Towards zero emission building by refurbishment: A multi-criteria decision-making approach

With each revision of the Energy Performance of Buildings Directive (EPBD), the requirements for both new and refurbished buildings have become increasingly demanding, driven by the need to reduce CO2 emissions, lower energy dependency, and enhance user comfort. Fortunately, the market now offers a wide range of solutions to meet these goals both through the use of passive (different envelopes) and active (HVAC systems) measures. In this context, optimization algorithms play a key role in identifying optimal design strategies. However, there is no single solution that satisfies the regulatory requirements, and additional factors such as initial investment, operational costs, and user comfort, among others, can lead to significantly different results. This research proposes a hybrid approach that combines multi-attribute decision-making algorithms with multi-objective optimization algorithms in the search for optimal solutions that take into account both regulatory requirements and user-specific criteria. Through the analysis of a real case study, a four-dwelling building in the south of France, the research shows the different configurations and objectives of the optimization algorithm used, the Non-Sorting Genetic Algorithm II (NSGA-II), as well as the key performance indicators (initial investment, operational cost, CO2 emissions, comfort, etc.) used by the multi-attribute decision making algorithm, TAMARIN, that help to select the most suitable solution for the user.