Using intelligent clustering techniques to classify the energy performance of school buildings

Santamouris, M.; Mihalakakou, G.; Patargias, Panagiotis Al.; Gaitani, Niki; Sfakianaki, K.; Papaglastra, M.; Pavlou, C.; Doukas, P.; Primikiri, Eleni; Geros, V.; Assimakopoulos, Margarita-Niki; Mitoula, R.; Zerefos, Stelios

doi:10.1016/j.enbuild.2006.04.018

Cited by 175 publications

(73 citation statements)

References 8 publications

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“…Recently cluster analysis has been employed to define homogenous classes and reference buildings within classes relying on data related to real energy uses [9,23,24]. In particular, Arambula Lara et al [9] applied the cluster analysis to a sample of about 60 schools in the North-East of Italy, identifying reference buildings within the clusters in order to optimize the energy retrofit measures.…”

Section: Introductionmentioning

confidence: 99%

“…The authors [9] correlated the real energy demands of the buildings' stock to their geometrical and technical characteristics by means of proper statistical analyses. A fuzzy clustering technique has been used by Santamouris et al [24] for the classification of energy data of 320 schools in Greece, clustered by similar characteristics. The clustering permitted the selection of representative schools for a more detailed analysis [23,24].…”

Section: Introductionmentioning

confidence: 99%

“…A fuzzy clustering technique has been used by Santamouris et al [24] for the classification of energy data of 320 schools in Greece, clustered by similar characteristics. The clustering permitted the selection of representative schools for a more detailed analysis [23,24]. The definition of reference buildings has been promoted also by the European Commission [25] for cost-optimal analyses of energy retrofits in the existing building stock.…”

Section: Introductionmentioning

confidence: 99%

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Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

et al. 2018

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

et al. 2018

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“…Related studies were conducted and various rating systems in EU countries were announced to determine energy rating of existing buildings [1,5,[18][19][20][21][22]. Theodoridou et al, studied energy consumption of residential building stock of two Greek cities.…”

Section: Introductionmentioning

confidence: 99%

On the relation between architectural considerations and heating energy performance of Turkish residential buildings in Izmir

Kazanasmaz

Uygun

Akkurt

et al. 2014

Energy and Buildings

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a b s t r a c tBy considering the energy efficiency legislations among the European Union, Turkey is responsible to provide regulations to comply for the latest European Energy Performance of Buildings Directive 2010/31/EC. New legislation in Turkey requires information about the evaluation of energy performance of existing buildings. This study aimed to determine energy performance of residential buildings in Izmir, regarding significant relationships between their performance and architectural configuration through statistical analysis. The focus was on the heating energy consumption due to Energy Efficiency Law (2007) and Building Energy Performance Regulation (2008), and Standard Assessment Method for Energy Performance of Dwellings (KEP-SDM). This energy performance assessment method was based on Turkish standard TS 825, and European standard EN ISO 13790. It is known that architectural configuration of buildings and design norms have impact on energy performance of buildings. However, emphasis was given on significant values of architectural considerations through certain area-based ratios. The levels of these ratios were matched with the levels of energy consumption. By this, the consideration was to take early-precautions against high energy consumptions in the early design stage and to enhance legislation by adding recommendations of concrete architectural values. These would assist to predict the level of energy performance in the early design phase. Findings would provide feedback information on the residential building stock inİzmir, Turkey.

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“…In their study of the lighting in three educational institutions, Motta-Cabrera and Zareipour [53] used association rules to discover existing relationships between time, occupancy, and lighting-related energy waste in classrooms. Santamouris et al [54] also proposed a method for rating and classifying the energy consumption and efficiency of school buildings as compared to other similar buildings. They found that fuzzy clustering techniques could be used to obtain a more robust set of classes, thus avoiding problems stemming from unbalanced classification.…”

Section: Economic Analysis Of Electric Consumptionmentioning

confidence: 99%

Data science for building energy management: A review

Molina-Solana

Ros

Ruiz

et al. 2017

Renewable and Sustainable Energy Reviews

219

108

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The energy consumption of residential and commercial buildings has risen steadily in recent years, an increase largely due to their HVAC systems. Expected energy loads, transportation, and storage as well as user behavior influence the quantity and quality of the energy consumed daily in buildings. However, technology is now available that can accurately monitor, collect, and store the huge amount of data involved in this process. Furthermore, this technology is capable of analyzing and exploiting such data in meaningful ways. Not surprisingly, the use of data science techniques to increase energy efficiency is currently attracting a great deal of attention and interest. This paper reviews how Data Science has been applied to address the most difficult problems faced by practitioners in the field of Energy Management, especially in the building sector. The work also discusses the challenges and opportunities that will arise with the advent of fully connected devices and new computational technologies.

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Using intelligent clustering techniques to classify the energy performance of school buildings

Cited by 175 publications

References 8 publications

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

On the relation between architectural considerations and heating energy performance of Turkish residential buildings in Izmir

Data science for building energy management: A review

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