring of complex systems: Real-time integration with telecontrol technology and a digital twin combined with automation and virtualization, allows for improved anticipation and enhanced flexibility utilization, making complex systems, such as energy supply systems, more resilient to operate. Learn more...
Innovation Goals
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:
- Event-driven processing
- Modularity and flexibility
- Scalability
- Open-source availability
- CGMES support (for energy-related use cases)
- Definition and information exchange via administration shells
- Hierarchical/nested digital twins
Persons
- Dr. Michael Brand (Contact Person)
- Jelke Wibbeke (Contact Person)
- Amit Kumar Singh
- Nils Huxoll
- Amin Raeiszadeh
Projects
Publications
- Digital Twin Architecture and Technologies for Hydrogen Electrolyser Applications
- Optimal Temperature-Based Condition Monitoring System for Wind Turbines
- Power Systems Digital Twin under Measurement and Model Uncertainties: Network Parameter Tuning Approach
- Wind Turbine Failure Prediction Model using SCADA-based Condition Monitoring System
- Measurement-based Modeling of Distribution Grid Dynamics: A Digital Twin Approach
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Projects
Publications
2024
Applying Trust for Operational States of ICT-Enabled Power Grid Services
Michael Brand, Anand Narayan, Sebastian Lehnhoff; April / 2024
Modelling the propagation of properties across services in cyber-physical energy systems
Anand Narayan, Michael Brand, Nils Huxoll, Batoul Hage Hassan, Sebastian Lehnhoff ; March / 2024
Poster Abstract: A Digital Twin Platform Applied to Hydrogen Electrolyzers
AMIT KUMAR SINGH, JELKE WIBBEKE, AMIN RAEISZADEH, NILS HUXOLL, MICHAEL BRAND; DACH+ Conference on Energy Informatics 2024; October / 2024
Resilience Quantification of Interdependent Power and ICT Systems using Operational State Classification
Anand Narayan; July / 2024
2023
ASSESS – Anomaliesensitive State Estimation mit Streaming Systemen in Smart Grids
Michael Brand; December / 2023
Assess: anomaly sensitive state estimation with streaming systems
Brand, Michael and Engel, Dominik and Lehnhoff, Sebastian; Energy Informatics; 2023
Demo Abstract: IT Platform for Provision of Ancillary Services from Distributed Energy Resources
Payam Teimourzadeh Baboli, Amin Raeiszadeh, Michael Brand, and Sebastian Lehnhoff; DACH+ Conference on Energy Informatics, Vienna, Austria; 2023
Impact of ICT Latency, Data Loss and Data Corruption on Active Distribution Network Control
Klaes, Marcel and Zwartscholten, Jannik and Narayan, Anand and Lehnhoff, Sebastian and Rehtanz, Christian; IEEE Access; 2023
Poster Abstract: Algorithms for Condition Monitoring of Complex Power Electronic Systems in Photovoltaics
Loeffler, Dominik; Abstracts of the 12th DACH+ Conference on Energy Informatics 2023; October / 2023
Poster abstract: modeling of resilient state estimation in cyber-physical energy systems
Hage Hassan, Batoul and Brand, Michael and Lehnhoff, Sebastian; Abstracts of the 12th DACH+ Conference on Energy Informatics; 2023
