Sol_BAR
Estimating solar potential for built structures in Zell am See
Introduction
Few other countries value the use of renewable energy like Austria. Well underway to becoming the totally dependent on green energy sources by 2030, only 23% of her energy requirements are currently being met by fossil fuel sources. Although, hydro and wind energy make up a large percentage of the renewable energy sources being used. Due to Austria's limited capacity for wind energy because of its natural geographic situation, solar energy is another popular option.
To implement solar energy, considerations have to be made for solar power indices like;
- Solar incidence
- Sunshine hours
- among others
Study Area
For my analysis, I would be accessing solar power potential for the Zell-am-See municipality city center, Salzburg.
In Zell-am-see, located 47.3235° N, 12.7969° E temperatures and daily hours of sunshine vary significantly during the winter and summer seasons, and so is the solar energy potential. I will be comparing these two different seasons.
The months with the most hours of sunshine on average is July, while the least is in December. Therefore, for seasonal comparison, I will be considering the months of July for Summer and December for Winter.
Focus Questions
- Estimate seasonal differences in solar energy potentials for buildings in Zell-am-see city center.
- Create a solar energy 'roof cadastre' for a community identifying best performing structures for solar potential
- Evaluating potential for solar powered public charging stations for tourists far away from their hotel rooms
In Conlclusion
This analysis represents an overview of how solar radiation can be estimated using ArcGIS pro. It is not exhaustive, but serves as an insight for further analysis and decision making. It is valuable for estimating solar energy output not only in Europe, but in other parts of the world that receive much more solar insolation and sunshine hours year round. For some of these, the solar energy potential is much underutilized, and although am interested in carrying out a similar analysis in such areas, for example my native Lagos, the unavailability of high resolution DSM hindered me. It would be much more rewarding for me to gain access to such important datasets that would allow further exploration in this regard.
