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A regression approach for assessment of building energy performance
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0002-7332-1521
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Reliable evaluation methods is needed to ensure that investments in energy conservation measures (ECMs) and the construction of new energy efficient buildings lives up to the promised and expected performance.

This thesis presents and evaluates a regression method for estimation of influential building parameters: transmission losses above ground (including air leakage), ground heat loss, and overall heat loss coefficient.

The analysis is conducted with separately metered electricity, heating and weather data using linear regression models based on the simplified steady-state power balance for a whole building.

The evaluation consists of analyzing the robustness of the extracted parameters, their suitability to be used as input values to building energy simulations (BES) tools. In addition, differences between uncalibrated and calibrated BES models are analyzed when they are used to calculate energy savings. Finally the suitability of using a buildings overall heat loss coefficient as a performance verification tool is studied.

The presented regression method exhibits high robustness and good agreement with theory. Knowledge of these parameters also proved beneficial in BES calibration procedures as well as in performance verifications. Thus, the presented method shows promising features for reliable energy performance assessments of buildings.

Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2014. , 25 p.
Keyword [en]
building energy simulation, measurements, regression, calibration parameters
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-92465ISBN: 978-91-7601-125-6 (print)OAI: oai:DiVA.org:umu-92465DiVA: diva2:748782
Presentation
2014-09-17, A302, Håken Gullessons väg 20, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2014-09-26 Created: 2014-08-26 Last updated: 2014-09-26Bibliographically approved
List of papers
1. 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
2. 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
3. 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

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