Analysis of cyber security attacks and its solutions for the smart grid using machine learning and blockchain methods
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
When smart cities get smarter via machine learning: An in-depth literature review
The manuscript represents a comeprehensive and systematic literature review on the
machine learning methods in the emerging applications of the smart cities. Application …
machine learning methods in the emerging applications of the smart cities. Application …
A Cyber-Secure generalized supermodel for wind power forecasting based on deep federated learning and image processing
H Moayyed, A Moradzadeh… - Energy Conversion and …, 2022 - Elsevier
Accurate wind power forecasting is one of the most important operations within the
economic dispatch problem to increase the performance of power and energy systems …
economic dispatch problem to increase the performance of power and energy systems …
Cyber resilience in renewable microgrids: A review of standards, challenges, and solutions
Increasing penetration of power electronic-based renewable energy generation resources,
decreasing total rotational inertia, and bidirectional power flow have changed the concept of …
decreasing total rotational inertia, and bidirectional power flow have changed the concept of …
A review of the applications of artificial intelligence in renewable energy systems: An approach-based study
Recent advancements in data science and artificial intelligence, as well as the development
of clean and sustainable energy sources, have created numerous opportunities for energy …
of clean and sustainable energy sources, have created numerous opportunities for energy …
Deep learning for cybersecurity in smart grids: Review and perspectives
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …
significant attention in recent years. The application of artificial intelligence (AI), particularly …
Research trends, themes, and insights on artificial neural networks for smart cities towards SDG-11
Smart Cities can promote economic growth, sustainable transport, environmental
sustainability, and good governance among cities. These benefits can support cities in …
sustainability, and good governance among cities. These benefits can support cities in …
[HTML][HTML] Electric load forecasting under False Data Injection Attacks using deep learning
Precise electric load forecasting at different time horizons is an essential aspect for electricity
producers and consumers who participate in energy markets in order to maximize their …
producers and consumers who participate in energy markets in order to maximize their …
A novel energy management framework incorporating multi‐carrier energy hub for smart city
The development of advanced and intelligent measurement instruments in recent years has
increased the intelligence of modern energy systems, especially power systems. Besides …
increased the intelligence of modern energy systems, especially power systems. Besides …
Deep learning-based cyber resilient dynamic line rating forecasting
Increased integration of renewable energy resources into the grid may create new difficulties
for ensuring a sustainable power grid which drives electric utilities to use a number of cost …
for ensuring a sustainable power grid which drives electric utilities to use a number of cost …