Publications by Jean-Sébastien Hubert Brouillon

Distributionally robust infinite-horizon control: from a pool of samples to the design of dependable controllers

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, Andrea Martin

We study control of constrained linear systems with only partial statistical information about the uncertainty affecting the system dynamics and the sensor measurements. Specifically, given a finite collection of disturbance realizations drawn from a gener ...

Institute of Electrical and Electronics Engineers (IEEE)2025

Power grid parameter estimation without phase measurements: Theory and empirical validation

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon

Reliable integration and operation of renewable distributed energy resources requires accurate distribution grid models. However, obtaining precise models by field inspection is often prohibitively expensive, given their large scale and the ongoing nature ...

Elsevier2024

Estimation and control under uncertainty with application to power systems

Jean-Sébastien Hubert Brouillon

The transition to sustainable energy demands a fundamental redesign of the electrical grid, especially at the distribution level. With the increasing deployment of distributed energy resources, the development of reliable models, accurate state estimation ...

EPFL2024

Minimal regret state estimation of time-varying systems

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon

Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear in practice. State observers based on the minimization of regret measures ar ...

Elsevier2023

Maximum likelihood estimation of distribution grid topology and parameters from Smart Meter data

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon

This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart Meters). First, we pre ...

IEEE2023

Bayesian Error-in-Variables Models for the Identification of Distribution Grids

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, Pulkit Nahata

The increasing integration of renewable energy requires a good model of the existing power distribution infrastructure, represented by its admittance matrix. However, a reliable estimate may either be missing or quickly become obsolete, as distribution gri ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Regularization for distributionally robust state estimation and prediction

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, Florian Dörfler

The increasing availability of sensing techniques provides a great opportunity for engineers to design state estimation methods, which are optimal for the system under observation and the observed noise patterns. However, these patterns often do not fulfil ...

2023

Regularization for distributionally robust state estimation and prediction

Jean-Sébastien Hubert Brouillon

Simulation script for the paper "Regularization for distributionally robust state estimation and prediction". Run tests/test_cdc.py to reproduce results. Extended versions can be found at https://github.com/DecodEPFL/. ...

Zenodo2023

Bayesian Methods for the Identification of Distribution Networks

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, Pulkit Nahata

The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...

IEEE2021