Abstract
Rapid urbanization and building sector growth emphasize the critical role of energy conservation in addressing global energy consumption and greenhouse emissions. Despite advancements in energy-efficient technologies, an ‘energy performance gap’ exists between predicted and actual energy use, significantly influenced by occupant behaviour. This study explores energy-related behaviour in office buildings by integrating existing behavioural theories including the Theory of Planned Behaviour and the Self-determination Theory, and construct of habit and comfort. Data from an online survey were analyzed using principal component analysis, two-step cluster analysis, and descriptive statistics, identifying three behavioral clusters: ‘Cautious Saver’, ‘Compelling Dissatisfied’, and ‘Coherent Potent’. These clusters represent distinct energy-related behaviours. A Clustering-based Agent System (CAS) was then proposed to simulate the energy-related behaviours of these clusters, offering a dynamic and adaptive modelling framework. The study advocates for a comprehensive approach, integrating behavioural theories to provide insights for developing accurate occupant behaviour models. Abbreviations: BD: Biodiesel; BR: Blending Ratio; BSFC: Brake Specific Fuel Consumption; BTE: Brake Thermal Efficiency; CI: Compression Ignition; CM: Coating Material; CO: Carbon Monoxide; CT DEE: Coating Thickness Diethyl Ether; D-Gun: Detonation Gun; DOA: Degree of Adiabacity; EGT: Exhaust Gas Temperature; HC: Hydrocarbon; HVOF: High-velocity oxy-fuel; IC: Internal Combustion; LHR: Low Heat Rejection; NOx: Oxides of Nitrogen; PVD: Physical Vapour Deposition; SEM: Scanning Electron Microscopy; SI: Spark Ignition; TBC: Thermal Barrier Coating; TMF: Thermal Mechanical Fatigue; WCO: Waste Cooking Oil; XRD: X-ray Diffraction; YSZ: Yttria-Stabilised Zirconia
Published Version
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