Policy makers need scientific support to set ambitious yet realistic environmental targets for the transition to energy efficient buildings and to develop cost-effective policies to meet these targets, but comprehensive, manageable procedures to this aim are still lacking. Our proposed method ranges from baseline creation to transition scenarios depending on annual retrofit budget and specifies the buildings to renovate according to location, size, and age, and the energy efficiency measures to apply based on cost and energy saving. We show how to extrapolate a baseline from few available data, determine retrofit costs, and create calibrated models to estimate energy savings. Retrofits are ranked by levelized cost of saved energy, which ensures that for any budget allocated to retrofit maximum energy savings are obtained at minimum cost to society. The results are summarized in an energy efficiency cost curve enabling policy makers to estimate potential costs and energy savings. We demonstrate the method on a housing stock in northern Italy and show that facade insulation of old buildings in colder climates can compete with gas heating. About 60% baseline energy consumption can be saved doubling current investments, while a maximum saving of 75% requires over three times the current investments.

Bottom-up building stock retrofit based on levelized cost of saved energy

Pernetti R.;
2020-01-01

Abstract

Policy makers need scientific support to set ambitious yet realistic environmental targets for the transition to energy efficient buildings and to develop cost-effective policies to meet these targets, but comprehensive, manageable procedures to this aim are still lacking. Our proposed method ranges from baseline creation to transition scenarios depending on annual retrofit budget and specifies the buildings to renovate according to location, size, and age, and the energy efficiency measures to apply based on cost and energy saving. We show how to extrapolate a baseline from few available data, determine retrofit costs, and create calibrated models to estimate energy savings. Retrofits are ranked by levelized cost of saved energy, which ensures that for any budget allocated to retrofit maximum energy savings are obtained at minimum cost to society. The results are summarized in an energy efficiency cost curve enabling policy makers to estimate potential costs and energy savings. We demonstrate the method on a housing stock in northern Italy and show that facade insulation of old buildings in colder climates can compete with gas heating. About 60% baseline energy consumption can be saved doubling current investments, while a maximum saving of 75% requires over three times the current investments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1349578
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