Assessment of modelling approaches for louver shading devices in office buildings

摘要

The presented paper focuses on the performance of exterior shading devices made of louvers.The analysis of the performance of these devices differs substantially from more traditionalscreens as their performance not only depends on the solar properties of the used materials butalso on the position of the sun with respect to the louvers. In order to capture this complexity,models predicting the solar transmittance of louver shading devices have to be integrated intobuilding energy simulation tools. A ray tracing method has been developed to describe theglobal solar transmittance of louver shading devices. Consecutively, this method is integratedin the dynamic building energy simulation program TRNSYS to assess the cooling demandand required cooling power in a south oriented office cell. The proposed integrated approachallows calculating the solar transmittance for each time step. The method however is alsoquite complex and requires an important computational effort. Therefore this researchcontrasts the results of this ray tracing method against the performance of other modellingapproaches to assess the performance of louver shading devices in dynamic building energysimulation programs. It is shown that representing the shading device as a fixed reductionfactor, independent of orientation, is an important simplification and is insufficient toincorporate the complexity of the performance and control of exterior louver systems.Deviations up to 102% were found for the cooling demand and up to 72% for the coolingpower. The use of view factor models typically underestimate the cooling demand by up to36% and the cooling power by up to 26%. The use of a simplified implementation of shadingfactors, however, is possible within acceptable margins if the results of a ray tracingcalculation are implemented in a building energy simulation tool. Implementing the results ofa ray tracing calculation of one representative average or sunny day reduces the deviations to14% for the cooling demand and 18% for the cooling power. Performing additional raytracing calculations for typical heating or cooling conditions or for every month further reducethe deviations to the order of 10% to 5% for the cooling demand and power respectively.