TU Delft researchers have developed a new approach for calculating fast and accurate the solar energy potential of surfaces in the urban environment. The new approach can significantly help architects and urban planners to incorporate photovoltaic (solar power) technology in their designs.
Buildings, trees and other structures in urban areas cause shading of solar modules, which strongly affects the performance of a PV system. Accurate assessment of this performance, and the related price/performance of PV systems, will facilitate their integration in the urban environment.
Computationally highly demanding
Several
tools are available for simulating the energy yield of PV systems.
These tools are based on mathematical models that determine the
irradiance incident on solar modules. By repeating the calculation of
the incident irradiance throughout the year, the tools deliver an annual
irradiation received by the modules. However, it is not easy to
determine accurately how much electricity a PV system generates in an
urban environment. Current simulations become computationally highly
demanding, as the dynamic shading of surrounding objects caused by the
annual movement of the sun has to be taken into account.
Two parameters
A new approach simplifies the calculation and enables the user to carry out a quick assessment of the solar energy potential for large urban areas whilst keeping high accuracy. It is based on a correlation between a skyline profile and the annual irradiation received at a particular urban spot. This method is explained and validated in a study published in Nature Energy journal. The study demonstrates that the total annual solar irradiation received by a selected surface in an urban environment can be quantified using two parameters that are derived from the skyline profile: the sky view factor and the sun coverage factor. While the first parameter is used to estimate the irradiation from the diffuse sunlight component, the second one is indicative for the irradiation from the direct sunlight component. These two parameters can be easily and quickly obtained from the skyline profile. The study shows that the use of these two parameters significantly reduces the computational complexity of the problem.
