Abstract
Retrofit optimization of existing buildings is one of the most relevant design activities when addressing energy efficiency and sustainability according to the guidelines of national and international policies. Optimal solutions have to be identified to save energy at a minimum global cost. To this aim, multi-objective optimization techniques coupled with building performance simulation proved highly effective and supportive of the choice of the professional and the owner. A detailed knowledge of the characteristics of the existing building and of the boundary conditions, among which weather reference data, is of paramount importance. Indeed, the definition of the intervention measures to be included in the optimal retrofits is highly affected by the representativeness of weather data. Typical Reference Years (TRY) are suitable to estimate the average behavior of the building. However, they lack of some information when it comes to sizing correctly the retrofit interventions and to assessing the resilience of the optimal building configurations to typical climatic variability in the historical weather data series. This work aims at exploring how renovation solutions optimized on TRY are affected by the climatic variability and how the outcomes of a multi-optimization process are robust to weather variability. Besides assessing the building performance in the typical conditions described by TRY, typical extreme conditions are considered, as summarized by Extreme Weather Years (ERY). Synthetic ERYs reveal to be an important tool to complement the information provided by TRY.