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20172026
most citedMultivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs

6 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Battery health prognosis using Physics-informed neural network with Quantum Feature mapping

Muhammad Imran Hossain, Md Fazley Rafy, Sarika Khushalani Solanki +1

Accurate battery health prognosis using State of Health (SOH) estimation is essential for the reliability of multi-scale battery energy storage, yet existing methods are limited in…

cs.LG2025

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN

Muhammad Imran Hossain, Jignesh Solanki, Sarika Khushlani Solanki

Ensuring power grid resilience requires the timely and unsupervised detection of anomalies in synchrophasor data streams. We introduce T-BiGAN, a novel framework that integrates wi…

eess.SY2024★ 6 cited

Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs

Mehdi Jabbari Zideh, Sarika Khushalani Solanki

Despite the relentless progress of deep learning models in analyzing the system conditions under cyber-physical events, their abilities are limited in the power system domain due t…

cs.CR2024★ 1 cited

An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids

Mehdi Jabbari Zideh, Mohammad Reza Khalghani, Sarika Khushalani Solanki

Detection of cyber attacks in smart power distribution grids with unbalanced configurations poses challenges due to the inherent nonlinear nature of these uncertain and stochastic…

eess.SY2024

Power Flow Analysis Using Deep Neural Networks in Three-Phase Unbalanced Smart Distribution Grids

Deepak Tiwari, Mehdi Jabbari Zideh, Veeru Talreja +3

Most power systems' approaches are currently tending towards stochastic and probabilistic methods due to the high variability of renewable sources and the stochastic nature of load…

eess.SY2023★ 4 cited

Physics-Informed Convolutional Autoencoder for Cyber Anomaly Detection in Power Distribution Grids

Mehdi Jabbari Zideh, Sarika Khushalani Solanki

The growing trend toward the modernization of power distribution systems has facilitated the installation of advanced measurement units and promotion of the cyber communication sys…

eess.SY2017

Online Coherence Identification Using Dynamic Time Warping for Controlled Islanding

Hasan Ul Banna, Zhe Yu, Di Shi +5

Controlled islanding is considered to be the last countermeasure to prevent system-wide blackouts in case of cascading failures. It splits the system into self-sustained islands to…