Future energy-optimised buildings — Addressing the impact of climate change on buildings
•Climate change and building load variations may impact optimised building designs.•A method using climate models and optimisation is used to optimise future buildings.•A case study is conducted on two cities in Australia: Canberra and Brisbane.•Results show that optimising for future climates can s...
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| Vydané v: | Energy and buildings Ročník 231; s. 110610 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Lausanne
Elsevier B.V
15.01.2021
Elsevier BV |
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| ISSN: | 0378-7788, 1872-6178 |
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| Abstract | •Climate change and building load variations may impact optimised building designs.•A method using climate models and optimisation is used to optimise future buildings.•A case study is conducted on two cities in Australia: Canberra and Brisbane.•Results show that optimising for future climates can save energy for Canberra.•For Brisbane, savings are small and the present-optimised design seems acceptable.
Building energy optimisation is generally performed under present climate conditions with fixed simulation parameters (e.g. internal loads). However, climate change and variations in simulation parameters over the building’s life span may impact the optimised design. A key question is whether a particular energy-optimised design under present climate conditions would remain energy-optimised in the future. Accordingly, in this paper, a new simulation-based optimisation method is developed, which uses climate models and Ant Colony Optimisation to compare the energy-optimised designs under present and future climates. To demonstrate its potential, this method is applied to a typical office building in two Australian cities, Brisbane and Canberra.
The results show that optimising under future climate conditions can lead to different optimal building designs. For Brisbane, the energy difference between optimising under present and future climate conditions is small, but in Canberra the cooling load is increased by up to 6%. This suggests that optimising the studied office building under present climate conditions is acceptable for Brisbane, while considering future climate may yield some savings in Canberra. Results also show that the energy-optimised building configuration for both future and present climates in Brisbane is less sensitive to changes in the load scenario than in Canberra. |
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| AbstractList | •Climate change and building load variations may impact optimised building designs.•A method using climate models and optimisation is used to optimise future buildings.•A case study is conducted on two cities in Australia: Canberra and Brisbane.•Results show that optimising for future climates can save energy for Canberra.•For Brisbane, savings are small and the present-optimised design seems acceptable.
Building energy optimisation is generally performed under present climate conditions with fixed simulation parameters (e.g. internal loads). However, climate change and variations in simulation parameters over the building’s life span may impact the optimised design. A key question is whether a particular energy-optimised design under present climate conditions would remain energy-optimised in the future. Accordingly, in this paper, a new simulation-based optimisation method is developed, which uses climate models and Ant Colony Optimisation to compare the energy-optimised designs under present and future climates. To demonstrate its potential, this method is applied to a typical office building in two Australian cities, Brisbane and Canberra.
The results show that optimising under future climate conditions can lead to different optimal building designs. For Brisbane, the energy difference between optimising under present and future climate conditions is small, but in Canberra the cooling load is increased by up to 6%. This suggests that optimising the studied office building under present climate conditions is acceptable for Brisbane, while considering future climate may yield some savings in Canberra. Results also show that the energy-optimised building configuration for both future and present climates in Brisbane is less sensitive to changes in the load scenario than in Canberra. Building energy optimisation is generally performed under present climate conditions with fixed simulation parameters (e.g. internal loads). However, climate change and variations in simulation parameters over the building's life span may impact the optimised design. A key question is whether a particular energy-optimised design under present climate conditions would remain energy-optimised in the future. Accordingly, in this paper, a new simulation-based optimisation method is developed, which uses climate models and Ant Colony Optimisation to compare the energy-optimised designs under present and future climates. To demonstrate its potential, this method is applied to a typical office building in two Australian cities, Brisbane and Canberra. The results show that optimising under future climate conditions can lead to different optimal building designs. For Brisbane, the energy difference between optimising under present and future climate conditions is small, but in Canberra the cooling load is increased by up to 6%. This suggests that optimising the studied office building under present climate conditions is acceptable for Brisbane, while considering future climate may yield some savings in Canberra. Results also show that the energy-optimised building configuration for both future and present climates in Brisbane is less sensitive to changes in the load scenario than in Canberra. |
| ArticleNumber | 110610 |
| Author | Bell, John Cholette, Michael E. Bamdad, Keivan Omrani, Sara |
| Author_xml | – sequence: 1 givenname: Keivan surname: Bamdad fullname: Bamdad, Keivan email: keivan.bamdadmasouleh@vu.edu.au organization: College of Engineering & Science, Victoria University, Melbourne, Australia – sequence: 2 givenname: Michael E. surname: Cholette fullname: Cholette, Michael E. organization: School of Mechanical, Medical and Process Engineering, Science and Engineering Faculty, Queensland University of Technology (QUT), Brisbane, Australia – sequence: 3 givenname: Sara surname: Omrani fullname: Omrani, Sara organization: School of Built Environment, Science and Engineering Faculty, Queensland University of Technology (QUT), Brisbane, Australia – sequence: 4 givenname: John surname: Bell fullname: Bell, John organization: School of Chemistry & Physics, Science and Engineering Faculty, Queensland University of Technology (QUT), Brisbane, Australia |
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| Keywords | Ant colony optimization Climate change impacts on buildings Energy-efficient buildings in Australia Metaheuristics Simulation-based optimization Future energy optimized buildings |
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| Title | Future energy-optimised buildings — Addressing the impact of climate change on buildings |
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