Mauro, Gerardo Maria (2015) Multi-objectvice optimization for cost-optimal energy retrofitting: from the single building to a stock. [Tesi di dottorato]

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Abstract

The energy retrofitting of the existing building stock is a key strategy to achieve tangible results in the reduction of worldwide energy consumption and, thus, polluting emissions. However, the path is very challenging. Indeed, the design of the building energy retrofit is a complex and arduous task, which involves two distinct perspectives: the collective (state) one, interested in energy savings, and the private (single building) one, interested in economic benefits. The Energy Performance of Buildings Directive Recast (2010/31/EU) aims to harmonize such perspectives by prescribing the cost-optimal analysis in order to detect the best packages of energy retrofit measures. This procedure yields a series of critical, still-open questions that have aroused a heated discussion in the scientific community. Among them, the main questions, identified in this study, can be outlined as follows: How to perform a reliable cost-optimal analysis of the retrofit measures for a single building? How to achieve global indications about the cost-optimality of energy retrofitting the existing building stock? How to evaluate the global cost of a building with a minimum computational time and a good reliability? A definitive and robust answer to these questions is fundamental to overcome the main obstacle to the large diffusion of the cost-optimal retrofitting practice. Such obstacle can be summarized in a last crucial question that includes the previous ones: How to perform a reliable, fast, 'ad hoc' cost-optimal analysis of the energy retrofit measures for each building of the stock? So far, the scientific literature did not propose a full and complete response to such critical questions. This thesis aims to provide a thorough answer to the aforementioned questions, by means of an original approach that handles all the issues involved in a robust and reliable cost-optimal analysis, achievable for every single building with an acceptable computational burden and complexity. Three novel methodologies (CAMO, SLABE, building energy simulation by ANNs) have been developed for proposing a complete response to the first three questions and, then, they are combined in a macro multi-stage methodology (CASA) that solves the final fundamental question, which represents the last step towards a wide-spread cost-optimal building retrofitting. The methodologies are tested by means of the application to different case studies. CASA is a step towards sustainability.

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