Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution
AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
[HTML][HTML] Reinforcement learning for electric vehicle applications in power systems: A critical review
Electric vehicles (EVs) are playing an important role in power systems due to their significant
mobility and flexibility features. Nowadays, the increasing penetration of renewable energy …
mobility and flexibility features. Nowadays, the increasing penetration of renewable energy …
Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review
Transportation electrification is one of the main research areas for the past decade. Electric
vehicles (EVs) are taking over the market share of conventional internal combustion engine …
vehicles (EVs) are taking over the market share of conventional internal combustion engine …
Reinforcement learning and its applications in modern power and energy systems: A review
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …
other emerging technologies, there are increasing complexities and uncertainties for …
A survey of recent advances in edge-computing-powered artificial intelligence of things
Z Chang, S Liu, X Xiong, Z Cai… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …
multitude of wired and wireless sensors generating a variety of heterogeneous data over …
Reinforcement learning for selective key applications in power systems: Recent advances and future challenges
With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …
modern power systems are confronted with new operational challenges, such as growing …
Deep reinforcement learning for power system applications: An overview
Due to increasing complexity, uncertainty and data dimensions in power systems,
conventional methods often meet bottlenecks when attempting to solve decision and control …
conventional methods often meet bottlenecks when attempting to solve decision and control …
[HTML][HTML] Artificial intelligence techniques for enabling Big Data services in distribution networks: A review
S Barja-Martinez, M Aragüés-Peñalba… - … and Sustainable Energy …, 2021 - Elsevier
Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …
systems by extracting value from the data generated by the deployed metering and sensing …
A multi-agent reinforcement learning-based data-driven method for home energy management
This paper proposes a novel framework for home energy management (HEM) based on
reinforcement learning in achieving efficient home-based demand response (DR). The …
reinforcement learning in achieving efficient home-based demand response (DR). The …