5 papers
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…
Optimal Parameter Design for Power Electronic Converters Using a Probabilistic Learning-Based Stochastic Surrogate Model
Akash Mahajan, Shivam Chaturvedi, Srijita Das +2
The selection of optimal design for power electronic converter parameters involves balancing efficiency and thermal constraints to ensure high performance without compromising safe…
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…