Abstract
This paper presents the development of an open source geographical information system (GIS) software module for mapping solar energy resources for urban areas. The main goal of this work is to demonstrate the potential use of the r.sun module, a component of GRASS software, in calculating real solar radiation for urban areas. Modelling of the spatial distribution of solar radiation is one of the program functions. The r.sun module is dedicated for that purpose; however, it can only generate the spatial distribution of potential solar radiation. To get the real solar radiation maps it is advisable to use meteorological data, that describe diminution of solar radiation caused by cloud cover. In order to facilitate the generation of maps a GRASS source code modification was made. As a result, the r.sun module used in this work generates the real spatial distribution of solar radiation. The results are shown to be comparable with solar radiation satellite data obtained from the HelioClim project.
Highlights
Nowadays, the demand for energy is growing very fast, but at the same time global energy resources are running out
Hofierka [8] presents a method for the assessment of photovoltaic potential in urban areas using an open source software GRASS (Geographic Resources Analysis Support System) and r.sun module dedicated to solar radiation estimation
It is possible to generate solar radiation maps in overcast conditions, but the user has to use coeff_bh and coeff_dh input raster maps defining the fraction of the respective clear-sky radiation reduced by atmospheric factors. These coefficients can be obtained from long-term meteorological measurements provided as raster maps with the spatial distribution of these coefficients separately for beam and diffuse radiation [9]
Summary
The demand for energy is growing very fast, but at the same time global energy resources are running out. Hofierka [8] presents a method for the assessment of photovoltaic potential in urban areas using an open source software GRASS (Geographic Resources Analysis Support System) and r.sun module dedicated to solar radiation estimation. He used a 3-D city model as input terrain data. It is possible to generate solar radiation maps in overcast conditions, but the user has to use coeff_bh and coeff_dh input raster maps defining the fraction of the respective clear-sky radiation reduced by atmospheric factors (e.g. cloudiness) These coefficients can be obtained from long-term meteorological measurements provided as raster maps with the spatial distribution of these coefficients separately for beam and diffuse radiation [9]. In this study the r.sun module modification has been developed to generate the spatial distribution of real solar radiation easier and faster by using the cloud cover parameter, which was calculated for Wroclaw city based on daily synops data obtained from Ogimet services [8] for the time period of 2007–2016
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