The goal of the research is to propose an optimization-based methodology for the evaluation of retrofit incentives, using as a benchmark the wide data collection reported by the ENEA Italian Agency since 2007. To determine the best mix of energy retrofit measures for different areas of Italy, two Linear Programming models are proposed. The first model maximizes energy savings and the second one minimizes retrofit costs. The results show a 17% reduction in the average cost for each MW h of saved energy. More importantly, the methodology can help decision-makers appreciate how energy efficiency incentives have been used so far and how effective they could be. Furthermore, the methodology can be used for setting future incentive distribution plans.

Optimizing the distribution of Italian building energy retrofit incentives with Linear Programming

DI PILLA, LORENZA;DESOGUS, GIUSEPPE;MURA, SALVATORE;RICCIU, ROBERTO;DI FRANCESCO, MASSIMO
2016

Abstract

The goal of the research is to propose an optimization-based methodology for the evaluation of retrofit incentives, using as a benchmark the wide data collection reported by the ENEA Italian Agency since 2007. To determine the best mix of energy retrofit measures for different areas of Italy, two Linear Programming models are proposed. The first model maximizes energy savings and the second one minimizes retrofit costs. The results show a 17% reduction in the average cost for each MW h of saved energy. More importantly, the methodology can help decision-makers appreciate how energy efficiency incentives have been used so far and how effective they could be. Furthermore, the methodology can be used for setting future incentive distribution plans.
Energy retrofits; Incentive distribution; Linear Programming; Optimization; Residential building stock; Civil and Structural Engineering; Building and Construction; Mechanical Engineering; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/182352
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