No abstract

The building energy performance pattern is predicted to be shifted in the future due to climate change. To analyze this phenomenon, there is an urgent need for reliable and robust future weather datasets. Several ways for estimating future climate projection and creating weather files exist. This paper attempts to comparatively analyze three tools for generating future weather datasets based on statistical downscaling (WeatherShift, Meteonorm, and CCWorldWeatherGen) with one based on dynamical downscaling (a future-typical meteorological year, created using a high-quality reginal climate model). Four weather datasets for the city of Rome are generated and applied to the energy simulation of a mono family house and an apartment block as representative building types of Italian residential building stock. The results show that morphed weather files have a relatively similar operation in predicting the future comfort and energy performance of the buildings. In addition, discrepancy between them and the dynamical downscaled weather file is revealed. The analysis shows that this comes not only from using different approaches for creating future weather datasets but also by the building type. Therefore, for finding climate resilient solutions for buildings, care should be taken in using different methods for developing future weather datasets, and regional and localized analysis becomes vital.

The EN ISO 52016-1:2018 technical standard has introduced a new simplified dynamic method for the calculation of the building energy need for heating and cooling. This new procedure combines a low amount of input data required, as for the previous quasi-steady and dynamic simplified methods of the withdrawn EN ISO 13790 standard, with an increased accuracy, which would reduce the gap with detailed dynamic methods. This work is part of a broader research activity aimed at investigating the new simplified dynamic model and highlighting its strengths and weaknesses, in terms of accuracy and robustness. Specifically, the work addresses the parameters that have a great influence on the final results and the effects of uncertainties in input data. To this purpose both standard and tailored energy performance assessments have been applied, in particular in the first one a continuous operation period of the space heating system was supposed, and in the second one an intermittent operation system was chosen. A sensitivity analysis was also carried out to quantify the variation of the heating and cooling loads with the set-point temperature, the windows physical properties, the heat capacity and the thermal transmission properties of opaque components, as well as the occupancy related input parameters, such as the internal heat gains and the ventilation flow rate. The analysis was applied to a multi-unit residential building located in Rome and built in the first half of the 20th century. The results outline absolute relevance of the set point temperatures. The significance of occupant behaviour and the importance of the correct definition of the component thermal properties is also pointed out through the comparison between the standard and tailored assessments.

Abstract. Downtime -as the time necessary to restore a system's functionality-is