Samuel Chevalier

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Data Collection

Machine Learning

Constrained Optimization

Top Venues

Publications

Samuel Chevalier, Ilgiz Murzakhanov, Spyros Chatzivasileiadis
GPU-Accelerated Verification of Machine Learning Models for Power Systems. HICSS (2024)
Omid Mokhtari, Samuel Chevalier, Mads Almassalkhi
Enhancing Scalability of Optimal Kron-based Reduction of Networks (Opti-KRON) via Decomposition with Community Detection. CoRR (2024)
Petros Ellinas, Samuel Chevalier, Spyros Chatzivasileiadis
A hybrid Quantum-Classical Algorithm for Mixed-Integer Optimization in Power Systems. CoRR (2024)
Seide Saba Rafiei, Samuel Chevalier
GPU-Accelerated DCOPF using Gradient-Based Optimization. CoRR (2024)
Matias Kühnau, Akylas C. Stratigakos, Simon Camal, Samuel Chevalier, Georges Kariniotakis
Resilient Feature-driven Trading of Renewable Energy with Missing Data. ISGT EUROPE (2023)
Samuel Chevalier, Ilgiz Murzakhanov, Spyros Chatzivasileiadis
GPU-Accelerated Verification of Machine Learning Models for Power Systems. CoRR (2023)
Ignasi Ventura Nadal, Samuel Chevalier
Scalable Bilevel Optimization for Generating Maximally Representative OPF Datasets. ISGT EUROPE (2023)
Dakota Hamilton, Samuel Chevalier, Amritanshu Pandey, Mads Almassalkhi
Towards Energysheds: A Technical Definition and Cooperative Planning Framework. CoRR (2023)
Vladimir Dvorkin, Samuel Chevalier, Spyros Chatzivasileiadis
Emission-Constrained Optimization of Gas Networks: Input-Convex Neural Network Approach. CDC (2023)
Samuel Chevalier
A Parallelized, Adam-Based Solver for Reserve and Security Constrained AC Unit Commitment. CoRR (2023)
Ignasi Ventura Nadal, Samuel Chevalier
Scalable Bilevel Optimization for Generating Maximally Representative OPF Datasets. CoRR (2023)
Samuel Chevalier, Robert Parker
Towards Perturbation-Induced Static Pivoting on GPU-Based Linear Solvers. CoRR (2023)
Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis
Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers. L4DC (2022)
Samuel Chevalier, Spyros Chatzivasileiadis
Global Performance Guarantees for Neural Network Models of AC Power Flow. CoRR (2022)
Jochen Stiasny, Samuel Chevalier, Rahul Nellikkath, Brynjar Sævarsson, Spyros Chatzivasileiadis
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems. CoRR (2022)
Robert I. Hamilton, Jochen Stiasny, Tabia Ahmad, Samuel Chevalier, Rahul Nellikkath, Ilgiz Murzakhanov, Spyros Chatzivasileiadis, Panagiotis N. Papadopoulos
Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations. CoRR (2022)
Vladimir Dvorkin, Samuel Chevalier, Spyros Chatzivasileiadis
Emission-Aware Optimization of Gas Networks: Input-Convex Neural Network Approach. CoRR (2022)
Ignasi Ventura Nadal, Samuel Chevalier
Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection. SmartGridComm (2022)
Samuel Chevalier, Mads R. Almassalkhi
Towards Optimal Kron-based Reduction Of Networks (Opti-KRON) for the Electric Power Grid. CoRR (2022)
Ignasi Ventura Nadal, Samuel Chevalier
Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection. CoRR (2022)
Samuel Chevalier, Mads R. Almassalkhi
Towards Optimal Kron-based Reduction Of Networks (Opti-KRON) for the Electric Power Grid. CDC (2022)
Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis
Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. CoRR (2021)
Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis
Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. SmartGridComm (2021)
Nils Müller, Samuel Chevalier, Carsten Heinrich, Kai Heussen, Charalampos Ziras
Uncertainty Quantification in LV State Estimation Under High Shares of Flexible Resources. CoRR (2021)
Alyssa Kody, Samuel Chevalier, Spyros Chatzivasileiadis, Daniel K. Molzahn
Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment. CoRR (2021)
Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis
Contracting Neural-Newton Solver. CoRR (2021)
Samuel Chevalier, Dan Wu
Dynamic Linepack Depletion Models for Natural Gas Pipeline Networks. CoRR (2020)
Tommaso Bradde, Samuel Chevalier, Marco De Stefano, Stefano Grivet-Talocia, Luca Daniel
Handling Initial Conditions in Vector Fitting for Real Time Modeling of Power System Dynamics. CoRR (2020)
Samuel Chevalier, Luca Schenato, Luca Daniel
Accelerated Probabilistic Power Flow via Model Order Reduction and Neumann Series Expansion. CoRR (2020)
Samuel Chevalier, Luca Schenato, Luca Daniel
Accelerated Probabilistic State Estimation in Distribution Grids via Model Order Reduction. CoRR (2020)
Samuel Chevalier, Kathleen Cavanagh, Konstantin S. Turitsyn, Luca Daniel, Petr Vorobev
Stability Certification Standards for DC Microgrid Networks with Arbitrary Load Configurations. CoRR (2020)
Petr Vorobev, Samuel Chevalier, Konstantin S. Turitsyn
Decentralized stability rules for microgrids. ACC (2019)
Samuel Chevalier, Petr Vorobev, Konstantin S. Turitsyn
A Passivity Enforcement Technique for Forced Oscillation Source Location. CoRR (2019)
Samuel Chevalier, Petr Vorobev, Konstantin S. Turitsyn, Bin Wang, Slava Maslennikov
Using Passivity Theory to Interpret the Dissipating Energy Flow Method. CoRR (2018)
Samuel Chevalier, Paul D. H. Hines
Mitigating the Risk of Voltage Collapse using Statistical Measures from PMU Data. CoRR (2018)
Samuel Chevalier, Petr Vorobev, Konstantin S. Turitsyn
A Bayesian Approach to Forced Oscillation Source Location Given Uncertain Generator Parameters. CoRR (2018)
Samuel Chevalier, Petr Vorobev, Konstantin S. Turitsyn
Using Effective Generator Impedance for Forced Oscillation Source Location. CoRR (2017)