Project Details
Description
TWIN-POWER aims to develop an advanced digital twin and optimization platform to support design and operation of sustainable power and propulsion systems for UK and global fleets. The project integrates deep learning–based digital twin, trained on high-frequency operational data, to generate time-dependent power demand and fuel consumption profiles under realistic operating conditions. These outputs feed multi-criteria feasibility platform evaluating innovative power technologies against technical, economic, environmental, and regulatory criteria. A time-dependent optimization framework then identifies optimal hybrid power system configurations and operational strategies. TWIN-POWER enables data-driven, stakeholder-informed decisions to improve performance, fuel optimal use, and decarbonisation outcomes.
| Short title | TWIN-POWER |
|---|---|
| Status | Not started |
| Effective start/end date | 1/05/26 → 31/10/26 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
-
SDG 6 Clean Water and Sanitation -
SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 13 Climate Action -
SDG 17 Partnerships for the Goals
Keywords
- Digital Twin
- Multi-Criteria Optimization
- Ship Power systems
- Propulsion Systems
- Deep Learning
- Decarbonisation
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.