No abstract

This work shows the outcomes of a research activity aimed at the energy characterization of residential users. Specifically, by data analysis related to the real energy consumption of sample buildings, the flexible loads amount has been identified so as to investigate on the opportunity to implement a demand/response (DR) program. The most meaningful input data have been collected by an on-line questionnaire created within an Excel spreadsheet allowing one to simulate and compare the calculations with the actual dwellings’ consumption; 412 questionnaires have been used as statistical sample and simulations have been performed based on single-zone dynamic model. Additionally, once the energy consumptions have been sorted by the different services, reference key performance indicators (KPIs) have been also calculated normalising those ones by people and house floor surface. From data analysis, it emerges how the Italian residential users are not very electrified. Furthermore, the flexible loads are low and, implementing minor maintenance interventions, the potential of flexibility can decrease up to 20%. For that reason, the current research can be further developed by investigating on suitable flexibility extensions as well as on the automation system requirements which is needed managing the flexible loads.

No abstract

Climate change affects the buildings’ performance, significantly influencing energy consumption, as well as the indoor thermal comfort. As a consequence, the growing outdoor environmental temperatures entail a slight reduction in heating consumption and an increase in cooling consumption, with different overall effects depending on the latitudes. This document focuses attention on the Italian residential sector, considering the current and reduced meteorological data, in anticipation of future climate scenarios. According to a sample of 419 buildings, referring to the climatic conditions of Milan, Florence, Rome, and Naples, the heating and cooling needs are calculated by a simplified dynamic model, in current and future conditions. The effects of the simplest climate adaptation measure, represented by the introduction of new air conditioners, have been also evaluated. The simulations results show an important reduction in complex energy consumption (Milan −6%, Florence −22%, Rome −25%, Naples −30%), due to the greater incidence of heating demand in the Italian context. However, the increase in air conditioning electrical consumption over the hot season (Milan +11%, Florence +20%, Rome +19%, Naples +16%) can play a critical role for the electrical system; for that reason, the introduction of photovoltaic arrays as a compensatory measure have been analysed.