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Final Application Portfolio Community Level Solar Energy System Daniel Marticello ESD.71 Fall 2010 1

Final Application Portfolio Community Level Solar Energy System

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Final Application Portfolio Community Level Solar Energy System. Daniel Marticello ESD.71 Fall 2010. Agenda. System Definition Model Structure Deterministic design results Flexible design results Conclusions and Reflections Next Steps. System Definition. The Vision - PowerPoint PPT Presentation

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Page 1: Final Application  Portfolio Community  Level Solar Energy System

Final Application Portfolio

 Community Level Solar Energy System

Daniel MarticelloESD.71

Fall 20101

Page 2: Final Application  Portfolio Community  Level Solar Energy System

Agenda

• System Definition• Model Structure• Deterministic design results• Flexible design results• Conclusions and Reflections• Next Steps

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Page 3: Final Application  Portfolio Community  Level Solar Energy System

System Definition

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The Vision•Community level system•Linked solar panels•Central energy storage•Negotiated off-peak rate

Exercise scope• Single home in Tucson AZ• Historic hourly solar data• 20-year timeframe

Page 4: Final Application  Portfolio Community  Level Solar Energy System

System Definition

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Solar panels• Initial install (5.52 kWh DC) [$17,000] • Additional increments are 0.92 kWh [~$2,500]

Flywheel energy storage• 5 kWh unit [$60,000]• Production systems from 5-25 kWh available [$60K-$120K]

Grid power• Peak and off-peak rates

“Green Power” Subsidy• $2.70/W DC• Reduced initial CAPEX by ~$15,000

Page 5: Final Application  Portfolio Community  Level Solar Energy System

Model Structure• Solar Panels– Output dependent on three factors• Size of the array: 24 panels• Solar insolation: Tucson AZ (representative hourly data)• Efficiency of conversion: 77% (system chosen for model)

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Page 6: Final Application  Portfolio Community  Level Solar Energy System

Model Structure• Home Power Consumption Profile– Energy consumption consists of two components• Variable load tied to amount of heating or cooling required• Base load that includes other usage (appliances, lighting, etc)• Used standard curves scaled to capture heating/cooling use

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Page 7: Final Application  Portfolio Community  Level Solar Energy System

Model Structure• Energy Storage (Flywheel storage system)– 20-year + lifetime (Not cycle limited)• Size based on static case (discharge cycle vs ops savings)• 5 kWh chosen to limit cost but get to flat peak in the curve

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175,200 Total data points• Hourly over 20 years

Page 8: Final Application  Portfolio Community  Level Solar Energy System

Model Structure• Grid Power– Price/kWh is source of uncertainty– Modeled as a random walk– Starting price of 10.3 cents/kWh

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5.00

5.50

6.00

6.50

7.00

7.50

8.00

8.50

9.00

9.50

10.00

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cents/KW

h

Year

Average  US Retail Electricity Price (1999 $)

Actuals 2000 AEO 2001 AEO 2002 AEO2003 AEO 2004 AEO 2005 AEO 2006 AEO2007 AEO 2008 AEO 2009 AEO(Ref) 2009 AEO(High)2009 AEO(low)

Page 9: Final Application  Portfolio Community  Level Solar Energy System

Simulation Decision Rule

If the current year’s grid provided electricity price is 10% or more above last year’s price, add an

additional 4 panels to each home’s array.• Reduce reliance on grid power as price increases• Justifies additional solar panel installation• Implemented using two different thresholds– 10% and 5% growth in electricity price year-to-year

• Discount rate of 10%

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Page 10: Final Application  Portfolio Community  Level Solar Energy System

Deterministic Design Results• $700-$1,500 saved in electricity costs per year • Savings are insufficient to overcome large CAPEX– Despite CAPEX subsidy of $2.70/W DC expense

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Summary of ResultsCAPEX $14,235.00Project NPV ($6,086.38) Loss

Year 0 1 2 3 4 5 6

Peak power ($/KWh) $0.10 $0.10 $0.11 $0.11 $0.11 $0.11 $0.11

Off-peak power ($/KWh) $0.07 $0.07 $0.07 $0.07 $0.07 $0.07 $0.07

Expand? 0 0 0 0 0 0

Capital Expense -$14,235.00

Ops Savings $799.92 $807.92 $816.00 $824.16 $832.40 $840.72 $849.13

Expansion Costs $0.00 $0.00 $0.00 $0.00 $0.00

Cash Flow -$13,435.08 $807.92 $816.00 $824.16 $832.40 $840.72 $849.13

DCF -$13,435.08 $734.47 $674.38 $619.20 $568.54 $522.02 $479.31

NPV -$6,086.38

Page 11: Final Application  Portfolio Community  Level Solar Energy System

Results (Uncertainty Included)

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Threshold Mean P90 P05 Std Dev10% w/ 1% trend ($6,087) ($5,821) ($6,351) $1575% w/ 2% trend ($5,446) ($5,013) ($5,796) $2605% w/ 3% trend ($4,379) ($3,123) ($5,160) $681

5.0% 90.0% 5.0%

-6351 -5821

-660

0-65

00-6

400-

6300

-620

0-61

00-6

000-

5900

-580

0-57

00-5

600-

5500

Values in $

0.0

0.2

0.4

0.6

0.8

1.0

NPV

NPV

Minimum-$6592.3105Maximum-$5594.3124Mean -$6087.0283Std Dev $157.2384Values 500

@RISK Student VersionFor Academic Use Only

5.0% 90.0% 5.0%

-5796 -5013

-620

0-60

00-5

800-

5600

-540

0-52

00-5

000-

4800

-460

0-44

00-4

200-

4000

Values in $

0.0

0.2

0.4

0.6

0.8

1.0

NPV

NPV

Minimum-$6029.0376Maximum-$4085.0788Mean -$5446.4247Std Dev $259.9598Values 500

@RISK Student VersionFor Academic Use Only

5.0% 90.0% 5.0%

-5160 -3123

-600

0-5

500

-500

0-4

500

-400

0-3

500

-300

0-2

500

-200

0

Values in $

0.0

0.2

0.4

0.6

0.8

1.0

NPV

NPV

Minimum-$5420.4292Maximum $586.7185Mean -$4379.2235Std Dev $680.5992Values 500

@RISK Student VersionFor Academic Use Only

10% DR1% growth rate

5% DR2% growth rate

5% DR3% growth rate

Page 12: Final Application  Portfolio Community  Level Solar Energy System

Conclusions• Large CAPEX makes system a financial loss– Large expense of flywheel– Historical growth rate of electricity price is small• Uncertaintly was too small to drive large change in outcome

• Potential game changers– Rapid increase in price of electricity– Incorporation of economy of scale (Demand response)• Scheduled energy use across multiple homes

– Carbon credits (system avoids ~6.8 metric tons/year)– Reduction in the cost of flyweel / other storage option

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Page 13: Final Application  Portfolio Community  Level Solar Energy System

Reflections• Assumptions are a key aspect of any model– Consumption profiles, uncertainty modeling, etc

• Screening models are valuable– Allows for more iterations and analysis

• Never stop looking for coding errors!Next Step

• Model that incorporates sharing across homes– Sharing of generating resources– Scheduling/deconfliction of energy consumption

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