Accurate information about terrain features is important for solar project development. Below we review a few reasons why it is necessary to have reliable information on the terrain on and around the project site:
Presently, Solargis database features elevation data with a resolution of 3 arcsec (nominally 90 m) on the land and 30 arcsec (nominally 1 km) for the sea bottom. The final dataset is the result of rigorous patching of a few available terrain datasets:
For land areas, primary dataset [1] is implemented. Dataset [2] is used to fill the lands above 60°N and below 60°S, and to fix or improve the identified problems in the dataset [1]. In a few cases of insufficient quality of [1] and [2], dataset [3] was post-processed and implemented. We have also tackled many issues in elevation data along the coastline. Finally, for sea bottom elevations, data source [4] is implemented.
Both parameters are calculated from terrain elevation data by Solargis approach. These are auxiliary parameters to elevation. A flat surface can be easily identified on the maps of both parameters. In case an inclined surface is identified at a project site, further analysis for optimal PV system design can be performed.
First, let’s explain two terms:
Solargis database features DEM terrain surface data (even though in some areas the noise from vegetation cover may be captured). The nominal resolution is 90 m, which is satisfactory for the regional analyses of the terrain structures in the neighbourhood (for example shading from surrounding mountains or hills).
For city models, DSM (digital surface model) is preferred, preferably in a sub-meter resolution. For detailed shading analyses of the roof PV, DSM model with a nominal resolution of about 10 cm or similar is recommended. Nowadays, there are no global DSM models in such high resolution available. However, there are regional activities to create country-wide products. Solargis models are capable to use high resolution data and compute solar resource and PV potential for the roofs of the entire city. However, in such case the computing capacity rises significantly, therefore such analyses are performed for limited areas.