An Epistemic-Deontic-Axiologic (EDA) agent-based Energy Management System in office buildings

[thumbnail of Open Access]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.
| Preview
Available under license: Creative Commons Attribution
[thumbnail of Submission version UoR CentAUR.pdf]
Text - Accepted Version
· Restricted to Repository staff only
· Available under License Creative Commons Attribution Non-commercial No Derivatives.
Restricted to Repository staff only

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Jiang, L., Yao, R. orcid id iconORCID: https://orcid.org/0000-0003-4269-7224, Liu, K. and McCrindle, R. (2017) An Epistemic-Deontic-Axiologic (EDA) agent-based Energy Management System in office buildings. Applied Energy, 205. pp. 440-452. ISSN 0306-2619 doi: 10.1016/j.apenergy.2017.07.081

Abstract/Summary

In the UK, buildings contribute about one third of the energy-related greenhouse gas emissions. Space heating and cooling systems are among the biggest energy consumers in buildings. This research aims to develop a novel Building Energy Management System (BEMS) to reduce the energy consumption of the heating, ventilation and air-conditioning (HVAC) system while fulfilling each occupant’ thermal comfort requirement. This paper presents a newly developed novel method, Epistemic-Deontic-Axiologic (EDA) Agent-based solution to support the Energy Management System meeting the dual targets of occupant thermal comfort and energy efficiency. The multi-agent solutions are applied to the BEMS. The problem decomposition method is used to define the architecture of the system. The Epistemic-Deontic-Axiologic (EDA) agent model is applied to develop the rational local and personal agents inside the system. These EDA-based agents select their optimal action plan by considering the occupants’ thermal sensations, their behavioural adaptations and the energy consumption of the HVAC system. The Newly-developed personal thermal sensation models and group-of-people-based thermal sensation models generated by support vector machine (SVM) based algorithms are applied to evaluate the occupants’ thermal sensations. These models are developed from the data collected in a real built environment. Simulation results prove that the newly-developed BEMS can help the HVAC system reduce the energy consumption by up to 10% while fulfilling the occupants’ thermal comfort requirements.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/71565
Identification Number/DOI 10.1016/j.apenergy.2017.07.081
Refereed Yes
Divisions Science > School of the Built Environment > Energy and Environmental Engineering group
Henley Business School > Digitalisation, Marketing and Entrepreneurship
Publisher Elsevier
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar