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Efficient electric vehicle charging infrastructure planning using data-driven optimization

Lookup NU author(s): Farzaneh FarhadiORCiD, Professor Roberto Palacin, Professor Phil BlytheORCiD

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Abstract

© The Institution of Engineering & Technology 2023. This paper presents a high-level overview of a data-driven methodology for optimising the implementation of policy commitments in the transportation sector, specifically focusing on electric vehicle (EV) charging infrastructure in Newcastle upon Tyne, United Kingdom. The study utilises a simulation model provided by the industrial partner, Arup Group Limited, and combines it with a genetic optimization algorithm inspired by Long Short-Term Memory (LSTM) and fuzzy logic. Four future energy scenarios from National Grid are considered to predict EV quantities and the energy demand, reflecting varying levels of decarbonisation and societal change. The optimization algorithm is applied to each scenario to determine the optimal charging point types, locations, quantities, total capital and operational expenditures, and operating hours of the charging points. This paper provides a high-level explanation of the methodology and results, without delving into the mathematical equations or detailed aspects of the simulation and optimization processes. The proposed methodology demonstrates a promising approach to efficiently implement policy commitments in the transport sector, particularly in the context of EV charging infrastructure, enabling local authorities to effectively plan and manage the transition to zero-emission vehicles.


Publication metadata

Author(s): Farhadi F, Wang S, Palacin R, Blythe P

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: EVI: Charging Ahead (EVI 2023)

Year of Conference: 2023

Pages: 1-6

Online publication date: 16/01/2024

Acceptance date: 02/04/2018

Publisher: IET

URL: https://doi.org/10.1049/icp.2023.3116

DOI: 10.1049/icp.2023.3116

Library holdings: Search Newcastle University Library for this item

Series Title: IET Conference Proceedings

ISBN: 9781839539961


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