2022 • In

Reinforcement learning aims to learn optimal policies from interaction with environments whose dy...

2022

Training recurrent neural networks is known to be difficult when time dependencies become long. C...

2022 • In

The recent major increase in decentralized energy resources (DERs) such as photovoltaic (PV) pane...

2022 • In

The recent major increase in decentralized energy resources (DERs) such as photovoltaic (PV) pane...

2022 • In

In power systems, large-scale optimisation problems are extensively used to plan for capacity exp...

2022 • In Jurasz, Jakub; Beluco, Alexandre (Eds.)

2022

The control of Renewable Energy Communities (REC) with controllable assets (e.g batteries) can be...

2022 • In

We consider the joint design and control of discrete-time stochastic dynamical systems over a fin...

2022

Local electricity markets represent a way of supplementing traditional retailing contracts for en...

2022

Wind is an infinitely renewable energy source that is not evenly distributed in space and time. T...

2021 • In

For transient stability analysis of a multi-machine power system, the Extended Equal Area Criteri...

2021 • In

This work addresses the problem of reconstructing topology and cable parameters of thr...

2021 • In

Active network management (ANM) of electricity distribution networks include many complex stochas...

2021 • In

The increase of photovoltaic panels and electric vehicles in low-voltage distribution systems lea...

2021 • In

This paper studies the problem of siting renewable power generation assets using large amounts of...

2021 • In

The large integration of variable energy resources is expected to shift a large part of the energ...

2021 • In

Distribution system operators have been upgrading their network over several decades, though not ...

2021 • In

This paper studies the economics of carbon-neutral synthetic fuel production from renewable elect...

2021 • In

Gym-ANM is a Python package that facilitates the design of reinforcement learning (RL) environmen...

2021 • In

The accurate representation of variable renewable generation (RES, e.g., wind, solar PV) assets i...

2021 • In

The success of local renewable energy communities, now foreseen by new the European Union directi...

2021

Getting the distance to objects is crucial for autonomous vehicles. In instances where depth sens...

2021 • In

A fundamental task for artificial intelligence is learning. Deep Neural Networks have proven to c...

2021 • In

This paper presents a simulation-based methodology for assessing the impact of employing differen...

2021 • In

This paper introduces four new algorithms that can be used for tackling multi-agent reinforcement...

2021

This paper introduces the graph-based optimization modeling language (GBOML), which enables the e...

2021 • In

In Wallonia, Belgium's southern region, the distribution component of the overall electricity ret...

2021 • In

This paper provides a detailed account of the impact of different offshore wind siting strategies...

2021

The distributional reinforcement learning (RL) approach advocates for representing the complete p...

2020 • In

Retailers and major consumers of electricity generally purchase an important percentage of their ...

2020 • In

As of March 13, 2020, the director general of the World Health Organization (WHO) considered Euro...

2020

A presentation that describes recent algorithmic developments for operating a renewable energy co...

2020 • In

Hastened by the emergence of new technologies, a revolution of the electricity retailing business...

2020 • In

Electrical distribution systems need to integrate more and more renewable energy generation in th...

2020 • In

This paper proposes an optimisation-based framework to tackle long-term centralised planning prob...

2020 • In

This paper proposes a framework to assess the complementarity between geographically dispersed va...

2020 • In Mauroy, Alexandre; Mezic, Igor; Susuki, Yoshihiko (Eds.)

Koopman operator theory offers numerous techniques for analysis and control of complex systems. I...

2020 • In

In this paper, we propose an extension to the policy gradient algorithms by allowing starting sta...

2019 • In

Animals excel at adapting their intentions, attention, and actions to the environment, making the...

2019 • In

The business of electricity retailing is changing following the current evolution of the electric...

2019 • In

Current global environmental challenges require vigorous and diverse actions in the energy sector...

2019 • In

This paper provides an analysis of the tradeoff between asymptotic bias (suboptimality with unlim...

2019 • In

The blockchain technology allows interested parties to access a common register, the update, and ...

