A fuzzy robust multi-objective optimization model for building energy retrofit considering utility function: A university building case study

Abstract The majority of energy sources are limited and non-renewable and will soon be depleted if overused. One of the world's significant energy consumers is the building sector, which also is accounted for a considerable amount of GHG emissions. This study uses mathematical modelling to find the best strategy for building energy retrofit. The multi-objective optimization model takes into account economic criteria such as profit, initial cost, and payback period, as well as environmental objectives such as energy-saving and the use of clean and renewable energy. On the other hand, unlike many previous studies in which the mathematical models consider specific parts of the building, the generalized mathematical model of this study can examine any desired parts of the building for the decision-maker and add new items to enhance energy efficiency. Besides, the problem is investigated and solved with certain and uncertain parameters to determine the impact of uncertainty on the results, which is closer to reality. In this study, an actual university building is simulated to evaluate the model's validity by implementing the obtained energy retrofit strategy on the simulated building, which led to a 40% decrease in energy consumption. The results indicate that the presented model can find the best possible strategy to improve energy efficiency and significantly affect buildings' energy saving.