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Fred Spiessens
Fred Spiessens
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Titel
Zitiert von
Zitiert von
Jahr
Battery energy management in a microgrid using batch reinforcement learning
BV Mbuwir, F Ruelens, F Spiessens, G Deconinck
Energies 10 (11), 1846, 2017
942017
Using reinforcement learning for demand response of domestic hot water buffers: A real-life demonstration
O De Somer, A Soares, K Vanthournout, F Spiessens, T Kuijpers, ...
2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2017
532017
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
302019
The Oz-E project: Design guidelines for a secure multiparadigm programming language
F Spiessens, PV Roy
International Conference on Multiparadigm Programming in Mozart/OZ, 21-40, 2004
292004
Distributed optimization algorithm for residential flexibility activation—Results from a field test
A Soares, O De Somer, D Ectors, F Aben, J Goyvaerts, M Broekmans, ...
IEEE Transactions on Power Systems 34 (5), 4119-4127, 2018
212018
POLIPO: policies & ontologies for interoperability, portability, and autonomy
D Trivellato, F Spiessens, N Zannone, S Etalle
2009 IEEE International Symposium on Policies for Distributed Systems and …, 2009
212009
Distributed optimization for scheduling energy flows in community microgrids
BV Mbuwir, F Spiessens, G Deconinck
Electric Power Systems Research 187, 106479, 2020
202020
A practical formal model for safety analysis in capability-based systems
F Spiessens, PV Roy
International Symposium on Trustworthy Global Computing, 248-278, 2005
202005
Patterns of safe collaboration.
F Spiessens
Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2007
192007
Reinforcement learning for control of flexibility providers in a residential microgrid
BV Mbuwir, D Geysen, F Spiessens, G Deconinck
IET Smart Grid 3 (1), 98-107, 2020
182020
Identification of multi-zone grey-box building models for use in model predictive control
J Arroyo, F Spiessens, L Helsen
Journal of Building Performance Simulation 13 (4), 472-486, 2020
162020
Reputation-based ontology alignment for autonomy and interoperability in distributed access control
D Trivellato, F Spiessens, N Zannone, S Etalle
2009 International Conference on Computational Science and Engineering 3 …, 2009
162009
Using reinforcement learning for maximizing residential self-consumption–Results from a field test
A Soares, D Geysen, F Spiessens, D Ectors, O De Somer, K Vanthournout
Energy and Buildings 207, 109608, 2020
122020
Self-learning agent for battery energy management in a residential microgrid
BV Mbuwir, F Spiessens, G Deconinck
2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2018
102018
A Python-based toolbox for model predictive control applied to buildings
J Arroyo, B Van Der Heijde, A Spiessens, L Helsen
102018
Transfer learning in demand response: A review of algorithms for data-efficient modelling and control
T Peirelinck, H Kazmi, BV Mbuwir, C Hermans, F Spiessens, J Suykens, ...
Energy and AI 7, 100126, 2022
82022
Domain randomization for demand response of an electric water heater
T Peirelinck, C Hermans, F Spiessens, G Deconinck
IEEE Transactions on Smart Grid 12 (2), 1370-1379, 2020
72020
Benchmarking regression methods for function approximation in reinforcement learning: heat pump control
BV Mbuwir, F Spiessens, G Deconinck
2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 1-5, 2019
72019
Transfer learning for operational planning of batteries in commercial buildings
BV Mbuwir, K Paridari, F Spiessens, L Nordström, G Deconinck
2020 IEEE International Conference on Communications, Control, and Computing …, 2020
62020
Reinforcement learning-based battery energy management in a solar microgrid
B Mbuwir, F Ruelens, F Spiessens, G Deconinck
Energy-Open 2 (4), 36, 2017
62017
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