Quantum Computing


  • Increase energy efficiency through more accurate modeling of the energy system and its uncertainties (uncertain input variables of the energy system, uncertainty regarding price development), incorporation of uncertainties into the planning phase for more efficient use of resources, reduction of lead time towards a real-time energy economy (increasing challenges for a (cost-)efficient and sustainable energy supply require faster solving of more complex models).
  • Exploitation of quantum computing for the cross-sectoral energy sector and there especially electromobility.
  • Demonstration of the advantages of quantum computing in real applications in the energy sector (quantum advantage).
  • Selection of suitable quantum computing hardware (superconducting qubits, trapped ions, neutral atoms, silicon nanodots (artificial atoms), etc.), suitable algorithms (hybrid quantum-classical algorithms such as QAOA and VQE, pure quantum algorithms such as Grover search algorithm), the dimensionality of the information carriers (two-dimensional qubits or multi-dimensional quudits) and suitable problem formulation based on the customer-specific problem.
  • Awareness raising (lack of understanding and intuition) for the general public, energy sector stakeholders, and engineers and computer scientists working in the energy sector.

Our solution and research work

  • Research on the solution of optimization problems by means of Quantum Computing using IBM's Quantum Computer (superconducting qubits) in Ehningen, Germany and the experimental setup of the University of Innsbruck (Dr. Ringbauer) based on trapped ions (qubits) and suitable emulators of Quantum Computers.
  • Problem specific adaptation and improvement of Quantum Algorithms to achieve Quantum Advantage.
  • Solving optimization problems considering the unpredictability/uncertainty of renewables, e.g., photoelectricity, using Quantum Computing.
  • Simultaneous optimization for minimum cost and minimum emission (multi-objective) charging and discharging (bidirectional charging) of electric vehicles.
  • Investigation of robust quantum optimization approaches.
  • Investigation of possible quantum-based computing approaches for energy time series prediction.
  • Investigate industry partners' problems for a Quantum Advantage and implement it on a quantum computer.

Research for the future

Our innovative research projects in quantum computing:



The QApps initiative was officially launched. Funded by the Saxon State Ministry of Science, Culture and Tourism, the prerequisites are created to realize competitive advantages through quantum computing together with industrial partners. This includes access to physical quantum computers, a high-performance computing cluster for simulations, integrations of manufacturing machines and a co-working space.



Energy modeling Formulation of the fundamental model in different complexity levels, qubit formulation, stochastic modeling and evaluation on alternative hardware architectures.



The vision of NeQST is to leverage recent advances in the control of d-level quantum systems, qudits, in order to generate foundational breakthroughs throughout the full value chain of quantum computing.