Agent-based models for residential energy consumption and intervention simulation

Abdallah, Fatima (2019) Agent-based models for residential energy consumption and intervention simulation. Doctoral thesis, Birmingham City University.

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Abstract

The increase in energy consumption in buildings has gained global concern due to its negative implications on the environment. A major part of this increase is attributed to human behavioural energy waste, which has triggered the development of energy simulation models. These models are used to analyse energy consumption in buildings, study the effect of human behaviour and test the effectiveness of energy interventions. However, existing models are limited in simulating realistic and detailed human dynamics, including occupant interaction with appliances, with each other or with energy interventions. This detailed interaction is important when simulating and studying behavioural energy waste. To overcome the limitations of existing models, this thesis proposes a complete layered Agent-Based Model (ABM) composed of three layers / models. The daily behaviour model simulates realistic and detailed behaviour of occupants by integrating a Probabilistic Model (PM) in the ABM. The peer pressure model simulates family-level peer pressure effect on the energy consumption of the house. This model is underpinned using well established human behaviour theories by Leon Festinger – informal social communication theory, social comparison theory and cognitive dissonance theory. The messaging intervention model implements and tests a novel messaging intervention that is proposed in the thesis along with the complete ABM. The intervention is a middle solution between the abstract data presented by existing energy feedback systems and the automated approach followed by existing energy management systems. Therefore, it detects and sends energy waste incidents to occupants who are allowed to take control of their devices. The proposed intervention is tested in the messaging intervention model, which takes advantage of the two other proposed models. The undertaken experiments showed that the model is able to overcome the limitations of exiting models by simulating realistic and detailed human behaviour dynamics. Besides, the experiments showed that the model can be used by policy makers to decide how to target family members to achieve optimal energy saving, thus addressing the world’s concern about increased energy consumption levels.

Item Type: Thesis (Doctoral)
Dates:
DateEvent
12 March 2019Completed
Uncontrolled Keywords: Agent-based model, energy consumption, energy interventions
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific)
Divisions: Doctoral Research College > Doctoral Theses Collection
Depositing User: Doris Riou
Date Deposited: 09 Jan 2020 11:25
Last Modified: 12 Jan 2022 13:01
URI: https://www.open-access.bcu.ac.uk/id/eprint/8691

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