The present master thesis contains an investigation about buildings' capacity of heat storage and a calculation tool able to prognosticate the heat demand after simple hourly method of EN ISO 13790.

Smart grid building are one of the newest technologies complying stricter becoming energy requirements of building regulations. To bring energy supply and energy consumption by means of a photovoltaic and heat pump heating system closer together, buildings need a relatively good capacity of storing heat due to the limited period of photovoltaic availability. To investigate which buildings are recommendable for implementing a smart grid system, eight different building variations are created and analysed regarding their ability to store a specific comfort temperature for a selected period of the day. Their heaviness is classified due to a varying heat capacity, ranging from extra light to extra heavy. Moreover, are mentioned heaviness categories further divided into today common standards regarding heat losses and passive house standard. Investigations are implemented in BSim, simulating a constant high heating phase in eight hours of day, to analyse the temperature drop in the remaining 16 hours without heating. An implementation of smart grids seems rational in buildings of actual standard that in majority include heavy materials. All versions of passive houses from light to heavy building heaviness are recommendatory for a smart grid implementation.

Further, is a main content of present master thesis the design of a calculation tool to make a prognosis regarding the heat demand, which can be implemented into heat pump controller. Chosen method is the simple hourly method after EN ISO 13790 due to the possible input of hourly data from conducted measurements of the smart grid building and its simplicity accompanied with a limited amount of input data. After a short presentation of the theory, a simplified sensitivity analysis is carried out, as the EN ISO 13790 leaves it to a certain degree to the user which weather parameters are to be implemented. External air temperature, solar radiation, wind and relative humidity are taken into consideration, as these can be achieved from weather services.

After the amount of input data is delimited, the necessary input information regarding building characteristics and ventilation system are explained. Further is a closer look given to solar and internal heat gains. The output of the calculation tool gives an overview of expected heating demand and expected internal air temperature, when the heating device only delivers in a limited period of the day.

To verify the calculation tool, simulated parameters are compared to measured heating supply and operative temperature of a building of the comfort house project. First, simulated operative temperatures with given heat demand are compared to measured operative temperatures. Second, the simulated heating demand with a given heating set temperature is juxtaposed to measured heating supply. Deviations lay in an acceptable range, which verifies the possible use of the calculation tool in heat pump controller.