Analysing the future energy performance of residential buildings in the most populated Italian climatic zone: A study of climate change impacts

Tootkaboni, Mamak P.; Ballarini, Ilaria; Corrado, Vincenzo

doi:10.1016/j.egyr.2021.04.012

Cited by 54 publications

(18 citation statements)

References 21 publications

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“…Based on the obtained results, the authors suggested that the higher spatial resolution of the dynamical downscaling compared to the statistical methods resulted in a better representation of the local climate conditions, leading to the higher accuracy of the dynamic buildings' energy performance simulations. A similar conclusion was also drawn by Tootkaboni et al [24], who comparatively assessed the effect of different future weather datasets, created both with statistical and dynamical downscaling approaches, on the dynamic energy performance analysis of typical buildings. As suggested by the authors, the statistical downscaling methods, including morphing and the stochastic approach, may provide adequate information to comparatively assess the long-term changes in energy building performance, but the dynamical downscaling method is found to be more reliable given its finer resolution.…”

Section: Dynamical Downscalingsupporting

confidence: 73%

“…There are three main operations for the morphing approach involving shifting, applied when an absolute change to a variable is required, the stretch or scaling factor when a relative or percentage change is predicted for a given variable, and a combination of shifting and scaling when both absolute and relative changes are predicted for a given variable. A detailed description of the morphing downscaling approach is given in [24,28,29].…”

Section: Statistical Downscalingmentioning

confidence: 99%

“…The Meteonorm stochastic weather generator for future weather file creation has been used in many previous studies, such as the work of Tootkaboni et al [24] and Moazami et al [37], who comparatively evaluated different future weather datasets and their effect on buildings' energy performance simulations. Certainly, the use of such weather generators facilitates the generation of both present-day and future time series, especially for locations where there are not sufficient historical data.…”

Section: Statistical Downscalingmentioning

confidence: 99%

“…At this point it must be emphasized that, in the existing literature, numerous studies have employed either statistical or dynamical downscaling approaches to assess the impact of climate change on the buildings' energy performance [21][22][23][24][25][26]. Yet, in all these cases, the buildings' energy performance is assessed only for the general governing climatic conditions without considering the microclimatic conditions characterizing each study area.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City

et al. 2021

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Climate change has a major impact on the urban built environment, both with respect to the heating and cooling energy requirements, but also regarding the higher probability of confronting extreme events such as heatwaves. In parallel, the ongoing urbanization, the urban microclimate and the formation of the urban heat island effect, compounding the ongoing climate change, is also a considerable determinant of the building’s energy behavior and the outdoor thermal environment. To evaluate the magnitude of the complex phenomenon, the current research investigates the effect of climate change and urban heat island on heating and cooling energy needs of an urban building unit in Thessaloniki, Greece. The study comparatively evaluates different tools for the generation of future weather datasets, considering both statistical and dynamical downscaling methods, with the latter involving the use of a regional climate model. Based on the output of the regional climate model, another future weather dataset is created, considering not only the general climatic conditions, but also the microclimatic parameters of the examined case study area, under the future climate projections. The generated future weather datasets are then used as an input parameter in the dynamic energy performance simulations with EnergyPlus. For all examined weather datasets, the simulation results show a decrease of the heating energy use, an effect that is strongly counterbalanced by the rise of the cooling energy demand. The obtained simulation results also reveal the contribution of the urban warming of the ongoing climate change, demonstrating the need to perform a holistic analysis for the buildings’ energy needs under future climate conditions.

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Section: Dynamical Downscalingsupporting

confidence: 73%

Section: Statistical Downscalingmentioning

confidence: 99%

Section: Statistical Downscalingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City

et al. 2021

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“…For example, Tootkaboni et al [24] analysed the impact of climate change on the future energy performance of residential buildings in the most populated Italian climate zone. The authors found a decrease of around 30.9% of the heating energy demand and a significant increase in cooling demand up to 255.1%.…”

Section: Problems Related To Climate Changementioning

confidence: 99%

Effect of Climate Change and Occupant Behaviour on the Environmental Impact of the Heating and Cooling Systems of a Real Apartment. A Parametric Study through Life Cycle Assessment

et al. 2021

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Climate change has a strong influence on the energy consumption of buildings, affecting both the heating and cooling demand in the actual and future scenario. In this paper, a life cycle assessment (LCA) was performed to evaluate the influence of both the occupant behaviour and the climate change on the environmental impact of the heating and cooling systems of an apartment located in southern Italy. The analysis was conducted using IPCC GWP and ReCiPe indicators as well as the Ecoinvent database. The influence of occupant behaviour was included in the analysis considering different usage profiles during the operational phase, while the effect of climate change was considered by varying the weather file every thirty years. The adoption of the real usage profiles showed that the impact of the systems was highly influenced by the occupant behaviour. In particular, the environmental impact of the heating system appeared more influenced by the operation hours, while that of the cooling system was more affected by the natural ventilation schedules. Furthermore, the influence of climate change demonstrated that more attention has to be dedicated to the cooling demand that in the future years will play an ever-greater role in the energy consumption of buildings.

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Dynamic Simulations of High-Energy Performance Buildings: The Role of Climatic Data and the Consideration of Climate Change

Τσόκα

2022

Innovative Renewable Energy

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Analysing the future energy performance of residential buildings in the most populated Italian climatic zone: A study of climate change impacts

Cited by 54 publications

References 21 publications

Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City

Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City

Effect of Climate Change and Occupant Behaviour on the Environmental Impact of the Heating and Cooling Systems of a Real Apartment. A Parametric Study through Life Cycle Assessment

Dynamic Simulations of High-Energy Performance Buildings: The Role of Climatic Data and the Consideration of Climate Change

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