4 papers
Physics-Informed Graph Neural Jump ODEs for Cascading Failure Prediction in Power Grids
Birva Sevak, Shrenik Jadhav, Van-Hai Bui
Cascading failures in power grids pose severe risks to infrastructure reliability, yet real-time prediction of their progression remains an open challenge. Physics-based simulators…
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…
Enhancing Power Flow Estimation with Topology-Aware Gated Graph Neural Networks
Shrenik Jadhav, Birva Sevak, Srijita Das +2
Accurate and scalable surrogate models for AC power flow are essential for real-time grid monitoring, contingency analysis, and decision support in increasingly dynamic and inverte…
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…