Response Surface Method to Calculate Energy Savings Associated with Thermal Comfort Improvement in Buildings

In developed countries, a large part of the building stock in 2050 will consist of currently existing buildings. Consequently, in order to achieve the objectives in terms of energy efficiency in the building sector we must consider not only new infrastructures but also the old ones. A reduction in e...

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Veröffentlicht in:Sustainability 2022-03, Vol.14 (5), p.2933
Hauptverfasser: García-Cuadrado, Juan, Conserva, Andrea, Aranda, Juan, Zambrana-Vasquez, David, García-Armingol, Tatiana, Millán, Gema
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Sprache:eng
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Zusammenfassung:In developed countries, a large part of the building stock in 2050 will consist of currently existing buildings. Consequently, in order to achieve the objectives in terms of energy efficiency in the building sector we must consider not only new infrastructures but also the old ones. A reduction in energy consumption for climate control of between 50 and 90% can be achieved by rehabilitation and the implementation of different energy efficiency measures. Currently, these measures to reduce energy consumption and associated CO2 emissions can be modelled using computer tools. However, high precision and detail of thermal behaviour models through simulations can mean a great computational cost for companies, which results in a blockage of servers and workers. In this paper, the Response Surface Methodology (RSM) is presented as an innovative methodology for the simplification of models for calculation of the energy savings associated with thermal comfort improvement in buildings. A single-family house model, located in three different climates, is presented as a case study in order to validate the proposed methodology. Different scenarios were simulated, addressing heating and cooling temperature set points and external wall insulation represented by the transmittance (U-value). Results obtained from energy simulation using Design Builder were contrasted against those estimated from the simplified model extracted from the RSM analysis. The results revealed a deviation lower than 3% when comparing both methods. Therefore, the simplified mathematical prediction models are demonstrated to be suitable for the study of the energy performance of buildings, saving computational time, costs and associated human resources.
ISSN:2071-1050
2071-1050
DOI:10.3390/su14052933