Agent-based model for simulating building energy management in student residences
Authored by Zhikun Ding, Ting Hu, Min Li, Xiaoxiao Xu, Patrick X W Zou
Date Published: 2019
DOI: 10.1016/j.enbuild.2019.05.053
Sponsors:
Australian Research Council (ARC)
Platforms:
AnyLogic
Model Documentation:
Other Narrative
Flow charts
Model Code URLs:
Model code not found
Abstract
Reducing energy consumption in buildings through behavioural changes has
been regarded as a relatively low-cost and sustainable method. However,
studies that focus on occupant building energy consumption in student
residences are few. In the context of shared residences, the energy
behaviour could be very different. This is because student-student and
student-building system interactions are complex. To address this
research gap, this study developed an agent-based simulation model
regarding students as heterogeneous individuals. Simulation parameters
include student basic information, status of staying at dormitories and
applicances using behaviours. All data were obtained from a university
campus in Shenzhen, China. Energy-saving scenarios under different
strategies were simulated, including different energy-saving strategies
and interaction behaviour energy-saving advertising. Results show that
(1) occupancy is the most important factor for dormitory energy
consumption; (2) reducing the time of air conditioner use has the
largest impact on energy-saving; (3) reducing computer standby time has
a great energy-saving potential; (4) students' attitude and awareness of
energy conservation and the communication and exchange of energy
information amongst students play an important role in energy saving.
According to these results, the university can take measures to promote
energy saving, which include strengthening education, establishing a
energy saving championship system for dormitory energy consumption and
implementing a reward-and-punishment mechanism.(C) 2019 Elsevier B.V.
All rights reserved.
Tags
Agent-based modelling
Performance
Market
Occupant behavior
Policy
information
Impact
Building energy consumption
Occupant behaviour
Complex adaptive
system