renewable energy optimization...

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Renewable Energy Optimization(REO)

Andy Walker

Principal Engineer

National Renewable Energy Laboratory

US DOE Federal Energy Management Program

[email protected]

Session

Date

mailto:[email protected]

Innovation for Our Energy Future

REO Team

Andy Walker, PI

Billy Roberts, GIS

Claire Kreycik, Incentives

Grace Griego, Reports

Chris Helm, Software Development

Dan Billelo, Donna Heimiller

Kate Anderson, Instructor


Purpose of REO

To identify and prioritize RE Project Opportunities

To estimate magnitude of cost and savings at each.

Project Pipeline:

Screening (REO)

Feasibility Studies

Procurement Specifications and Financing

Contract and administration

Acceptance testing and commissioning


Renewable Energy Technologies Photovoltaics

Daylighting

Biomass Heat/PowerConcentrating Solar Heat/Power

Solar Vent Air Preheat

Solar Water HeatingWind Power

Ground Source Heat Pump Landfill Gas


Best Mix of Renewable Energy Technologies Depends

on:

Renewable Energy Resources

Technology Characterization Cost ($/kW installed, O&M Cost)

Performance (efficiency)

Economic Parameters Discount rates

Fuel Escalation Rates

State, Utility and Federal Incentives

Mandates (Executive Order, Legislation)


Optimization Procedure

Site Data

Geographical Information System (GIS) Data

Incentive Data from DSIREUSA.ORG

PV SVPWind DaylightingSWH CSP Biomass

Dispatch Algorithm

Life Cycle Cost

Technology Characteristics.

Optimization


Site Information

Building name

Location

Square Footage

Number of Floors

Use and cost of utilities

Ventilation Rates

Lighting Levels

Hot Water Use


Renewable Energy Resources

Geographical Information System (GIS)

Datasets

NREL Datasets:

solar radiation 10x10 km grid

• Horizontal, South-facing vertical, tilt=latitude

Wind Energy 200mx1000m grid

Biomass Resources

Illuminance for Daylighting

Temperature and Heating Degree Days

Purchased Datasets

utility rates (wholesale/retail) for each service territory and customer class (residential, industrial,commercial) (Platts)

State and utility incentives and utility policy (from www.DSIREUSA.org)

City Cost Adjustments (RS Means & Co.)

Location Independent

Installed Hardware Costs from NREL technology databook

Economic Parameters (discount rate, inflation rate)


Example of NREL GIS Data

Wind Energy in vicinity of Fairfield CA


Technology Characteristics

Heuristic Models

Cost

(Size, m2)*(Unit Cost, $/m2)

Performance

(Size, m2)*(Resource, kWh/m2)*(efficiency)


Technology Characteristics: Photovoltaics

Jesse Dean, NREL, 2009

Initial Cost $/kW

7.0386 coefficient of cost curve

(0.0240) exponent of kw size in cost curve

$5.00 minimum cost

O$M 0.006 $/kWh Renewable Energy Technology Characterizations, EPRI TR-109496, 1997.C185

BOS Efficiency 0.77 PVWatts documentation www.nrel.gov

Acres per MW 6.5

Ref. Efficiency 0.168 % depends on module type

y = 7.0386x-0.024

R2 = 0.1529

0

1

2

3

4

5

6

7

8

9

10

0 200 400 600 800 1000 1200

PV size (KW)

Co

ist

pe

r W

att

($/W

)


y = 10605x-0.2182

R2 = 0.9506

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

0 500 1000 1500 2000 2500

Wind Project Size (kW)

Win

d P

roje

ct

Co

st

($)

Characteristics of Wind Power Technology

Wind Turbine Efficiency 35%

Capital Cost $1,528 $/m2 swept area

O&M Cost 7.9 $/year/kW

Power/Area 0.46 kW/m2

Capital Cost 3300 $/kW

Wind cost and performance data from “Forces Behind Wind Power.” Louise Guey-Lee http://www.eia.doe.gov/cneaf/solar.renewables/rea_issues/wind.html, 2/2001. PG&E Available Funding and Program Statistics (updated 06/05/07) http://www.pge.com/suppliers_purchasing/new_generator/incentive/available_funding_and_program_statistics.html

