Ottimizzazione multi-obiettivo per l’efficientamento energetico di edifici in clima caldo e temperato

In the light of the European and national regulations on the buildings energy performance, the designer comes up today against the need to choose among alternative technological solutions for the energy efficiency, having to assess their effectiveness according to several -sometimes conflicting- points of view, such as the energy saving, the indoor comfort, the environmental and economic impact. The problem of "multi-objective optimization", treated for centuries in different fields (e.g. through the Pareto efficiency approach), can be effectively addressed today to seek the optimum design solutions by varying several parameters through the use of stochastic algorithms, that explore the range of solutions with a probabilistic approach at a high computational efficiency. Several studies describe cases of multioptimization for buildings design, applying stochastic methodologies and in relation to multiple objective functions. However, few studies include the assessment of the economic aspects (life cycle costing) or the evaluation of thermal comfort and of cooling energy consumption in summer season, aspects that could lead to re-evaluate the convenience and effectiveness of applying outermost solutions to limit heating consumption in hot and temperate climates. This paper reports the results of the application of genetic algorithms -a class of stochastic algorithms- to solve a multiobjective optimization problem in a building energy retrofit intervention in warm and temperate climate. In particular, by means of the algorithm implemented in jEPlus + EA, integrated to the dynamic energy analysis software EnergyPlus, we looked at the design solutions able to simultaneously maximize the performance of the building in terms of energy consumption, indoor summer comfort and global costs in the life cycle. The results, even if related to a particular case-study, suggest the optimal efficiency measures, whose robustness was tested in different Italian climatic zones.