Multi-objective Smart Charge Control of Electric Vehicles

Das, Ridoy (2020) Multi-objective Smart Charge Control of Electric Vehicles. Doctoral thesis, Northumbria University.

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With the increasing integration of electric vehicles and renewable energy sources in electricity networks, key opportunities in terms of a cleaner environment and a sustainable energy portfolio are unlocked. However, the widespread deployment of these two technologies, can entail significant challenges for the electricity grid and in a larger context for the society, when they are not optimally integrated. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are being proposed as crucial solutions to achieve economic, technical and environmental benefits in future smart grids. The implementation of these technologies involves a number of key stakeholders, namely, the end-electricity user, the electric vehicle owner, the system operators and policy makers. For a wider and efficient implementation of the smart grid vision, these stakeholders must be engaged and their aims must be fulfilled. However, the financial, technical and environmental objectives of these stakeholders are often conflicting, which leads to an intricate paradigm requiring efficient and fair policies. With this focus in mind, the present research work develops multi-objective optimisation algorithms to control the charging and discharging process of electric vehicles. Decentralised, hybrid and real-time optimisation algorithms are proposed, modelled, simulated and validated. End user energy cost, battery degradation, grid interaction and CO2 emissions are optimised in this work and their trade-offs are highlighted. Multi-criteria-decision-making approaches and game theoretical frameworks are developed to conciliate the interests of the involved stakeholders. The results, in the form of optimal electric vehicle charging/discharging schedules, show improvements along all the objectives while complying with the user requirements. The outcome of the present research work serves as a benchmark for informing system operators and policy makers on the necessary measures to ensure an efficient and sustainable implementation of electro-mobility as a fundamental part of current and future smart grids.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Optimisation, Distributed control, Renewable Energy, Battery degradation, Game theory
Subjects: H300 Mechanical Engineering
H600 Electronic and Electrical Engineering
H900 Others in Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Rachel Branson
Date Deposited: 28 Jul 2020 08:43
Last Modified: 28 Jun 2022 08:01

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