Damien Ernst
Damien Ernst
Professor of Electrical Engineering and Computer Science, ULiège
Verified email at - Homepage
Cited by
Cited by
Extremely randomized trees
P Geurts, D Ernst, L Wehenkel
Machine learning 63, 3-42, 2006
Tree-Based Batch Mode Reinforcement Learning
D Ernst, P Geurts, L Wehenkel
Journal of Machine Learning Research 6 (4), 2005
Reinforcement learning and dynamic programming using function approximators
L Busoniu, R Babuska, B De Schutter, D Ernst
CRC press, 2017
Transient stability of power systems: a unified approach to assessment and control
M Pavella, D Ernst, D Ruiz-Vega
Springer Science & Business Media, 2012
Active management of low-voltage networks for mitigating overvoltages due to photovoltaic units
F Olivier, P Aristidou, D Ernst, T Van Cutsem
IEEE Transactions on Smart Grid 7 (2), 926-936, 2015
Power systems stability control: reinforcement learning framework
D Ernst, M Glavic, L Wehenkel
IEEE transactions on power systems 19 (1), 427-435, 2004
The impact of different COVID-19 containment measures on electricity consumption in Europe
A Bahmanyar, A Estebsari, D Ernst
Energy Research & Social Science 68, 101683, 2020
Reinforcement learning versus model predictive control: a comparison on a power system problem
D Ernst, M Glavic, F Capitanescu, L Wehenkel
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2008
Contingency filtering techniques for preventive security-constrained optimal power flow
F Capitanescu, M Glavic, D Ernst, L Wehenkel
IEEE Transactions on Power Systems 22 (4), 1690-1697, 2007
Interior-point based algorithms for the solution of optimal power flow problems
F Capitanescu, M Glavic, D Ernst, L Wehenkel
Electric Power systems research 77 (5-6), 508-517, 2007
Reinforcement learning for electric power system decision and control: Past considerations and perspectives
M Glavic, R Fonteneau, D Ernst
IFAC-PapersOnLine 50 (1), 6918-6927, 2017
Reinforcement learning of heuristic EV fleet charging in a day-ahead electricity market
S Vandael, B Claessens, D Ernst, T Holvoet, G Deconinck
IEEE Transactions on Smart Grid 6 (4), 1795-1805, 2015
The global grid
S Chatzivasileiadis, D Ernst, G Andersson
Renewable Energy 57, 372-383, 2013
Deep reinforcement learning solutions for energy microgrids management
V François-Lavet, D Taralla, D Ernst, R Fonteneau
European Workshop on Reinforcement Learning (EWRL 2016), 2016
A unified approach to transient stability contingency filtering, ranking and assessment
D Ernst, D Ruiz-Vega, M Pavella, PM Hirsch, D Sobajic
IEEE Transactions on Power Systems 16 (3), 435-443, 2001
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach
D Ernst, GB Stan, J Goncalves, L Wehenkel
Proceedings of the 45th IEEE Conference on Decision and Control, 667-672, 2006
An application of deep reinforcement learning to algorithmic trading
T Théate, D Ernst
Expert Systems with Applications 173, 114632, 2021
How to discount deep reinforcement learning: Towards new dynamic strategies
V François-Lavet, R Fonteneau, D Ernst
arXiv preprint arXiv:1512.02011, 2015
A comparison of Nash equilibria analysis and agent-based modelling for power markets
T Krause, EV Beck, R Cherkaoui, A Germond, G Andersson, D Ernst
International Journal of Electrical Power & Energy Systems 28 (9), 599-607, 2006
Coordinated primary frequency control among non-synchronous systems connected by a multi-terminal high-voltage direct current grid
J Dai, Y Phulpin, A Sarlette, D Ernst
IET generation, transmission & distribution 6 (2), 99-108, 2012
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