DECARBONISATION OF BUILDING STOCK: DATA ANALYSIS TECHNIQUES TO EXTRACT USEFUL INSIGHTS FOR THE SUPPORT OF RENOVATION PROCESSES (original) (raw)

The identification of techno-economically feasible decarbonisation paths and sustainability transitions for the built environment is a necessary task for research today and building stock renovation processes can act in synergy with innovative economic and technological development paradigms to achieve different types of benefits such as economic growth and employment, together with resource efficiency and sustainability for the whole sector. The research presented aims at selecting the most relevant data analysis processes and techniques to respond to practical technical questions and to support decision-making in the built environment, at multiple scales of analysis, from individual buildings, to building stock and urban environment. The research aims to indicate in this way the possibility to join the micro-scale view, involving technological and behavioural issues in buildings, and the macro-scale view, involving strategic problems at market and policy levels for energy and sustainability planning. Further, the combined use of modelling techniques with large scale data acquisition and processing could guarantee multiple feed-backs from measured data, useful for the evolution, first of all, of design and operation practices in building but also, more in general, of the whole value chain of the sector. A synthesis and integration of modelling methodologies is presented through case studies, showing a path to improve transparency of performance assessment across building life cycle phases. Finally, multivariate data visualization techniques are presented to ease the use of the numerical techniques described, ensuring a wider applicability. 1 INTRODUCTION Buildings have a great impact in terms of carbon emission at the EU [1], US and global scale [2]. At EU level, for example, building accounts for approximately 40% of carbon emission, determined by their direct energy use, and a larger impact if we consider the direct and indirect use of resources. Different modelling approaches at the state of the art can be used for extracting useful insights for the support of building stock renovation processes, dealing with relevant technical issues. A detailed discussion on the suitability of energy modelling approaches with respect to multiple criteria can be found in literature [3]. Energy efficiency measures can create multiple advantages [4], but the increase of efficiency of energy systems strengthens the interdependency between design and operational optimization with an impact at multiple scales, from individual technologies, to single buildings, to building stock and infrastructures. This higher interdependency determines the need for formalized rules in optimization based approaches for energy research and practical applications [5], as well as the need for larger quantities of specific data for effective deployment of innovative strategies for built environment [6]. For this reason, a tight integration and comparability among different models is the focus of research. We should be able to pass from models to simulated data (model output, forward approach) and from measured data back to models (model input, inverse approach), in multiple ways, implementing effectively cycles of continuous improvement.