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Abstract
Globally, more than 30% of the world's energy consumption arises in buildings. Optimization of buildings is a key opportunity for reducing energy consumption and carbon emissions, improving operational efficiency and occupant well-being and comfort. While building generative design and control systems have received considerable research attention, optimizing space utilization, particularly for flexible spaces is an underdeveloped research area that is relevant to existing buildings. Flexible spaces, for example, rooms with movable walls, are increasingly common in modern building designs where space requirements are dynamic. In this paper, a novel space usage optimization framework is proposed, including a practical task formulation that enables room reallocation, combination and removal, a machine learning model for energy cost estimation (XGBoost) based on real sensor data and a multi-objective optimization component to minimize energy consumption and maximize room thermal comfort simultaneously (NSGA-II). Its effectiveness is tested and discussed through two representative problem scenarios. Our case studies show that we can reduce energy cost substantially by around 40% in comparison with the original space usage setting, while additionally improving thermal comfort for the occupants. This work shows great potential of using AI techniques for optimizing building space usage.
Original language | English |
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Title of host publication | 2024 IEEE Conference on Artificial Intelligence (CAI) |
Publisher | IEEE |
Pages | 932-939 |
Number of pages | 8 |
ISBN (Electronic) | 9798350354096 |
ISBN (Print) | 9798350354102 |
DOIs | |
Publication status | Published - 30 Jul 2024 |
Event | 2024 IEEE Conference on Artificial Intelligence - Marina Bay Sands, Singapore Duration: 25 Jul 2024 → 27 Jul 2024 |
Publication series
Name | Artificial Intelligence (CAI), IEEE Conference on |
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Conference
Conference | 2024 IEEE Conference on Artificial Intelligence |
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Abbreviated title | IEEE CAI 2024 |
Country/Territory | Singapore |
Period | 25/07/24 → 27/07/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Building Optimization
- Building Space Management
- Energy Optimization
- Flexible Space Utilization
- Machine Learning
- Multi-Objective Optimization
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Modelling and Simulation
Fingerprint
Dive into the research topics of 'Multi-Objective Optimization for Flexible Building Space Usage'. Together they form a unique fingerprint.Projects
- 2 Active
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Adaptive Multi-Source Transfer Learning Approaches for Environmental Challenges
Wang, S. (Principal Investigator)
Engineering & Physical Science Research Council
1/03/24 → 28/02/26
Project: Research Councils
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Systems-Mechanobiology of Health and Disease
Spill, F. (Principal Investigator)
1/02/21 → 30/09/25
Project: Research Councils