Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …
autonomous software that optimizes decision-making and energy distribution operations …
[HTML][HTML] Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities
Despite widespread adoption and outstanding performance, machine learning models are
considered as “black boxes”, since it is very difficult to understand how such models operate …
considered as “black boxes”, since it is very difficult to understand how such models operate …
[HTML][HTML] A systematic review of machine learning techniques related to local energy communities
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …
processes in several sectors, as in the case of electrical power systems. Machine learning …
Hierarchical operation of electric vehicle charging station in smart grid integration applications—An overview
With the fast development of electrifications of vehicles, EV charging stations are booming in
coming years. Meanwhile, the growing demand for charging power, and the stochastic …
coming years. Meanwhile, the growing demand for charging power, and the stochastic …
[HTML][HTML] Demand side management of electric vehicles in smart grids: A survey on strategies, challenges, modeling, and optimization
The shift of transportation technology from internal combustion engine (ICE) based vehicles
to electric vehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater …
to electric vehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater …
Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
energy technologies to keep the environment safe by reducing CO 2 emissions. The …
Deep reinforcement learning for continuous electric vehicles charging control with dynamic user behaviors
This paper aims to crack the individual EV charging scheduling problem considering the
dynamic user behaviors and the electricity price. The uncertainty of the EV charging demand …
dynamic user behaviors and the electricity price. The uncertainty of the EV charging demand …
Energy demand prediction with federated learning for electric vehicle networks
In this paper, we propose novel approaches using state-of-the-art machine learning
techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These …
techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These …
Review on scheduling, clustering, and forecasting strategies for controlling electric vehicle charging: Challenges and recommendations
The usage and adoption of electric vehicles (EVs) have increased rapidly in the 21st century
due to the shifting of the global energy demand away from fossil fuels. The market …
due to the shifting of the global energy demand away from fossil fuels. The market …
Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing
N Fescioglu-Unver, MY Aktaş - Renewable and Sustainable Energy …, 2023 - Elsevier
The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …