Analys av energianvändningen i kvarteren Carolina och Jenny : en fallstudie

An energy study has been performed on two blocks in an area called Gävle Strand. The buildings are owned by a tenant-owner’s association called brf Carolina and were built by the company Skanska 2008. The builder as well as brf Carolina are pussled by the fact that electricity use is higher than expected while heating is less. Skanska is also very interested in finding out how much heat recovery from stale exhaust air through a geo-thermal heat pump is contributing to the general heating requirement and energy balance in four out of the ten buildings located on the properties. To find possible answers to the higher electricity use a literature survey on user behaviour was conducted. Simulations were executed in the energy simulation program BV2 testing the efficiency of a mechanical ventilation system with fans dispatching the used stale air with heat recovery through the geo-thermal heat pump in comparison to a HRV-system. As BV2 can’t simulate heat pumps its impact was instead calculated manually and added to the result from BV2. The result show that there are significant differences in both water and electricity use between households. The mean value in brf Carolina is also higher for both water and electricity use than the typical pattern value most commonly used in energy simulations for new buildings. The simulations and calculations show that a HRV-system is practically equal to the system chosen for these buildings. The geo-thermal heat pump make a substantial contribution to the heating requirements but also increases the electricity use in comparison to the HRV-system. The buildings over all have a good energy performance. The chosen heat recovery system is working well. If the source for energy is also valued a HRV-system is still preferable since it requires less electricity.In regards to user behaviour the under floor heating installed in the bathrooms and operated by the occupants is very likely to have a substantial impact on the higher than average electricity use. There are however many other factors that could have an impact on energy use due to behaviour factors. This is also a factor when varations between households are viewed. Key words; energy, energy simulation, user behaviou