Advanced Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 21
Special Issue Editor
Interests: power systems operation and planning; renewable energy systems; smart grids; electric vehicles; electricity market
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to announce a Special Issue entitled “Advanced Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies” to be published in Energies. The rapid growth in the integration of Electric Vehicles (EVs) and the increasing prevalence of renewable energy sources present new opportunities and challenges in power grid management. As the demand for sustainable energy solutions continues to grow, the interplay between electric vehicles and the grid has become a critical area of research.
This Special Issue invites original and innovative research papers and review articles that address advancements in G2V and V2G technologies, their applications, and future directions. Topics of interest for this special issue include, but are not limited to, the following:
- Advanced grid-to-vehicle (G2V) communication and control techniques;
- Vehicle-to-grid (V2G) system architectures, algorithms, and methodologies;
- Smart charging and discharging strategies for EVs;
- V2G and G2V integration with renewable energy sources (e.g., solar, wind);
- Grid stability and balancing using V2G and G2V systems;
- Economic and business models for G2V and V2G systems;
- Impacts of V2G/G2V on grid operations and energy management;
- Cybersecurity and privacy concerns in V2G/G2V systems;
- Multi-agent systems and machine learning for V2G/G2V optimization;
- Policy and regulatory frameworks for V2G and G2V technologies;
- Data analytics for V2G and G2V integration;
- Case studies and real-world implementations of V2G and G2V.
We believe that by sharing knowledge and insights, we can enhance the understanding of the challenges and opportunities associated with the integration of advanced Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) technologies into power grids. Your contribution to this Special Issue will be crucial in advancing the field and shaping the future of smart grid systems and energy management.
Dr. Mahmoud Ghofrani
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- vehicle-to-grid
- grid-to-vehicle
- smart charging and discharging
- renewable energy sources
- cybersecurity
- privacy
- machine learning
- multi-agent systems
- data analytics
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