Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis
Lee, Timothy and Yao, Runming (2012) Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis. Energy Policy, 52. pp. 363-372. ISSN 0301-4215
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Abstract
The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing
models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed.
It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour
has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model.
Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed
and tested, which demonstrates the feasibility of an agent approach. This model shows that an agentbased approach is promising as a means to predict the effectiveness of various policy measures.
| Item Type: | Article |
|---|---|
| Identification Number: | 10.1016/j.enpol.2012.09.048 |
| Dates: | Date Event 17 September 2012 Accepted 23 October 2012 Published Online |
| Uncontrolled Keywords: | Domestic, Energy model, Buying behaviour |
| Subjects: | CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-02 - building |
| Divisions: | Faculty of Computing, Engineering and the Built Environment > College of Built Environment |
| Depositing User: | Timothy Lee |
| Date Deposited: | 10 Aug 2018 06:55 |
| Last Modified: | 20 Jun 2024 11:47 |
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/6223 |
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