Tower Height 2.5 times blade length, m

Wind Shear Exponent 0.115

acres per MW 60

Wind Turbine Efficiency 28%

Wind Speed Turbine Rated at 15 m/s

Capital Cost $10,605 $/kW

-0.2182

O&M Cost 7.9 $/year/kW

Minimum Capital Cost 2000 $/kW

Maximum Capital Cost 11000 $/kW

Technology

Characteristics:

Wind Power


Technology Characteristics:

Solar Water Heating

Efficiency: Craig Christensen and Greg Barker, NREL Cost: RS Means & Co.

SDHW Efficiency 0.4

Cost 866.41 $/sf

-0.2673

250

O&M Cost 0.005 % of initial cost

Aux efficiency 0.8

Building Type Warehouse Area (sf)Office Area (sf) Laboratory (sf) Workshop (sf)All Other Area (sf)

Hot Water Percent of

Energy Use 5.22% 8.95% 15.00% 40.38% 8.00%

y = 866.41x-0.2673

R2 = 0.9989

0

100

200

300

0 2000 4000 6000 8000 10000 12000

Size (ft2)

Co

st

($/s

f)



Solar Ventilation Air Preheat

Cost: Conserval Engineering

Flow Rate: Chuck Kutscher, NREL

Material Cost $11.40 /sf

Installation Cost $12.00 /sf

Other $4.00 /sf

Initial Cost 27.4 $/sf

O&M Cost 0

Flow Rate 4 CFM/sf

Warehouse

Area (sf)

Office Area

(sf)

Laborator

y (sf)

Worksho

p (sf)

All Other

Area (sf)

Ventilation Rate (cfm/sf) 0.1 0.34 1 1 0.34



Concentrating Solar Heat/Power

http://www.nrel.gov/csp/troughnet/pdfs/3516.pdf

Hx= heat exchanger

Solar Thermal cost 73 $/sf

O&M cost $0.127 $/therm/year

Efficiency 50.60%

Cost of thermal storage $1,465 $/therm

Cogen Cost 1650 $/kW

cogen Efficiency 18.98%

Boiler Capacity Factor 85.00%

Hx effectiveness 70.00%

Round trip storage effciency 80.00%


Technology Characterization

Biomass Heat and Electricity

0A biodiesel combustion with conventional steam cycle

Boiler Cost intercept 400000 $/MBH

Cogen Cost 1650 $/kW

Fuel Storage and Handling 250000 $/MBH

Boiler Efficiency 0.75

Cogen Efficiency 0.3

Boiler Capacity Factor 0.85

Hx effectiveness 0.7

avoided cost on-site waste 0 $/ton

fixed cost per ton purchased fuel 20 $/ton

trucking cost 0.1 $/sq mile/ton

Boiler O&M Cost 5000 $/yr/Mmbtuh

Cogen O&M Cost 270 $/kW/year

Cost of Biomass Operator $/year 0 $/year

y = 400000e-0.0739x

R2 = 0.8715

$0

$50,000

$100,000

$150,000

$200,000

$250,000

$300,000

$350,000

$400,000

$450,000

0 5 10 15 20 25 30

Biomass Plant Size (MBtu/h)

Bio

mass P

lan

t C

ost

($/M

btu

)

Hx= heat exchanger


Technology

Characteristics:

