22.0 Energy Tradeoffs

Frank R. Leslie, B. S. E. E., M. S. Space Technology, LS IEEE

4/15/2010, Rev. 2.0

fleslie @fit.edu; (321) 674-7377

www.fit.edu/~fleslie

In Other News . . .

Crude oil continues at ~$86/bblSouthwest Windpower will use 3Tier wind

mapping below

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22 Overview: Trade Studies

Trade studies provide decision-making information as to selection of choices

The selection of parameters with which to make the choice requires thought and a source of reliable data

There is often a tendency to judge the answer as “wrong” if it disagrees with the prejudged answer!

Following are a few examples, but there are many more approaches not covered here; search for “systems engineering methodologies” to find others

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22.0 Generic Trades in Energy

Energy trade-offs are required to make rational large-dollar decisions

PV is expensive (~$3.00 per watt for hardware + ~$5 per watt for shipping and installation = ~$8 per watt) compared to wind energy ($1.50 per watt for hardware + $5 per watt for installation = $6.50 per watt total)

Are Compact Fluorescent Lamps (CFLs) better to use?

Ref.: www.freefoto.com/pictures/general/ windfarm/index.asp?i=2

Ref.: www.energy.ca.gov/edu

cation/story/story-images/solar.jpeg

Photo of FPL’s Cape Canaveral Plant by F. Leslie, 2001

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22.1 How do we trade off choices?

Usually, we want the “best” result for the least cost

So “all” we have to do is define a “best” score and then compute $/score points! Oh . . . . sometimes that’s hard!

What does “best” mean anyway?What is “good”? What is “good

enough”?What is “nonpolluting”?What is “clean”? What is “green”?

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22.1 How do we decide on “best”? If it’s a simple choice like buying gasoline

The usual or typical price is known for stationsOur car should run “without complaint”, and the

gasoline shouldn’t cause noticeable service problems

Gasoline is “almost” a commodity (“special” additives/ dyes!)

Price per gallon is the comparison for most of us There may be other nongasoline factors

Where the station is located (don’t drive far away)Convenience of paying at the pump (slide that

card!)Traffic and getting back on the roadCompany is accused of ignoring social justice in

South America or Africa (Nigerian Ken Sara-Wiwa) If any of these items are too inconvenient or troubling,

we may buy more expensive gasoline elsewhere

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22.1 Leslie’s “Best” Restaurant Rule

The food is tasty, and the prices are low (or at least not “high” --- a reference to artificial intelligence fuzzy logic)

Look for a police car, fire truck, or ambulance outsideUsually means they’re eating there (as

opposed to business --- if flashing red lights are off!)

They know all the restaurants around town that they like and don’t like, and they eat out daily

The food is usually good and doesn’t cost much

The marginal utility between a “fine cuisine” restaurant and a local “family” restaurant is small

Presence of “locals” there indicates they believe they usually get good value for their money

(This gratuitous aside brought to you without extra charge)

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22.2 Tradeoff Matrices

Tradeoff matrices describe key attributes for various choices; a common systems engineering tool

There are four main attribute categories: performance, cost, schedule, and riskThere should be approximately equal numbers of

each attributeThese scores are also known as “Figures of Merit”The attributes should be measured so higher

numbers indicate “better” --- high scorers wantedA combination of these FOMs is necessary to get the

“one juicy number” that summarizes/ranks the results

A spreadsheet is nearly perfect for this work

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Trade-off ComparisonWind vs. Solar Choices

4/14/2003Frank R. Leslie

Constraints:1000 watts/day on average, wind under 15 mph 70% of time, bright sun <50 of time, etc

Attributes

Relative Importance Weighting,

%

Wind Power

Parameter

Wind Power Scaling

Wind Power Option Score

Solar Power

Parameter

Solar Power Scaling

Solar Power Option Score Comments

A 15 40 1.50 897.2 30 2.00 900.0B 20 15 4.00 1200.0 14 4.29 1200.2C 30 10 6.00 1800.0 9 6.67 1800.0D 10 9 6.63 597.0 10 6.00 600.2E 15 190 0.32 899.3 210 0.29 900.0F 10 30 2.00 600.0 25 2.39 597.7

0 20 10.00 0.0 0.00.0 0.0

Total Weighted Score 100 5993.5 5998.2

Cost [dollars] 5,000$ 20,000$ -0.08% % Difference re average

Choose either

Cost/Score [$/point] 0.834 3.33-119.95% % Difference re average

Choose Wind Power

Wind Power Solar Power

22.2.1 Weighted Scoring Technique

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22.2.2 Trade Matrix Formula

Attributes

Relative Importance

Weighting, %

Wind Power

ParameterWind Power

ScalingWind Power Option

ScoreSolar Power Parameter Solar Power Scaling

Solar Power Option Score

A 15 40 =1.6*10/10.7 =$B12*C12*D12 30 2 =$B12*F12*G12B 20 15 4 =$B13*C13*D13 14 =14/2.3*10/14.2 =$B13*F13*G13C 30 10 6 =$B14*C14*D14 9 =9/1.5*10/9 =$B14*F14*G14D 10 9 =6.7*10/10.1 =$B15*C15*D15 10 =10/1.7*10/9.8 =$B15*F15*G15E 15 190 =0.325*10/10.3 =$B16*C16*D16 210 =210/35/21 =$B16*F16*G16F 10 30 2 =$B17*C17*D17 25 =25/16.7/6.2*10*10/10.2*1.01=$B17*F17*G17

0 20 10 =$B18*C18*D18 =$B18*F18*G18=$B19*C19*D19 =$B19*F19*G19

Total Weighted Score=SUM(B12:B19) =SUM(E12:E19) =SUM(H12:H19)

