Methodology for evaluating the energy renovation effects on the thermal performance of social housing buildings: Monitoring study and grey box model development

Terés-Zubiaga, J.; Escudero-Revilla, C.; García-Gáfaro, C.; Sala, J.M.

doi:10.1016/j.enbuild.2015.06.010

Cited by 26 publications

(25 citation statements)

References 32 publications

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“…in Ref. [20,21,22,7]). Consequently, a prior knowledge of the building characteristics is necessary either to implement the set of different grey box structures (RxCy) from which the optimal one is drawn or to compute adequate initial values of the model parameters.…”

Section: The Building Energy Models Used During the Design Phasementioning

confidence: 97%

Automated grey box model implementation using BIM and Modelica

Andriamamonjy

Klein

Sælens

2019

Energy and Buildings

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A large part of energy usage in buildings occurs during the operational phase, emphasising the need for efficient and improved facility management, operation and control. Model Predictive Control (MPC) or Fault Detection and Diagnosis (FDD) are among the strategies that allow minimising energy use and costs during operation. However, the need for fast and accurate dynamic models (e.g. grey box model), which are time-consuming and challenging to implement, precludes their systematic integration in the built environment. A typical grey-box modelling approach consists of manually implementing several grey-box model structures with an increasing level of complexity before performing a forward selection procedure to identify the optimal configuration. The link between the different grey-box models and the monitored data is also established manually. Such an approach can be both time-consuming and error-prone and involves a significant cost that hampers the broad adoption of strategies such as MPC and FDD. This study proposes a tool-chain that uses BIM to automatically generate several grey-box structures with added complexities stemming from the specific geometry and design of the building. More specifically, an existing rule-based IFC to Modelica interface is extended to automatically create several Modelica-based grey box models that gradually take into account the building's specific information and characteristics. Additional rules are also proposed to automate the connection between the models and the building monitoring system. As a forward selection approach, a multi-objective optimisation using the NSGA-2 algorithm is adopted. The application of the tool-chain on two case studies shows that the integration of BIM to automate the implementation of grey box models, not only reduces the human involvement in the modelling process but can also produce more accurate models. Besides, this study shows that the use of multi-objective optimisation with datasets from two different seasons results in models that are valid for all seasons.

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Section: The Building Energy Models Used During the Design Phasementioning

confidence: 97%

Automated grey box model implementation using BIM and Modelica

Andriamamonjy

Klein

Sælens

2019

Energy and Buildings

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“…Seigarren kapitulu honetan, ikerketari buruzko informazio gehiago nahi izanez gero, RC ereduaren garapen honen ondoriozko artikulua irakur daiteke [8].…”

Section: Jon Terés-zubiagaunclassified

Birgaitze energetikoak gizarte etxebizitzan: portaera termikoaren analisia

Terés-Zubiaga

2018

EKAIA

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Laburpena: «Birgaitze energetikoak gizarte-etxebizitzan: portaera termikoaren analisia» doktorego-tesia eraikinen birgaikuntza energetikoaren ebaluazioan datza, eta prozedura honek barne hartzen dituen atal ezberdinak kontuan hartzen ditu: datu-eskuratzea eta monitorizazioa, datuen tratamendua eta lortutako emaitzen analisiak, esaterako. Helburu horrekin, atal esperimentalean bi monitorizazio ezberdin barne hartzen ditu. Lehenik, hamar gizarte-etxebizitzen landa-azterketa bat aurkezten da hirugarren kapituluan; laugarren kapituluan etxebizitza adierazgarri baten monitorizazio zehatz baten deskripzioan arreta jartzen du. Estazio klimatiko bat kokatzeaz gain, etxebizitzaren monitorizazioa eginahal izateko hirurogei tenperatura-sentsore baino gehiago erabili izan dira. Monitorizazioa egin ondoren, atal esperimentalean lortutako datuen tratamendua garatzen da bi simulazio ereduren bidez. Azkenik, tesi honen azken atalak simulazioaren diseinuan eta aipatutako simulazioen bidez lortutako emaitzen ebaluazioan arreta jartzen du. Bestalde,eraikinen portaera energetikoa aztertzeko ikuspegi exergetikoak duen erabilgarritasuna aztertzen da tesi honen azken kapituluan.Hitz gakoak: simulazio energetikoa, TRNSYS, monitorizazio termikoa, exergia, eraginkortasun energetikoa eraikuntzan, birgaitze energetikoa. Abstract: Energy retrofits in social housing. Analysis of its thermal behaviour» PhD Thesis deals with the evaluation of energy renovations in buildings, facing the different parts involved in that process, such as data acquisition and monitoring, data treatment and analysis of obtained results. With this aim in mind,

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“…The grey-box models provide some advantages in the buildings' thermal modeling process, in particular, ease of their use and the possibility to link their parameters to global buildings' physical characteristics, such as the heat resistance and the mass capacity. These models can be used for different purposes such as control of the indoor environment [8,9], forecasting energy consumption, and evaluating buildings' energy performance [10][11][12]. However, their practical use is subjected to the difficulty of the determination of their optimal order.…”

Section: Introductionmentioning

confidence: 99%

Determination of the Optimal Order of Grey-Box Models for Short-Time Prediction of Buildings’ Thermal Behavior

et al. 2019

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The use of grey-box models for short-time forecasting of buildings' thermal behavior requires the determination of the models' order since this order could influence the grey-box models' performance. This paper presents an analysis of the optimal order of these models for different thermal conditions. The novelty of this work consists of considering the influence of the heating conditions on the determination of the performances of grey-box models. The analysis is based on experimental tests that were conducted in a room with different thermal conditions, related to the variation of the heating power. Experimental results were used for the determination of the optimal grey-box models' order that minimizes the gap between the experimental results and the grey-box forecasting. Results show that the optimal grey-box models' order depends on the buildings' thermal conditions, but generally lies between two and three with an error less than 0.2 • C and a fit percent greater than 90%.

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Methodology for evaluating the energy renovation effects on the thermal performance of social housing buildings: Monitoring study and grey box model development

Cited by 26 publications

References 32 publications

Automated grey box model implementation using BIM and Modelica

Automated grey box model implementation using BIM and Modelica

Birgaitze energetikoak gizarte etxebizitzan: portaera termikoaren analisia

Determination of the Optimal Order of Grey-Box Models for Short-Time Prediction of Buildings’ Thermal Behavior

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