An agent-based model for energy investment decisions in the residential sector

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Title: An agent-based model for energy investment decisions in the residential sector
Authors: Sachs, J
Meng, Y
Giarola, S
Hawkes, A
Item Type: Journal Article
Abstract: Energy-related investment decisions in the buildings sector are heterogeneous in that the outcome for each individual varies according to budget, values, and perception of a technology, even if an apparently identical decision task is faced. In particular, the rate of adoption of new energy-efficient technologies is often hard to model and underlines the need for an advanced approach to capture diversity in decision-making, and enable the inclusion of economic, comfort, environmental and social aspects. This paper presents an enhanced agent-based model that captures several characteristics of consumer behaviour that influence investment decisions. Multiple agents with different objectives, search strategies, and decision methods are implemented. A case study is presented which illustrates the benefits of the approach for the residential sector in the UK. The agent-based method shows diversity in investment decisions, without requiring the constraints on uptake needed in many models. This leads to a range of technologies in the market during a transition phase, continuous investment in low capital cost technologies, and eventually the emergence of a low carbon system based on new mass market technologies. The system that emerges is vastly different from one observed when economically rational investment is assumed and uptake constraints are applied.
Issue Date: 1-Apr-2019
Date of Acceptance: 30-Jan-2019
URI: http://hdl.handle.net/10044/1/66291
DOI: https://doi.org/10.1016/j.energy.2019.01.161
ISSN: 0360-5442
Publisher: Elsevier
Start Page: 752
End Page: 768
Journal / Book Title: Energy
Volume: 172
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor/Funder: Natural Environment Research Council (NERC)
Funder's Grant Number: NE/N018656/1
Keywords: Science & Technology
Physical Sciences
Technology
Thermodynamics
Energy & Fuels
Energy systems model
Agent-based
Residential
CO2
INNOVATION DIFFUSION
CHOICE MODELS
TECHNOLOGY
SYSTEMS
PREFERENCES
ACCEPTANCE
SIMULATION
HEAT
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
0914 Resources Engineering and Extractive Metallurgy
Energy
Publication Status: Published
Embargo Date: 2020-02-04
Online Publication Date: 2019-02-04
Appears in Collections:Faculty of Engineering
Earth Science and Engineering
Chemical Engineering



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