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Lookup NU author(s): Dr Myriam Neaimeh, Dr Matthew Deakin
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 The Author(s).The uptake of electric vehicles (EVs) and renewable energy technologies is changing the magnitude, variability, and direction of power flows in electricity networks. To ensure a successful transition to a net zero energy system, it will be necessary for a wide range of stakeholders to understand the impacts of these changing flows on networks. However, there is a gap between those with the data and capabilities to understand electricity networks, such as network operators, and those working on adjacent parts of the energy transition jigsaw, such as electricity suppliers and EV charging infrastructure operators. This paper describes the electric vehicle network analysis tool (EVENT), developed to help make network analysis accessible to a wider range of stakeholders in the energy ecosystem who might not have the bandwidth to curate and integrate disparate datasets and carry out electricity network simulations. EVENT analyses the potential impacts of low-carbon technologies on congestion in electricity networks, helping to inform the design of products and services. To demonstrate EVENT's potential, we use an extensive smart meter dataset provided by an energy supplier to assess the impacts of electricity smart tariffs on networks. Results suggest both network operators and energy suppliers will have to work much more closely together to ensure that the flexibility of customers to support the energy system can be maximized, while respecting safety and security constraints within networks. EVENT's modular and open-source approach enables integration of new methods and data, future-proofing the tool for long-term impact.
Author(s): Neaimeh M, Deakin M, Jenkinson R, Giles O
Publication type: Article
Publication status: Published
Journal: Data-Centric Engineering
Year: 2023
Volume: 4
Online publication date: 10/01/2023
Acceptance date: 19/12/2022
Date deposited: 24/01/2023
ISSN (electronic): 2632-6736
Publisher: Cambridge University Press
URL: https://doi.org/10.1017/dce.2022.41
DOI: 10.1017/dce.2022.41
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