activity
20242026
most citedOptimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks

1 citations · 1 across the 6 of their papers we have counts for

collaborators

10 papers

cs.LG2026

SmartMeterFM: Unifying Smart Meter Data Generative Tasks Using Flow Matching Models

Nan Lin, Yanbo Wang, Jacco Heres +2

Smart meter data is the foundation for planning and operating the distribution network. Unfortunately, such data are not always available due to privacy regulations. Meanwhile, the…

eess.SY2025

Distributed Reinforcement Learning using Local Smart Meter Data for Voltage Regulation in Distribution Networks

Dong Liu, Juan S. Giraldo, Peter Palensky +1

Centralised reinforcement learning (RL) for voltage magnitude regulation in distribution networks typically involves numerous agent-environment interactions and power flow (PF) cal…

eess.SY2025

Quantum-Enhanced Reinforcement Learning for Accelerating Newton-Raphson Convergence with Ising Machines: A Case Study for Power Flow Analysis

Zeynab Kaseb, Matthias Moller, Lindsay Spoor +4

The Newton-Raphson (NR) method is widely used for solving power flow (PF) equations due to its quadratic convergence. However, its performance deteriorates under poor initializatio…

eess.SY2025

Optimal Droop Control Strategy for Coordinated Voltage Regulation and Power Sharing in Hybrid AC-MTDC Systems

Hongjin Du, Tuanku Badzlin Hashfi, Rashmi Prasad +3

With the growing integration of modular multilevel converters (MMCs) in Multi-Terminal Direct Current (MTDC) transmission systems, there is an increasing need for control strategie…

eess.SY2025

Model-Free Privacy Preserving Power Flow Analysis in Distribution Networks

Dong Liu, Juan S. Giraldo, Peter Palensky +1

Model-free power flow calculation, driven by the rise of smart meter (SM) data and the lack of network topology, often relies on artificial intelligence neural networks (ANNs). How…

eess.SY20251 cited

Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks

Stavros Orfanoudakis, Peter Palensky, Pedro P. Vergara

Maintaining grid stability amid widespread electric vehicle (EV) adoption is vital for sustainable transportation. Traditional optimization methods and Reinforcement Learning (RL)…