Abstract:The aim of this paper is to assess the use of an intelligent glass envelope in the refurbishment of existing buildings in Italy in order to fit their energetic performance considering Mediterranean climate inputs. With the new European and Italian regulations on energy efficiency of buildings, envelopes are not only forced to respect heat transmission limits (e.g. U value) and to improve their thermal insulation, but also to use and receive benefits from environmental input such as passive solar gains. Comparing to the North European solutions, a glass envelope seems not to be the most suitable solution for a Mediterranean climate, mainly due to the great incidence of solar gains and the risks of overheating during summer season. Examples presented in this paper indicates how double skin glass façades, that are commonly used in new constructions where the concept starts from a low environmental impact, can be also employed in the refurbishment of existing buildings, which is the main challenge for the global reduction of CO 2 . An overview on the main technical of intervention can indicate to architects and planners the weakness/strength points to take in consideration in the use of a double layer glass façade in a Mediterranean climate in order to reduce the overall energy balance.
Analyzing urban districts to promote energy efficiency and smart cities control could be very complex as big data have to be analyzed filtered to discover unpredictable patterns. Using clustering method, specifically K-means algorithm, allows to create an energy profiling characterization of urban district models with multiple advantages: as first, large quantity of data can be managed and synthesized, easing the creation of algorithm patterns that could be replicable. Thus, it is possible to operate in a large scale and in a small scale in the same time, choosing the level of detail that is more appropriate for the specific analysis. In the large scale, the disadvantages are the dependence from data, i.e. if there are missing input values, it is hard to rebuild them because of the quantity of data. Missing values can confuse the analysis because scripts cannot identify the entire row missing it. Working with clustering analysis it is thus useful when large amount of data should be organized and interpreted and the technique can help the planner to make faster the analyses process. The research aims at demonstrate the efficiency of clustering methods when adopted for energy consumption issues at city level. In the paper, the clustering process concerning building energy profiles of a European city for the identification of building models is described. This means that an energy template on urban scale is used and clusters are applied on energy profiles based on architectural and energy similarity in order to find representative models. In particular, the study is focused on the relationships between building characteristics and actual building energy profiles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.