A New Methodology for Assessing the Energy Consumption of Building Stocks

Ballarini, Ilaria; Corrado, Vincenzo

doi:10.3390/en10081102

Cited by 23 publications

(13 citation statements)

References 18 publications

(19 reference statements)

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“…It should be noted that while for the real project both the energy demand and consumption show the values for the thermal energy, in the case of the tool the value of the consumption includes also the electricity consumption mainly for covering the lighting requirements (not including equipment). Bearing in mind these considerations, the difference between the values of the real project and the tool is around 20%, which, even if quite high, is still lower than the existing practices [39].…”

Section: Validation Of Results Against Real Performance Datamentioning

confidence: 88%

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

García-Fuentes¹,

Álvarez²,

Serna³

et al. 2019

Sustainability

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The evident need for improving the existing building stock still suffers from important barriers, such as the fragmentation of the value chain, the lack of information regarding some solutions, and the lack of confidence with respect to energy savings, which prevent unlocking investments, and the difficult communication among stakeholders. Therefore, new processes based on exploiting the potential of existing and new tools are required. In this framework, the OptEEmAL project has developed a tool that integrates stakeholders, data and tools in order to ease the process of designing energy efficient retrofitting projects at building and district scale. This tool works around an optimisation framework in order to evaluate, compare and optimise candidate retrofitting scenarios against a set of indicators showing the performance of the district. This evaluation and optimisation method is based on aggregating indicators through transforming the priorities of stakeholders into a mathematical weighting scheme, which makes it possible to provide scenarios within their expectations. Therefore, the generation of these scenarios is driven by their design parameters, being thus flexible and adapted to their needs. This paper shows the implementation of this tool and specifically 3 different prioritisation schemes, analysing how they impact into the decision making process and selection of the retrofitting strategy.Buildings account for approximately 40% of energy consumption and 36% of GHG emissions in the context of the EU [1]. When analysing the stock of existing buildings, around 30% of the building stock is more than 50 years old [2] and almost 75% is energy inefficient [3,4]. The implications of this energy inefficiency not only result in an energy and environmental cost, but also provoke other impacts, such as health problems due to the low levels of comfort within these buildings [5]. It is then imperative to focus on upgrading an ageing building stock, whose current renovation rates are low, at~1.2%. To achieve these targets, this rate should increase to 3% [6].On the other hand, the retrofitting market is quite fragmented, with multiple stakeholders with different and often conflicting interests. This is mirrored in the communication and information exchanges between them. This strong barrier is added to others, such as the lack of knowledge of some technologies among construction professionals, the varying ambition of performance requirements present within regulations, lack of awareness, and uncertainty as to the expected savings, which make

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Section: Validation Of Results Against Real Performance Datamentioning

confidence: 88%

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

García-Fuentes¹,

Álvarez²,

Serna³

et al. 2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…To show the potential of the calculation framework even on a large scale, the whole Italian building stock as represented by the Italian building typology matrix developed in the framework of the IEE-TABULA project [3] and of its follow-up IEE-EPISCOPE [51] has been considered. The matrix, originally built based on the analysis of Piedmont region data, well represents the building stock of Italian middle climatic zone, including most of Lombardy region and the city of Brescia in particular.…”

Section: Building Typology Matrix and Additional Datamentioning

confidence: 99%

Dynamic Approach to Evaluate the Effect of Reducing District Heating Temperature on Indoor Thermal Comfort

et al. 2020

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To reduce energy consumption for space heating, a coordinated action on energy supply, building fabric and occupant behavior is required to realize sustainable improvements. A reduction in district heating supply temperature is an interesting option to allow the incorporation of renewable energy sources and reduce distribution losses, but its impact on the final users must be considered. This aspect is especially critical as most European countries feature an old building stock, with poor insulation and heating systems designed for high-temperature operation. In this study, a complete methodology is devised to evaluate the effect of district heating temperature reduction on the end users by modeling all the stages of the system, from the primary heat exchanger to the indoor environment. A dynamic energy performance engine, based on EN ISO 52016-1:2017 standard and completed with a heat exchanger model, is implemented, and its outputs are used to calculate thermal comfort indicators throughout the heating season. As a practical application, the method is used to evaluate different scenarios resulting from the reduction of primary supply temperature of a second-generation district heating network in Northern Italy. Several building typologies dating back to different periods are considered, in the conservative assumption of radiator heating. The results of the simulations show that the most severe discomfort situations are experienced in buildings built before 1990, but in recent buildings the amount of discomfort occurrences can be high because of the poor output of radiators when working at very low temperatures. Among the possible measures that could help the transition, actions on the primary side, on the installed power and on the building fabric are considered. The investigation method requires a limited amount of input data and is applicable to different scales, from the individual building to entire urban areas lined up for renovation.

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“…In turn, the definition of archetypes is essential for reference building analysis (statistically representative buildings) and for parametric studies, where an appropriate level of simplification is crucial to enable a correct analysis process. Examples in this sense can be found for the simulation of simplified building models (Pernigotto et al, 2014), for city scale modelling (Delmastro et al, 2016;Dogan et al, 2016;Dogan and Reinhart, 2017;Ghiassi and Mahdavi, 2017), and for building stock modelling (Ballarini and Corrado, 2017). An explicative example of the hierarchical structure of data in building energy modelling is reported in Table 1.…”

Section: Hierarchical Structure Of Building Energy Modelling Datamentioning

confidence: 99%

Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

2020

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The reduction of energy usage and environmental impact of the built environment and construction industry is crucial for sustainability on a global scale. We are working towards an increased commitment towards resource efficiency in the built environment and to the growth of innovative businesses following circular economy principles. The conceptualization of change is a relevant part of energy and sustainability transitions research, which is aimed at enabling radical shifts compatible with societal functions. In this framework, building performance has to be considered in a whole life cycle perspective because buildings are long-term assets. In a life cycle perspective, both operational and embodied energy and carbon emissions have to be considered for appropriate comparability and decision-making. The application of sustainability assessments of products and practices in the built environment is itself a critical and debatable issue. For this reason, the way energy consumption data are measured, processed, and reported has to be progressively standardized in order to enable transparency and consistency of methods at multiple scales (from single buildings up to building stock) and levels of analysis (from individual components up to systems), ideally complementing ongoing research initiatives that use open science principles in energy research. In this paper, we analyse the topic of linking design and operation phase’s energy performance analysis through regression-based approaches in buildings, highlighting the hierarchical nature of building energy modelling data. The goal of this research is to review the current state of the art of in order to orient future efforts towards integrated data analysis workflows, from design to operation. In this sense, we show how data analysis techniques can be used to evaluate the impact of both technical and human factors. Finally, we indicate how approximated physical interpretation of regression models can help in developing data-driven models that could enhance the possibility of learning from feedback and reconstructing building stock data at multiple levels.

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A New Methodology for Assessing the Energy Consumption of Building Stocks

Cited by 23 publications

References 18 publications

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

Dynamic Approach to Evaluate the Effect of Reducing District Heating Temperature on Indoor Thermal Comfort

Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

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