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.

A methodology to assess and improve the impact of public energy policies for retrofitting the building stock: Application to Italian office buildings

DE STASIO, Claudio;Mauro G. M.
;
VANOLI, Giuseppe Peter
2016-01-01

Abstract

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.
2016
Building energy retrofit; Building stock; Dynamic energy simulations; Energy policies; Representative building sample
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/41289
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? ND
social impact