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Estimating Olympia’s
potential for roof mounted
            photovoltaic's.




  http://science.nasa.gov/science-news/science-at-nasa/2002/solarcells/429,r:0,s:0
Motivation
 To provide clean energy to Olympia
 To test assumptions about P.V in the
  Northwest.
 Miles of empty roof’s
Do photovoltaic's have potential
inOlympia?


   Fastest growing energy technology
   Clean
   Dropping costs
   High energy incentives
   Better solar resource then Germany, the world leader in installed
    solar capacity.

   Questions: what makes for good potential?
   Roofspace
   Insolation
   Economics
Hypotheses:

   H1.a:

   H1.b:

   H1.c

   H1. null
Contribution
 Include screen shot (how do you take a
  screen shot?)
 Estimate 10% of each land type
  (residential, apartment, farm, industrial
  etc..)




Software augmented estimation
 Using the estimated power produced in
  10% of an areas buildings, find power
  density (w/m^2).
 Apply power density to the rest of the
  area.
 Olympia’s solar potential is the sum of its
  areas.




Power density
   Areaswith high potential power density
    will be the most economic.

   Wooded areas will be less economically
    feasible

   A significant fraction of Olympia's power
    may be met by P.V power.




Expected Outcomes

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Solarpresentation

  • 1. Estimating Olympia’s potential for roof mounted photovoltaic's. http://science.nasa.gov/science-news/science-at-nasa/2002/solarcells/429,r:0,s:0
  • 2. Motivation  To provide clean energy to Olympia  To test assumptions about P.V in the Northwest.  Miles of empty roof’s
  • 3. Do photovoltaic's have potential inOlympia?  Fastest growing energy technology  Clean  Dropping costs  High energy incentives  Better solar resource then Germany, the world leader in installed solar capacity.  Questions: what makes for good potential?  Roofspace  Insolation  Economics
  • 4. Hypotheses:  H1.a:  H1.b:  H1.c  H1. null
  • 6.  Include screen shot (how do you take a screen shot?)  Estimate 10% of each land type (residential, apartment, farm, industrial etc..) Software augmented estimation
  • 7.  Using the estimated power produced in 10% of an areas buildings, find power density (w/m^2).  Apply power density to the rest of the area.  Olympia’s solar potential is the sum of its areas. Power density
  • 8. Areaswith high potential power density will be the most economic.  Wooded areas will be less economically feasible  A significant fraction of Olympia's power may be met by P.V power. Expected Outcomes