2019 • In

In the context of increasing decentralised electricity generation, this paper evaluates the effec...

2019 • In

This paper focuses on market design options for operational balancing management in self-dispatch...

2018 • In

This paper proposes an optimisation-based framework to tackle long-term centralised planning prob...

2018

This paper focuses on market design options for operational balancing management in self-dispatch...

2018 • In

As more and more photovoltaic units are being installed, some LV networks have already attained t...

2018 • In

Energy communities and peer-to-peer energy exchanges are expected to play an important role in th...

2018 • In

Energy communities and peer-to-peer energy exchanges are expected to play an important role in th...

2018 • In

We address the problem faced by the operator of a microgrid participating in a continuous real-ti...

2018 • In

The problem faced by the operator of a storage device participating in a continuous intra-day (CI...

2018 • In

This work fits in the context of community migrogrids, where entities of a community can exchange...

2018 • In

This paper introduces a multi-agent dynamical system of the interaction between electricity consu...

2018 • In

Local energy communities (LECs) usually occur at the level of low-voltage distribution networks, ...

2018 • In

When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the ...

2018 • In

Energy communities and peer-to-peer energy exchanges are expected to play an important role in th...

2018 • In

This study proposes a hybrid energy storage system (HESS) composed of the superconducting energy ...

2018 • In

This paper presents a multi-agent simulator that describes the interactions between the agents of...

2018 • In

In applications, such as biomedicine and systems/synthetic biology, technical limitations in actu...

2018 • In

Many possibilities exist to organise exchanges of flexibility within a distribution system. In th...

2017

The aim of this document is to present SiSTEM, a multi-level simulation model of European short-t...

2017

2017 • In

This paper is dedicated to electricity prosumer communities, which are groups of people producing...

2017 • In

In this paper, we review past (including very recent) research considerations in using reinforcem...

2017 • In Cottier, Thomas; Ilaria, Espa (Eds.)

2017 • In

This paper highlights the importance of the knowledge of the phase identification for the differe...

2017 • In Soriano, Jordi; Battaglia, Demian; Guyon, Isabelle

In this work, we propose a simple yet effective solution to the problem of connectome inference i...

2017 • In

The main goal of the E-Cloud, as with every microgrid, is to maximize the consumption of energy p...

2017 • In

In an electrical system where decentralized and embedded productions are becoming more and more i...

2017 • In

Bayesian Reinforcement Learning (BRL) agents aim to maximise the expected collected rewards obtai...

2017 • In

The emergence of electric vehicles (EVs), combined with the rise of renewable energy production c...

2017 • In

This paper addresses the problem of an aggregator controlling residential heat pumps to offer a d...

2017 • In Jones, Lawrence (Ed.)

The Global Grid advocates the connection of all regional power systems into one electricity trans...

2017 • In

This work presents a biased random-key genetic algorithm (BRKGA) to solve the electric distributi...

2017 • In Furze, James N.; Swing, Kelly; Gupta, Anil K.

This chapter falls within the context of modeling the deployment of renewable en-ergy production ...

2017 • In

The major challenges in power systems are driven by the energy shortage and environmental concern...

2017 • In

There is a need to clearly state an interaction model that formalizes interactions between actors...

2016 • Colloque 2016 de la CODT : Territoire(s) wallon(s) : tendances et perspectives

Ce support PPT est basé sur les travaux menés sur le volet Analyses sectorielles de l'Etat du ter...

2016 • In

This paper addresses the problem of efficiently operating the storage devices in an electricity m...

2016 • In

With the increasing share of renewable and distributed generation in electrical distribution syst...

2016 • In

Probabilistic methods are emerging for operating electrical networks, driven by the integration o...

2016 • In

This paper addresses the problem of an aggregator controlling residential heat pumps to offer a d...

2016 • In

This paper extends the Global Capacity ANnouncement
procedure proposed in [5] along two direction...

2016 • In

In this paper, the penetration of grid-connected pho- tovoltaic systems is studied, experimentall...

