Data-Driven Smart Buildings
DDSB
The ZUB office building (Centre for Environmentally Conscious Building) was designed in 2001 with the purpose of testing low-energy and carbon technologies. With the building having primarily heating demands, the design annual heating demand was estimated to be less than 20 kWh/m2. Energy demand in operation was 16.5 kWh/m2, achieving the best possible rating according to the German Energy code “Wärmeschutzverordnung 95”.
The energy concept of the building included construction with very low U-value, triple glazed windows and design to use natural lighting and natural ventilation. Solar gains meet most heating demands through the south-facing façade. When additional heating is required, this is delivered through a communal district heating network. Cooling demands are met by a ground-source heat pump placed under the ZUB basement. As the building is air-tight, an 80% mechanical ventilation with heat recovery system is used.
The characteristic that defines the building is the high inertial behaviour due to the weight of the building walls and the massive radiant systems installed to deliver heating and cooling. These types of high thermal mass slabs allow water supply temperatures close to the internal ambient temperatures, i.e. use of low water temperatures during the heating season and relatively high water temperatures during the cooling period. Combining these strategies leads to reduced energy consumption by maximising the exergetic use of the climate control systems.
Implementation of a model-based control strategy to ensure proper use of the thermal mass to meet heating and cooling demands and ensure occupant comfort. Comparison of baseline rule-based control to model-based control. Implementation and testing of continuous monitoring and data analytics platform.
The building has more than 800 data points available with 1-min interval records kept since 2001. In some years, there have been gaps in data storage.
Good indoor comfort for the occupants was an important requirement from the building owner. After ten years of use, the building energy demand was low. Due to the occupant loads and solar radiation, the building was overheating in both winter and summer operations. This led to significant occupants’ discomfort and complaints.
Occupants could manually control the blinds to balance solar gains. The high thermal inertia of the building reduced controllability and created challenges to the building control. A model-based predictive control approach was adopted to check if using models to predict behaviour could lead to improved operation and thermal comfort.