Daylighting

skylight transmittance 0.7

lightwell transmittance 0.5

Coefficient of Utilization Daylight 0.55

Coefficient of Utilization Elec Light 0.55

Luminous Efficacy Elec Light 100 lumens/watt

Roof U-value 0.1 btu/hr/F

Skylight Uvalue 0.5 btu/hr/F

Cooling COP 3.5

Heating Efficiency 0.8

Skylight Cost 25 $/sf

Controls cost 0.25 $/sf floor areaCOP= coefficient of performance


Comparison of TEAM REO and Site Visit Reports for DOE Sites


Integration of multiple projects…

kWh from utility = kWh load – kWh renewables

kWh load

kWh renewables

kWh from utility


Integration of multiple projects…

kWhfrom utility= kWload (hload-hrenewables)

kWhto utility= (kWrenewables – kWload) hrenewables

kW load kW renewables

h loadh renewables


Two approaches to integration:

Time Series. Identify state of system at each time step, and step through time

series (8,760 hours/year) to perform integration.

Eg: HOMER, SAM, IMBY, PVWatts, etc.

Polynomial Expansion: Identify states that system could be in and calculate

percentage of time system is in that state. Time period is arbitrary, currently

24 time periods used to represent year (January day, January night, February

day, etc etc.)

Eg. REO


Stochastic Integration of Renewable Energy Technologies by the method of Polynomial Expansion

(SIRET)

This simplified figure shows seven possible states the system could be in,

but the model actually has 128 states for seven technologies.


$10,000

$100,000

$1,000,000

$10,000,000

$10,000 $100,000 $1,000,000 $10,000,000

Hourly Simulation REO

CO Commercial $655,076 $614,862

CO Industrial $5,158,624 $5,870,856

CO Residential $62,117 $49,463

WA Commercial $460,039 $568,455

WA Industrial $3,149,595 $4,533,277

WA Residential $53,587 $62,304

AZ Commercial $555,003 $522,448

AZ Industrial $4,469,720 $4,891,129

AZ Residential $53,567 $41,256

Compare/Contrast with Hourly Simulation

Comparison of Annual Average and Hourly Simulation in Renewable Energy Technology System Sizing

Christine L. Lee, University of Colorado at Boulder, 2009

REO

Simulation

Life Cycle Cost ($)


Optimization Problem

Determine the least cost

combination of renewable

energy technologies for a

facility

Objective: Minimize Life Cycle Cost ($)

Variables: Size of Each Technology

Constraints: limited only by the imagination


Objective Function of Optimization:

Life Cycle Cost

Minimize Life Cycle Cost: Sum of 25 years (or 40) of cash flows

• Initial costs minus any rebates, tax credits, etc.

• Electric, Gas, and Biomass Fuel Costs escalated at NIST rates

• Operation and Maintenance Costs escalated at general inflation

• Production Incentives

• Accelerated Depreciation

Future costs are discounted to present value based on discount rate


Objective Function

Other possible objective functions:

Maximize renewable energy delivery under constraint of same life cycle

cost

Minimize initial cost under constraint of percent carbon reduction.


Variables in the Optimization

1. kW of photovoltaics

2. kW of wind power

3. Sf of solar water heating

4. Sf of solar ventilation air preheating

5. Sf of solar parabolic trough collectors

6. Thermal storage (therms)

7. kW of solar thermal electric cogeneration

8. Mbtu of biomass gasifier capacity

9. kW of biomass gasifier cogeneration

10. Ft3 of biomass anaerobic digester

11. kW of biomass anaerobic digester cogeneration

12. Percent ceiling area skylights for daylighting

13. MCF of landfill gas collection system

14. kW of landfill gas cogeneration

15. Tons of ground source heat pump capacity


Constraints on the Optimization

No Constraints: just minimize life cycle cost

Examples of Constraints:

% Renewables Goal

• 3.75% renewable energy (GSA)

• 15% renewable energy (Anheuser Busch)

Net Zero Goal

• 100% net renewable energy, net annual basis

• Frito Lay Casa Grande; National Zoo; USCG HI; San Nicolas Island

Initial Investment Constraint

Land area Constraint

Reliability Constraint > 99.9999% (future work)


Completed REO Analyses

Multiple Buildings at one site:

