Home // ENERGY 2023, The Thirteenth International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies // View article
Authors:
Hengxuan Wang
Sumiyoshi Daisuke
Keywords: occupants’ behavior model; energy demand of residential buildings; public stochastic data; particle swarm optimization; dynamic time warping
Abstract:
For the target of energy demand estimation of residential buildings in urban scale, occupants’ behavior model has been paid much attention. In this paper, a new model for simulating occupants’ behavior schedules in urban scale has been proposed using only public stochastic data (national lifetime survey) combined with Dynamic Time Warping and Particle Swarm Optimization algorithms. We use this proposed model to simulate the working-male’s behavior schedules with 5-mintues interval in resting day as an example. The simulated results - percentages of occupants adopt the given behavior at specific moments are calculated and compared with public stochastic data to verify the accuracy. Compared with existing models, the proposed model is more efficient and accurate. We believe this model could be useful for building energy demand estimation in urban scale combined with appliance operation possibility based on occupants’ behaviors.
Pages: 17 to 22
Copyright: Copyright (c) IARIA, 2023
Publication date: March 13, 2023
Published in: conference
ISSN: 2308-412X
ISBN: 978-1-68558-054-4
Location: Barcelona, Spain
Dates: from March 13, 2023 to March 17, 2023