TRF4.0
Transformer 4.0 – Digital revolution of power transformers Systems Engineering and Management
Description
The MIT-Pt flagship project Transformer4.0 (TRF4.0), aimed at developing a novel concept for the digital twin of a complex energy grid device, was finished in 2023. The project was led by EFACEC, a Portuguese company operating in the energy, engineering and mobility sectors, that aimed at digitalising the life cycle of a complex product - the Power Transformer. The central developing concept was the Digital Twin of this product that, as the virtual counterpart of the physical system, enabled innovative approaches in the transformer design and manufacturing with new data and information management models and offered new added value services, such as intelligent condition monitoring, preventive maintenance, ageing evaluation conditions, among others.
A Digital Twin-enabled platform, powered with optimization and artificial intelligence tools, enables valuable insights about designing future products and predicting the system’s response to different types of disruptions in the grid. Furthermore, digital manufacturing will be explored through additive manufacturing, which has the potential to revolutionize the design and manufacturing of some power transformer parts. This feature, integrated with the Digital Twin platform, will foster disruptive business models for these products.
TRF4.0 joins complementary research competencies: EFACEC, as a manufacturer of power transformers, INESCTEC (computer science, industry and innovation) and INEGI (mechanical and industrial engineering) as Portuguese research institutes and the MIT’s Sociotechnical Systems Research Centre, enabling a comprehensive and multidisciplinary research programme. Although this sector has been a conservative innovator, the proposed research project prepared the conventional power transformers for the complex challenges, trends, needs and opportunities of a fast-evolving Energy 4.0 sector.
Scientific Advances
TRF4.0 proposed the following advances:
- Digitalize the power transformer product lifecycle by developing its digital-twin concept.
- Design Knowledge-Based Engineering processes and techniques supported by digital twin-based digital platform.
- Supporting the creation and evolution of new products and services based on the digital twin.
Impact
The research tasks which INESC TEC participated produced the following results:
1. Knowledge-Based Engineering & Product-Service System Design Supported by the Digital-Twin
- An innovative Digital Platform concept was developed to manage the Digital Twin instances (DTbDP), integrating the relevant information for the digitalisation of the PT: models (e.g. engineering models), data (e.g. historical data describing performance), documents (e.g. maintenance reports);
- Rethinking of the engineering design processes using the DTbDP.
- A genetic algorithm-based recommendation system for new power transformer product-service features.
- DTbDP approach to a Model-Based Systems Engineering environment, where modelling and simulation have a stronger presence.
2. Tools for Digital-Twin-based Life-Cycle Management
- Shoopfloor and Welding Construction Traceability System.
- Tools for Optimization and Assisted Operation: Dynamic Load and Ageing Models, DGA Monitoring, Health Index Models.
3. Sociotechnical Design Theory Research
- Recommended intervention strategies for the implementation of digital twin-based transformations.
- A novel sociotechnical systems analysis framework.
- Concept of operations analysis for enterprise-level digital transformation.
A Digital Twin-enabled platform, powered with optimization and artificial intelligence tools, enables valuable insights about designing future products and predicting the system’s response to different types of disruptions in the grid. Furthermore, digital manufacturing will be explored through additive manufacturing, which has the potential to revolutionize the design and manufacturing of some power transformer parts. This feature, integrated with the Digital Twin platform, will foster disruptive business models for these products.
TRF4.0 joins complementary research competencies: EFACEC, as a manufacturer of power transformers, INESCTEC (computer science, industry and innovation) and INEGI (mechanical and industrial engineering) as Portuguese research institutes and the MIT’s Sociotechnical Systems Research Centre, enabling a comprehensive and multidisciplinary research programme. Although this sector has been a conservative innovator, the proposed research project prepared the conventional power transformers for the complex challenges, trends, needs and opportunities of a fast-evolving Energy 4.0 sector.
Scientific Advances
TRF4.0 proposed the following advances:
- Digitalize the power transformer product lifecycle by developing its digital-twin concept.
- Design Knowledge-Based Engineering processes and techniques supported by digital twin-based digital platform.
- Supporting the creation and evolution of new products and services based on the digital twin.
Impact
The research tasks which INESC TEC participated produced the following results:
1. Knowledge-Based Engineering & Product-Service System Design Supported by the Digital-Twin
- An innovative Digital Platform concept was developed to manage the Digital Twin instances (DTbDP), integrating the relevant information for the digitalisation of the PT: models (e.g. engineering models), data (e.g. historical data describing performance), documents (e.g. maintenance reports);
- Rethinking of the engineering design processes using the DTbDP.
- A genetic algorithm-based recommendation system for new power transformer product-service features.
- DTbDP approach to a Model-Based Systems Engineering environment, where modelling and simulation have a stronger presence.
2. Tools for Digital-Twin-based Life-Cycle Management
- Shoopfloor and Welding Construction Traceability System.
- Tools for Optimization and Assisted Operation: Dynamic Load and Ageing Models, DGA Monitoring, Health Index Models.
3. Sociotechnical Design Theory Research
- Recommended intervention strategies for the implementation of digital twin-based transformations.
- A novel sociotechnical systems analysis framework.
- Concept of operations analysis for enterprise-level digital transformation.