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 | 470* | 2016 |
Battery energy management in a microgrid using batch reinforcement learning BV Mbuwir, F Ruelens, F Spiessens, G Deconinck Energies 10 (11), 1846, 2017 | 176 | 2017 |
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 | 165 | 2016 |
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 | 139 | 2016 |
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 | 102 | 2014 |
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 | 71 | 2018 |
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 | 71 | 2015 |
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 | 50 | 2014 |
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 | 47 | 2019 |
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 | 37 | 2013 |
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 | 37 | 2012 |
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 | 36 | 2018 |
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 | 33 | 2012 |
Using reinforcement learning for optimizing heat pump control in a building model in Modelica T Peirelinck, F Ruelens, G Deconinck 2018 IEEE International Energy Conference (ENERGYCON), 1-6, 2018 | 32 | 2018 |
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 | 16 | 2015 |
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 | 12 | 2016 |
Reinforcement learning-based battery energy management in a solar microgrid B Mbuwir, F Ruelens, F Spiessens, G Deconinck Energy-Open 2 (4), 36, 2017 | 10 | 2017 |
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 | 10 | 2013 |
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 | 9 | 2013 |
Residential Demand Response Using Reinforcement Learning: From Theory to Practice F Ruelens | 6 | 2016 |