collaborators

6 papers

eess.SY2026

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…

eess.SY2025

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…

cs.LG2025

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…

eess.SY2025

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…

eess.SY2025

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…

eess.SY2025

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…