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Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

Energy Efficiency volume 10, pages 359–382 (2017)Cite this article

Abstract

In recent years, big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods, Generative Topographic Mapping and k-means, to obtain reference dwellings that can be considered as representative of the different energy patterns and energy systems of the neighbourhood. Then, simulation of energy demand and indoor temperature against the monitored comfort conditions in a short period is performed to obtain end use load disaggregation. This methodology was applied in a district at Terrassa City (Spain), and six reference dwellings were selected. Results showed that the method was able to identify the main patterns and provide occupants with feasible recommendations so that they can make required decisions at neighbourhood level. Moreover, given that the proposed method is based on the comparison with similar buildings, it could motivate building occupants to implement community improvement actions, as well as to modify their behaviour.

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Abbreviations

IEA-EBC:

International Energy Agency–Energy in Building and Communities

EPBD:

European Union Energy Performance of Buildings Directive

EUI:

Energy use intensity

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Acknowledgments

Xavier Cipriano is thankful to the Catalan Housing Agency of the Catalan Government for funding the main research, as well as to María Heras, Nuria Cardellach, and Eduard Calderón for their participation in the energy audits and surveys to tenants. We also are thankful to Dr. Nicolas Kosoy for his suggestions in the socio-economic analysis of surveys, as well as the Can Jofresa’s neighbour association for their answers and information about their homes. Jaime Martí-Herrero is thankful to the Prometeo Project of the Secretariat for Higher Education, Science, Technology and Innovation of the Republic of Ecuador that funded part of his work.

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Authors and Affiliations

  1. Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Building Energy and Environment Group, Edifici GAIA (TR14), C/Rambla Sant Nebridi 22, 08222, Terrassa, Barcelona, Spain

    X. Cipriano, J. Martí-Herrero & S. Danov

  2. Computer Science, Universitat Politècnica de Catalunya (UPC Barcelona Tech), Campus Nord UPC, 08034, Barcelona, Spain

    A. Vellido

  3. Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Building Energy and Environment Group, CIMNE-UdL Classroom, Pere de Cabrera s/n. Building, CREA. O-ce 1.15, 25001, Lleida, Spain

    J. Cipriano

  4. PROMETEO Researcher, Instituto Nacional de Eficiencia Energética y Energías Renovables (INER), 6 de Diciembre N33-32, Quito, Ecuador

    J. Martí-Herrero

Authors
  1. X. Cipriano
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  2. A. Vellido
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  3. J. Cipriano
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  4. J. Martí-Herrero
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  5. S. Danov
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Correspondence to X. Cipriano.

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Cipriano, X., Vellido, A., Cipriano, J. et al. Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects. Energy Efficiency 10, 359–382 (2017). https://doi.org/10.1007/s12053-016-9460-9

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Keywords

  • Building energy use
  • Energy building simulation
  • Clustering analysis
  • Urban energy refurbishment