Testing methods of quantum computing and quantum communication in the energy sector.

Challenges

  • Need to take into account nonlinearities and uncertainties in the power system e.g. due to nonlinear processes in power plants (efficiency dependencies) or nonlinear optimization problems (avoiding peak loads in EV fleet charging management) as well as increased influence of stochastically fluctuating renewable energies.
  • Solving difficult mixed integer (nonlinear) optimization problems using continuous or binary variables instead of integer variables.
  • Decreasing security of current communication encryption due to the development of quantum computers.

Our solution and research work

  • Development/improvement of algorithms for solving mixed integer optimization problems using integer variables in the form of QuDits (quantum mechanical multilevel state systems) and binary variables in the form of QuBits (two-level state systems) [EnerQuant and NeQST projects].
  • Exploration of suitable quantum mechanical models and algorithms for solving optimization problems considering uncertainties. [NeQST and EnerQuant.]
  • Exploring probabilistic prediction methods with quantum computers. [EnerQuant]
  • Exploring the potential applications of quantum-based encryption methods. [Quantum Hub Thuringia]
  • Investigation of improvement potentials of classical encryption methods by using single quantum-based methods. [Quantum Hub Thuringia]

Quantum computing for intelligent charging of electric vehicles.

Quantum Hub Thüringen

Podcast »E-Autos schlauer laden durch Quantencomputer«