Building activity is the sector that affects for the most part the anthropogenic climate change. Indeed, even if differences can be found among countries, according to the level of development and climates, buildings require about 30-40% of the overall energy demand, with similar share concerning the greenhouse emissions. According to the more recent EU Directives in matter of energy efficiency in energy use, a great attention has to be paid to energy refurbishments of existing buildings. Indeed, the turnover rate of the EU building stock is generally low in fully-developed countries, so that the energy retrofits are also more important compared to new nearly zero-energy buildings. The proposed investigation concerns the demonstrative role of the public hand, whose necessity is underlined by the EU Directives 2010/31/EU and 2012/27/EU, through a multi-step and multi-objective optimization of an educational building of an Italian University. All preliminary investigations aimed at a reliable modelling, the iterative method that combines genetic algorithms and transient energy simulations tailored on calibrated numerical models make the investigation complete and repeatable. All levers of energy efficiency have been pressed, and thus the refurbishment of building envelope, HVAC systems, integration of energy supply by renewables. The multi objective optimisation concerns costs, incentives, indoor comfort, energy demands for heating and cooling and a novel approach is proposed for choosing the best configuration of retrofit. It is resulted that the most profitable energy efficiency measures involve the modernization of energy systems, even if also the retrofit of the building envelope can be profitable under favourable financial conditions. The cost-effective refurbishment reduces the primary energy demand up to a value of 12 kWh/m(2)a, so that the building can be surely considered as nZEB. (C) 2017 Elsevier B.V. All rights reserved.

Energy retrofit of educational buildings: Transient energy simulations, model calibration and multi-objective optimization towards nearly zero-energy performance

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

Abstract

Building activity is the sector that affects for the most part the anthropogenic climate change. Indeed, even if differences can be found among countries, according to the level of development and climates, buildings require about 30-40% of the overall energy demand, with similar share concerning the greenhouse emissions. According to the more recent EU Directives in matter of energy efficiency in energy use, a great attention has to be paid to energy refurbishments of existing buildings. Indeed, the turnover rate of the EU building stock is generally low in fully-developed countries, so that the energy retrofits are also more important compared to new nearly zero-energy buildings. The proposed investigation concerns the demonstrative role of the public hand, whose necessity is underlined by the EU Directives 2010/31/EU and 2012/27/EU, through a multi-step and multi-objective optimization of an educational building of an Italian University. All preliminary investigations aimed at a reliable modelling, the iterative method that combines genetic algorithms and transient energy simulations tailored on calibrated numerical models make the investigation complete and repeatable. All levers of energy efficiency have been pressed, and thus the refurbishment of building envelope, HVAC systems, integration of energy supply by renewables. The multi objective optimisation concerns costs, incentives, indoor comfort, energy demands for heating and cooling and a novel approach is proposed for choosing the best configuration of retrofit. It is resulted that the most profitable energy efficiency measures involve the modernization of energy systems, even if also the retrofit of the building envelope can be profitable under favourable financial conditions. The cost-effective refurbishment reduces the primary energy demand up to a value of 12 kWh/m(2)a, so that the building can be surely considered as nZEB. (C) 2017 Elsevier B.V. All rights reserved.
2017
Energy modelling and model calibration; Educational buildings; Building energy retrofit; Multi-objective optimization; Cost-optimal analysis; Genetic algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/38456
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