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

Vahidinasab, V ORCID: https://orcid.org/0000-0002-0779-8727, Nikkhah, S, Allahham, A and Giaouris, D, 2021. Boosting integration capacity of electric vehicles: a robust security constrained decision making. International Journal of Electrical Power and Energy Systems, 133: 107229. ISSN 0142-0615

Preview

Text 1445353_Vahidinasab.pdf - Post-print Download (471kB) | Preview

Abstract

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.

Item Type:	Journal article
Publication Title:	International Journal of Electrical Power and Energy Systems
Creators:	Vahidinasab, V., Nikkhah, S., Allahham, A. and Giaouris, D.
Publisher:	Elsevier BV
Date:	December 2021
Volume:	133
ISSN:	0142-0615
Identifiers:	Number Type 10.1016/j.ijepes.2021.107229 DOI 1445353 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	14 Jun 2021 10:45
Last Modified:	11 Jun 2022 03:00
Related URLs:	Publisher
URI:	https://irep.ntu.ac.uk/id/eprint/43050

Actions (login required)

Edit View

Statistics

Views

Downloads