Decarbonization energy concept selection with optimal design and operation by using quantum computing

Kurzfassung

The industrial sector is a major contributor to total energy-related CO2 emissions in Europe, making the transition of existing industrial systems toward renewable energy solutions a key priority. Decarbonization strategies focus on integrating novel energy transition concepts into existing production sites. These concepts encompass various renewable energy sources along with conversion technologies. Additionally, energy storage systems enhance flexibility and security of energy supply when incorporated into such concepts. The key challenge is to select the optimal combination of these energy components with optimal capacity and operation to meet the energy demand while minimizing both CO2 emissions and costs. This entire synthesis optimization problem is typically formulated as a mixed-integer non-linear programming problem with discrete and continuous variables that is computationally intensive to solve. A promising approach to tackle this complexity is to leverage quantum computing to optimize the selection and configuration of energy components as part of the synthesis problem, which consists primarily of binary decision variables. The decisions of the remaining continuous design and operation variables can be solved as a non-linear programming problem on classical computers. This hybrid approach is presented here and the formulation for solving binary decisions problems is discussed in detail. The results of the binary optimization problems are compared between quantum annealing (QA) and classical solvers such as Gurobi and simulated annealing. QA shows faster computation compared to the classical solvers, but the optimality gap of QA increases with increasing problem size. However, QA systems will become more fault-tolerant and powerful and can be used effectively in the future to optimize a vast range of binary decisions problems. By appropriately integrating quantum computing into the decision-making process, industrial stakeholders can explore a broader range of decarbonization scenarios faster, enabling more effective and cost-efficient energy transition strategies.