A review on challenges and future of green charging networks for zero emission electric transportation
There has been a notable increase in awareness within the scientific community regarding the advancement of cognitive approaches designed to address the inherent vulnerabilities of electric transportation. This study provides a comprehensive analysis of various important aspects related to electric...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Energy Conversion and Management: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590174524003453 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | There has been a notable increase in awareness within the scientific community regarding the advancement of cognitive approaches designed to address the inherent vulnerabilities of electric transportation. This study provides a comprehensive analysis of various important aspects related to electric automobile (EA) navigation, EA recharging planning, design optimization and deployment of EA recharging facilities, and the complexities of power or demand optimization. The study conducts a comprehensive analysis of the advantages and limitations of computational tools in addressing complex challenges, thereby assessing their potential effectiveness. Furthermore, this paper provides a concise summary of the main statistical frameworks that are commonly employed to tackle the complexities encountered in smart transportation computing. Using independent and interlinked mathematical models, authors examine contemporary computational approaches that manage corporate architectural challenges in novel manners. The aim of this work is to investigate potential avenues for future research, with a focus on attaining sustainable mobility while also promoting the intelligent advancement of microgrids. This study makes a valuable contribution to the field of energy strategy for smart transportation by providing a thorough evaluation of the effects of EAs and outlining a path towards the development of sustainable and intelligent transportation systems. |
|---|---|
| ISSN: | 2590-1745 |