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An Insight of Deep Learning Based Demand Forecasting in Smart Grids. [PDF]
Sensors (Basel), 2023 Smart grids are able to forecast customers’ consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand.
Aguiar-Pérez JM, Pérez-Juárez MÁ.
europepmc +2 more sources
Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review [PDF]
Renewable & Sustainable Energy Reviews, 2022 Governments' net zero emission target aims at increasing the share of renewable energy sources as well as influencing the behaviours of consumers to support the cost-effective balancing of energy supply and demand.
Weiqi Hua +5 more
semanticscholar +1 more source
Applied Sciences, 2023 Nowadays, voltage sag continues to remain a critical PQ issue in the industry. Since it is not possible to install a voltage analyzer on every node, optimal monitoring locations must be determined.
Vladislav Liubčuk +3 more
doaj +1 more source
Load Forecasting Techniques and Their Applications in Smart Grids
Energies, 2023 The growing success of smart grids (SGs) is driving increased interest in load forecasting (LF) as accurate predictions of energy demand are crucial for ensuring the reliability, stability, and efficiency of SGs. LF techniques aid SGs in making decisions
H. Habbak +4 more
semanticscholar +1 more source
Journal of Cybersecurity and Privacy, 2023 Smart grids have emerged as a transformative technology in the power sector, enabling efficient energy management. However, the increased reliance on digital technologies also exposes smart grids to various cybersecurity threats and attacks. This article
A. Bouramdane
semanticscholar +1 more source
Secondary Voltage Control in a Hybrid Microgrid [PDF]
International Journal of Industrial Electronics, Control and Optimization, 2019 Compared to individual DC or AC microgrids, the Hybrid microgrids (HMGs) are more efficient and inexpensive due to eliminating of multiple DC-AC-DC conversions.
YousefReza Jafarian +2 more
doaj +1 more source
An Overview of Hydrogen’s Application for Energy Purposes in Lithuania
Applied Sciences, 2023 Hydrogen has emerged as a promising climate-neutral energy carrier able to facilitate the processes of the European Union (EU) energy transition. Green hydrogen production through the electrolysis process has gained increasing interest recently for ...
Darius Pranckevičius +3 more
doaj +1 more source
Electronics, 2023 With the assistance of machine learning, difficult tasks can be completed entirely on their own. In a smart grid (SG), computers and mobile devices may make it easier to control the interior temperature, monitor security, and perform routine maintenance.
Tehseen Mazhar +8 more
semanticscholar +1 more source
Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey [PDF]
Computer Science Review, 2021 Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed.
Viet Quoc Pham +9 more
semanticscholar +1 more source
Distributed Anomaly Detection in Smart Grids: A Federated Learning-Based Approach
IEEE Access, 2023 The smart grid integrates Information and Communication Technologies (ICT) into the traditional power grid to manage the generation, distribution, and consumption of electrical energy. Despite its many advantages, it faces significant challenges, such as
J. Jithish +3 more
semanticscholar +1 more source