Review on interpretable machine learning in smart grid
In recent years, machine learning, especially deep learning, has developed rapidly and has
shown remarkable performance in many tasks of the smart grid field. The representation …
shown remarkable performance in many tasks of the smart grid field. The representation …
Stability and control of power grids
Power grids are critical infrastructure in modern society, and there are well-established
theories for the stability and control of traditional power grids under a centralized paradigm …
theories for the stability and control of traditional power grids under a centralized paradigm …
A short-term voltage stability online prediction method based on graph convolutional networks and long short-term memory networks
G Wang, Z Zhang, Z Bian, Z Xu - International Journal of Electrical Power & …, 2021 - Elsevier
Due to complex dynamic characteristics and large scale of power systems, it is a great
challenge to predict short-term voltage stability (STVS) online. To address this challenge, a …
challenge to predict short-term voltage stability (STVS) online. To address this challenge, a …
Data-driven short-term voltage stability assessment based on spatial-temporal graph convolutional network
Y Luo, C Lu, L Zhu, J Song - International Journal of Electrical Power & …, 2021 - Elsevier
Post-fault dynamics of short-term voltage stability (SVS) present spatial-temporal
characteristics, but the existing data-driven methods for online SVS assessment fail to …
characteristics, but the existing data-driven methods for online SVS assessment fail to …
Intelligent short-term voltage stability assessment via spatial attention rectified RNN learning
Focusing on fully learning intrinsic spatial and temporal dependencies from smart grids'
complicated transients in a computationally efficient way, this article develops an intelligent …
complicated transients in a computationally efficient way, this article develops an intelligent …
Applications of artificial intelligence in distribution power system operation
Due to the energy transition and the distribution of electricity generation, distribution power
systems gain a lot of attention as their importance increases and new challenges in …
systems gain a lot of attention as their importance increases and new challenges in …
A graph attention networks-based model to distinguish the transient rotor angle instability and short-term voltage instability in power systems
Digital simulation is significant for the operating mode and control decision-making of power
systems. In the process of simulation data analysis, stability analysis is an essential part …
systems. In the process of simulation data analysis, stability analysis is an essential part …
Robust representation learning for power system short-term voltage stability assessment under diverse data loss conditions
L Zhu, W Wen, Y Qu, F Shen, J Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the help of neural network-based representation learning, significant progress has
been recently made in data-driven online dynamic stability assessment (DSA) of complex …
been recently made in data-driven online dynamic stability assessment (DSA) of complex …
Networked time series shapelet learning for power system transient stability assessment
L Zhu, DJ Hill - IEEE Transactions on Power Systems, 2021 - ieeexplore.ieee.org
While many machine learning approaches have been widely applied to power system
online dynamic stability assessment, how to sufficiently learn spatial-temporal correlations …
online dynamic stability assessment, how to sufficiently learn spatial-temporal correlations …
Comprehensive review of short-term voltage stability evaluation methods in modern power systems
The possibility to monitor and evaluate power system stability in real-time is in growing
demand. Whilst most stability-related studies focus on long-term voltage stability and …
demand. Whilst most stability-related studies focus on long-term voltage stability and …