[HTML][HTML] A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging

H George-Williams, N Wade, RN Carpenter - Renewable and Sustainable …, 2022 - Elsevier
Abstract Smart energy hubs (Smart Hubs) equipped with Vehicle-to-Grid (V2G) charging,
photovoltaic (PV) energy generation, and hydrogen storage capabilities, are an emerging …

Grid-vehicle-grid (G2V2G) efficient power transmission: an overview of concept, operations, benefits, concerns, and future challenges

S Hossain, M Rokonuzzaman, KS Rahman… - Sustainability, 2023 - mdpi.com
Electric vehicles (EVs) are proportionally increasing day-by-day with the inclusion of
upgraded technology toward considered zero carbon emission efforts. To mitigate …

Electric Vehicles and Vehicle–Grid Interaction in the Turkish Electricity System

HH Coban, W Lewicki, E Sendek-Matysiak, Z Łosiewicz… - Energies, 2022 - mdpi.com
Electric vehicles and energy storage systems are technologies in the stage of intensive
development. One of the innovative ways to use electric cars is the Vehicle to Grid (V2G) …

Placement of public fast-charging station and solar distributed generation with battery energy storage in distribution network considering uncertainties and traffic …

A Pal, A Bhattacharya, AK Chakraborty - Journal of Energy Storage, 2021 - Elsevier
In this paper, a sustainable solution for the allocation of Public Fast-Charging Stations
(PFCSs) and Solar Distributed Generations (SDGs) along with Battery Energy Storages …

Charge scheduling optimization of plug-in electric vehicle in a PV powered grid-connected charging station based on day-ahead solar energy forecasting in Australia

F Titus, SB Thanikanti, S Deb, NM Kumar - Sustainability, 2022 - mdpi.com
Optimal charge scheduling of electric vehicles in solar-powered charging stations based on
day-ahead forecasting of solar power generation is proposed in this paper. The proposed …

A transfer learning method for electric vehicles charging strategy based on deep reinforcement learning

K Wang, H Wang, Z Yang, J Feng, Y Li, J Yang, Z Chen - Applied Energy, 2023 - Elsevier
Reinforcement learning (RL) is popularly used for the development of an orderly charging
strategy for electric vehicles (EVs). However, a new environment (eg, charging areas and …

Planning of EV charging station with distribution network expansion considering traffic congestion and uncertainties

A Pal, A Bhattacharya… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Proper planning for electric vehicle (EV) charging stations along with the required expansion
of the distribution network is essential for the continuous growth of EV and conventional …

Cyberattacks in Smart Grids: Challenges and solving the Multi-Criteria Decision-Making for cybersecurity options, including ones that incorporate artificial intelligence …

AA Bouramdane - Journal of Cybersecurity and Privacy, 2023 - mdpi.com
Smart grids have emerged as a transformative technology in the power sector, enabling
efficient energy management. However, the increased reliance on digital technologies also …

Electric vehicle optimum charging-discharging scheduling with dynamic pricing employing multi agent deep neural network

B Aljafari, PR Jeyaraj, AC Kathiresan… - Computers and Electrical …, 2023 - Elsevier
Abstract Electric Vehicles (EVs) are environmentally friendly. Extensive progress makes EVs
popularly deployed and adopted. Once EVs are connected to the smart grid, EVs can act as …

A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile

Z Zhao, CKM Lee, J Ren - Applied Energy, 2024 - Elsevier
This paper investigates the electric vehicle (EV) charging scheduling problem for public EV
charging stations (EVCSs) that can accommodate heterogeneous charging demands …