Coordinating electric vehicle charging with multiagent deep Q-networks for smart grid load balancing

LP Maguluri, A Umasankar, DV Babu… - … Informatics and Systems, 2024 - Elsevier
Abstract Integrating EVs (Electric Vehicles) with the electrical system presents essential load
distribution difficulties because EV recharging structures are unpredictable and variable …

[PDF][PDF] Enhancing hybrid renewable energy performance through deep Q-learning networks improved by fuzzy reward control

C Ameur, S Faquir, A Yahyaouy… - International Journal of …, 2022 - academia.edu
In a stand-alone system, the use of renewable energies, load changes, and interruptions to
transmission lines can cause voltage drops, impacting its reliability. A way to offset a change …

Deep Q‐network application for optimal energy management in a grid‐tied solar PV‐Battery microgrid

G Muriithi, S Chowdhury - The Journal of Engineering, 2022 - Wiley Online Library
This paper presents a deep Q‐network (DQN) technique to optimally manage energy
resources in a microgrid in which the algorithm learns tasks in the same way as humans do …

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

DJB Harrold, J Cao, Z Fan - Energy, 2022 - Elsevier
As the world seeks to become more sustainable, intelligent solutions are needed to increase
the penetration of renewable energy. In this paper, the model-free deep reinforcement …

Planning a Sustainable Electric Vehicle Infrastructure Considering Battery Life: Modeling and Resolution by the Multi-agent Q-learning Metaheuristic

H Elbaz, M Bourzik, A Elhilali Alaoui - Arabian Journal for Science and …, 2024 - Springer
The DWCS (dynamic wireless charging system) is an innovative electric vehicle charging
solution that allows for charging while the vehicle is in motion without requiring direct …

[图书][B] Application of artificial intelligence in three phase unbalanced smart power distribution grid

D Tiwari - 2021 - search.proquest.com
Electrification of the transportation sector can play an essential role in curbing fossil fuel
scarcity and oil shortages in the world. Electric vehicles (EVs) can significantly reduce CO 2 …

[PDF][PDF] AI Integration for Enhanced Smart Grids and Electric Vehicle Efficiency

MJM Louis - researchgate.net
This paper explores the integration of artificial intelligence (AI) technologies to enhance
smart grids and optimize electric vehicle (EV) efficiency. It examines the role of AI in load …

[HTML][HTML] Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation

MM Shibl, LS Ismail, AM Massoud - Energy Reports, 2023 - Elsevier
EVs are becoming more popular and widely used worldwide due to their environmentally
friendliness as part of the world efforts to decrease the effects of climate change. Moreover …

Hybrid methodology-based energy management of microgrid with grid-isolated electric vehicle charging system in smart distribution network

K Kalaiselvan, R Saravanan, B Adhavan… - Electrical …, 2023 - Springer
The integration of renewable energy sources (RESs) and smart power system has turned
microgrids (MGs) into effective platforms for incorporating various energy sources into …

Context Aware-Resource Optimality in Electric Vehicle Smart2Charge Application. A Deep Reinforcement Learning Base Approach

M Sharif, G Lückemeyer, H Seker - IEEE Access, 2023 - ieeexplore.ieee.org
Electric vehicle (EV) adoption is expanding, posing new issues for grid operators, fleet
operators, charging station operators, and EV owners. The challenge is to devise an efficient …