Group leader: Jean-Louis Scartezzini
Postdoc: Ali Motamed
PhD student: Marta Benedetti
To address energy and sustainability issues at building and city scale, the numerous parameters contributing to the footprint of the built environment as well as their interactions must be understood and managed in a smart way. Much progress has been made in building control through the development of algorithms and systems that optimse both energy and indoor comfort (cf LESO-PB work in biomimetic building control). Research is now stepping up in scale to work towards smart cities.
Building services (heating, cooling, ventilation, electric lighting, blinds and daylighting devices) can be controlled either manually or automatically. Advanced automatic control systems have the following advantages:
- they provide an optimal indoor comfort (thermal, visual, air quality), as a continuous response to changing conditions (weather, building occupancy, user preferences, etc);
- in case the room or the building is not occupied, they can provide optimal energy use while still keeping an inside comfort that can be quickly returned to optimal in case the users are coming back.
In short, they can simultaneously optimize energy consumption and inside visual and thermal comfort when somebody is present.
In order to be well accepted by the users, the automatic control systems must comply with the following requirements:
- they must allow the users to override them in all cases, except for safety reasons (storm, rain, etc);
- they must first provide the best possible indoor comfort (thermal, visual, air quality), energy considerations being only a second priority;
- they should progressively adapt to the user preferences.
Research carried out in this field
- Self-sufficient lighting systems – High dynamic range vision controller
- Green-Mod: Toward Reliable Stochastic-Driven Models Applied to the Energy Savings in Buildings
- Advanced Control of Electrochromic Glazing
- Advanced Energy-Efficient Renovation of Buildings
- Swiss project BELControl
- European project Ecco-Build
- EPFL project AdControl
- Swiss project NEUROBAT
- European project EDIFICIO
- European project DELTA
- EPFL project Stochastic Control
PhD theses
| 8277 | 2017 | Ali Motamed | Integrated Daylighting and Artificial Lighting Control based on High Dynamic Range Vision Sensors |
| 6440 | 2015 | Nikos Zarkadis | Novel models towards predictive control of advanced building systems and occupant comfort in buildings |
| 4935 | 2011 | David Daum | On the Adaptation of Building Controls to the Envelope and the Occupants |
| 3918 | 2007 | David Lindelöf | Bayesian optimisation of visual comfort |
| 3900 | 2007 | Jessen Page | Simulating occupant presence and behaviour in buildings |
| 3482 | 2006 | Mario Germano | Qualitative modelling of the natural ventilation potential in urban context |
| 2778 | 2003 | Antoine Guillemin | Using genetic algorithms to take into account user wishes in an advanced building control system Chorafas Award 2004 |
| 1792 | 1998 | Manuel Bauer | Gestion biomimétique de l’énergie dans le bâtiment |