Parametric energy performance analysis and monitoring of buildings—HEART project platform case study
Parametric energy performance analysis and monitoring of buildings—HEART project platform case study
Building performance analysis changed the way in which buildings are designed and operated. The evaluation of different design and operation options is becoming more resource intensive than ever before. Although building dynamic simulation tools are potentially a suitable way for assessing energy performance of buildings accurately, they require adequate training and a careful evaluation of model input data. In Europe, the majority of buildings were constructed before 1990 and are in urgent need for a significant energy efficiency improvement, through deep renovation. In this respect, advanced renovation solutions are available, but costly and lengthy renovation processes and technical complexities hinder the achievement of a large scale impact. Energy refurbishment of buildings is an open challenge and essentially requires the adoption of a valid methodological approach to link design and operational performance analysis transparently, in order to address the potential gap between simulated and measured results. The HEART project, funded in the EU Horizon 2020 program, aims to address the increasing need for deep retrofit interventions and to develop systemic strategies leading to high performance and cost effective solutions. The research for the cloud platform used in the project is based on two fundamental tools: parametric simulation to produce a large spectrum of possible building energy performance outcomes (considering realistically the impact of the user behaviour and variable operating conditions from the very beginning), and model calibration employing simple, robust and scalable techniques. In this paper we present the preliminary development and testing of the computational processes that will be implemented in the cloud platform, employing the first pilot case study of HEART Project in Italy, currently under refurbishment.
Building performance analysis, Deep refurbishment, M&V, Model calibration, Multivariate regression, Parametric energy modelling, Performance monitoring
Manfren, Massimiliano
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Aste, Niccolò
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Leonforte, Fabrizio
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Del Pero, Claudio
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Buzzetti, Michela
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Adhikari, Rajendra S.
758186c7-dcd8-4c6c-b01e-7da1e1f0990a
Zhixing, Li
eff9c62a-0d8d-4dbb-898a-94a1f75055c3
1 October 2020
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
Aste, Niccolò
9f0175c5-0192-4167-ac2e-c3735c794fde
Leonforte, Fabrizio
f4d9dad5-2d48-49b2-a6f7-b9dcda5ab9de
Del Pero, Claudio
3462791d-5f1b-4c2c-9f0a-4f9005b47435
Buzzetti, Michela
7f18e4ac-ec4a-4f80-beea-bb65651a4bc2
Adhikari, Rajendra S.
758186c7-dcd8-4c6c-b01e-7da1e1f0990a
Zhixing, Li
eff9c62a-0d8d-4dbb-898a-94a1f75055c3
Manfren, Massimiliano, Aste, Niccolò, Leonforte, Fabrizio, Del Pero, Claudio, Buzzetti, Michela, Adhikari, Rajendra S. and Zhixing, Li
(2020)
Parametric energy performance analysis and monitoring of buildings—HEART project platform case study.
Sustainable Cities and Society, 61, [102296].
(doi:10.1016/j.scs.2020.102296).
Abstract
Building performance analysis changed the way in which buildings are designed and operated. The evaluation of different design and operation options is becoming more resource intensive than ever before. Although building dynamic simulation tools are potentially a suitable way for assessing energy performance of buildings accurately, they require adequate training and a careful evaluation of model input data. In Europe, the majority of buildings were constructed before 1990 and are in urgent need for a significant energy efficiency improvement, through deep renovation. In this respect, advanced renovation solutions are available, but costly and lengthy renovation processes and technical complexities hinder the achievement of a large scale impact. Energy refurbishment of buildings is an open challenge and essentially requires the adoption of a valid methodological approach to link design and operational performance analysis transparently, in order to address the potential gap between simulated and measured results. The HEART project, funded in the EU Horizon 2020 program, aims to address the increasing need for deep retrofit interventions and to develop systemic strategies leading to high performance and cost effective solutions. The research for the cloud platform used in the project is based on two fundamental tools: parametric simulation to produce a large spectrum of possible building energy performance outcomes (considering realistically the impact of the user behaviour and variable operating conditions from the very beginning), and model calibration employing simple, robust and scalable techniques. In this paper we present the preliminary development and testing of the computational processes that will be implemented in the cloud platform, employing the first pilot case study of HEART Project in Italy, currently under refurbishment.
Text
2020_05_22_Manfren_Manuscript_final revision
- Accepted Manuscript
More information
Accepted/In Press date: 28 May 2020
e-pub ahead of print date: 1 June 2020
Published date: 1 October 2020
Keywords:
Building performance analysis, Deep refurbishment, M&V, Model calibration, Multivariate regression, Parametric energy modelling, Performance monitoring
Identifiers
Local EPrints ID: 442069
URI: http://eprints.soton.ac.uk/id/eprint/442069
ISSN: 2210-6707
PURE UUID: 7858a8f6-09c1-4a2a-aaa4-e55f55bb0d5c
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Date deposited: 06 Jul 2020 16:37
Last modified: 18 Mar 2024 05:26
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Contributors
Author:
Niccolò Aste
Author:
Fabrizio Leonforte
Author:
Claudio Del Pero
Author:
Michela Buzzetti
Author:
Rajendra S. Adhikari
Author:
Li Zhixing
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