2016 • In

This chapter falls within the context of the optimization of the levelized energy cost (LEC) of m...

2016 • In

In this paper, the overvoltage problems that might arise from the integration of photovoltaic pan...

2016 • In

Video games have become more and more complex over the past decades. Today, players wander in vis...

2016 • First Seminar on Demand Response

This paper addresses the problem of an aggregator controlling residential heat pumps to offe...

2016 • In

This article proposes an open-source testbed to simulate interaction models governing the exchang...

2015 • In Woon, Wei Lee; Zeyar, Aung; Stuart, Madnick (Eds.)

This paper aims to design an algorithm dedicated to operational planning for microgrids in the ch...

2015 • In

Using deep neural nets as function approximator for reinforcement learning tasks have recently be...

2015 • In

We propose a pragmatic procedure to facilitate the connection process of Distributed Generation (...

2015 • In

A new indirect quadrangular mesh generation algorithm which relies on sequential decision-making ...

2015 • In

This paper addresses the problem of defining a day-ahead consumption plan for charging a fleet of...

2015 • In

This article deals with the problem of automatically es- tablishing a correspondence between two ...

2015 • In

This paper presents a general process set in the GREDOR (French acronym for “Gestion des Réseaux ...

2015 • In

To ease the transition towards the future of distribution grid management, regulators must revise...

2015 • In

With modern video games frequently featuring sophisticated and realistic environments, the need f...

2015 • 12th International Conference on the European Energy Market - EEM 2015

2015 • In

In this work, an electricity zone with 100% renewables is simulated to determine the optimal sizi...

2015 • In

We consider a price signal with two settings: off-peak tariff and on-peak tariff.
Some loads are ...

2014 • In

This paper proposes a methodology to estimate the maximum revenue that can be generated by a comp...

2014 • In

This review shows the potential ground-breaking impact that mathematical tools may have in the an...

2014 • In

Immunological failure is identified from the estimation of certain parameters of a mathematical m...

2014 • In Jones, Lawrence (Ed.)

The Global Grid advocates the connection of all regional power systems into one electricity trans...

2014 • In

We consider a class of optimal power flow (OPF) applications where some loads offer a modulation ...

2014 • In

We propose and analyze a day-ahead reserve market model that handles bids from flexible loads.
T...

2014 • In

In this paper, a distributed model-free control scheme to mitigate overvoltage problems caused by...

2014 • In

This paper addresses the problem of decision making in unknown finite Markov decision processes (...

2014 • In Soriano, Jordi; Battaglia, Demian; Guyon, Isabelle

In this work, we propose a simple yet effective solution to the problem of connectome inference i...

2014 • In

Cet article aborde le problème de prise de décision séquentielle dans des processus de déci- sion...

2014 • In

This paper proposes a methodology to estimate the maximum revenue that can be generated by a comp...

2014 • In

Afin d’opérer un réseau de distribution d’électricité de manière fiable et efficace, c’est-à-dire...

2014 • In

In this paper, we consider the problem of optimal exogenous control of gene regulatory networks. ...

2014 • In

Direct policy search (DPS) and look-ahead tree (LT) policies are two popular techniques for solvi...

2014 • In

A large number of problems can be formalized as finding the best symbolic expression to maximize ...

2014 • In

We study the minmax optimization problem introduced in [Fonteneau et al. (2011), ``Towards min ma...

2014 • In

Cet article se situe dans le cadre de l’apprentissage par renforcement en mode batch, dont le pro...

2014 • In Savulescu, Savu (Ed.)

A general approach to real-time transient stability control is described, yielding various comple...

2013 • In

In this paper, we consider the periodic reference tracking problem in the framework of batch-mode...

2013 • In

This article studies a decision making problem faced by an aggregator willing to offer a load mod...

2013 • In

Much current research in AI and games is being devoted to Monte Carlo search (MCS) algorithms. Wh...

2013 • In

We consider an original problem that arises from the issue of security analysis of a power system...

