Development of a Decisional Procedure Based on Fuzzy Logic for the Energy Retrofitting of Buildings

Linda Barelli, Elisa Belloni, Gianni Bidini, Cinzia Buratti and Emilia Maria Pinchi
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Linda Barelli: Department of Engineering, University of Perugia, 06125 Perugia, Italy
Elisa Belloni: Department of Engineering, University of Perugia, 06125 Perugia, Italy
Gianni Bidini: Department of Engineering, University of Perugia, 06125 Perugia, Italy
Cinzia Buratti: Department of Engineering, University of Perugia, 06125 Perugia, Italy
Emilia Maria Pinchi: Department of Engineering, University of Perugia, 06125 Perugia, Italy

Sustainability, 2021, vol. 13, issue 16, 1-17

Abstract: This paper concerns the development of an automatic tool, based on Fuzzy Logic, which is able to identify the proper solutions for the energy retrofitting of existing buildings. Regarding winter heating, opaque and glazing surfaces are considered in order to reduce building heat dispersions. Starting from energy diagnosis, it is possible to formulate retrofitting proposals and to evaluate the effectiveness of the intervention considering several aspects (energy savings, costs, intervention typology). The innovation of this work is represented by the application of a fuzzy logic expert system to obtain an indication about the proper interventions for building energy retrofitting, providing as inputs only few parameters, with a strong reduction in time and effort with respect to the software tools and methodologies currently applied by experts. The novelty of the paper is the easy handling properties of the developed tool, which requires only a few data about the buildings: not many such methods were developed in the last years. The energy requirements for winter heating before and after particular interventions were evaluated for a consistent set of buildings in order to produce the required knowledge base for the tool’s development. The identified appropriate inputs and outputs, their domains of discretization, the membership functions associated to each fuzzy set, and the linguistic rules were deduced on the basis of the knowledge determined in this was. Therefore, the system was successfully validated with reference to further buildings characterized by different design and architecture features, showing a good agreement with the intervention opportunities evaluated.

Keywords: building design and architecture; energy retrofitting; energy efficiency in buildings; energy diagnosis; fuzzy logic (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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