Project Q-NextGrid, BMFTR
Multi-Objective Quantum Optimization for Future Energy Grid Resilience
News
About this Project
The Q-NextGrid research project aims to ensure the transformation of the German electricity grid into a decentralised system dominated by renewable energy sources. The Q-NextGrid project is developing quantum optimisation methods for two key applications for distribution system operators (DSOs): firstly, for corrective measures (‘redispatch’) to eliminate grid bottlenecks and protect against overloads. Secondly, the ‘grid expansion’ use case is to be investigated and supported, so that investment in new power lines can be balanced against the associated costs, reliability and flexibility. In addition to integrating realistic DSO data, Q-NextGrid is developing quantum algorithms specifically for these multi-objective optimisation problems with constraints. Furthermore, one of the project’s objectives is to bridge the gap between theoretical quantum research and industrial application. By focusing on the energy transition, the project makes a direct contribution to security of supply and climate neutrality, as more efficient grids enable greater integration of renewable energies.
Our Consortium
E.ON Digital Technology
LMU Munich
Aqarios GmbH
E.ON Digital Technology
Since 2019, E.ON Digital Technology GmbH has been building up a specialist quantum computing team with the aim of developing industry-relevant quantum applications to support the energy transition. Key milestones include the coordination of the BMFTR-funded Q-GRID project (2022–2025) and the award of the QMPC project (2024–2026), funded by DLR-QCI/BMWK. E.ON is supporting the Q-NextGrid project in implementing the end-to-end quantum workflow pipeline for the redispatch and grid planning use cases. The aim is to develop application-specific solutions that translate real grid data into optimisation models with constraints and can be run on both simulators and real quantum hardware.
LMU Munich
Ludwig Maximilian University of Munich (LMU) is a university of excellence with proven expertise in the fields of quantum computing and optimisation methods. For the past nine years, the QAR-Lab at the Chair of Mobile and Distributed Systems has been conducting research into quantum applications in the fields of machine learning and optimization, as well as the simulation of classical physical systems. Within the consortium, LMU is responsible for the scientific development and evaluation of new multi-objective optimization algorithms, as well as their prototypical implementation in the QC-NextGrid Stack.
Aqarios GmbH
The Aqarios GmbH is a deep-tech start-up based in Munich. It was founded in 2021 as a spin-off from Ludwig Maximilian University (LMU) Munich and its QAR Lab, and now comprises an interdisciplinary team of experts with backgrounds in computer science, physics, mathematics and engineering. The company’s focus is on making quantum computing accessible for industrial applications and transforming cutting-edge research into practical tools.
Publikationen
Nüßlein, J., Roch, C., Gabor, T., Stein, J., Linnhoff-Popien, C., & Feld, S. (2023, July). Black Box Optimization Using QUBO and the Cross Entropy Method. In International Conference on Computational Science (pp. 48-55).
Contact
Please direct inquiries to the consortium to:
E-Mail: qar-lab@mobile.ifi.lmu.de
Telefon: +49 89 2180-9153
QAR-Lab – Quantum Applications and Research Laboratory
Ludwig-Maximilians-Universität München
Oettingenstraße 67
80538 München
Funded by:
Copyright © Q-NextGrid
