Large-scale spatiotemporal calculation of photovoltaic capacity factors using ray tracing: A case study in urban environments

Abstract

Photovoltaics (PVs) on building facades, either building-integrated or building-attached, offer a large energy yield potential especially in densely populated urban areas. Targeting this potential requires the availability of planning tools such as insolation forecasts. However, calculating the PV potential of facade surfaces in an urban environment is challenging. Complex time-dependent shadowing and light reflections must be considered. In this contribution, we present fast ray tracing calculations for insolation forecasts in large urban environments using clustering of Sun positions into typical days. We use our approach to determine time resolved PV capacity factors for rooftops and facades in a wide variety of environments, which is particularly useful for energy system analyses. The advantage of our approach is that the determined capacity factors for one geographic location can be easily extended to larger geographic regions. In this contribution, we perform calculations in three exemplary environments and extend the results globally. Especially for facade surfaces, we find that there is a pronounced intra-day and also seasonal distribution of PV potentials that strongly depends on the degree of latitude. The consideration of light reflections in our ray tracing approach causes an increase in calculated full load hours for facade surfaces between 10% and 25% for most geographical locations.