Statistic data based holistic building performance analysis: Method development through case study on finnish residential sector

Genku Kayo, Vahid Arabzadeh, Ivo Martinac, Risto Lahdelma

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

This paper describes the study on method development (regression analysis model and genetic algorithm model) and shows the results of the preliminary tests. The proposed holistic building performance analysis allows analysing the transition of energy demand, and understanding the impact of energy efficiency improvement in the building sector driven by nZEB implementation. By applying Finnish statistic data as open data source, the feasibility and potential of analysis was studied. It is clarified that a room for improvement is remained, but both proposed methods have potentials to provide informative outputs for the future energy analysis.

Original languageEnglish
Title of host publicationPLEA 2018 - Smart and Healthy within the Two-Degree Limit
Subtitle of host publicationProceedings of the 34th International Conference on Passive and Low Energy Architecture
EditorsEdward Ng, Square Fong, Chao Ren
PublisherChinese University of Hong Kong (CUHK)
Pages1181-1182
Number of pages2
ISBN (Electronic)9789628272365
Publication statusPublished - Dec 2018
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Passive and Low Energy Architecture - Hong Kong, China
Duration: 10 Dec 201812 Dec 2018
Conference number: 34

Publication series

NamePLEA 2018 - Smart and Healthy within the Two-Degree Limit: Proceedings of the 34th International Conference on Passive and Low Energy Architecture
Volume3

Conference

ConferenceInternational Conference on Passive and Low Energy Architecture
Abbreviated titlePLEA
Country/TerritoryChina
CityHong Kong
Period10/12/201812/12/2018

Keywords

  • Building performance
  • Genetic algorithms
  • Regression analysis
  • Statistic data

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