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 language | English |
|---|---|
| Title of host publication | PLEA 2018 - Smart and Healthy within the Two-Degree Limit |
| Subtitle of host publication | Proceedings of the 34th International Conference on Passive and Low Energy Architecture |
| Editors | Edward Ng, Square Fong, Chao Ren |
| Publisher | Chinese University of Hong Kong (CUHK) |
| Pages | 1181-1182 |
| Number of pages | 2 |
| ISBN (Electronic) | 9789628272365 |
| Publication status | Published - Dec 2018 |
| MoE publication type | A4 Article in a conference publication |
| Event | International Conference on Passive and Low Energy Architecture - Hong Kong, China Duration: 10 Dec 2018 → 12 Dec 2018 Conference number: 34 |
Publication series
| Name | PLEA 2018 - Smart and Healthy within the Two-Degree Limit: Proceedings of the 34th International Conference on Passive and Low Energy Architecture |
|---|---|
| Volume | 3 |
Conference
| Conference | International Conference on Passive and Low Energy Architecture |
|---|---|
| Abbreviated title | PLEA |
| Country/Territory | China |
| City | Hong Kong |
| Period | 10/12/2018 → 12/12/2018 |
Keywords
- Building performance
- Genetic algorithms
- Regression analysis
- Statistic data
