A novel approach for the identification of the optimal strategy for building retrofit is presented and applied to a case study in northern Italy. Increased envelope insulation, more efficient heat-generating systems, thermal distribution and terminal units, heating control systems, electric distribution systems, and renewable energies exploitation were considered as possible measures. A tailored multi-criteria decision analysis tool is developed to embrace the entire building life cycle and includes all the possible combinations in a discretized approach, with the aim of optimising conflicting design parameters, such as energy consumption, costs, GHG emissions, and comfort level. The proposed methodology is applied to two scenarios: nominal building parameters, and the validated model obtained using dynamic energy simulations. In both cases, most energy-efficient solutions are found to be optimal, however, large differences in overall energy consumption are found between the two scenarios resulting in different sizing of optimal renewable-energy installations and different electric distribution systems. A sensitivity analysis is also performed to estimate how results respond to the variation of input parameters. Despite a large difference between the two scenarios, the proposed methodology is found to be stable in identifying the optimal solution and offers full customisation features to adapt to different cases.

A life-cycle approach for multi-objective optimisation in building design: methodology and application to a case study

Bonamente E.
;
Brunelli C.;Castellani F.;Piccioni E.
2018

Abstract

A novel approach for the identification of the optimal strategy for building retrofit is presented and applied to a case study in northern Italy. Increased envelope insulation, more efficient heat-generating systems, thermal distribution and terminal units, heating control systems, electric distribution systems, and renewable energies exploitation were considered as possible measures. A tailored multi-criteria decision analysis tool is developed to embrace the entire building life cycle and includes all the possible combinations in a discretized approach, with the aim of optimising conflicting design parameters, such as energy consumption, costs, GHG emissions, and comfort level. The proposed methodology is applied to two scenarios: nominal building parameters, and the validated model obtained using dynamic energy simulations. In both cases, most energy-efficient solutions are found to be optimal, however, large differences in overall energy consumption are found between the two scenarios resulting in different sizing of optimal renewable-energy installations and different electric distribution systems. A sensitivity analysis is also performed to estimate how results respond to the variation of input parameters. Despite a large difference between the two scenarios, the proposed methodology is found to be stable in identifying the optimal solution and offers full customisation features to adapt to different cases.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1462884
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