Machine learning driven smart electric power systems: Current trends and new perspectives

MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

A review of machine learning applications in IoT-integrated modern power systems

M Farhoumandi, Q Zhou, M Shahidehpour - The Electricity Journal, 2021 - Elsevier
A review of machine learning applications in IoT-integrated modern power systems -
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Visual inspection of fault type and zone prediction in electrical grids using interpretable spectrogram-based CNN modeling

C Ardito, Y Deldjoo, T Di Noia, E Di Sciascio… - Expert Systems with …, 2022 - Elsevier
In electrical grids, fault diagnosis (fault type and fault location classifications) are critical due
to their economic and important implications. Numerous smart grid applications have …

High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers

V Veerasamy, NI Abdul Wahab… - Neural Computing and …, 2019 - Springer
This paper presents the high-impedance fault (HIF) detection and identification in medium-
voltage distribution network of 13.8 kV using discrete wavelet transform (DWT) and …

Fault Classification in Distribution Systems Using Deep Learning With Data Preprocessing Methods Based on Fast Dynamic Time Warping and Short-Time Fourier …

NC Yang, JM Yang - IEEE Access, 2023 - ieeexplore.ieee.org
Traditional fault classification methods typically rely on manual feature extraction and the
application of machine-learning algorithms. However, these approaches encounter …

An enhanced protective relaying scheme for TCSC compensated line connecting DFIG-Based wind farm

SK Mohanty, PK Nayak, PK Bera… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The electricity generated from the present-day large capacity doubly fed induction generator
(DFIG) installed wind farm is generally transmitted to utility grid via medium or high voltage …

[HTML][HTML] An improved high-impedance fault identification scheme for distribution networks based on kernel extreme learning machine

W Sheng, K Liu, D Jia, Y Wang - International Journal of Electrical Power & …, 2024 - Elsevier
In distribution networks, high-impedance faults (HIFs) occur frequently and have a harmful
impact on the distribution network. However, fault detection and fault phase selection of HIFs …

A convolution power-based protection scheme for hybrid multiterminal HVDC transmission systems

X Chen, H Li, G Wang, C Xu… - IEEE Journal of Emerging …, 2020 - ieeexplore.ieee.org
Compared with conventional HVDC systems, the hybrid multiterminal HVDC (Hybrid-MTDC)
system has a more sophisticated network topology composed of line commutated converter …

A new fault classifier in transmission lines using intrinsic time decomposition

M Pazoki - IEEE Transactions on Industrial Informatics, 2017 - ieeexplore.ieee.org
As nonstationarity exists in fault signals of transmission lines, their classification and
quantification remain a challenging issue. This paper presents a new scheme for feature …

Digital real-time harmonic estimator for power converters in future micro-grids

I Askarian, S Eren, M Pahlevani… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
One of the main challenges in future micro-grids is the presence of transients and
fluctuations inevitably imposed by nonlinear loads. Therefore, real time identification of …