| All you need to know about model predictive control for buildings J Drgoňa, J Arroyo, IC Figueroa, D Blum, K Arendt, D Kim, EP Ollé, ... Annual Reviews in Control 50, 190-232, 2020 | 665 | 2020 |
| Reinforced model predictive control (RL-MPC) for building energy management J Arroyo, C Manna, F Spiessens, L Helsen Applied Energy 309, 118346, 2022 | 128 | 2022 |
| Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings D Blum, J Arroyo, S Huang, J Drgoňa, F Jorissen, HT Walnum, Y Chen, ... Journal of Building Performance Simulation 14 (5), 586-610, 2021 | 101 | 2021 |
| 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 | 61 | 2020 |
| Ten questions concerning reinforcement learning for building energy management Z Nagy, G Henze, S Dey, J Arroyo, L Helsen, X Zhang, B Chen, ... Building and Environment 241, 110435, 2023 | 42 | 2023 |
| Prototyping the BOPTEST framework for simulation-based testing of advanced control strategies in buildings D Blum, F Jorissen, S Huang, Y Chen, J Arroyo, K Benne, Y Li, V Gavan, ... | 42 | 2020 |
| An open-ai gym environment for the building optimization testing (boptest) framework J Arroyo, C Manna, F Spiessens, L Helsen Building Simulation 2021 17, 175-182, 2021 | 29 | 2021 |
| Comparison of optimal control techniques for building energy management J Arroyo, F Spiessens, L Helsen Frontiers in Built Environment 8, 849754, 2022 | 21 | 2022 |
| A data driven method for optimal sensor placement in multi-zone buildings G Suryanarayana, J Arroyo, L Helsen, J Lago Energy and Buildings 243, 110956, 2021 | 19 | 2021 |
| Comparison of model complexities in optimal control tested in a real thermally activated building system J Arroyo, F Spiessens, L Helsen Buildings 12 (5), 539, 2022 | 15 | 2022 |
| A Python-based toolbox for model predictive control applied to buildings J Arroyo, B Van Der Heijde, A Spiessens, L Helsen | 12 | 2018 |
| Flexibility quantification in the context of flexible heat and power for buildings J Arroyo, S Gowri, F De Ridder, L Helsen The REHVA European HVAC Journal, 2017 | 6 | 2017 |
| Synergy between control theory and machine learning for building energy management J Arroyo | 5 | 2022 |
| Parameter Estimation of Modelica Building Models Using CasADi CD Cañas, J Arroyo, J Gillis, L Helsen Modelica Conferences, 301-310, 2023 | 2 | 2023 |
| Prototyping the DOPTEST Framework for Simulation-Based Testing of System Integration Strategies in Districts J Arroyo, L Verleyen, L Bex, L Hermans, MH Saeed, Y Lu, J Depoortere, ... | 2 | 2023 |
| Safe deep reinforcement learning for building energy management X Wang, P Wang, R Huang, X Zhu, J Arroyo, N Li Applied Energy 377, 124328, 2025 | | 2025 |
| TECHPED-Identifying technically feasible and effective solutions towards Positive Energy Districts L Verleyen uSIM2022-Urban Energy in a Net Zero World, Date: 2022/11/25-2022/11/25 …, 2022 | | 2022 |
| TECHPED–Identifying technically feasible and effective solutions towards Positive Energy Districts (PEDs) L Verleyen, L Hermans, J Arroyo, L Helsen Proceedings of the uSim Conference 2022 3, 2022 | | 2022 |
| BOPTEST workshop at EnergyVille: Introduction to the BOPTEST framework for simulation-based benchmarking of advanced controllers J Arroyo, D Blum, I Cupeiro Figueroa, K Benne Workshop, Location: EnergyVille, 2021 | | 2021 |
| BOPTEST workshop at BS2021: Introduction to the BOPTEST framework for simulation-based benchmarking of advanced controllers J Arroyo, D Blum, K Benne Building Simulation 2021 Conference, Date: 2021/09/01-2021/09/03, Location …, 2021 | | 2021 |
