Search Results for author: Laurent Pagnier

Found 7 papers, 0 papers with code

System-Wide Emergency Policy for Transitioning from Main to Secondary Fuel

no code implementations15 Nov 2023 Laurent Pagnier, Igal Goldshtein, Criston Hyett, Robert Ferrando, Jean Alisse, Lilah Saban, Michael Chertkov

Inspired by the challenges of running the Israel's power system -- with its increasing integration of renewables, significant load uncertainty, and primary reliance on natural gas -- we investigate an emergency scenario where there's a need to transition temporarily to a pricier secondary fuel until the emergency resolves.

Machine Learning for Electricity Market Clearing

no code implementations23 May 2022 Laurent Pagnier, Robert Ferrando, Yury Dvorkin, Michael Chertkov

This paper seeks to design a machine learning twin of the optimal power flow (OPF) optimization, which is used in market-clearing procedures by wholesale electricity markets.

BIG-bench Machine Learning

Towards Model Reduction for Power System Transients with Physics-Informed PDE

no code implementations26 Oct 2021 Laurent Pagnier, Michael Chertkov, Julian Fritzsch, Philippe Jacquod

This manuscript reports the first step towards building a robust and efficient model reduction methodology to capture transient dynamics in a transmission level electric power system.

Physics-informed machine learning

Embedding Power Flow into Machine Learning for Parameter and State Estimation

no code implementations26 Mar 2021 Laurent Pagnier, Michael Chertkov

Modern state and parameter estimations in power systems consist of two stages: the outer problem of minimizing the mismatch between network observation and prediction over the network parameters, and the inner problem of predicting the system state for given values of the parameters.

BIG-bench Machine Learning

Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems

no code implementations12 Feb 2021 Laurent Pagnier, Michael Chertkov

Parameter Estimation (PE) and State Estimation (SE) are the most wide-spread tasks in the system engineering.

Locating line and node disturbances in networks of diffusively coupled dynamical agents

no code implementations17 Mar 2020 Robin Delabays, Laurent Pagnier, Melvyn Tyloo

A wide variety of natural and human-made systems consist of a large set of dynamical units coupled into a complex structure.

Time Series Time Series Analysis

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