A method for generating hourly solar radiation profiles on building rooftops accounting for cloud cover variability

Building Integrated Photovoltaic systems (BIPV) are gaining popularity as urban energy systems move towards decentralization. The calculation of the incoming solar radiation for building rooftops at a high temporal resolution is a key input to perform an energy balance of buildings within the larger context of an urban energy planning exercise and to control the supply and demand of energy. Solar radiation on building rooftop surfaces is highly stochastic due to highly variable cloud cover. Hence, for improving the accuracy in calculating the energy potential of BIPV, it is important to incorporate varying cloud cover in the simulation approach. This study presents a GIS based methodology for calculating hourly solar radiation on building rooftop surfaces taking into account the variability in cloud cover. The location of the study is the Fluntern weather station in Zurich, Switzerland. The r.sun module of the open source GIS software suit GRASS is used to calculate the clear sky irradiation (CSR). To account for the cloud cover, a reduction factor called the clear sky index (KC) which is dependent on the cloud cover is applied to the calculated CSR to obtain the real sky radiation. KC is calibrated for different values of cloud cover and time of day using measured meteorological data spanning a time period from 1981 to 2014 from the weather station. The hourly cloud cover is predicted through a discrete state Markov process. KC, the measured cloud cover, the simulated clear sky radiation are then used to obtain the real sky radiation and is validated against the measured values of solar radiation. Results show that the taking into account the cloud cover for calculating radiation reduces the root mean square error and the mean bias deviation by 37% and 86% respectively.