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United States solar PV roof policy method

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Open-pv.png This page is part of an MTU graduate course MY5490/EE5490: Solar Photovoltaic Science and Engineering. Both the course documentation and the course generated content is open source. However, the course runs over Spring semesters during this time it is not open edit. Please leave comments using the discussion tab.



Introduction[edit]

Below is a working draft of the methods section of a communications paper regarding solar PV roof policy in the United States. Overall policy target is to federally mandate that all newly constructed federal buildings incorporate solar PV when feasible. It is also recommended that all existing state and federal buildings incorporate solar PV when feasible in the next 10-15 years. Additional "roof mandates" for residential and commercial buildings may be discussed, but the primary focus of this paper will be state and federal buildings.

Methods[edit]

Determining number of annual federal buildings constructed[edit]

  • Raw Number of State and Federal Buildings: The overall number of federal buildings can be found in the annual Federal Real Property Charts files. The United States General Services Administration (GSA) publishes an annual report detailing the number of federal buildings and their square footage. The number of buildings for listed FY2012 (fiscal year 2012) is 361,318. This number comprises of 306,166 owned buildings and 55,152 leased buildings.
  • If a policy requiring all new state and federal buildings to install solar PV when feasible is implemented, what is the number of annual buildings affected? This is an excellent question, and one I have yet to find an answer to. Finding the number of newly constructed federal buildings has not been easy. Because of this, I will be shifting my focus for how we can retroactively use Solar PV on existing buildings and structures to make federal buildings more efficient.
Ok -- but also quickly try to get a buildings per year of square foot per year, or take a subset and find out the year of construction and extrapolate. 
Important to consider gradual build out as being more likely scenario than an all up front retrofit - 
also harder, less optimal from and engineering standpoint and more costly than planning it in.
  • Additionally, the large governmental reports only breakdown Federal/State square footage by state, not the number of buildings. A method needs to be determined to estimate the potential roof square footage based on the given total square footage per state. The average square footage of a federal building was listed as 6,700 square feet in John Howards The Federal Commitment to Green Building: Experiences and Expectations
  • Residential: Average square footage: 1,971. Average number of stories: 1.31 (obviously we can't have 1.31 stories, most residential houses are one story, but to make our calculations more reasonable I'm going to use 1.5 so that the eventual usable roof area is not inflated. Data calculated from EIA. Additionally, the average pitch is 4/12, the industry standard and I will assume it is the average.
  • Using data and extrapolations from a EERE report, I will also be moving forward using the estimation that 2 million new homes are built each year in the U.S.
  • As far as federal square footage goes, it has remained fairly stagnant and for a good many years was decreasing. The trend line on the figure is only trending upward because for fiscal years 11 and 12, the square footage rose. Still have yet to find a reliable estimate of yearly additions. Retrofitting might be the only consideration other than using residential numbers to demonstrate a point.

Breaking down by state[edit]

  • Construct a table listing the number of new buildings constructed per state, the average solar flux in the state (can be found fairly accurately by using NREL solar prospector. Using the solar prospector map, click within a state and average the locations found (should be a more accurate way to outline specific region, query seems to fail). Solar flux/Ir radiance on the Solar Prospector is reported as an Annual DNI, with units of kWh/m^2/day,' where kWh is kilo-watt hours which is the unit of energy equal to 1000 watt hours, m^2 which is the unit area that the annual DNI is normalized to. Additionally, raw data can be crawled through on another NREL site found here. I ended up using data from the second source. Overall, it was harder than I thought to find a table of solar flux by state, I'm going to expand my Google Spreadsheet to include multiple tip angles and other variable so that others can easily and quickly have access to this info.
  • Current table can be found in a Google Spreadsheet.

Solar PV Energy Created[edit]

  • By knowing the number of new annual buildings created per state and estimating their potential installed capacity, an energy estimation can be calculated and simulated with RETSCREEN.

GHG Reduction Calculations[edit]

  • In turn, the estimated newly installed capacity figure can be used to determine the CO2 offset by determing the estimated kwH produced per year and analytically solving for the CO2 reduction based on taking that load off of the grid (i.e. since the solar panels are providing X number of kwH, the coal plant down the road doesn't have to pollute as much).
  • To do this, I still need to determine/find the average grid carbon densities per state. Or, to more conservatively estimate the CO2 savings, use the CO2/kwH for the most efficient power plant in the region. The value will be normalized to some CO2 value (in grams) per kWh.
  • Additionally, intrinsic cost of the manufacturing the solar PV modules will need to be taken into consideration.

Job Impacts[edit]

Cost[edit]

  • Determining cost of different types of PV installs per state. Different sources of PV modules (will impact the GHG estimation, Chinese modules higher upfront C02 cost)
  • Breakdown cost of using different types of modules from different primary manufacturers.
If you assume all flat roof mounted large arrays -- instead just do a sensitivity analysis starting with $5/W and going down to $0.50/W by $0.50/W increments

Negative Impacts[edit]

  • Will increase upfront cost of buildings. Cost per state can be found in the Google Spreadsheet
See info above about cost- dont use state averages as they are misleading - if the Gov did this all at once they would have bulk discount purchase power
Make assumption using a good ~reasonably efficient module - on W/m2 so you can calculate additional costs as a percentage of new construction costs