City Research Online

Abstract

As climate change accelerates and the energy crisis deepens, electric vehicle adoption is growing rapidly with strong governmental support. However, this growth is straining electricity networks, prompting expensive infrastructure upgrades and a need for smart charging solutions, including Grid-to-Vehicle and Vehicle-to-Grid. This research synthesizes residential vehicle travel patterns from statistical data to model the electrical demand profile from uncoordinated charging, capturing the diversity in driving behaviour. It then develops scalable models for unidirectional and bidirectional smart charging to assess their impact on system reliability and their capacity credit within a probabilistic Monte Carlo framework. The case studies additionally present sensitivities on smart charging participation, electric vehicle uptake, and installed wind capacity. Results show that both smart charging concepts enhance reliability and that their capacity contributions grow with increased user engagement and wind generation, though the benefits plateau beyond certain thresholds.

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) license to any Accepted Manuscript version arising.
Publisher Keywords:	electric vehicles, Monte Carlo, reliability, smart charging, vehicle-to-grid
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments:	School of Science & Technology School of Science & Technology > Department of Engineering
SWORD Depositor:	Symplectic Administrator

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