Multicriteria adjustable regret robust optimization for building energy supply design

In this work, the task of designing a building's energy supply is studied. The problem is examined under the aspect of conflicting goals (monetary and environmental goals) and uncertainties. Uncertainties can lie in future prices of energy, e.g., gas and electricity. The problem is modeled as an adjustable robust multicriteria optimization problem, considering worst-case cost regret as the monetary goal and carbon emissions as the environmental goal. We provide a full overview of the possible trade-offs, where single points are computed using an ɛ-constraint approach in combination with a specialized column or column and constraint generation algorithm. The model, a solution strategy, and different scenarios for a case study are presented and discussed. In an example, it is demonstrated that the worst-case regret can be reduced by 12% compared to results that are found with a non-robust approach.