The climate evolution towards a progressive increase of Earth's temperature is leading to many worrying consequences, involving different aspects of World life. Among them, a specific focus should be given to the resilience of building energy design to global warming, since the efficiency and effectiveness of energy conservation measures over time can be highly affected by climate change. In this vein, the paper applies a multi-stage, multi-objective approach to find robust cost-optimal energy retrofit solutions and to assess their resilience to global warming. The approach combines the software EnergyPlus and MATLAB (R) to implement an optimization genetic algorithm and a smart research strategy. This framework allows to explore a huge solution domain by investigating sundry performance indicators, such as energy needs, polluting emissions and global costs, thereby ensuring a robust assessment of cost-optimality. Different cost-optimal retrofit solutions are found for different global warming and economic scenarios. Finally, a careful decision-making is performed to identify a recommended solution that provides the highest resilience to the cited scenarios, yielding the best trade-off among energy, environmental and economic performances. The approach is applied to a typical Mediterranean building, located in South Italy. The recommended solution includes the energy retrofit of the whole building envelope and the replacement of energy systems. It requires an investment around 100(sic)/m(2) and, in most scenarios, produces high potential benefits in terms of primary energy savings (42 44 kWh/m(2)a), polluting emission reductions (11.5/12.0 kgCO(2)-eq/m(2)a) and global cost savings (5/78 (sic)/m(2)). (C) 2017 Elsevier B.V. All rights reserved.

Resilience of robust cost-optimal energy retrofit of buildings to global warming: A multi-stage, multi-objective approach

De Masi, Rosa Francesca;Mauro, Gerardo Maria;Vanoli, Giuseppe Peter
2017-01-01

Abstract

The climate evolution towards a progressive increase of Earth's temperature is leading to many worrying consequences, involving different aspects of World life. Among them, a specific focus should be given to the resilience of building energy design to global warming, since the efficiency and effectiveness of energy conservation measures over time can be highly affected by climate change. In this vein, the paper applies a multi-stage, multi-objective approach to find robust cost-optimal energy retrofit solutions and to assess their resilience to global warming. The approach combines the software EnergyPlus and MATLAB (R) to implement an optimization genetic algorithm and a smart research strategy. This framework allows to explore a huge solution domain by investigating sundry performance indicators, such as energy needs, polluting emissions and global costs, thereby ensuring a robust assessment of cost-optimality. Different cost-optimal retrofit solutions are found for different global warming and economic scenarios. Finally, a careful decision-making is performed to identify a recommended solution that provides the highest resilience to the cited scenarios, yielding the best trade-off among energy, environmental and economic performances. The approach is applied to a typical Mediterranean building, located in South Italy. The recommended solution includes the energy retrofit of the whole building envelope and the replacement of energy systems. It requires an investment around 100(sic)/m(2) and, in most scenarios, produces high potential benefits in terms of primary energy savings (42 44 kWh/m(2)a), polluting emission reductions (11.5/12.0 kgCO(2)-eq/m(2)a) and global cost savings (5/78 (sic)/m(2)). (C) 2017 Elsevier B.V. All rights reserved.
2017
Building energy retrofit; Multi-objective optimization; Global warming; Genetic algorithm; Cost-optimal; Resilience
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/38447
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