Challenge / Goal
The former Philips industrial complex in the “Strijp-S” neighborhood of Eindhoven is being transformed into a creative smart district. A significant potential exists to reduce the energy consumption of the Strijp-S office buildings. The main goal was to save an estimated 20% of energy
An innovative concept has been developed to optimize energy consumption in buildings while maintaining user comfort that includes the following elements:
1) the individual control of office floors;
2) self-learning capabilities of the control algorithm;
3) dynamic working hours prediction
The Use Case stimulates energy-efficient behavior through an incentive system and has a high degree of potential success due to the fact that an attractive app invites to this behavior while the total concept does only in part rely on the behavioral change of the user. Additional important energy saving capacities result from the self-learning capabilities of the system which allows it to recognize patterns and adapt the energy management system accordingly.
The pilot consists of the installation of a number of sensors for 1 office wing (1600m2) in the building Video lab, together with a central controller and modifications to the Heating, Ventilation and Air-conditioning System (HVAC). In addition a cloud based control algorithm has been installed to enable peak shaving. The energy consumption and energy optimization are monitored and visualized via the application, users can see this information. Based on the behavior (patterns) and energy usage the HVAC can be managed more efficient.
The system monitors window openings, temperature, and occupancy. It gives users insights into energy use and promotes sustainable behavior. For example, to receive a message when you open a window in winter but want higher indoor temperature.
Predictive control algorithm used to independently control rooms in a building. The system can be used to setup a room before the user arrives. Encourages sustainable behavior through developing a sense of competition between users
App was used by VolkerWessels' employees too. Therefore, constant feedback received from end user. Feedbacks from other potential users were taken into account.
monitor temperature, air quality in room
remote control heating, ventilation and lighting of individual rooms
predicts the required climate conditions based on users
sends notification for behaviour change to users
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