  | Aittahar, S., Manuel de Villena Millan, M., Derval, G., Castronovo, M., Boukas, I., Gemine, Q., & Ernst, D. (2023). Optimal Control of Renewable Energy Communities with Controllable Assets. Frontiers in Energy Research. doi:10.3389/fenrg.2023.879041  Peer Reviewed verified by ORBi |
 | Manuel De Villena, M., Aittahar, S., Mathieu, S., Boukas, I., Vermeulen, E., & Ernst, D. (2022). Financial Optimization of Renewable Energy Communities Through Optimal Allocation of Locally Generated Electricity. IEEE Access, 10, 77571 - 77586. doi:10.1109/ACCESS.2022.3191804 Peer Reviewed verified by ORBi |
 | Bolland, A., Boukas, I., Berger, M., & Ernst, D. (January 2022). Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent. Journal of Artificial Intelligence Research, 73, 117-171. doi:10.1613/JAIR.1.13350 Peer reviewed |
 | De Villena, M. M., Aittahar, S., Mathieu, S., Boukas, I., Vermeulen, E., & Ernst, D. (2022). Allocation of locally generated electricity in renewable energy communities. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/250878. |
 | Boukas, I., Ernst, D., Théate, T., Bolland, A., Huynen, A., Buchwald, M., Wynants, C., & Cornélusse, B. (2021). A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding. Machine Learning. doi:10.1007/s10994-021-06020-8 Peer Reviewed verified by ORBi |
 | Shinde, P., Boukas, I., Radu, D.-C., de Villena, M. M., & Amelin, M. (2021). Analyzing trade in continuous intra-day electricity market: An agent-based modeling approach. Energies, 14 (13). doi:10.3390/en14133860 Peer Reviewed verified by ORBi |
 | Totaro, S., Boukas, I., Jonsson, A., & Cornélusse, B. (2021). Lifelong control of off-grid microgrid with model-based reinforcement learning. Energy, 232. doi:10.1016/j.energy.2021.121035 Peer Reviewed verified by ORBi |
 | Boukas, I. (2021). Deep Reinforcement Learning for the Control of Energy Storage in Grid-Scale and Microgrid Applications [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/258490 |
 | Manuel de Villena Millan, M., Boukas, I., Mathieu, S., Ernst, D., & Vermeulen, E. (2020). A Framework to Integrate Flexibility Bids into Energy Communities to Improve Self-Consumption. In 2020 IEEE PES General Meeting. IEEE. doi:10.1109/PESGM41954.2020.9282036 Peer reviewed |
  | Dakir, S., Boukas, I., Lemort, V., & Cornélusse, B. (2020). Sizing and Operation of an Isolated Microgrid with Building Thermal Dynamics and Cold Storage. IEEE Transactions on Industry Applications. doi:10.1109/TIA.2020.3005370 Peer Reviewed verified by ORBi |
 | Boukas, I., El Mekki, S., & Cornélusse, B. (2019). Data-driven Parameterized Policies for Microgrid Control. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/240141. |
 | Dakir, S., Boukas, I., Lemort, V., & Cornélusse, B. (2019). Sizing and Operation of an Isolated Microgrid with Cold Storage. In Powertech Milano 2019 Proceedings. doi:10.1109/PTC.2019.8810700 Peer reviewed |
 | Dakir, S., Boukas, I., Lemort, V., & Cornélusse, B. (2019). Sizing and Operation of an Isolated Microgrid with Building Thermal Dynamics and Cold Storage. In EEEIC Genoa 2019 Proceedings. doi:10.1109/EEEIC.2019.8783514 Peer reviewed |
 | Dumas, J., Boukas, I., Manuel de Villena Millan, M., Mathieu, S., & Cornélusse, B. (2019). Probabilistic Forecasting of Imbalance Prices in the Belgian Context. In 2019 16th International Conference on the European Energy Market (EEM). doi:10.1109/EEM.2019.8916375 Peer reviewed |
 | Boukas, I., Ernst, D., & Cornélusse, B. (2018). Real-Time Bidding Strategies from Micro-Grids Using Reinforcement Learning. In Proceedings of CIRED Workshop 2018. Peer reviewed |
 | Boukas, I., Ernst, D., Papavasiliou, A., & Cornélusse, B. (2018). Intra-day Bidding Strategies for Storage Devices Using Deep Reinforcement Learning. In International Conference on the European Energy Market, Łódź 27-29 June 2018 (pp. 6). Peer reviewed |
