PRIN 2022 NeTS
DC Smart grids for Next generation Transportation Systems
The project in a nutshell
Transport accounts for nearly 25% of Europe’s greenhouse gas emissions and remains the top source of urban air pollution. To make cities cleaner and more livable, public transport must become more efficient and appealing.
Digital Twins (DTs) offer a new way forward. By creating real-time digital replicas of Urban Traction Electrification Systems (UTESs) and Public Transport Vehicles (PTVs), cities can monitor energy use, predict failures, and optimize performance. Powered by AI, machine learning, and big data, DTs enable smarter decisions, predictive maintenance, and a faster transition toward sustainable, connected urban mobility. This is the framework of the NeTS project, funded by the Ministry of Universities and Research (MUR) through the PRIN 2022 programme.
The project aims to:
- Identify the barriers to the implementation of UTES Digital Twins (DTs), as well as strategies to overcome them.
- Design, develop and test — both in the lab and on site — a prototype of a multifunction low cost smart meter to monitor pantograph voltage and current demand, as well as the geographical position of a PTV in UTES characterised by a rated voltage up to 1.5 kV.
- Design, develop and test an open source, multi layer, client server DT model of a UTES.
- Use the UTES DT model within two research areas: (i) the integration of DC connected generators and loads into UTESs, and (ii) the implementation of Predictive Maintenance (PM) algorithms.
Objectives
Team
The project is driven by the collaboration of three leading Italian institutions: Politecnico di Torino, University of Trento, and INRiM (Istituto Nazionale di Ricerca Metrologica).
Politecnico di Torino and the University of Trento bring together strong expertise in power systems, energy management, and digital technologies, enabling advanced modeling and optimization of electrified transport networks. INRiM complements this with its excellence in metrology and precision measurement, ensuring accuracy and reliability in all experimental and digital processes.
Learn more about the project partners and their roles on the dedicated page.
Our research has led to significant scientific contributions in the field of sustainable and intelligent urban mobility. The project’s results have been presented at international conferences and published in peer-reviewed journals, showcasing advancements in Digital Twin technologies, energy efficiency, and predictive maintenance for public transport systems.
Discover the full list of publications and learn more about our scientific achievements on the dedicated page.
Outcomes
Contacts
For more information about the project or potential collaborations, please get in touch:
Dr. Pietro Colella
Principal Investigator
Email: pietro.colella@polito.it