Modeling of Micro Level Solar Radiation Using High Resolution Topographic Data through Remote Sensing and GIS

Abstract

In the current climate change scenario every nation is looking forward to taking control of their greenhouse emissions as a mitigation measure. Rapid exploitation of renewable energy and energy competence has culminated in significant energy safety and self-reliance for the fossil fuel importing countries, apart from climate change mitigation and economic benefits. Availability of solar radiation data is essential in order to evaluate the potential of renewable energy options such as photovoltaic power generation capability in a developing economy like Papua New Guinea. Installation of roof top solar panels can easily generate electricity without affecting the environment. So this research is an initiation to identify potential roof-tops for installation of solar panel. Therefore a micro level solar radiation modeling is attempted using high resolution topographic database for four spatial days and four different months, like March, June, September and December. ArcGIS spatial analyst, model builder and raster calculator tools are used to prepare solar radiation database through a GIS-based solar radiation model. Different essential parameters like latitude, elevation, slope and aspect, viewshed, sky map, sun map and atmospheric condition in terms of aerosol content induced transmitivity are taken into account for micro level solar radiation modeling. The modeled output data set represents global radiation or total amount of incoming solar insolation in kilo watts per square meter (Kw/m2/day) calculated for pixel-by-pixel of the input surface. The resulted output database highlights average monthly global radiation of 5.34 KW/m2/day in the month of March, 4.00 KW/m2/day in June, 5.25 KW/m2/day in September and 5.15 KW/m2/day in December. As expected in a country of southern hemisphere, the output map indicates higher solar radiation in the north facing roof of buildings than other parts of the roof as well as the road and open area. Shaded zones can be easily identified as no direct solar radiation is available over those places. With the help of the expected energy output computed rationally, such type of study can be useful for identifying optimal sites for roof-mounted solar panels for captive electricity generation.