A Non-intrusive Heuristic for Energy Messaging Intervention Modelled using a Novel Agent-based Approach

Abdallah, Fatima and Basurra, Shadi and Gaber, Mohamed Medhat (2018) A Non-intrusive Heuristic for Energy Messaging Intervention Modelled using a Novel Agent-based Approach. IEEE Access, 7. pp. 1627-1646. ISSN 2169-3536

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In response to the increased energy consumption in residential buildings, various efforts have been devoted to increase occupant awareness using energy feedback systems. However, it was shown that feedback provided by these systems is not enough to inform occupant actions to reduce energy consumption. Another approach is to control energy consumption using automated energy management systems. The automatic control of appliances takes-out the occupant sense of control, which is proved to be uncomfortable in many cases. This paper proposes an energy messaging intervention that keeps the control for occupants whilst supporting them with actionable messages. The messages inform occupants about energy waste incidents happening in their house in real-time, which enables occupants to take actions to reduce their consumption. Besides, a heuristic is defined to make the intervention non-intrusive by controlling the rate and time of the messages sent to occupants. The proposed intervention is evaluated in a novel layered agentbased model. The first layer of the model generates detailed energy consumption and realistic occupant activities. The second layer is designed to simulate the peer pressure effect on the energy consumption behaviour of the individuals. The third layer is a customisable layer that simulates energy interventions. The implemented intervention in this paper is the proposed non-intrusive messaging intervention. A number of scenarios are presented in the experiments to show how the model can be used to evaluate the proposed intervention and achieve energy efficiency targets.

Item Type: Article
Identification Number: https://doi.org/10.1109/ACCESS.2018.2886146
24 November 2018Accepted
11 December 2018Published Online
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Mohamed Gaber
Date Deposited: 13 Dec 2018 11:11
Last Modified: 22 Mar 2023 12:01
URI: https://www.open-access.bcu.ac.uk/id/eprint/6733

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