The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece

The construction of nearly zero-emission buildings in Europe and internationally has become mandatory by legislation. In parallel with these developments, the non-reversible increase in ambient temperatures stresses the buildings’ energy systems during the summer months with extreme temperatures, wi...

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Main Authors: Antiopi-Malvina Stamatellou, Tassos Stamatelos
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/18/5/1032
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author Antiopi-Malvina Stamatellou
Tassos Stamatelos
author_facet Antiopi-Malvina Stamatellou
Tassos Stamatelos
author_sort Antiopi-Malvina Stamatellou
collection DOAJ
description The construction of nearly zero-emission buildings in Europe and internationally has become mandatory by legislation. In parallel with these developments, the non-reversible increase in ambient temperatures stresses the buildings’ energy systems during the summer months with extreme temperatures, with their severity varying according to the local microclimate. These phenomena result in an increase in the summer cooling loads. Thus, the HVAC system’s performance during summer needs more careful study, especially for the residential sector and wherever the night cooling effect is no longer capable of releasing the stress. In the present work, the impact of climate change on a residential building’s energy performance is studied through energy simulations. The effect of the future increases in the intensity and duration of summer heat waves is assessed by exploiting the long-term forecasting capabilities of a transformer neural network model, trained by existing meteorological data for the period 2007–2023. Based on the forecasted climatic conditions for 2030 and 2040 produced in this way, the projected effects on the system’s energy performance are assessed. The long-term forecast was aided by 43 years of ambient temperature data for Europe, available through the ERA5 Copernicus program datasets. The respective predictions of the building’s HVAC electricity consumption during future summer heat wave episodes of long durations point to the necessity of special measures to keep the internal grid’s autonomy and reduce unwanted interactions with the external grid. Moreover, further improvements in nZEB building design for improved summer energy performance would be critical to the success of this policy during the next two decades.
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spelling doaj-art-a231fc29494549628e75a15d2e3ffc192025-08-20T02:59:14ZengMDPI AGEnergies1996-10732025-02-01185103210.3390/en18051032The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, GreeceAntiopi-Malvina Stamatellou0Tassos Stamatelos1Department of Mechanical Engineering, University of Thessaly, 38221 Volos, GreeceDepartment of Mechanical Engineering, University of Thessaly, 38221 Volos, GreeceThe construction of nearly zero-emission buildings in Europe and internationally has become mandatory by legislation. In parallel with these developments, the non-reversible increase in ambient temperatures stresses the buildings’ energy systems during the summer months with extreme temperatures, with their severity varying according to the local microclimate. These phenomena result in an increase in the summer cooling loads. Thus, the HVAC system’s performance during summer needs more careful study, especially for the residential sector and wherever the night cooling effect is no longer capable of releasing the stress. In the present work, the impact of climate change on a residential building’s energy performance is studied through energy simulations. The effect of the future increases in the intensity and duration of summer heat waves is assessed by exploiting the long-term forecasting capabilities of a transformer neural network model, trained by existing meteorological data for the period 2007–2023. Based on the forecasted climatic conditions for 2030 and 2040 produced in this way, the projected effects on the system’s energy performance are assessed. The long-term forecast was aided by 43 years of ambient temperature data for Europe, available through the ERA5 Copernicus program datasets. The respective predictions of the building’s HVAC electricity consumption during future summer heat wave episodes of long durations point to the necessity of special measures to keep the internal grid’s autonomy and reduce unwanted interactions with the external grid. Moreover, further improvements in nZEB building design for improved summer energy performance would be critical to the success of this policy during the next two decades.https://www.mdpi.com/1996-1073/18/5/1032micro-gridsnearly zero-emission buildingsclimate changedeep neural networksbuilding energy simulationHVAC system sizing
spellingShingle Antiopi-Malvina Stamatellou
Tassos Stamatelos
The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
Energies
micro-grids
nearly zero-emission buildings
climate change
deep neural networks
building energy simulation
HVAC system sizing
title The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
title_full The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
title_fullStr The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
title_full_unstemmed The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
title_short The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
title_sort implications of long term local climate change for the energy performance of an nzeb residential building in volos greece
topic micro-grids
nearly zero-emission buildings
climate change
deep neural networks
building energy simulation
HVAC system sizing
url https://www.mdpi.com/1996-1073/18/5/1032
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