Cost [dollars] 5000 20000=(E20-H20)/AVERAGE(E20,H20)

Choose

Cost/Score [$/point] =E21/E20 =H21/H20=(E24-H24)/AVERAGE(E24,H24)

Choose

Wind Power Solar Power

Comments

% Difference re average

=+IF(ABS(H22)<0.05,"either",IF(H22>0,C10,F10))

% Difference re average

=+IF(ABS(H25)<0.05,"either",IF(H22>0,F10,C10))

22.3 Difficulties of Selection

Some specifications are available to provide necessary informationThese “specs” can be entered in the

spreadsheet, and a conversion factor developed to change the spec to a score

The various scores are then weighted to indicate the relative importance

The sum of the weighted scores yields a score that indicates the relative worth of the choice

The relative difference of the scores may be trivial, indicating that one is not really better than the other choice; take your pick

A significant difference (at the 95% confidence level) may point to selecting one choice over the other

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22.3 Value of a Recounted Vote

From www.sie.arizona.edu/syseng

22.4 Ranking by “Somehow”

Ranking from the best option down to worst sometimes produces focus without specific quantification

This approach can suggest two or three choices for extensive examination by the priority thus given

The ranking may be done by majority voting of a panel of “experts”Each person may vote for one to all of the projects

If a person likes only one, s/he votes for only that one

If s/he likes two of them, s/he votes for bothThe total of the votes for each alternative then

immediately indicates the preferred ranking by the group as a whole without the expense of re-voting (IEEE elects its next president this way)

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22.4 Ranking through Pairing

Compare pair-wise to find a predominance; point to the best of each pair choice; add/subtract to find net preference for each

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Option A: 3-2 = +1 (for orange area)

Option B: 3-2 = +2

Option C: +2+3 = +5

Option D: 2-3 = -1

Option E: 3-2 = +1

Option F: 0-5 = -5

22.5 Social Factors and Optimization

There are often difficult-to-quantify aspects like beauty of the site, attractiveness, pure “viewscape”, or sound levels that are personal impressions, philosophy

The optimization of the site to make it attractive to the public can be a major factor in gaining approval

Involving the public in preliminary stages in meetings (charrettes) often can assist in final decisions and provide data to advocate your position

Those strongly concerned one way or the other will have come there, thus their opinions outweigh those who didn’t show up (just like in election voting)Should presidential elections be simplified to simply

getting donations to go to the treasury? Most $ wins!

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22 Conclusion: Trades

Renewable energy faces the same types of problems that affect other areas of daily livingNecessary to get permission to do something

different than what is codified in law or local ordinances

Requires convincing the public or government officials that the project is not a public nuisance and will be beneficial to the community

Trade studies that produce a well-written report documenting the situation, goals, choices, and selections may help to sway those with the power to approve or disapprove your proposal Example: Campus Sustainability

Practice these trade studies on small projects to be prepared to do the large projects well

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Olin Engineering Complex 4.7 kW Solar PV Roof Array

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Questions?

References: Books

Boyle, Godfrey. Renewable Energy, Second Edition. Oxford: Oxford University Press, 2004, ISBN 0-19-26178-4. (my preferred text)

Brower, Michael. Cool Energy. Cambridge MA: The MIT Press, 1992. 0-262-02349-0, TJ807.9.U6B76, 333.79’4’0973.

Duffie, John and William A. Beckman. Solar Engineering of Thermal Processes. NY: John Wiley & Sons, Inc., 920 pp., 1991

Gipe, Paul. Wind Energy for Home & Business. White River Junction, VT: Chelsea Green Pub. Co., 1993. 0-930031-64-4, TJ820.G57, 621.4’5

Patel, Mukund R. Wind and Solar Power Systems. Boca Raton: CRC Press, 1999, 351 pp. ISBN 0-8493-1605-7, TK1541.P38 1999, 621.31’2136

Sørensen, Bent. Renewable Energy, Second Edition. San Diego: Academic Press, 2000, 911 pp. ISBN 0-12-656152-4.

Tester, Jefferson W. , Elisabeth M. Drake, Michael J. Driscoll, Michael W. Golay and William A. PetersSustainable Energy Choosing Among Options. Boston: MIT Press, 870 pp. July 2005 ISBN-10:0-262-20153-4

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References: Websites, etc.

http://www.ite.org/traffic/seminar/htmlseminar/session7/sld021.htm The charrette process of public involvementhttp://www.sei.cmu.edu/publications/documents/02.reports/02tn010/02tn010.html#chap03http://www.incose.org.uk/incose99/tutt05.htm Tradeoff analyseshttp://tucson.sie.arizona.edu/sysengr/slides/tradeoff.ppt

http://www.geocities.com/SouthBeach/1285/syspaper.html Systems Engineering and Life: Designing, Developing, and Maintaining a Permanent Relationship

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awea-windnet@yahoogroups.com. Wind Energy elistawea-wind-home@yahoogroups.com. Wind energy home powersite elistgeothermal.marin.org/ on geothermal energymailto:energyresources@egroups.com rredc.nrel.gov/wind/pubs/atlas/maps/chap2/2-01m.html PNNL wind energy map of CONUS

windenergyexperimenter@yahoogroups.com. Elist for wind energy experimenterswww.dieoff.org. Site devoted to the decline of energy and effects upon populationwww.ferc.gov/ Federal Energy Regulatory Commissionwww.hawaii.gov/dbedt/ert/otec_hi.html#anchor349152 on OTEC systemstelosnet.com/wind/20th.htmlwww.google.com/search?q=%22renewable+energy+course%22solstice.crest.org/dataweb.usbr.gov/html/powerplant_selection.html

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