Unleashing the potential of blockchain and machine learning: Insights and emerging trends from bibliometric analysis
Blockchain and machine learning (ML) has garnered growing interest as cutting-edge
technologies that have witnessed tremendous strides in their respective domains …
technologies that have witnessed tremendous strides in their respective domains …
Blockchain for securing ai applications and open innovations
Nowadays, open innovations such as intelligent automation and digitalization are being
adopted by every industry with the help of powerful technology such as Artificial Intelligence …
adopted by every industry with the help of powerful technology such as Artificial Intelligence …
Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading
The multi-energy system (MES), which is regarded as an optimum solution to a high-
efficiency, green energy system and a crucial shift towards the future low-carbon energy …
efficiency, green energy system and a crucial shift towards the future low-carbon energy …
Incremental incentive mechanism design for diversified consumers in demand response
Demand response has been proven to be an effective way to improve energy utilization
efficiency. It is notable that the diversified characteristics of residential consumers, which …
efficiency. It is notable that the diversified characteristics of residential consumers, which …
Virtual power plant containing electric vehicles scheduling strategies based on deep reinforcement learning
J Wang, C Guo, C Yu, Y Liang - Electric power systems research, 2022 - Elsevier
Virtual power plants (VPPs), which aggregate customer-side flexibility resources, provide an
effective way for customers to participate in the electricity market, and provide a variety of …
effective way for customers to participate in the electricity market, and provide a variety of …
CBLSTM-AE: a hybrid deep learning framework for predicting energy consumption
Multisource energy data, including from distributed energy resources and its multivariate
nature, necessitate the integration of robust data predictive frameworks to minimise …
nature, necessitate the integration of robust data predictive frameworks to minimise …
Blockchain intelligence: Intelligent blockchains for web 3.0 and beyond
As the next-generation Internet characterized by readability, writability, and ownability, Web
3.0 necessitates the fusion of blockchain and artificial intelligence (AI) technologies to …
3.0 necessitates the fusion of blockchain and artificial intelligence (AI) technologies to …
Artificial intelligence and mathematical models of power grids driven by renewable energy sources: A survey
To face the impact of climate change in all dimensions of our society in the near future, the
European Union (EU) has established an ambitious target. Until 2050, the share of …
European Union (EU) has established an ambitious target. Until 2050, the share of …
[HTML][HTML] Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units
This paper proposes a safe reinforcement learning algorithm for generation bidding
decisions and unit maintenance scheduling in a competitive electricity market environment …
decisions and unit maintenance scheduling in a competitive electricity market environment …
VirtElect: A peer-to-peer trading platform for local energy transactions
An average UK electricity bill is made up of at least 60% service charge, with approximately
22% related to network characteristics including distance charge. This makes distance and …
22% related to network characteristics including distance charge. This makes distance and …