Background

Solar resource maps are an important component of establishing solar power grids. Local effects, such as the shading of trees, other buildings, or natural features can impact the total incoming solar radiation at the surface. Along urban pathways, trees offer shade and more comfortable environments for pedestrians and bike riders, e.g. Tucson's Loop. 

An early attempt at solar siting was done by Chave and Bahill (2008). Our project will be superior to the Chave and Bahill (2008) effort in numerous capacities: (1) increased resolution using up-to-date LiDAR data over the entire city basin, (2) the inclusion of object shading from local features, (3) calculation of indirect, direct, diffuse, and global radiation, as well as hourly radiation from GRASS r.sun.

Solar radiation also has an enormous impact on the heating of surfaces and thermal emittance as long wavelength heat. Albedo effects of surfaces can greatly impact the overall heat load requiring buildings to cool themselves (Simpson and McPherson 1997). An additional use of our models will be in locating roof and wall surfaces of homes where upgrades to surface reflectance or insulation might lead to increases in energy efficiency, and also help in the placement of gardens or shade trees. 

Regional maps of solar potential are at a broader scale which is not as applicable to individuals or city government. Our map will have a greater utility to the public in this regard. 

The project is like Google's Project Sunroof (full disclosure, the workflow for this project was designed in the ACIC 2014 course prior to the public release of Project Sunroof). The workflow we are developing is independent of the Google Project and uses different software and will be fully opensource.  

Deliverables

• GRASS r.sun solar radiation model outputs over the Tucson basin in an online map (e.g. GoogleMaps, OpenStreetMap) that also shows a time series of solar hours per day/month/year.
• The ability to query the surface for information about locations (like building and home roof footprints, yards for gardens, shading for paths and sidewalks) 
  • https://developers.google.com/earth-engine/charts_image_series_by_region?hl=en

Requirements

• Use CyVerse Wiki to maintain a complete lab workbook, documenting development cycles with as in-depth of notes as possible.
• All code to be hosted on Github.
• All code must adhere to OpenSource standards.  
• Develop a new workflow atop the executing Sol framework in a Map UI for use over the UA HPC (or NSF XSEDE platform).
• Recompile GRASS 7 (over current 6.4) onto the UA HPC (and OpenScienceGrid-XSEDE platform).
• Optimize r.sun for faster computation of surface models - possibly leveraging OpenCL and GPU/CUDA platforms if available. 

Developers

Nicholas Callahan

Laurence McCormick

Kyle Sedate

Timothy Wood

Client

Tyson L. Swetnam 

References

Simpson, J. R., & McPherson, E. G. (1997). The effects of roof albedo modification on cooling loads of scale model residences in Tucson, Arizona.Energy and Buildings, 25(2), 127-137.