2013 • In

In the context of multistage stochastic optimization problems, we propose a hybrid strategy for g...

2013 • In

Cet article aborde le problème de généralisation minmax dans le cadre de l'apprentissage par renf...

2013 • In

We study the min max optimization problem introduced in Fonteneau et al. [Towards min max reinfor...

2013 • In

Cet article présente deux stratégies d’échantillonnage dans le contexte de l’apprentissage par re...

2013 • In

This paper addresses the problem faced by a distribution system operator (DSO) when planning the ...

2013 • In

This paper studies look-ahead tree based control policies from the viewpoint of online decision m...

2013 • In Filipe, Joaquim; Fred, Ana (Eds.)

The exploration/exploitation (E/E) dilemma arises naturally in many subﬁelds of Science. Multi-ar...

2012 • Neural Information Processing Systems (NIPS)

We consider Markov reward processes and study OLS-LSTD, a framework for selecting basis functions...

2012 • In

Motivated by issues of security analysis for power systems, we analyze a new problem, called opti...

2012 • DYSCO Study Day : Dynamical systems, control and optimization Kickoff of phase VII

We study a decision making problem faced by an aggregator willing to offer a load modulation serv...

2012 • In

In this paper, we address the problem of computing interpretable solutions to reinforcement learn...

2012

In this paper we argue that contextual multi-armed bandit algorithms could open avenues for desig...

2012 • International Conference on Brain Dynamics and Decision Making

Living organisms are able to successfully perform challenging tasks such as perception, classific...

2012 • In

On s’intéresse au problème de généralisation min max dans le cadre de l’apprentissage par renforc...

2012 • 31st Benelux Meeting on Systems and Control

Living organisms are able to successfully perform challeng- ing tasks such as perception, classif...

2012 • In

The authors consider a power system composed of several non-synchronous AC areas connected by a m...

2012 • In

We propose a learning approach to pre-compute K-armed bandit playing policies by exploiting prior...

2012 • In

We consider the problem of learning high-performance Exploration/Exploitation (E/E) strategies fo...

2012 • In

Over the past decades, video games have become increasingly popular and complex. Virtual worlds h...

2012 • In Hussein, Abbas (Ed.)

In this paper we argue that contextual multi-armed bandit algorithms
could open avenues for desig...

2012 • In

This paper presents the first formal framework for identifying and filtering SPIT calls (SPam in ...

2012 • In

Monte-Carlo Tree Search (MCTS) techniques are essentially known for their performance on turn-bas...

2011 • In

We study the min max optimization problem introduced in [Fonteneau, 2011] for computing policies ...

2011 • In

For now over a decade, real-time strategy (RTS) games have been challenging intelligence, human a...

2011 • In

This paper addresses the problem of ancillary services in ac systems interconnected by a multi-te...

2011 • In

This paper addresses the problem of HVDC control using real-time information to avoid loss of syn...

2011 • In

2011 • In

Reinforcement learning (RL) allows agents to learn how to optimally interact with complex environ...

2011 • In

We propose a strategy for experiment selection - in the context of reinforcement learning - based...

2011 • In

This paper introduces an algorithm for direct search of control policies in continuous-state, dis...

2011 • In Sucar, L. Enrique; Morales, Eduardo F.; Hoey, Jesse (Eds.)

In this chapter, we present the multistage stochastic programming framework for sequential decisi...

2011 • In Filipe, Joaquim; Fred, Ana; Sharp, Bernadette (Eds.)

In this paper, we introduce a min max approach for addressing the generalization problem in Reinf...

2011 • In

This paper addresses the problem of frequency control for non-synchronous AC areas connected by a...

2011 • In

We propose an approach for discovering in an automatic way formulas for ranking arms while playin...

2011 • In

We consider in this paper look-ahead tree techniques for the discrete-time control of a determini...

2011 • In

We introduce the Optimal Sample Selection (OSS) meta-algorithm for solving discrete-time Optimal ...

2010 • In

This paper addresses the problem of sharing primary frequency control reserves among nonsynchrono...

