Building energy optimisation under uncertainty using ACOMV algorithm

Bamdad, Keivan and Cholette, Michael E and Guan, Lisa and Bell, John (2018) Building energy optimisation under uncertainty using ACOMV algorithm. Energy and Buildings, 167. pp. 322-333. ISSN 0378-7788


Abstract

This study develops a new scenario-based optimisation methodology to address building parameter uncertainty. A multi-objective optimisation problem based on three objective functions (“low”, “base”, and “high” simulation scenarios) is developed and scalarised using the weighted sum method to find the optimised compromise between energy use for different scenarios. Necessitated by the increased computational demand of multi-objective problems, a modified version of the Ant Colony Optimisation algorithm for Mixed Variables (ACOMV-M) is developed. A comparison between ACOMV-M and a benchmark algorithm showed that ACOMV-M converged to solutions of similar quality with approximately 50% fewer simulations. The results on an Australian office building showed that the energy-optimised building parameters can vary significantly for different assumptions. Furthermore, inaccurate assumptions on internal loads and infiltration rate can reduce energy savings achieved by optimisation up to 4.8 percentage points. The proposed methodology is used to identify parameters that are sensitive to different scenarios and demonstrated that more robust solutions can be achieved through modest sacrifices in optimality to any one scenario.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current - Research and Innovation Division (12 Jul 2012 -)
Faculty/School / Institute/Centre: Current - Research and Innovation Division (12 Jul 2012 -)
Date Deposited: 04 Sep 2020 01:49
Last Modified: 11 Sep 2020 02:49
Uncontrolled Keywords: Building optimisation, Ant colony optimisation, Uncertainty Analysis, Robust optimised design, Australian commercial building
Fields of Research (2008): 12 Built Environment and Design > 1299 Other Built Environment and Design > 129999 Built Environment and Design not elsewhere classified
09 Engineering > 0999 Other Engineering > 099999 Engineering not elsewhere classified
Identification Number or DOI: https://doi.org/10.1016/j.enbuild.2018.02.053
URI: http://eprints.usq.edu.au/id/eprint/39351

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