Welcome to ReSE-Lab:
Data-Driven Strategies for Intelligent Resilient Renewable Energy Systems Under Wartime Conditions
Project Reference: 100714621
The project explores intelligent resilient renewable energy systems under conditions of war or physical attack — a topic of paramount importance for Ukraine and an increasingly pressing concern for the EU.
The information-science approach relies on methods such as digital twins, data analytics, and machine learning, forming the basis of a long-term German-Ukrainian research collaboration in „Smart Energy and Artificial Intelligence“.
Project Information
What you should know about the project?
01.11.2026-31.10.2029
Project type:
Funded by the Federal Ministry of Research, Technology and Space (BMFTR) within the framework of the German-Ukrainian research cooperation for sustainable reconstruction. Project reference: 100714621.
Grant holder:
Dortmund University of Applied Sciences and Arts (FH Dortmund)
Project Coordinator:
Carsten Wolff
Contact:
Anzhelika Parkhomenko
What is our scope, goals, and outcomes?
Core Objectives
The objective of the project is to develop a set of solutions for each of the four phases of the resilience model: prevention of energy system failures (Prevention), support of the operation of (sub)systems (Survivability), (self)recovery (Self-healing) and integration of new knowledge into the system (Adaptation and Learning). The following results are expected to be achieved:
- A joint German-Ukrainian research center on intelligent resilient renewable
energy systems will be established. - Pilot projects, digital twins of system components, and a data integration and analysis platform will form the basis of a virtual laboratory for the design, analysis, and operation of energy systems (Resilient Smart Energy Lab, ReSE-Lab), which will serve as a long-term shared research infrastructure for the partners.
Work packages
- Work Package 1: Scenario Development & Digital Twin
- Work Package 2: Development of the Data Integration and Analysis Platform
- Work Package 3: Digitalisation (Physical Twin) in Campus Projects
- Work Package 4: Fault Detection & Condition Monitoring
- Work Package 5: ML-based Survival Strategies: Partitioning & Islanding
- Work Package 6: Self-Healing: Multi-Agent System & GA
- Work Package 7: Federated Learning, Optimisation & Decision Support
- Work Package 8: Integration with the Virtual Lab and Open Data Portal
- Work Package 9: Dissemination, Exploitation & Networking
- Work Package 10: Project Management
Who is working on the project?
- Dortmund University of Applied Sciences and Arts (Fachhochschule Dortmund), Dortmund, Germany
- National University “Zaporizhzhia Polytechnic” (NUZP), Zaporizhzhia, Ukraine
- West Ukrainian National University (WUNU), Ternopil, Ukraine
Where is our working space?
To enter Nextcloud (is following)
NextCloud – content online collaboration platform
To enter Confluence (is following)
Confluence – collaboration wiki tool
To enter Moodle (is following)
Moodle – learning management system
Funded by
News
The new research project, funded by the Federal Ministry of Research, Technology and Space (BMFTR)
Contact
Anzhelika Parkhomenko
anzhelika.parkhomenko@fh-dortmund.de