Town of Greensburg, KS

National Zoo, DC

High School in Sun Valley, ID

San Nicolas Island, CA

DOE Waste Isolation Pilot Plant, NM

DOE Savannah River Plant SC

Pacific Missile Range Facility, HI

Presidio of San Francisco CA

Multiple Sites:

7 Frito Lay North America plants

62 Anheuser Busch facilities

8 Agricultural Research Stations in TX

31 DOE Laboratories

85 Air Force Bases

121 GSA Land Ports of Entry

32 DHS Land Ports of Entry

3 USCG Bases


REO Example: Frito Lay North America

Objective: Minimize Life Cycle Cost

Constraints: None

Photovoltaics

Size (kW)

Wind

Capacity

(kW)

Solar Vent

Preheat

Area (ft2)

Solar

Thermal

Area (ft2)

Biomass

Boiler

Size (M

Btu/h)

Biomass

Cogeneration

Size (kW)

Daylighting

Office Utility

Skylight/Floor

Area Ratio

Daylighting

Warehouse

Skylight/Floor

Area Ratio

Casa Grande Plant 189 408 5460 218727 7 614 2.200% 2.088%

Frankfort Core Plant 0 0 8962 0 28 0 1.760% 0.920%

Jonesboro Plant 0 3107 13098 469623 44 3180 4.896% 3.647%

Kern Plant 977 970 10187 900370 35 3101 3.352% 1.849%

Modesto Plant 100 831 10373 289181 27 406 6.031% 3.248%

Perry (GA) Plant 0 0 15030 0 59 5027 9.465% 4.630%

Topeka Plant 0 0 10963 0 23 0 2.878% 1.048%




Constraints: None

0

200000

400000

600000

800000

1000000

1200000

Plant

#1 Bas

ecas

e

Plant

#1 RE C

ase

Plant

#2 Bas

ecas

e

Plant

#2 RE C

ase

Plant

#3 Bas

ecas

e

Plant

#3 RE C

ase

Plant

#4 Bas

eCas

e

Plant

#4 RE C

ase

Plant

$5 Bas

ecas

e

Plant

#5 RE C

ase

Plant

#6 B

asec

ase

Plant

#6 RE C

ase

Plant

#7 Bas

ecas

e

Plant

#7 RE C

ase

An

nu

al

En

erg

y (

Mb

tu)

Electric (Mbtu) Natural Gas (Mbtu) Other Fuel (Mbtu)

Photovoltaics (Mbtu) Wind (Mbtu) Solar Vent Preheat (Mbtu)

Solar Themal (Mbtu) Biomass (Mbtu) Daylighting (Mbtu)


Frito Lay North America

Solar Thermal at Sunchips Plant Modesto CA




Constraint: 100% renewables (Net Zero)

0

200000

400000

600000

800000

1000000

1200000

Plant

#1 Bas

ecas

e

Plant

#1 Net

Zero

Plant

#2 Bas

ecas

e

Plant

#2 Net

Zero

Plant

#3 Bas

ecas

e

Plant

#3 Net

Zero

Plant

#4 Bas

eCas

e

Plant

#4 Net

Zero

Plant

#5 Bas

ecas

e

Plant

#5 Net

Zero

Plant

#6 Bas

ecas

e

Plant

#6 Net

Zero

Plant

#7

Plant

#7 Net

Zero

An

nu

al

En

erg

y (

Mb

tu)

Electric (Mbtu) Natural Gas (Mbtu) Other Fuel (Mbtu)

Photovoltaics (Mbtu) Wind (Mbtu) Solar Vent Preheat (Mbtu)

Solar Themal (Mbtu) Biomass (Mbtu) Daylighting (Mbtu)


REO Example: Frito Lay Optimization for Seven Manufacturing

Plants. Constraint: Net Zero

Photovoltaics

Size (kW)

Wind

Capacity

(kW)

Solar Vent

Preheat

Area (ft2)

Solar

Thermal

Area (ft2)

Biomass

Boiler Size

(M Btu/h)

