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Efficient energy modelling of heterogeneous building portfolios

Identifiers
URI: http://hdl.handle.net/20.500.12251/3030
View/Open: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989221926&doi=10.1016%2fj.scs.2016.08.001&partnerID=40&md5=497444ed2ee6bda6708d92854526b28f
ISSN: 2210-6707(ISSN)
DOI: 10.1016/j.scs.2016.08.001
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Author
Pacheco Torres, Rosalía; Heo, Y.; Choudhary, R.
Date
2016
Subject/s

Centro educativo

Simulación energética - herramientas

Auditoría energética

Monitorización de edificios

Universidad

Unesco Subject/s

3311.02 Ingeniería de Control

3311.17 Equipos de Verificación

3305.26 Edificios Públicos

Abstract

The paper reports the energy modelling process of 11 university buildings with the use of a normative energy calculation method. The broad aim of this exercise is to model a set of buildings efficiently so as to capture heterogeneity across buildings and minimize auditing requirements. First, energy model inputs are scrutinized and improved to better represent the actual use of the buildings. The second set of model improvements aim to identify and test those parameters that can be uniformly described across all the buildings, thus reducing overall modelling effort. Using sensitivity analysis of parameters per building, we demonstrate the validity of assigning a common range of values to key input parameters across the building portfolio. Gas and electricity consumption are analyzed separately. Our results show that for electricity consumption, a deeper sub-categorization of activities within buildings is important. On the other hand, accuracy of gas consumption relies on parameters associated with the building fabric. © 2016 The Authors

The paper reports the energy modelling process of 11 university buildings with the use of a normative energy calculation method. The broad aim of this exercise is to model a set of buildings efficiently so as to capture heterogeneity across buildings and minimize auditing requirements. First, energy model inputs are scrutinized and improved to better represent the actual use of the buildings. The second set of model improvements aim to identify and test those parameters that can be uniformly described across all the buildings, thus reducing overall modelling effort. Using sensitivity analysis of parameters per building, we demonstrate the validity of assigning a common range of values to key input parameters across the building portfolio. Gas and electricity consumption are analyzed separately. Our results show that for electricity consumption, a deeper sub-categorization of activities within buildings is important. On the other hand, accuracy of gas consumption relies on parameters associated with the building fabric. © 2016 The Authors

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