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An innovation diffusion model of a local electricity network that is influenced by internal and external factors

Hattam, Laura and Vukadinović Greetham, Danica (2018). An innovation diffusion model of a local electricity network that is influenced by internal and external factors. Physica A: Statistical Mechanics and its Applications, 490 pp. 353–365.

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Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes’ model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes’ equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

Item Type: Journal Item
Copyright Holders: 2017 Elsevier
ISSN: 0378-4371
Project Funding Details:
Funded Project NameProject IDFunding Body
New Thames Valley VisionSSET203Low Carbon Network Fund established by Ofgem
Keywords: Innovation diffusion; Travelling waves; Electricity network; FEM
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Related URLs:
Item ID: 55694
Depositing User: Danica Vukadinovic Greetham
Date Deposited: 16 Aug 2018 13:18
Last Modified: 05 Jun 2020 23:25
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