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A statistical data analysis approach to Energy Data: A Case Study in Building Performance Analysis of Thermal Energy Loss
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The usage of energy in buildings is higher in Sweden’s cold climate, most buildings consume

significant energy to heat buildings during the winter and cool the buildings during the summer, using

the district heat and electricity. The building energy loss is the difference between indoor and outdoor

temperatures. When the temperature difference is higher during the heating season (winter), there is

a need to balance the indoor temperature. More power supply is needed to warm the indoor area. In

order to find which factor has a significant impact on the building, heat loss and gain can be used as

variables in the multiple linear regression model to analyze the building energy performance. In order

to build the multiple – linear regression model which is used, the measured parameters for the building

and some of the data should be calculated, such as solar heat gain through windows from the (North,

East, West &South) building. The heat loss to the ground is based on constructed material, the thermal

conductivity of the material, indoor and outdoor temperature, and steady state ground heat transfer

coefficient. After building the model, an analysis of the fit model test is needed, to investigate if the

coefficients are properly estimated. Based on this analysis, we can see the comparison between

renovated building and non renovated building significant impact of the energy consumption for

given the energy and financial investment.

Place, publisher, year, edition, pages
2015.
Keyword [en]
Building energy performance, Solar heat gain, ground heat loss, Linear interpolation, Variance Inflation Factor, Heteroskedascity and Autocorrelation, Multiple linear regression.
National Category
Other Social Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:du-19032OAI: oai:DiVA.org:du-19032DiVA: diva2:846913
Available from: 2015-08-18 Created: 2015-08-18

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf