Coupling building energy simulation software with microclimatic simulation for the evaluation of the impact of urban outdoor conditions on the energy consumption and indoor environmental quality
Το work with title Coupling building energy simulation software with microclimatic simulation for the evaluation of the impact of urban outdoor conditions on the energy consumption and indoor environmental quality by Gobakis Konstantinos, Kolokotsa Dionysia is licensed under Creative Commons Attribution 4.0 International
Bibliographic Citation
K. Gobakis and D. Kolokotsa, "Coupling building energy simulation software with microclimatic simulation for the evaluation of the impact of urban outdoor conditions on the energy consumption and indoor environmental quality," Energy Build., vol. 157, pp. 101-115, Dec., 2017. doi: 10.1016/j.enbuild.2017.02.020
https://doi.org/10.1016/j.enbuild.2017.02.020
The indoor energy simulation software of buildings, by default do not include the actual meteorological conditions (outside humidity, temperature, etc.) but uses average external weather data obtained by statistical analysis, which do not take into account local outdoor microclimate variations due to the urban landscape. This may lead to miscalculation of the needed energy for cooling and heating if the model is integrated in a real time building control scheme. Another important parameter in the energy simulation is the convection heat transfer coefficient between the outside environment and the building outside walls. The coefficient is calculated, in most energy simulation software, based on equations generated by wind tunnel experiments. In our approach a microclimatic environment simulation coupled with the indoor energy simulation will calculate dynamically the convection heat transfer coefficient between the outside environment and the building outside walls. The use of the meteorological data produced by a microclimatic simulation along with the dynamic calculation of the convection heat transfer coefficient is implemented in this work to achieve a better energy simulation of the building. Finally, the coupling of the two domains can lead to a ±40% difference in heating/cooling needs