Statistical analysis of the heating demand in residential buildings located in Mediterranean climate and proposals for refurbishment

The latest horizon for the construction sector is the achievement of nearly zero en-ergy buildings by means of several procedures indicated in apposite design guidelines. The involved methods concern the improvement of the building envelope and/or the in-tegration of high efficient heating/cooling systems supplied by renewable sources. Therefore, new buildings will be conceived in accordance with modern construction techniques in order to minimize costs for the air conditioning, whilst also guaranteeing internal comfort conditions. However, these actions on new buildings will provide lim-ited environmental advantages as they take only 2% of the whole building stock into ac-count. Consequently, suitable actions for existing buildings are recommended. Regard-ing existing envelopes located in South Italy, buildings built before 1960, prior to the introduction of mandatory energy consumption limitation standards, constitute the larg-est part. Moreover, the majority of these buildings have never undergone refurbishment actions and many of them are classified as historic buildings. The real challenge for the future is the possibility to achieve appreciable energy savings in these buildings without sacrificing thermal comfort. The paper deals with the investigation of the heating energy consumptions of a sample of residential buildings located in South Italy, more precisely in the region of Calabria, which is located in the heart of the Mediterranean Sea. A sur-vey for the collection of data concerning the energy performance certificates, the physi-cal characteristics of the envelopes and of the air-conditioning plants, as well as the real consumption of the involved primary sources, was conducted for a sample of buildings spread across the whole region. In the first phase of the investigation, the energy perfor-mances and the construction characteristics of the examined buildings are presented. In the second phase, a statistical analysis developed with the SPSS software and aimed at the identification of the main parameters that affect the heating energy requirements, is developed. Finally, by means of a multiple regression analysis, a general correlation to use for the prediction of heating energy consumption to apply in existing buildings is presented. Therefore, designers could use the obtainable results in order to identify the suitable action strategies for the retrofitting of buildings in the considered area.