Abstract
This chapter summarizes a long list of research activities aimed at defining a method to assess the retrofit potential of school buildings, based on maintenance needs, energy-saving potential, and the life cycle cost of the retrofitted building. New concepts are introduced as the gained comfort cost (GCC) as well as new methods are suggested as a probabilistic approach to describe users’ behavior. Moreover, innovative methods as artificial neural networks have been employed to predict school buildings’ energy performances. The GCC is a new key performance indicator employed to compare different retrofit strategies, focusing on a single classroom. Furthermore, the retrofit potential is evaluated also for the whole school building, exploiting building information modelling (BIM) to collect and transfer information to the building energy model (BEM). This method to analyze energy savings associated with the retrofit of a school building is combined with a method to manage and forecast the running costs of building stocks. The cost forecasting method has been validated through 11 case studies. Eventually, the scale is widened to all the school buildings in Regione Lombardia and the potential energy savings are computed by artificial neural networks (ANN) and Geographical Information Systems (GIS). These methods allow to evaluate energy retrofit potential of school buildings and their life cycle costs at different scales of intervention, from the single classroom to all the buildings in a region, allowing the public decision-maker to choose the best policy for retrofitting his school building stock.
Highlights
Educational buildings account for about more than 4% of the European built stock in terms of net floor area, they represent a critical asset: because of their age and maintenance needs; even more, because of their influence in the learning performance of their students.Comfort, safety and security conditions, have a strong influence on the learning process
Thresholds of suitable internal areal heat capacity related to periodic thermal transmittance (Y ie) have been defined for school buildings envelopes ranging between 50 kJ/m2 K for Y ie ≤ 0.04; 70 kJ/m2 K for 0.04 ≤ Y ie ≤ 0.08 and 90 kJ/m2 K for 0.08 ≤ Y ie ≤ 0.12
The methodology adopted in the present study focuses on the assessment of the thermal indoor conditions into a representative unit or classroom of a school building in northern Italy, equipped with traditional envelope (Table 1) and compared to improved scenarios including refurbishment strategies
Summary
Educational buildings account for about more than 4% of the European built stock in terms of net floor area (even less, about 3%, in terms of energy consumption, BPIE 2011, and little more than 1 MToe, following Citterio and Fasano 2009), they represent a critical asset: because of their age and maintenance needs; even more, because of their influence in the learning performance of their students. European buildings are old (ENEA FIRE 2012) and, slightly less aged than the average built asset, educational buildings are even less “updated” than others This is true in Italy, where more than 40,000 buildings hosting the more than 52,000 Italian public educational institutions (Source: MIUR Open Data: an older estimation, Citterio and Fasano 2009, accounted about 43,000 buildings, from other sources) have been poorly retrofitted and maintained, in the last 50 years and scarcely adapted to innovative teaching models. Them, their feasibility and potential, and the data sources we can access and organize to enforce the evidence of our understanding, either for a more general, strategic decision, or for the optimization of a specific case study
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