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Review on deep learning applications in frequency analysis and control of modern power system
The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …
regional power grids in wide area and large scale have led the modern power system to …
Situation awareness in ai-based technologies and multimodal systems: Architectures, challenges and applications
Situation Awareness (SA) is a process of sensing, understanding and predicting the
environment and is an important component in complex systems. The reception of …
environment and is an important component in complex systems. The reception of …
[HTML][HTML] Analysis of renewable-friendly smart grid technologies for the distributed energy investment projects using a hybrid picture fuzzy rough decision-making …
Smart grid systems help increase RWJ projects (RWJ) so that environmentally friendly
energy production can be generated. However, efficient technologies should be …
energy production can be generated. However, efficient technologies should be …
A real-time hierarchical framework for fault detection, classification, and location in power systems using PMUs data and deep learning
Abstract Frequency Disturbance Events (FDEs) occur due to various events such as
Generator Trip (GT), Line Outage (LO), and Load Disconnection (LD), which affect the …
Generator Trip (GT), Line Outage (LO), and Load Disconnection (LD), which affect the …
Optimal energy storage system-based virtual inertia placement: A frequency stability point of view
In this paper, the problem of optimal placement of virtual inertia is considered as a techno-
economic problem from a frequency stability point of view. First, a data driven-based …
economic problem from a frequency stability point of view. First, a data driven-based …
[HTML][HTML] Intelligent fault detection and classification schemes for smart grids based on deep neural networks
Effective fault detection, classification, and localization are vital for smart grid self-healing
and fault mitigation. Deep learning has the capability to autonomously extract fault …
and fault mitigation. Deep learning has the capability to autonomously extract fault …
Fault detection and classification in ring power system with DG penetration using hybrid CNN-LSTM
A modern electric power system integrated with advanced technologies such as sensors
and smart meters is referred to as a “smart grids”, aimed at enhancing electrical power …
and smart meters is referred to as a “smart grids”, aimed at enhancing electrical power …
A data-driven under frequency load shedding scheme in power systems
This paper presents a measurement-based under-frequency load shedding scheme that
considers time delays, measurement uncertainties, and communication network faults …
considers time delays, measurement uncertainties, and communication network faults …
Power system event identification based on deep neural network with information loading
Online power system event identification and classification are crucial to enhancing the
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …