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Title: Agent-based models for residential energy consumption and intervention simulation
Author: Abdallah, Fatima
ISNI:       0000 0004 8501 8399
Awarding Body: Birmingham City University
Current Institution: Birmingham City University
Date of Award: 2019
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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.
Supervisor: Basurra, Shadi ; Gaber, Mohamed Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: G400 Computer Science ; G900 Others in Mathematical and Computing Sciences ; H100 General Engineering