Public energy policies must support the deep energy retrofit of buildings in order to fight climate change and energy poverty. Assessing the impact of such policies is extremely important because the supported energy retrofit measures (ERMs) can ensure huge energy, economic and environmental benefits. However, the energy investigation of wide building stocks is very complex. This issue is here tackled by using and enhancing the methodology SLABE ('Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance'), which conducts reliable analyses of energy retrofitting building categories. SLABE employs Latin hypercube sampling to generate Representative Building Samples (RBSs), which represent the energy behaviour of the explored building stock. Then, post-processing is applied to assess the impact of proper ERMs on energy consumption, polluting emissions and lifecycle costs. Thus, the cost-optimal retrofit solutions are found in absence and presence of financial incentives, respectively. The outcomes are exploited to assess the effectiveness of current energy policies and to propose potential improvements for harmonizing the public and private perspectives. The methodology combines EnergyPlus and MATLAB®. As case study, it is applied to the Italian office building stock. The outcomes show huge potential energy and cost savings as well as polluting emission reductions.
|Digital Object Identifier (DOI):||http://dx.doi.org/10.18280/ijht.34S213|
|Codice identificativo ISI:||WOS:000389215800014|
|Codice identificativo Scopus:||2-s2.0-84994607239|
|Titolo:||A methodology to assess and improve the impact of public energy policies for retrofitting the building stock: Application to Italian office buildings|
|Appare nelle tipologie:||1.1 Articolo in rivista|