A Point-Cloud Solar Radiation Tool

Current software solutions for solar-radiation modeling in 3D focus on the urban environment. Most of the published tools do not implement methods to consider complex objects, such as urban greenery in their models or they expect a rather complex 3D mesh to represent such objects. Their use in an en...

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Bibliographic Details
Main Authors: Filip Pružinec, Renata Ďuračiová
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/15/19/7018
Description
Summary:Current software solutions for solar-radiation modeling in 3D focus on the urban environment. Most of the published tools do not implement methods to consider complex objects, such as urban greenery in their models or they expect a rather complex 3D mesh to represent such objects. Their use in an environment that is difficult to represent geometrically, such as vegetation-covered areas, is rather limited. In this paper, we present a newly developed solar-radiation tool focused on solar-radiation modeling in areas with complex objects, such as vegetation. The tool uses voxel representations of space based on point-cloud data to calculate the illumination and ESRA solar-radiation model to estimate the direct, diffuse, and global irradiation in a specified time range. We demonstrate the capabilities of this tool on a forested mountain area of Suchá valley in the Hight Tatra mountains (Slovakia) and also in the urban environment of Castle Hill in Bratislava (Slovakia) with urban greenery. We compare the tool with the r.sun module of GRASS GIS and the Area Solar Radiation tool of ArcGIS using point-cloud data generated from the digital-terrain model of Kamenistá valley in High Tatra mountains in Slovakia. The results suggest a higher detail of the model in rugged terrain and comparable results on smooth surfaces when considering its purpose as a 3D modeling tool. The performance is tested using different hardware and input data. The processing times are less than 8 min, and 8 GB of memory is used with 4 to 16 core processors and point clouds larger than 100,000 points. The tool is, therefore, easily usable on common computers.
ISSN:1996-1073