Projects
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Representation of Energy Flexibility with a Semantic Ontology, funded by PITA and Johnson Controls (05/2023 – present)
- Aim: Facilitating application portability across building automation systems through machine-readable descriptions of physical environments with a specific focus on energy flexibility applications.
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Leveraging Sensor Networks for Flexibility and Comfort (08/2022 – 08/2023)
- Data Scale: Handled a large dataset involving 5-minute resolution data from 1000 houses, equipped with multiple sensors, for the year 2017.
- ML-Driven Analysis: Employed ML techniques for enhancing comfort in multi-room single-zone houses using smart thermostats and sensor data.
- Physics-Based Modeling: Applied physics-based ML algorithms to analyze and model energy dynamics in 100 residential units, each equipped with sensor networks comprising 6 nodes.
Publications
Mulayim, O. B., Severnini, E., & Bergés, M. (2024). Unmasking the Role of Remote Sensors in Comfort, Energy and Demand Response.
Data-Centric Engineering (Accepted).
Mulayim, O. B., & Bergés, M. (2024). Beyond Average: Evaluating Indoor Average Temperature in Grey Box Modeling.
International High Performance Buildings Conference (Finalist for best-paper award).
Mulayim, O. B., & Bergés, M. (2024). Leveraging Grey Box Models for Enhanced Energy Flexibility in Centralized and Decentralized Single-Zone Multi-Node Systems.
IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (Accepted).
Mulayim, O. B., & Bergés, M. (2023, November). Unmasking the Thermal Behavior of Single-Zone Multi-Room Houses: An Empirical Study.
In Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 21-30).