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Title: Linking agent-based model to dynamic building simulation model : a co-simulation system for modelling occupants interactions with buildings
Author: Alfakara, A.
ISNI:       0000 0004 8498 806X
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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Human activities have been progressively influencing the climate system (IPCC, 2014), to which the building sector is a major contributor. In efforts to reduce this impact, using building performance assessment such as dynamic building simulation models (DBSM) is becoming increasingly important. Energy consumption in buildings is highly influenced by the behaviours of their occupants, yet, current DBSMs consider occupant using fixed schedules, with similar behaviour overtime. Thus, it may contribute to "the performance gap" or the disparity seen between modelled and actual energy use in buildings. Recent research has been investigating occupant behaviour and its impact on energy and internal conditions in buildings. However, these behavioural model have been developed in isolation of improving occupant representation in DBSM. Therefore, this research investigated the development of a co-simulation system of an Agent-based model (ABM) that simulated dynamic occupant behaviour in buildings, which was dynamically linked to a DBSM. The ABM does not yet contain many of the requisite features for a fully-fledged ABM model ​but does provide a robust framework for building up to a complete feature-set. The ABM was linked to the widely used EnergyPlus building simulation model using the Functional Mock-up Interface Standard (FMI). This novel linkage allowed co-simulation of the occupants-building systems, and a real-time exchange of inputs/outputs at 15 minutes interval, between the two dynamic models. The results of the co-simulation system were compared to a conventional EnergyPlus simulation of a case study dwelling with different family types, which showed a considerable variation with a reduction of 64% and 11% of annual gas and electricity consumption respectively. The study has delivered insights into the importance of accounting of dynamic occupant behaviour, necessitates more advanced occupant behavioural models to be implemented in existing DBSMs. Moreover, it has provided a framework for a new approach to enhance occupant behaviour modelling in current DBSMs programs.
Supervisor: Croxford, B. ; Mavrogianni, A. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available