Pedro P. Vergara
Scholar

Pedro P. Vergara

Google Scholar ID: r-a55GMAAAAJ
Associate Professor - Delft University of Technology
Distribution NetworksOptimal Power FlowMathematical ProgrammingMachine LearningReinforcement
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Citations & Impact
All-time
Citations
1,320
 
H-index
22
 
i10-index
38
 
Publications
20
 
Co-authors
13
list available
Contact
No contact links provided.
Publications
10 items
Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
2026
Cited
0
SmartMeterFM: Unifying Smart Meter Data Generative Tasks Using Flow Matching Models
2026
Cited
0
Quantum-Enhanced Reinforcement Learning for Accelerating Newton-Raphson Convergence with Ising Machines: A Case Study for Power Flow Analysis
2025
Cited
0
Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids
2025
Cited
0
Solving Power System Problems using Adiabatic Quantum Computing
2025
Cited
0
Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks
2025
Cited
0
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
2025
Cited
0
Adaptive Informed Deep Neural Networks for Power Flow Analysis
arXiv.org · 2024
Cited
0
Resume (English only)
Co-authors
13 total
Peter Palensky
Peter Palensky
TU Delft
Co-author 2
Co-author 2
Co-author 3
Co-author 3
Phuong H. Nguyen
Phuong H. Nguyen
Eindhoven University of Technology
Co-author 5
Co-author 5
Bo Nørregaard Jørgensen
Bo Nørregaard Jørgensen
Professor, PhD., Head of Center for Energy Informatics, University of Southern Denmark
Matthias Möller
Matthias Möller
Associate Professor of Numerical Analysis, Delft University of Technology
Co-author 8
Co-author 8