Thermal building simulation

The current type of construction preferred for new high energy efficient buildings in Germany, featuring highly insulated building components and an almost completely airtight building shell, raises several new challenges with regard to design, construction and use of these buildings. Cooling, in particular, is an issue that gains importance also in the residential sector, in connection with rising temperatures induced by the climate change.

The energy consumption needed for establishing a good indoor climate in shopping centres is often very high due to high internal heat loads from lighting and equipment and from a high people density at certain time intervals. This heat surplus result in a need for cooling during most of the year, typically also during the winter, and often the needed cooling is provided by a mechanical ventilation system with integrated mechanical cooling.

In order to quantify uncertainty in thermal building simulation stochastic modelling is applied on a building model. Part l deals with the stochastic thermal building model and a test case. This paper deals with the determination of the stochastic input loads. The importance of obtaining a proper statistical description of the input quantities to a stochastic model is addressed and exemplified by stochastic models for the external air temperature and the solar heat gain.

In order to quantify uncertainty in thermal building simulation stochastic modelling is applied on a building model. An application of stochastic differential equations is presented in Part I comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions. Randomness in the input as well as the model coefficients is considered. Two different approaches are presented namely equations for first and second order time varying statistical moments and Monte Carlo Simulation.