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Boosting integration capacity of electric vehicles: A robust security constrained decision making

Lookup NU author(s): Dr Saman Nikkhah, Dr Adib Allahham, Professor Damian Giaouris

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Elsevier Ltd, 2021.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 2021 The Author(s)Global electric vehicles (EVs) fleet is expanding at a rapid pace. Considering the uncertain driving pattern of EVs, they are dynamic consumers of electricity and their integration can give rise to operational problems and jeopardize the security of the power system. Under such circumstances, the implementation of demand-side response (DSR) programs is more likely to be an effective solution for reducing the risks of load curtailment or security problems. This study proposes a voltage stability constrained DSR-coordinated planning model for increasing the penetration level of EVs in a distribution system consisting of photovoltaics (PVs), wind turbines (WTs) and responsive loads. The uncertainties of PV/WT generation, the driving pattern of EVs, and load demand are modeled by an improved form of information gap decision theory (IGDT), hereafter called weighted IGDT (WIGDT). Due to the fact that the proposed model is nonlinear and non-convex, a linearization technique is adopted and the proposed model is formulated as a mixed-integer linear programming (MILP), solved using the general algebraic modeling system (GAMS) software. The standard 33-bus distribution test system and a real-world smart distribution network, based in the Isle of Wight in the UK, are used to evaluate the performance of the model.


Publication metadata

Author(s): Vahidinasab V, Nikkhah S, Allahham A, Giaouris D

Publication type: Article

Publication status: Published

Journal: International Journal of Electrical Power and Energy Systems

Year: 2021

Volume: 133

Print publication date: 01/12/2021

Online publication date: 20/05/2021

Acceptance date: 11/06/2021

Date deposited: 29/07/2021

ISSN (print): 0142-0615

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.ijepes.2021.107229

DOI: 10.1016/j.ijepes.2021.107229


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Funding

Funder referenceFunder name
731268

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