Pareto navigation for multicriteria building energy supply design

The design of a building's energy supply is a difficult task, where uncertainty in the requirements has to be taken into account and different conflicting objectives have to be optimized. To date, there exist various studies that consider different objective functions, different concepts of dealing with uncertainty, and different approximation techniques to find efficient solutions. However, there is no approach that gives the decision maker a complete overview of all trade-off solutions with their immediate consequences for the design configuration. This paper addresses the question of how much money and carbon emissions can be saved by allowing a certain amount of undersupply in the heating and cooling of an office building. To explore the trade-offs between the three objectives of minimizing cost, carbon emissions and inconvenience, the Pareto front of the multicriteria linear program is approximated with a Sandwiching algorithm. Then, it is explored using Pareto navigation. This allows to see all (approximate) Pareto points and also to visually observe the behavior of the decision variables by navigating across the front by pulling sliders in a specific software. In a case study, the navigation is demonstrated and ways to overcome modeling limitations that arise from using a fully linear programming approach are shown.