Antoine Lesage-Landry

Jérôme Lafontaine

Maîtrise recherche - Polytechnique

Louis Lalonde

Maîtrise recherche - Polytechnique

Hannah Merrigan

Doctorat - Polytechnique

Abraham N’Zi

Doctorat - Polytechnique

Laure-Anne Réau

Maîtrise recherche - Polytechnique

Christina G. Soldati

Doctorat - Polytechnique

Noureddine Toumi Toumi

Postdoctorat - Polytechnique

Chao Yin

Doctorat - Polytechnique

Maeva Zambou Zoleko

Doctorat - Polytechnique

William Zhang

Maîtrise recherche - Polytechnique

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Publications

Practical Solutions to Volt-var Optimization under Uncertainty via Blackbox Optimization

Feng Li

Ilhan Kocar

In this work, we propose an optimal reactive power dispatch (ORPD) stochastic program for volt-var optimization (VVO) of power distribution … (voir plus)networks. The formulation considers not only control settings of conventional VVO devices, e.g., voltage regulators, capacitor banks, and on-load tap changers, but also optimal settings for volt-var droop curves of distributed energy resources (DERs), compliant with the IEEE 1547-2018 standard. Instead of including the power flow equations in the optimization problem which makes it nonlinear and nonconvex, a power flow solver is utilized and the problem is solved by blackbox optimization (BBO). The feasibility of the derived solution is improved by using unbalanced power flow simulations. The solution is effective under various demand and DER generation scenarios such that device settings are not frequently changed, making it practical for in-field implementations. Through numerical simulations on IEEE test feeders, we illustrate the performance of the solutions of our proposed approach on both in-sample and out-of-sample scenarios. We show that our approach outperforms a benchmark reinforcement learning method, and is also scalable to large-scale distribution networks.

2025-12-31

IEEE Transactions on Power Delivery (publié)

Distributed Combined Space Partitioning and Network Flow Optimization: an Optimal Transport Approach

Théo Laurentin

Patrick Coirault

Emmanuel Moulay

Jerome Le Ny

2025-12-08

2025 IEEE 64th Conference on Decision and Control (CDC) (publié)

arxiv.org

Task Mapping Strategies for Electric Power System Simulations on Heterogeneous Clusters

Julie Durette

Gunes Karabulut Kurt

In this work, we propose improved task mapping strategies for real-time electric power system simulations on heterogeneous computing cluster… (voir plus)s, considering both heterogeneous communication links and processing capacities, with a focus on bottleneck objectives. We approach the problem through two complementary models: the bottleneck quadratic semi-assignment problem (BQSAP), which optimizes task configuration for a fixed number of computing nodes while minimizing communication and computation costs; and the variable-size bin packing problem with quadratic communication constraints (Q-VSBPP), which minimizes the required number of computing nodes, valuable for resource provisioning scenarios. We extend the PuLP library to solve approximately both problems, explicitly including communication costs and processing constraints, and formalize the nomenclature and definitions for bottleneck objectives in graph partitioning. This formalization fills a gap in the existing literature and provides a framework for the rigorous analysis and application of task mapping techniques to real-time electric power system simulation. Finally, we provide a quantitative study and benchmark the extended PuLP library with the SCOTCH partitioning library in the context of real-time electromagnetic transient (EMT) simulation task mapping.

2025-09-29

IEEE International Conference on Smart Grid Communications (publié)

On the frequency variation in load-flow calculations for islanded alternating current microgrids

Matthias Molénat

Jean Mahseredjian

Nasim Rashidirad

2025-09-01

Mathematics and Computers in Simulation (publié)

On the frequency variation in load-flow calculations for islanded alternating current microgrids

Matthias Molénat

Jean Mahseredjian

Nasim Rashidirad

2025-09-01

Mathematics and Computers in Simulation (publié)

On the frequency variation in load-flow calculations for islanded alternating current microgrids

Matthias Molénat

Jean Mahseredjian

Nasim Rashidirad

2025-09-01

Mathematics and Computers in Simulation (publié)

Distributed Combined Space Partitioning and Network Flow Optimization: an Optimal Transport Approach (Extended Version)

Th'eo Laurentin

Patrick Coirault

Emmanuel Moulay

J'erome Le Ny

2025-08-29

ArXiv (prépublication)

arxiv.org

Efficient Deep Reinforcement Learning-Based Supplementary Damping Control With a Coordinated RMS Training and EMT Testing Scheme

Tao Xue

Mingxuan Zhao

Ilhan Kocar

Mohsen Ghafouri

Siqi Bu

Ziqing Zhu

Inverter-based resources (IBRs) can cause instability in weak AC grids. While supplementary damping controllers (SDCs) effectively mitigate … (voir plus)this instability, they are typically designed for specific resonance frequencies but struggle with large shifts caused by changing grid conditions. This paper proposes a deep reinforcement learning-based agent (DRL Agent) as an adaptive SDC to handle shifted resonance frequencies. To address the time-consuming nature of training DRL Agents in electromagnetic transient (EMT) simulations, we coordinate fast root mean square (RMS) and EMT simulations. Resonance frequencies of the weak grid instability are accurately reproduced by RMS simulations to support the training process. The DRL Agent’s efficacy is tested in unseen scenarios outside the training dataset. We then iteratively improve the DRL Agent’s performance by modifying the reward function and hyper-parameters.

2025-08-01

IEEE Transactions on Power Delivery (publié)

Efficient Deep Reinforcement Learning-Based Supplementary Damping Control with a Coordinated RMS Training and EMT Testing Scheme

Tao Xue

Mingxuan Zhao

Ilhan Kocar

Mohsen Ghafouri