Parametric performance analysis and energy model calibration workflow integration - a scalable approach for buildings
Parametric performance analysis and energy model calibration workflow integration - a scalable approach for buildings
High efficiency paradigms and rigorous normative standards for new and existing buildings are fundamental components of sustainability and energy transitions strategies today. However, optimistic assumptions and simplifications are often considered in the design phase and, even when detailed simulation tools are used, the validation of simulation results remains an issue. Further, empirical evidences indicate that the gap between predicted and measured performance can be quite large owing to different types of errors made in the building life cycle phases. Consequently, the discrepancy between a priori performance assessment and a posteriori measured performance can hinder the development and diffusion of energy efficiency practices, especially considering the investment risk. The approach proposed in the research is rooted on the integration of parametric simulation techniques, adopted in the design phase, and inverse modelling techniques applied in Measurement and Verification (M&V) practice, i.e., model calibration, in the operation phase. The research focuses on the analysis of these technical aspects for a Passive House case study, showing an efficient and transparent way to link design and operation performance analysis, reducing effort in modelling and monitoring. The approach can be used to detect and highlight the impact of critical assumptions in the design phase as well as to guarantee the robustness of energy performance management in the operational phase, providing parametric performance boundaries to ease monitoring process and identification of insights in a simple, robust and scalable way.
Building performance simulation, Energy efficiency, Energy management, Model calibration, Parametric modelling, Passive House
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
Nastasi, Benedetto
0d19eabe-134e-4cbe-9912-ff4c095410cd
1 February 2020
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
Nastasi, Benedetto
0d19eabe-134e-4cbe-9912-ff4c095410cd
Manfren, Massimiliano and Nastasi, Benedetto
(2020)
Parametric performance analysis and energy model calibration workflow integration - a scalable approach for buildings.
Energies, 13 (3), [621].
(doi:10.3390/en13030621).
Abstract
High efficiency paradigms and rigorous normative standards for new and existing buildings are fundamental components of sustainability and energy transitions strategies today. However, optimistic assumptions and simplifications are often considered in the design phase and, even when detailed simulation tools are used, the validation of simulation results remains an issue. Further, empirical evidences indicate that the gap between predicted and measured performance can be quite large owing to different types of errors made in the building life cycle phases. Consequently, the discrepancy between a priori performance assessment and a posteriori measured performance can hinder the development and diffusion of energy efficiency practices, especially considering the investment risk. The approach proposed in the research is rooted on the integration of parametric simulation techniques, adopted in the design phase, and inverse modelling techniques applied in Measurement and Verification (M&V) practice, i.e., model calibration, in the operation phase. The research focuses on the analysis of these technical aspects for a Passive House case study, showing an efficient and transparent way to link design and operation performance analysis, reducing effort in modelling and monitoring. The approach can be used to detect and highlight the impact of critical assumptions in the design phase as well as to guarantee the robustness of energy performance management in the operational phase, providing parametric performance boundaries to ease monitoring process and identification of insights in a simple, robust and scalable way.
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energies-13-00621-v3
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Accepted/In Press date: 27 January 2020
Published date: 1 February 2020
Keywords:
Building performance simulation, Energy efficiency, Energy management, Model calibration, Parametric modelling, Passive House
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Local EPrints ID: 438390
URI: http://eprints.soton.ac.uk/id/eprint/438390
ISSN: 1996-1073
PURE UUID: f8d38390-20bd-4d4f-9d4d-4d762b2ece77
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Date deposited: 09 Mar 2020 17:30
Last modified: 17 Mar 2024 03:46
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Author:
Benedetto Nastasi
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