Simulation-based Optimization of Solar Combisystem Sensitivity Analysis at Optimum

In this paper, a solar thermal combisystem is optimized for minimal solar energy costs at specified extended fractional energy savings by applying hybrid genetic CHC - binary search optimization algorithm. An optimization potential of around 13% in terms of solar energy costs or 19 percent points in terms of extended fractional energy savings can be achieved when compared to the system configuration planned by experts. A Pareto front is built showing the optimal solar energy costs at desired energy savings of the system, or vice versa. The influence of variations of domestic hot water and space heating demand as well as geographical location on course and position of the Pareto front and optimal combisystem configuration is investigated. To determine the most important parameters and quantify their influence on the solar energy costs, methods of global sensitivity analysis are applied near the optimum.