Building energy performance analysis: A case study

Vollaro, Roberto De Lieto; Guattari, Claudia; Evangelisti, Luca; Battista, Gabriele; Carnielo, Emiliano; Gori, Paola

doi:10.1016/j.enbuild.2014.10.080

Cited by 86 publications

(40 citation statements)

References 21 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Observing the percentage of energy savings in Table 8, it is possible to notice that the declared savings by the designer after the retrofit and the achievable energy savings obtained by means of the dynamic model are not far and the differences can be related to the different adopted simulation codes. The declared energy savings were obtained by means of steady-state simulation tools, less accurate than the dynamic one, yet able to fully reproduce hourly environmental boundary conditions and consider structural inertial effects [43]. These percentage differences can be also ascribed, to a lesser extent, to the modified weather conditions, which play an important role for calculating buildings energy demands.…”

Section: Energy Performance Analysis Of the Reference Schoolsmentioning

confidence: 99%

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

et al. 2018

Self Cite

View full text Add to dashboard Cite

A large part of the stock of Italian educational buildings have undertaken energy retrofit interventions, thanks to European funds allocated by complex technical-administrative calls. In these projects, the suggested retrofit strategies are often selected based on the common best practices (considering average energy savings) but are not supported by proper energy investigations. In this paper, Italian school buildings' stock was analyzed by cluster analysis with the aim of providing a methodology able to identify the best energy retrofit interventions from the perspective of cost-benefit, and to correlate them with the specific characteristics of the educational buildings. This research is based on the analysis of about 80 school buildings located in central Italy and characterized by different features and construction technologies. The refurbished buildings were classified in homogeneous clusters and, for each of them, the most representative building was identified. Furthermore, for each representative building a validating procedure based on dynamic simulations and a comparison with actual energy use was performed. The two buildings thus singled out provide a model that could be developed into a useful tool for Public Administrations to suggest priorities in the planning of new energy retrofits of existing school building stocks.

show abstract

Section: Energy Performance Analysis Of the Reference Schoolsmentioning

confidence: 99%

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Deciding which building properties to select depends on the direct observation of the site [68][69][70][71][72], while the inside temperature of indoor spaces is set to 299 K [73].…”

Section: Simulationsmentioning

confidence: 99%

Evaluation of Different Urban Microclimate Mitigation Strategies through a PMV Analysis

et al. 2015

View full text Add to dashboard Cite

Abstract:Outdoor thermal comfort affects the health of the people and the quality of life in urban areas. This is the reason why in the past few years different mitigation strategies for the microclimate have been studied and examined. These strategies depend on those passive factors characterizing the urban setting that are able to affect the values of local meteorological variables, as the limit surfaces of the urban space (parterre and façades of the buildings). This paper examines the Cloister by Giuliano da Sangallo, which is part of the Faculty of Engineering of Sapienza University of Rome. The case study compares the present configuration of the Cloister with four other configurations characterized by some vegetation and materials with a high albedo by taking into consideration the PMV (Predicted Mean Vote) model. Microclimatic variables are calculated through numerical simulations performed by the ENVI-met software. Such a comparison is performed during a typical summer day. While examining the results it can be noticed how the strategy presenting the best results is the one with some vegetation, whereas the materials with a high albedo improve the microclimate if applied on surfaces characterized by a high sky view factor. OPEN ACCESSSustainability 2015, 7 9013

show abstract

“…θ i, nε temperature of the internal air (1,2) θ si, nε temperature of the internal wall surface (1,2,4,6,7,8,9) θ se, nε temperature of the external wall surface (1,3,5,6,7,8,9,10,11) Let us note that the numbers of factors can be arbitrary. In the provided example the first 11 factors were used to ensure better clarity of notation.…”

Section: Analysis Of Results and Discussionmentioning

confidence: 99%

“…Basing on the quoted works as well as on other works [6][7][8][9], we know that the thermal properties of a building have direct impact on the annual consumption of energy. We also know that the thermal conductivity of a wall depends on the thermal conductivity of each layer of that wall, and therefore, the thermal resistance of the whole wall can be modeled in the way analogous to the resistance of resistors in electrical Jerzy Skrzypczyk died before publication of this work was completed.…”

Section: Introductionmentioning

confidence: 99%

Estimation of thermal transmittance based on temperature measurements with the application of perturbation numbers

et al. 2017

View full text Add to dashboard Cite

Fast estimation of thermal transmittance based on temperature measurements is uncertain, and the obtained results can be burdened with a large error. Nevertheless, such attempts should be undertaken merely due to the fact that a precise measurement by means of heat flux measurements is not always possible in field conditions (resentment of the residents during the measurements carried out inside their living quarters), and the calculation methods do not allow for the nonlinearity of thermal insulation, heat bridges or other fragments of building envelope of diversified thermal conductivity. The present paper offers the estimation of thermal transmittance and internal surface resistance with the use of temperature measurements (in particular with the use of thermovision). The proposed method has been verified through tests carried out on a laboratory test stand built in the open space, subjected to the influence of real meteorological conditions. The present elaboration involves the estimation of thermal transmittance by means of temperature measurements. Basing on the mentioned estimation, the authors present correction coefficients which have impact on the estimation accuracy. Furthermore, in the final part of the paper, various types of disturbance were allowed for using perturbation numbers, and the introduced by the authors Bcredibility area of thermal transmittance estimation^was determined.

show abstract

Building energy performance analysis: A case study

Cited by 86 publications

References 21 publications

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

Evaluation of Different Urban Microclimate Mitigation Strategies through a PMV Analysis

Estimation of thermal transmittance based on temperature measurements with the application of perturbation numbers

Contact Info

Product

Resources

About