Data driven energy efficiency in an air heated office building in Norway

Abstract

There are lots of data stored about buildings that could be better used to improve the operation of existing and new buildings. In the long run, this means that building data can be used much more efficiently for energy, heat rate, and electricity reduction based on price and load. However, building data are only stored and the knowledge that may be found in this data is not fully utilized. The aim of the study was to evaluate potentials and opportunities with continuous energy, heat rate, and power reduction in an all-air heated office building in Trondheim, Norway. The observed building has an area of 14 000 m2 and the building was built according to the passive house standard. The background for the work was that high peak loads in electricity and heat are challenging for both the district heating and power grid. By reducing or moving the energy use of the ventilation heat to periods with low grid loads, cost savings can be achieved through a reduced rate in district heating and electricity. In this study, a model of the building was created in the simulation program IDA-ICE, where data about building body, outdoor climate, energy supply, energy distribution, set points for room control, operation and schedules were used from a real building. This included measurements of the outdoor temperature, supply temperature, internal loads, electricity use, district heating, and hot water, as well as indoor temperatures and air flow rates. Various scenarios were developed to reduce peak loads in heating and electricity with the focus on controlling the ventilation system. The results for the annual simulation showed a reduction in ventilation heat rate from 12% to 33%. Further, the results showed a cost saving for heat and electricity from of 10% to 16%. The study may be useful for facility managers, operators, and end users of office buildings that want cost-effective building performance improvement.