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20222026
most citedPhysics-Informed Neural Networks in Power System Dynamics: Improving Simulation Accuracy

7 citations · 20 across the 6 of their papers we have counts for

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6 papers

eess.SY2026

Systematic Gray-Box Identification Methodology for Voltage Source Converters

Nicolae Darii, Luis A. Garcia-Reyes, Ignasi Ventura Nadal +4

This paper introduces a systematic gray-box identification framework for voltage-source converter models based solely on terminal time-series data. The proposed approach combines a…

eess.SY2025

Physics-Informed Neural Network Models for EMT Simulators

Ignasi Ventura Nadal, Nicolae Darii, Petros Aristidou +4

This is the first paper, to the best of our knowledge, to propose a framework that integrates Physics-Informed Neural Network (PINN) models in Electromagnetic Transient (EMT) simul…

eess.SY2025★ 1 cited

Toolbox for Developing Physics Informed Neural Networks for Power Systems Components

Ioannis Karampinis, Petros Ellinas, Ignasi Ventura Nadal +2

This paper puts forward the vision of creating a library of neural-network-based models for power system simulations. Traditional numerical solvers struggle with the growing comple…

eess.SY2025★ 7 cited

Physics-Informed Neural Networks in Power System Dynamics: Improving Simulation Accuracy

Ignasi Ventura Nadal, Rahul Nellikkath, Spyros Chatzivasileiadis

The importance and cost of time-domain simulations when studying power systems have exponentially increased in the last decades. With the growing share of renewable energy sources,…

eess.SY2023★ 7 cited

Scalable Bilevel Optimization for Generating Maximally Representative OPF Datasets

Ignasi Ventura Nadal, Samuel Chevalier

New generations of power systems, containing high shares of renewable energy resources, require improved data-driven tools which can swiftly adapt to changes in system operation. M…

eess.SY2022★ 5 cited

Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection

Ignasi Ventura Nadal, Samuel Chevalier

This paper provides a systematic investigation into the various nonlinear objective functions which can be used to explore the feasible space associated with the optimal power flow…