Author
Listed:
- Kavousighahfarokhi, Arash
- Hannan, M.A.
- Abu, Sayem M.
- Ker, Pin Jern
- Wong, Richard TK.
- Jang, Gilsoo
Abstract
The transition to electric transportation significantly impacts power grid operations amid environmental and energy challenges. Future smart grids are expected to facilitate two-way energy exchange through electric vehicles (EVs), enhancing efficiency and benefiting consumers and producers. To maximize the advantages of EV integration within smart grids and the Internet of Energy (IoE) use, challenges related to energy transfer, battery technologies, and operational standards must be addressed, as current grid infrastructure limits the full potential of EV contributions. This paper reviews EV charging technologies and their integration into smart grids and the IoE use towards data dissemination and management. It covers energy transfer, battery technologies, charging schemes, and management standards. The research explores EV classifications, powertrains, energy sources, and grid integration. It emphasizes intelligent charging solutions and data management within EV networks and renewable energy sources. Notably, IoE-enabled agent-based modeling can boost renewable energy utilization by 50.1 %, significantly enhancing system sustainability. The paper reviews distributed energy management schemes, connectivity issues, and current charging methods, discussing optimization through neural network strategies. The standards for EV integrations and outlines future research directions are highlighted and demonstrated to improve grid-integrated EV's energy system efficiency and sustainability through IoE utilization.
Suggested Citation
Kavousighahfarokhi, Arash & Hannan, M.A. & Abu, Sayem M. & Ker, Pin Jern & Wong, Richard TK. & Jang, Gilsoo, 2025.
"Grid-integrated electric vehicle charging station technologies and data dissemination through internet of energy use,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 220(C).
Handle:
RePEc:eee:rensus:v:220:y:2025:i:c:s1364032125005775
DOI: 10.1016/j.rser.2025.115904
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