2010 • In

This paper presents an approach for assessing, in operation planning studies, the security of a l...

2010 • In

This paper addresses the problem of coordinating voltage control in a large-scale power system pa...

2010 • In

Reinforcement learning (RL) is a promising paradigm for learning optimal control. Although RL is ...

2010 • In

We propose new methods for guiding the generation of informative trajectories when solving discre...

2010 • In

We propose an algorithm for estimating the finite-horizon expected return of a closed loop contro...

2010 • In

We propose an algorithm for estimating the finite-horizon expected return of a closed loop contro...

2010 • In

In this paper, we consider the problem of exploiting spectrum resources for a secondary user (SU)...

2010 • In

Reinforcement learning (RL) is a promising paradigm for learning optimal control. Traditional RL ...

2010 • In

Reinforcement learning is a promising paradigm for learning optimal control. We consider policy i...

2010 • In

In the context of a deterministic Lipschitz continuous environment over continuous state spaces, ...

2009 • In

We suggest in this paper that many problems related to Cognitive Radio’s (CR) decision making ins...

2009 • In

This paper studies the influence of apoptosis in the dynamics of the HIV infection. A new modelin...

2009 • In

We consider the problem of performing N − k security analyses in large scale power systems. In su...

2009 • In

Graphical representations of power systems are systematically used for planning and operation. Th...

2009 • In

This paper introduces a novel algorithm for approximate policy search in continuous-state, discre...

2009 • In

Cet article propose une revue de littérature concernant les applications de l’apprentissage par r...

2009 • In Watanabe, Osamu; Zeugmann, Thomas (Eds.)

We propose a generic method for obtaining quickly good upper bounds on the minimal value of a mul...

2009 • In

Optimizing decisions on an ensemble of incomplete disturbance trees and aggregating their first s...

2009 • In

This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified ...

2009 • In

Despite very intensive research efforts in the field of transient stability during the last five ...

2009 • In

We propose an approach for inferring bounds on the finite-horizon return of a control policy from...

2009 • In

This paper presents three HVDC modulation strategies to improve transient stability in an interco...

2009 • In

This paper addresses the problem of centralized optimization of an interconnected power system pa...

2009 • In

This paper addresses the problem of reactive power dispatch in a power system partitioned into se...

2009 • In

The paper addresses the problem of decentralized optimization for a power system partitioned into...

2008 • In

This paper presents research and education activities of the power systems group of the Departmen...

2008 • In

2008 • In

On the basis of the human immunodeficiency virus (HIV) infection dynamics model proposed by Adams...

2008 • In

We consider power systems for which the amount of power produced by their individual power plants...

2008 • In

We propose in this paper a novel approach for identifying rare events that may endanger power sys...

2008 • In

Reinforcement learning (RL) is a widely used paradigm for learning control. Computing exact RL so...

2008 • In

Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. Because exact...

2008 • In Tuyls, K.; Nowé, A.; Guessoum, Z.

Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist s...

2008 • In Defourny, Boris

This paper addresses the problem of solving discrete-time optimal sequential decision making prob...

2008 • NIPS-08 Workshop on Model Uncertainty and Risk in Reinforcement Learning

This paper considers sequential decision making problems under uncertainty, the tradeoff between ...

2008 • European Workshop on Reinforcement Learning 2008 (EWRL'08)

Dynamic treatment regimes (DTRs) can be inferred from data collected through some randomized clin...

2008 • In

This paper addresses the problem of transmission loss allocation in a power system where the gene...

2008 • In

In this paper, we consider an interconnected power system, where the different Transmission Syste...

2007 • In

This paper focuses on contingency filtering to accelerate the iterative solution of preventive se...

2007 • In

This paper investigates a possibility for estimating rotor angles in the time frame of transient ...

2007 • In

Interior-point method (IPM) is a very appealing approach to the optimal power flow (OPF) problem ...

2007 • In

We introduce in this paper a new approach for efficiently identifying Nash equilibria for games c...

2007 • In

Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. Well-understo...

2007 • In

Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorith...

2007 • In

Model predictive control (MPC) and reinforcement learning (RL) are two popular families of method...

2007 • In

We present an application of a cross-entropy based combinatorial optimization method for solving ...

2007 • In

A general response-based technique is presented for closed-loop transient stability emergency con...

2007 • In

In this paper we propose a collaborative framework to carry out multi-area dynamic security asses...

2006 • In

In this paper we compare Nash equilibria analysis and agent-based modelling for assessing the mar...

2006 • In

The transmission network plays a key role in an oligopolistic electricity market. In fact, the ca...

2006 • In

This paper proposes to formulate security control as a sequential decision making problem and pre...

2006 • In

Model predictive control (MPC) and reinforcement learning (RL) are two popular families of method...

2006 • In

We report in this paper some positive simulation results obtained when image pixels are directly ...

2006 • In

This paper addresses the problem of computing optimal structured treatment interruption strategie...

2006 • In

This paper addresses the problem of computing optimal structured treatment interruption strategie...

2006 • In

The main idea behind the concept, proposed in the paper, is the opportunity to make control syste...

2006 • In

In this paper we present a new tree-based ensemble method called “Extra-Trees”. This algorithm av...

2006 • In

We present our recent results on using previously introduced framework for multi-area security as...

2006 • In

The paper introduces a framework for information exchange and coordination of security assessment...

2006 • In

The paper considers the possible uses of automatic learning for improving power system performanc...

2006 • In

This paper proposes to formulate security control as a sequential decision making problem and pre...

2005 • In

This paper proposes an application of a Reinforcement Learning (RL) method to the control of a dy...

2005 • In

This paper suggests that the appropriate combination of a stability-oriented and a performance-or...

2005 • In

The paper presents a technical overview of a large research project on Dynamic Security Assessmen...

2005 • In

We derive an algorithm for selecting from the set of samples gathered by a reinforcement learning...

2005 • In

In this paper we explain how to design intelligent agents able to process the information acquire...

2005 • In

In this paper we compare Nash equilibria analysis and agent-based modelling for assessing the mar...

2005 • In

In this paper we present the basic principles of supervised learning and reinforcement learning a...

2005 • In

A general approach to real-time transient stability control is described, yielding various comple...

2005 • In

In this paper we study the concept of electric power system control, when the responsibility for ...

2004 • In

In this paper, we explore how a computational approach to learning from interactions, called rein...

2004 • In

In this paper we consider a tool for analyzing the market outcomes when competitive agents (power...

2004 • In

In this paper, we study the behavior of power suppliers who submit their bids to the market place...

2004 • In

In this paper we consider an electricity market in which not only the power producers but also th...

2003 • In

Reinforcement learning aims to determine an (infinite time horizon) optimal control policy from i...

2003 • In

This paper proposes an application of a Reinforcement Learning (RL) method to the control of a dy...

2003 • In

An on-line transient stability emergency control approach is proposed, which couples an open-loop...

2002 • In

Reinforcement learning consists of a collection of methods for approximating solutions to determi...

2001 • In

This paper proposes a unified approach to contingency filtering, ranking and assessment in power ...

2001 • In

It has been veri"ed that a controllable series capacitor with a suitable control scheme can impro...

2001 • In

An approach to modal analysis and modal identification is proposed, capable of complementing the...

2000 • In

Transient Stability Assessment, preventive control measures and dynamic A X calculations are addr...

2000 • In

This paper investigates the use of reinforcement learning in electric power system emergency cont...

2000 • In

The question of transient stability control is revisited, various types of controls are identifie...

2000 • In

A unified approach to transient stability closed-loop control is presented. It relies on the gene...

2000 • In

2000 • In

A general transient stability control technique is applied to the design of preventive countermea...

1999 • In

This paper proposes a new approach able to maximize the interface flow limits in power systems an...

1998 • In

A method is proposed for during transients emergency control which predicts the evolution of a sy...