Flexible machine learning-based cyberattack detection using spatiotemporal patterns for distribution systems
This letter develops a flexible machine learning detection method for cyberattacks in
distribution systems considering spatiotemporal patterns. Spatiotemporal patterns are …
distribution systems considering spatiotemporal patterns. Spatiotemporal patterns are …
Feature extraction and classification of time-varying power load characteristics based on PCANet and CNN+ Bi-LSTM algorithms
S Bian, Z Wang, W Song, X Zhou - Electric Power Systems Research, 2023 - Elsevier
The feature extraction and classification of power load characteristics are vital for time-
varying load modeling. However, due to the influence of the season variation, the existing …
varying load modeling. However, due to the influence of the season variation, the existing …
Probabilistic time-varying parameter identification for load modeling: A deep generative approach
M Khodayar, J Wang - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
The uncertainty of power resources introduces significant challenges for classic load
modeling approaches. Moreover, load parameter identification techniques are affected by …
modeling approaches. Moreover, load parameter identification techniques are affected by …
Robust time-varying synthesis load modeling in distribution networks considering voltage disturbances
Uncertain power sources are increasingly integrated into distribution networks and causes
more challenges for the traditional load modeling. A variety of distributed load components …
more challenges for the traditional load modeling. A variety of distributed load components …
Toward online power system model identification: A deep reinforcement learning approach
The rapidly increasing penetration of power electronic equipment has complicated the
dynamic characteristics of modern power systems, which has promoted the development of …
dynamic characteristics of modern power systems, which has promoted the development of …
Mathematical representation of WECC composite load model
Composite load model of Western Electricity Coordinating Council (WECC) is a newly
developed load model that has drawn great interest from the industry. To analyze its …
developed load model that has drawn great interest from the industry. To analyze its …
Wide-area composite load parameter identification based on multi-residual deep neural network
Accurate and practical load modeling plays a critical role in the power system studies
including stability, control, and protection. Recently, wide-area measurement systems …
including stability, control, and protection. Recently, wide-area measurement systems …
An optimal method based on HOG-SVM for fault detection
P Xu, L Huang, Y Song - Multimedia Tools and Applications, 2022 - Springer
In this paper, an improved method based on HOG-SVM (histogram of oriented gradient
characteristic and support vector machine) is proposed for fault diagnosis. First, by …
characteristic and support vector machine) is proposed for fault diagnosis. First, by …
Real-time parameter tracking of power-electronics interfaced composite ZIP load model
SMH Rizvi, SK Sadanandan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Modeling load and voltage dependency can enhance the accuracy of system analysis (eg,
voltage control and situational awareness). Typically ZIP load model is used to model the …
voltage control and situational awareness). Typically ZIP load model is used to model the …
Data-driven modeling of power system dynamics: Challenges, state of the art, and future work
With the continual deployment of power-electronics-interfaced renewable energy resources,
increasing privacy concerns due to deregulation of electricity markets, and the diversification …
increasing privacy concerns due to deregulation of electricity markets, and the diversification …