Sunshine, Taxes, and Maps

I’ve recently been looking at economic incentives for solar power in the U.S.  I thought I’d consider what incentives might encourage the installation of solar panels for different locations across the country.

First, let’s see how much sunshine different parts of the country get annually:

Click for better resolution
This plot is generated in R using the shapefile GIS data provided by the National Renewable Energy Laboratory (NREL) via the Open Energy Information (OpenEI) platform.  It is based off a model that takes input from 14,000+ solar radiation stations across the country.

Naturally, increased sunlight can provide more incentive to install solar panels.  However, that is only a small part of the story.

What happens when we recreate the above map, but measure the economic value of installing the solar panels due to:

Clearly, there’s quite a bit of information to coalesce.  To simplify things, I consider two scenarios:

The Residential Scenario:

Source: http://256.com/solar/ Used with permission
  • 20 sq. meters of solar panelling installed on a single family residence, unobstructed
  • Solar panels show a 10% energy conversion efficiency (reasonable, if low)
  • Installation costs $50,000
  • Home owners bear a tax rate of approximately 15%

The resulting gross payout of tax incentives and energy production (not subtracting the cost of installation on the residence) extrapolated over time, looks as follows:  (Be sure to click for the high resolution version)

Click for better resolution


In addition to the residential scenario above, I also considered a more commercial scenario, which involved a different set of state level tax incentives, and a few other assumptions.

The Commercial Scenario:

Source: http://schools-wikipedia.org/images/258/25899.jpg.htm Used with permission
  • 200 sq. meters of solar panelling installed on a business, unobstructed
  • Solar panels show a 10% energy conversion efficiency
  • Installation costs $500,000
  • Corporation bears a tax rate of approximately 30%

The resulting gross payout of tax incentives and energy production (not subtracting the cost of installation on the residence) extrapolated over time, looks as follows:  (Be sure to click for the high resolution version)

Click for better resolution

 

Naturally, there are a huge number of assumptions baked into these maps.  (Stable tax rates, typical weather, steady energy prices … the list goes on.)  Nevertheless, I think it’s interesting to see, at least according to the data I used, how tax write-offs start out dominating the state-to-state variation in payout.  But, after a few decades, solar potential begins playing a more critical role.

 

A few things I learned along the way:

  • I taught myself quite a bit about R in this little study.
  • Using industry standard tools for GIS for the first time (namely becoming familiar with the structure of a “shapefile”).  This was probably the most challenging part.
  • In dealing with tax incentives, the number of stipulations and caveats can be absolutely crushing.  I found the best way to deal with these were to simply hypothesize a couple of scenarios, and run with the results.

Questions and comments are welcome.

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