2 citations · 4 across the 9 of their papers we have counts for
9 papers
FedAvgIm: Federated Learning for Multi-Site Impedance Identification of Inverter-Based Resources
Quang Manh Hoang, Guilherme Vieira Hollweg, Akhtar Hussain +2
With the increasing integration of inverter-based resources (IBRs) into power systems, assessing small-signal interaction stability has become essential. Impedance/admittance model…
A Hybrid Two-Stage Machine Learning Pipeline for Fault Detection and Classification in Power Transmission Systems
Sahil Manikshete, Atharva Gujarathi, Thanh Long Vu +2
Rapid and accurate fault detection in high-voltage transmission networks is essential for grid reliability and equipment protection. Transmission fault datasets are frequently imba…
Scalable Impedance Identification of Diverse IBRs via Cluster-Specialized Neural Networks
Quang Manh Hoang, Guilherme Vieira Hollweg, Bang Nguyen +3
Modern machine learning approaches typically identify the impedance of a single inverter-based resource (IBR) and assume similar impedance characteristics across devices. In modern…
Scalable Fairness Shaping with LLM-Guided Multi-Agent Reinforcement Learning for Peer-to-Peer Electricity Markets
Shrenik Jadhav, Birva Sevak, Srijita Das +3
Peer-to-peer (P2P) energy trading is becoming central to modern distribution systems as rooftop PV and home energy management systems become pervasive, yet most existing market and…
FairMarket-RL: LLM-Guided Fairness Shaping for Multi-Agent Reinforcement Learning in Peer-to-Peer Markets
Shrenik Jadhav, Birva Sevak, Srijita Das +3
Peer-to-peer (P2P) trading is increasingly recognized as a key mechanism for decentralized market regulation, yet existing approaches often lack robust frameworks to ensure fairnes…
Enhancing Forecasting Accuracy in Dynamic Environments via PELT-Driven Drift Detection and Model Adaptation
Nikhil Pawar, Guilherme Vieira Hollweg, Akhtar Hussain +2
Accurate time series forecasting models are often compromised by data drift, where underlying data distributions change over time, leading to significant declines in prediction per…
Deep Reinforcement Learning-Based Optimization of Second-Life Battery Utilization in Electric Vehicles Charging Stations
Rouzbeh Haghighi, Ali Hassan, Van-Hai Bui +2
The rapid rise in electric vehicle (EV) adoption presents significant challenges in managing the vast number of retired EV batteries. Research indicates that second-life batteries…
PSO-based Sliding Mode Current Control of Grid-Forming Inverter in Rotating Frame
Quang-Manh Hoang, Guilherme Vieira Hollweg, Akhtar Hussain +3
The Grid-Forming Inverter (GFMI) is an emerging topic that is attracting significant attention from both academic and industrial communities, particularly in the area of control de…
A Critical Review of Safe Reinforcement Learning Techniques in Smart Grid Applications
Van-Hai Bui, Srijita Das, Akhtar Hussain +2
The high penetration of distributed energy resources (DERs) in modern smart power systems introduces unforeseen uncertainties for the electricity sector, leading to increased compl…