Multi-agent systems in Peer-to-Peer energy trading: A comprehensive survey
Energy networks around the world have experienced a significant increase in the amount of
distributed generation. This decentralization of energy markets has led to a surge of interest …
distributed generation. This decentralization of energy markets has led to a surge of interest …
A state of the art review on energy management techniques and optimal sizing of DERs in grid-connected multi-microgrids
DB Aeggegn, GN Nyakoe, C Wekesa - Cogent Engineering, 2024 - Taylor & Francis
In recent times, there has been a growing focus on multi-micro-grids (MMGs) system, owing
to its well-suited structures for efficiently accommodating large-scale integration of …
to its well-suited structures for efficiently accommodating large-scale integration of …
RAN resource slicing in 5G using multi-agent correlated Q-learning
5G is regarded as a revolutionary mobile network, which is expected to satisfy a vast number
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
Multiagent Bayesian deep reinforcement learning for microgrid energy management under communication failures
Microgrids (MGs) are important players for the future transactive energy systems where a
number of intelligent Internet of Things (IoT) devices interact for energy management in the …
number of intelligent Internet of Things (IoT) devices interact for energy management in the …
Variational autoencoder generative adversarial network for synthetic data generation in smart home
Data is the fuel of data science and machine learning techniques for smart grid applications,
similar to many other fields. However, the availability of data can be an issue due to privacy …
similar to many other fields. However, the availability of data can be an issue due to privacy …
Peer-to-peer energy trading in dairy farms using multi-agent systems
To accomplish the desired reduction in carbon emissions, society must improve the
integration of renewable generation and accelerate the adoption of technologies like peer-to …
integration of renewable generation and accelerate the adoption of technologies like peer-to …
Smart Home Energy Management: VAE-GAN synthetic dataset generator and Q-learning
In recent years, there has been a growing interest in academia and industry in the analysis
of electrical consumption in residential buildings and the implementation of smart home …
of electrical consumption in residential buildings and the implementation of smart home …
Deep reinforcement learning based coalition formation for energy trading in smart grid
M Sadeghi, M Erol-Kantarci - 2021 IEEE 4th 5G World Forum …, 2021 - ieeexplore.ieee.org
Peer-to-peer energy trading is a promising approach to better integrate renewable energy
resources, reduce customer costs and increase the reliability of the smart grid by employing …
resources, reduce customer costs and increase the reliability of the smart grid by employing …
Optimized Energy Dispatch for Microgrids with Distributed Reinforcement Learning
The increasing integration of renewable energy resources (RES) introduces uncertainties in
modern power systems and makes the dynamic energy dispatch (DED) problem …
modern power systems and makes the dynamic energy dispatch (DED) problem …
Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms
Farm businesses are increasingly adopting renewables to enhance energy efficiency and
reduce reliance on fossil fuels and the grid. This shift aims to decrease dairy farms' …
reduce reliance on fossil fuels and the grid. This shift aims to decrease dairy farms' …