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Improved building energy simulations and verifications by regression
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0002-7332-1521
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

It is common with significant differences between calculated and actual energy use in the building sector. These calculations are often performed with whole building energy simulation (BES) programs. In this process the analyst must make several assumptions about the studied building and its users. These calculations are often verified with measured data through the EUI benchmark indicator which is calculated by normalizing the annual energy use (from the grid) with the floor area. Due to the highly aggregated nature of the EUI indicator it is problematic to use this indicator to deduce erroneous assumptions in the calculations. Consequently, the learning process is often troublesome.

Against this background, the main aim of this thesis has been to develop methods that can provide feedback (key building performance parameters) from measured data which can be used to increase simulation accuracy and verify building performance. For the latter, regression models have been widely used in the past for verifying energy use. This thesis has the focus on the use of regression analysis for accurate parameter identification to be used to increase the agreement between BES predictions and actual outcome. For this, a BES calibration method based on input from regressed parameters has been developed which has shown promising features in terms of accurate predictions and user friendliness. The calibration method is based on input from regressed estimations of air-to-air-transmission losses, including air leakage (heat loss factor) and ground heat loss. Since it is known that bias models still can give accurate predictions, these parameters have been evaluated in terms of robustness and agreement with independent calculations. In addition, a method has been developed to suppress the bias introduced in the regression due to solar gain. Finally, the importance of calibrated simulations was investigated.

The regressed parameters were found to be robust with yearly variations in the heat loss factor of less than 2%. The regressed estimates of ground heat loss were also in good agreement with independent calculations. The robustness of the heat loss factor based on data from periods of substantial solar gain was also found to be high, with an average absolute deviation of 4.0%. The benefit with calibrated models was mainly found to be increased accuracy in predictions and parameters in absolute terms. With increased access to measured data and the promising results in this thesis it is believed that the presented regression models will have their place in future energy quantification methods for accessing energy performance of buildings. 

Abstract [sv]

Det är vanligt med betydande skillnader mellan beräknad och verklig energi användning inom byggnadssektorn. Dessa beräkningar utförs ofta med hjälp av byggnads energi simulerings (BES) program där användaren måste göra ett flertal antaganden om den aktuella byggnaden och dess brukare. Det beräknade resultatet kontrolleras ofta i ett senare skede mot byggnadens faktiska behov av energi från nätet. I denna kontroll är det dock svårt att särskilja den energimängd som byggnaden behöver och den del som är kopplad till brukaren. Detta gör att lärdomarna som kan dras i denna verifieringsprocess ofta blir begränsade.

Mot denna bakgrund, har det huvudsakliga syftet med denna avhandling varit att utveckla metoder som kan användas för att extrahera information om byggnadens prestanda från mätdata. De extraherade parametrarna skall kunna användas för att öka noggrannheten i prediktioner från BES modeller och för att verifiera byggnaders prestanda. Regression analys har ofta använts i det senare fallet i avseendet att verifiera energi användning. Denna avhandling fokuserar på att utveckla regressionsmodeller som ger en hög noggrannhet i modellens parametrar som möjliggör att de bl.a. kan användas för att kalibrera BES modeller och på så sätt minska den vanligt förekommande diskrepans mellan simulerat och faktiskt utfall. En BES kalibrerings metodik har utvecklats baserat på skattning av transmissions förluster ovan mark, inklusive luftläckage (värmeförlust koefficient) samt värmeförlust till mark (G) med hjälp av regressionsanalys. Denna kalibrerings metodik uppvisar lovande egenskaper i form av noggranna prediktioner och användarvänlighet. Goda prediktioner är dock ingen garanti för att modellens ingående parametrar är fysikaliskt rimliga. Därför har regressionsmodellernas parametrar utvärderats i termer av robusthet och överensstämmelse med oberoende beräkningar. Dessutom har en metod utvecklats för att minimerar solens inverkan på regressionsskattningarna. Slutligen har vikten av kalibrerade simuleringar undersökts.

Parametrarna i de framtagna regressionsmodellerna visade sig vara robusta, med årliga variationer i värmeförlust koefficient mindre än 2%. Ytterligare visade sig G var i god överensstämmelse med oberoende beräkningar. Robustheten i värmeförlustfaktorn baserad på data från perioder av betydande solstrålning konstaterades också att vara hög, med en genomsnittlig absolut avvikelse på 4.0%. Fördelen med kalibrerade modeller visade sig främst vara en ökad noggrannhet i prediktioner och modell parametrar i absoluta tal. Med ökad tillgång till mätdata och lovande resultat i denna avhandling är det författarens övertygelse att de presenterade regressionsmodellerna kommer att ha sin plats i framtida bedömnings metoder av byggnaders energiprestanda.

Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2016. , 51 p.
Keyword [en]
Calibrated simulations, Energy signature, Regression, BES, IDA ICE, Multifamily buildings, EUI
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:umu:diva-117248ISBN: 978-91-7601-430-1 (print)OAI: oai:DiVA.org:umu-117248DiVA: diva2:906440
Public defence
2016-03-17, N450, Naturvetarhuset, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2016-02-25 Created: 2016-02-24 Last updated: 2016-02-24Bibliographically approved
List of papers
1. Evaluation of energy conservation measures in a multifamily building, using on site measurements
Open this publication in new window or tab >>Evaluation of energy conservation measures in a multifamily building, using on site measurements
2012 (English)In: Proceeding of the Technoport Conference, Trondheim, 2012Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Trondheim: , 2012
National Category
Energy Systems
Identifiers
urn:nbn:se:umu:diva-106999 (URN)
Conference
Technoport Conference, Trondheim, Norway, 16-18 April, 2012
Available from: 2015-08-15 Created: 2015-08-15 Last updated: 2016-02-24
2. Utilizing a regression approach for troubleshooting energy performance of Swedish buildings
Open this publication in new window or tab >>Utilizing a regression approach for troubleshooting energy performance of Swedish buildings
2016 (English)In: CLIMA 2016 - proceedings of the 12th REHVA World Congress, 2016, Vol. 8Conference paper, Published paper (Refereed)
Abstract [en]

The follow-up of calculated and actual energy performance for new buildings is important to enable a learning process. Performance verification is however not a trivial task since the traditional energy use intensity indicator (EUI) can display large variations even for buildings with similar design and HVAC systems. Hence, there exists a risk for confusion between building owners and developers when predicted and actual outcome are compared using only this indicator. In this paper, simple methods, based on area normalization and regression analysis are investigated for interpretation of wide discrepancies in measured EUIs within four similar, newly built multifamily buildings in Umeå, Sweden. It was found that the discrepancies in specific annual energy demand were dependent on the area used for normalization but did not fully explain the variation in the EUIs. The utilization of linear regression for identification and comparison of the buildings heat-loss factor, (ventilation and transmission), and effective solar aperture provided further insights. The regression analysis indicated that the differences in EUIs were due to a combination of chosen area for normalization and solar gain and not the consequence of variations in actual U-values and HVAC systems. Due to the regression methods robustness against influence from the users, it was concluded that the method works well as a complement to the EUI indicator since it provides insights of the buildings thermal performance. This is often of interest to verify for the developer and the property owner since the thermal performance can be controlled in the construction process.

Keyword
Energy use intensity, EUI, Regression, Heat loss factor, Shape factor
National Category
Civil Engineering
Identifiers
urn:nbn:se:umu:diva-92398 (URN)87-91606-33-0 (vol 8) (ISBN)87-91606-36-5 (set) (ISBN)
Conference
CLIMA 2016 - 12th REHVA World Congress, 22-25 May 2016, Aalborg, Denmark
Note

Originally published in manuscript form.

Available from: 2014-08-26 Created: 2014-08-26 Last updated: 2016-05-30Bibliographically approved
3. Robustness of a regression approach, aimed for calibration of whole building energy simulation tools
Open this publication in new window or tab >>Robustness of a regression approach, aimed for calibration of whole building energy simulation tools
2014 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 81, 430-434 p.Article in journal (Refereed) Published
Abstract [en]

An approach, able to easily and effectively integrate field measured data in whole Building Energy Simulation (BES) models is crucial to increase simulation accuracy for existing buildings. In this paper the robustness of a linear regression method for extracting transmission losses above ground (including air leakage) and ground heat loss parameters are analyzed. The regression method is evaluated on two documented and monitored multifamily buildings with mechanical supply and exhaust ventilation systems, with and without heat recovery.   

The obtained results are found to be robust, with variations less than 2% in the extracted estimates of transmission losses above ground (including air leakage) and with a high goodness of fit (R2>0.96) against measured data from two years. In addition, the estimations of the buildings ground heat loss were in good agreement with calculations in accordance with EN ISO 13370:2007. The high quality output from the used regression method serves as good prerequisites for the method to be used in conjunction with BES models to aid the analyst in a BES calibration process

Place, publisher, year, edition, pages
Elsevier, 2014
Keyword
case study, multifamily buildings, measurements, regression, calibration parameters
National Category
Building Technologies Energy Engineering
Identifiers
urn:nbn:se:umu:diva-92401 (URN)10.1016/j.enbuild.2014.06.035 (DOI)000343363700041 ()2-s2.0-84905562576 (Scopus ID)
Available from: 2014-08-26 Created: 2014-08-26 Last updated: 2017-12-05Bibliographically approved
4. Calibration of low-rise multifamily residential simulation models using regressed estimations of transmission losses
Open this publication in new window or tab >>Calibration of low-rise multifamily residential simulation models using regressed estimations of transmission losses
2016 (English)In: Journal of Building Performance Simulation, Taylor & Francis, ISSN 1940-1493, E-ISSN 1940-1507, Vol. 9, no 3, 304-315 p.Article in journal (Refereed) Published
Abstract [en]

In this study, we evaluated a proposed calibration approach for whole-building energy simulation models. This approach was based on a regression analysis of measured data collected during a time period when the global solar radiation was the lowest. The proposed approach was compared with a more conventional calibration approach with different degrees of complexity, starting from design stage assumptions, through audits, and lastly by refining the model with detailed measurements and numerical calculations. The evaluation was performed using measured data from two multifamily buildings located in Umeå, Sweden, and the IDA ICE 4.61 simulation software. The best agreement between simulated and measured data was obtained with the proposed calibration approach. The monthly normalized mean bias error and the coefficient of variation was less than 5.0% and 6.0% respectively. For the conventional calibration approach, detailed measurements and time-consuming numerical calculations were required to reach similar results. 

Keyword
IDA ICE, calibrated simulation, regression, BES models
National Category
Physical Sciences
Identifiers
urn:nbn:se:umu:diva-106815 (URN)10.1080/19401493.2015.1067257 (DOI)000374992500005 ()2-s2.0-84938651135 (Scopus ID)
Available from: 2015-08-07 Created: 2015-08-07 Last updated: 2017-12-04Bibliographically approved
5. A single-variate building energy signature approach for periods with substantial solar gain
Open this publication in new window or tab >>A single-variate building energy signature approach for periods with substantial solar gain
2016 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 122, 185-191 p.Article in journal (Refereed) Published
Abstract [en]

The use of regression analysis for the identification of building performance parameters based on measurements is often difficult due to collinearity between the outdoor temperature and the global solar radiation (S). This study proposes a method to overcome this issue. The proposed method is based on using the seasonal symmetry of S to pair data from time-periods equidistant from the winter solstice. In addition, a method to utilize synthetic data to fine-tune the paired-data approach is presented. To evaluate the paired-data approach, two years data from a multifamily building in Umeå was used to estimate the heat loss factor (air-to-air transmission including air leakage). The results were compared with results obtained when S was very low (S ≈ 0). It was found that, the fine-tuned paired-data approach resulted in a modest deviation in the heat loss factor with an average absolute deviation of 4.0%. The small deviation indicates that the paired-data approach can extend the use of single-variate regression models for accurate identification of heat loss factors to situations where the solar gain is substantial. The paired-data approach was also used to calibrate a commercial energy building simulation tool. 

Keyword
Regression, Energy signature models, IDA-ICE, Building, Solar gain
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-117244 (URN)10.1016/j.enbuild.2016.04.040 (DOI)000376833300018 ()
External cooperation:
Available from: 2016-02-24 Created: 2016-02-24 Last updated: 2017-11-30Bibliographically approved
6. The influence from input data provided by the user on calculated energy savings
Open this publication in new window or tab >>The influence from input data provided by the user on calculated energy savings
2014 (English)In: 10th Nordic Symposium on Building Physics, Lund, Sweden,15-19 June, 2014, 2014, 1301-1308 p.Conference paper, Published paper (Refereed)
Abstract [en]

It is generally accepted that the most correct decisions are made when the used support system provides the most accurate description of the starting point as possible. That is, in this case, a detailed initial description of a building, planned to be refurbished and evaluated with the building energy simulation software IDA ICE (v 4.5).In order to assess this statement, we have used two different models to predict energy savings due to different planned energy conservation measures (ECMs):

 - A basic model based on inputs from currently available standards and as-built drawings.

 - A calibrated model based on an analysis of measurements from two months, together with measured air handling unit parameters, hourly electricity usage and indoor temperatures.

The relative prediction differences between the models are investigated as well as compared with the actual outcome in a neighboring building where the analyzed ECMs have been implemented. The result indicates that a calibrated model should be used, in order to accurately determine the post-retrofit energy demand. However, if only investigation of ECMs which aims to decrease a buildings transmission loss is of interest, the findings suggest that BES calibration is of minor importance.

Keyword
Simulation, energy savings, retrofit, model calibration, regression
National Category
Engineering and Technology
Identifiers
urn:nbn:se:umu:diva-92355 (URN)978-91-88722-53-9 (ISBN)
Conference
10th Nordic Symposium on Building Physics, Lund, Sweden,15-19 June, 2014
Available from: 2014-08-26 Created: 2014-08-26 Last updated: 2016-02-24Bibliographically approved

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