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Frederik Ruelens
Frederik Ruelens
Ph.D. researcher
Verified email at esat.kuleuven.be
Title
Cited by
Cited by
Year
Residential demand response of thermostatically controlled loads using batch reinforcement learning
F Ruelens, BJ Claessens, S Vandael, B De Schutter, R Babuška, ...
IEEE Transactions on Smart Grid 8 (5), 2149-2159, 2016
451*2016
Battery energy management in a microgrid using batch reinforcement learning
BV Mbuwir, F Ruelens, F Spiessens, G Deconinck
Energies 10 (11), 1846, 2017
1692017
Convolutional neural networks for automatic state-time feature extraction in reinforcement learning applied to residential load control
BJ Claessens, P Vrancx, F Ruelens
IEEE Transactions on Smart Grid 9 (4), 3259-3269, 2016
1582016
Experimental analysis of data-driven control for a building heating system
GT Costanzo, S Iacovella, F Ruelens, T Leurs, BJ Claessens
Sustainable Energy, Grids and Networks 6, 81-90, 2016
1362016
Demand response of a heterogeneous cluster of electric water heaters using batch reinforcement learning
F Ruelens, BJ Claessens, S Vandael, S Iacovella, P Vingerhoets, ...
2014 power systems computation conference, 1-7, 2014
992014
Model-free control of thermostatically controlled loads connected to a district heating network
BJ Claessens, D Vanhoudt, J Desmedt, F Ruelens
Energy and Buildings 159, 1-10, 2018
712018
Cluster control of heterogeneous thermostatically controlled loads using tracer devices
S Iacovella, F Ruelens, P Vingerhoets, B Claessens, G Deconinck
IEEE Transactions on Smart Grid 8 (2), 528-536, 2015
692015
A flexible stochastic optimization method for wind power balancing with PHEVs
W Leterme, F Ruelens, B Claessens, R Belmans
IEEE Transactions on Smart Grid 5 (3), 1238-1245, 2014
502014
Direct load control of thermostatically controlled loads based on sparse observations using deep reinforcement learning
F Ruelens, BJ Claessens, P Vrancx, F Spiessens, G Deconinck
CSEE Journal of Power and Energy Systems 5 (4), 423-432, 2019
442019
Peak shaving of a heterogeneous cluster of residential flexibility carriers using reinforcement learning
BJ Claessens, S Vandael, F Ruelens, K De Craemer, B Beusen
IEEE pes isgt europe 2013, 1-5, 2013
372013
Comparing neural architectures for demand response through model-free reinforcement learning for heat pump control
C Patyn, F Ruelens, G Deconinck
2018 IEEE international energy conference (ENERGYCON), 1-6, 2018
362018
Demand side management of electric vehicles with uncertainty on arrival and departure times
F Ruelens, S Vandael, W Leterme, BJ Claessens, M Hommelberg, ...
2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 1-8, 2012
362012
Self-learning demand side management for a heterogeneous cluster of devices with binary control actions
BJ Claessens, S Vandael, F Ruelens, M Hommelberg
2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 1-8, 2012
332012
Using reinforcement learning for optimizing heat pump control in a building model in Modelica
T Peirelinck, F Ruelens, G Decnoninck
2018 IEEE International Energy Conference (ENERGYCON), 1-6, 2018
322018
Residential demand response applications using batch reinforcement learning
F Ruelens, B Claessens, S Vandael, B De Schutter, R Babuska, ...
arXiv preprint arXiv:1504.02125, 2015
162015
Beyond theory: Experimental results of a self-learning air conditioning unit
T Leurs, BJ Claessens, F Ruelens, S Weckx, G Deconinck
2016 IEEE International Energy Conference (ENERGYCON), 1-6, 2016
122016
Double-layered control methodology combining price objective and grid constraints
S Iacovella, F Geth, F Ruelens, N Leemput, P Vingerhoets, G Deconinck, ...
2013 IEEE International Conference on Smart Grid Communications …, 2013
102013
Reinforcement learning-based battery energy management in a solar microgrid
B Mbuwir, F Ruelens, F Spiessens, G Deconinck
Energy-Open 2 (4), 36, 2017
92017
Stochastic portfolio management of an electric vehicles aggregator under price uncertainty
F Ruelens, S Weckx, W Leterme, S Vandael, BJ Claessens, R Belmans
IEEE PES ISGT Europe 2013, 1-5, 2013
82013
Residential Demand Response Using Reinforcement Learning: From Theory to Practice
F Ruelens
62016
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