X-Novation Center
On the roof of the X-Novation Center scientific demonstrator
The X-Novation Center at École Polytechnique is an intelligent building demonstrator for research and experimentation on the energy transition of tertiary buildings, in real conditions. It integrates a photovoltaic production infrastructure, storage and control of electricity consumption as well as a network of sensors and meters producing an exceptional flow of data over a long history. Faced with the weight of buildings in greenhouse gas emissions, the X-Novation Center explores responses combining sobriety, electrification of uses and management intelligence.
- 53 photovoltaic panels for a total of 16.7 kWp
- 30kWh battery
- 30 electrical measurement points (heating, air conditioning, ventilation, lighting, electrical outlets, water heater, photovoltaic production, battery)
- 1 electric charging station for a car-sharing vehicle
- Measurements since 2016, with a resolution of 1 second to 15 minutes
- Laboratories involved: LMD, CRG, SAMOVAR, GeePs, LVMT, LPICM, LIX
Liste des publications associées
- Calderón-Obaldía, F., Anvari-Moghaddam, A. M., Guerrero, J. M., Badosa, J., Migan-Dubois, A., & Bourdin, V. (2018, septembre). Operating reserve in microgrids : An approach to deal with uncertainty. https://doi.org/10.1109/TSG.2012.2231440
- Calderon-Obaldia, F., Badosa, J., Migan-Dubois, A., & Bourdin, V. (2019, septembre). Estimation and integration of net demand uncertainty in a microgrid management. https://hal.science/hal-03312275
- Calderon-Obaldia, F., Badosa, J., Migan-Dubois, A., & Bourdin, V. (2020). A Two-Step Energy Management Method Guided by Day-Ahead Quantile Solar Forecasts : Cross-Impacts on Four Services for Smart-Buildings. Energies, 13(22), 5882. https://doi.org/10.3390/en13225882
- Dridi, A., Afifi, H., Moungla, H., & Badosa, J. (2022). A Novel Deep Reinforcement Approach for IIoT Microgrid Energy Management Systems. IEEE Transactions on Green Communications and Networking, 6(1), 148 159. https://doi.org/10.1109/TGCN.2021.3112043
- Dridi, A., Moungla, H., Afifi, H., Badosa, J., Ossart, F., & Kamal, A. E. (2020). Machine Learning Application to Priority Scheduling in Smart Microgrids. 2020 International Wireless Communications and Mobile Computing (IWCMC), 1695 1700. https://doi.org/10.1109/IWCMC48107.2020.9148096
- Hamdipoor, V., Nguyen, H. N., Mekhaldi, B., Parra, J., Badosa, J., & Obaldia, F. C. (2025). Experimental validation of scenario-based stochastic model predictive control of nanogrids. Control Engineering Practice, 157, 106249. https://doi.org/10.1016/j.conengprac.2025.106249
- Levent, T., Preux, P., Le Pennec, E., Badosa, J., Henri, G., & Bonnassieux, Y. (2019). Energy Management for Microgrids : A Reinforcement Learning Approach. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 1 5. https://doi.org/10.1109/ISGTEurope.2019.8905538