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Supercomputing Challenge

Modeling the Efficiency of Alternative Resources

Team: 21

School: BOSQUE SCHOOL

Area of Science: Environmental Sciences


Interim: Problem Definition
With our energy crisis going on, we need to find ecologically friendly, alternative methods of producing power. Alternative resources, including wind, hydroelectric, solar, and geothermal energy among others, are more environmentally conscience than conventional means. If the country or even individual households were to set up solar panels, or windmills, the amount of energy consumed would drop significantly. We therefore are trying to show the benefits of alternative methods of energy production.

Thusly, our project is to model the efficiency of alternative energy resources, to determine which is more beneficial. Contrary to our proposal, we decided to first focus on solar power, being as we found more information on this type of energy production. We are modeling this method in C++. We settled on modeling the cost efficiency of these methods, as that seems to be the most accurate, and most influential factor of energy today.

Problem Solution
Our plan to solve this problem is to make a series of small, computational models on C++ to determine the cost efficiency of some of the different alternative resources. We are doing this on an individual household scale, meaning how cost efficient it is for one household to use these alternative resources. We are looking at cost efficiency over time, so we will look at consumption changes through different seasons, as well as possible inflation in energy prices. These models will use the same components, so we will be able to compare them accurately. We are hoping to eventually scale these models up to a nationwide scale, so we can compare hydroelectric power, and other, larger forms of renewable energy.

Progress to Date
Thus far we have a basic working model of the cost efficiency of a household run bysolar power. All of our amounts are linear however, and we are now working on adding inflation prices, and daylight differences into the equation. Our model as of now shows that it will take close to 17 years to pay off a 1000 watt solar cell, with the price of a kilowatt hour being $0.08. We figured this looking at the average cost of a solar cell ($7 - $9 per watt), assuming that our solar cell was $8 per watt, and the solar cell produces 10 kilowatts hours of power (an average of 10 hours of daylight per day) at 8 cents a kilowatt hour. This means the household pays off 80 cents a day, or 292 dollars per year. At this constant rate, it will take 17 years to pay off the initial costs (that’s not looking at maintenance costs). If the solar cell is increased to 2000 watts, it will take 35 years and so forth. However we expect these numbers to change as we add an inflation rate of the price of power, as well as differences in the amount of power produced in different parts of the year.

Our biggest hindrance this far has been finding a mentor. We have contacted PNM, Northern Arizona Wind and Sun, as well as the New Mexico Solar Energy Association, but have failed to get a response. We are hoping that in the near future, we will be able to contact someone who can mentor us. Presently, we are relying exclusively on our own research for these models.

Expected Results
We expect our results to show that renewable resources are more cost effective than traditional methods over time. Looking at our current data, we believe wind power will prove most efficient; however these results are inconclusive as our models are subject to change. As of now, we really can’t have any idea of what our results show. Our team needs to complete more research, and find a mentor with knowledge of sustainability and power production to be able to better predict our results.

Works Cited
Unknown, author."Solar System Costs." Solar System Basics. Febuary 23, 2006. Northern Arizona Wind and Sun. 27 Nov. 2006 .

"Frequently Asked Questions." About Renewable Energy. American Solar Energy Society. 1 Dec. 2006 .

"Operation and Wind Costs for Wind Turbines." wind power. May 12, 2003. Danish Wind Industry Association. 6 Dec. 2006 .

"Sustainability Report 2005." My Environment. 2005. Power New Mexico. 4 Dec. 2006 .

"Solar Power." Alternative Energy Sources. University of Utah. 30 Nov. 2006 .


Team Members:

  Kelly Dickey
  Liv Maclake
  Danielle Rabold

Sponsoring Teacher: Thomas Allen

Mail the entire Team