Addressing Large-Scale Energy Retrofit of a Building Stock via Representative Building Samples: Public and Private Perspectives

Fabrizio Ascione, Nicola Bianco, Claudio De Stasio, Gerardo Maria Mauro and Giuseppe Peter Vanoli
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Fabrizio Ascione: Department of Industrial Engineering, Università degli studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
Nicola Bianco: Department of Industrial Engineering, Università degli studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
Claudio De Stasio: Department of Industrial Engineering, Università degli studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
Gerardo Maria Mauro: Department of Industrial Engineering, Università degli studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
Giuseppe Peter Vanoli: Department of Medicine, Università degli studi del Molise, Via Cesare Gazzani 47, 86100 Campobasso, Italy

Sustainability, 2017, vol. 9, issue 6, 1-18

Abstract: Scientific literature about energy retrofit focuses on single buildings, but the investigation of whole building stocks is particularly worthy because it can yield substantial energy, environmental and economic benefits. Hence, how to address large-scale energy retrofit of existing building stocks? The paper handles this issue by employing a methodology that provides a robust energy analysis of building categories. This is denoted as SLABE, “Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance”. It was presented by the same authors and is here enhanced to investigate a whole and heterogeneous building stock that includes various categories. Each category is represented via a Representative Building Sample (RBS), which is defined through Latin hypercube sampling and uncertainty analysis. Hence, optimal retrofit packages are found in function of building location, intended use and construction type. Two families of optimal solutions are achieved. The first one collects the most energy-efficient (and thus sustainable) solutions, among the ones that produce global cost savings, thereby addressing the public perspective. The second one collects cost-optimal solutions thereby addressing the private perspective. EnergyPlus is employed as a simulation tool and coupled with MATLAB ® for data analysis and processing. The methodology is applied to a significant share of the Italian public administration building stock, which includes several building categories depending on location, use destination and construction type. The outcomes show huge potential energy and economic savings, and could support a deep energy renovation of the Italian building stock.

Keywords: building energy performance; energy simulations; building stock; retrofit; building sampling; representative building sample; large-scale analysis; cost-optimal; public incentives (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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