Biomass

Cogeneration

Size (kW)

Daylighting

Office Utility

Skylight/Floor

Area Ratio

Daylighting

Warehouse

Skylight/Floor

Area Ratio

Plant #1 200 491 5456 509196 19 1669 2.2% 2.1%

Plant #2 0 6187 8953 391987 87 3097 3.8% 2.0%

Plant #3 0 3107 13098 469621 44 3180 4.9% 3.6%

Plant #4 1011 1000 10213 1360535 78 4108 3.4% 1.8%

Plant #5 1003 998 10327 704140 44 3327 6.1% 3.4%

Plant #6 0 0 10322 1529609 74 6020 err err

Plant #7 0 3699 10802 673761 43 2193 3.3% 3.7%


REO Example: Net Zero Zoo

National Zoological Park (NZP) and Conservation Research Center (CRC), Washington DC

-40000

-20000

0

20000

40000

60000

80000

100000

120000

140000

160000

Bas

ecas

e

RE C

ase

An

nu

al E

ne

rgy

(M

btu

)

Daylighting (Mbtu)

Biomass (Mbtu)

Solar Themal (Mbtu)

Solar Water Heating

Solar Vent Preheat (Mbtu)

Wind (Mbtu)

Photovoltaics (Mbtu)

Other Fuel (Mbtu)

Natural Gas (Mbtu)

Electric (Mbtu)

Electric

generation

at CRC

Cancels

remaining

gas use at

NZP

Zoo Entrance

Tai Shan the Panda

http://en.wikipedia.org/wiki/Image:Washington_Zoo_entrance.jpg


USCG FacilityDiamond Head, HI

with incentives

Initial Cost for Renewable Energy Projects ($) $90,868

Annual Electric Savings (kWh/year) 39,074

Annual Cost Savings ($/year) $5,972

Simple Payback Period (years) 15.2

Rate of Return 7.0%

Percent Renewables 100%

Sizes of Each Technology:

Photovoltaics (kW) 14.6

Wind Energy (kW) 2.4

Solar Water Heating (sf) 137.8

Skylight Area (sf) 272.4


REO Example: Minimize Life Cycle Cost

US Navy San Nicolas Island CA

0

10000

20000

30000

40000

50000

60000

70000

80000

Basec

ase

RE C

ase

with

bat

terie

s

RE C

ase

no b

atte

ries

An

nu

al E

ne

rgy

(M

btu

)

Daylighting (Mbtu)

Anaerobic Digester (Mbtu)

Biomass Gasifier (Mbtu)

Biomass Combustion

(Mbtu)

Solar Themal (Mbtu)

Solar Water Heating

Solar Vent Preheat (Mbtu)

Wind (Mbtu)

Photovoltaics (Mbtu)

JP5 Fuel (Mbtu)


119 Land Ports of Entry

01000

2000

3000

4000

5000

Dalton C

ache,

AK

Alc

an,

AK

Skagw

ay,

AK

Lukevi

lle,

AZ

Nogale

s,

AZ

Sasabe,

AZ

Dougla

s,

AZ

San L

uis

, A

ZN

aco,

AZ

)San L

uis

AZ (

not

built

yet

Nogale

s,

AZ

Cale

xic

o W

est,

CA

San Y

sid

ro,

CA

Andra

de,

CA

Ota

y M

esa,

CA

Tecate

, C

AC

ale

xic

o,

CA

Eastp

ort

, ID

Port

hill

, ID

Ferr

y P

oin

t, M

EC

oburn

Gore

, M

EF

ort

Fairfie

ld,

ME

Houlton,

ME

Jackm

an,

ME

Lim

esto

ne,

ME

Orient,

ME

Vanceboro

, M

EV

anB

ure

n,

ME

Mill

tow

n M

ES

t. F

rancis

, M

EM

adaw

aska,

ME

Fort

Kent,

ME

St.

Fra

ncis

, M

ED

etr

oit C

arg

o,

MI

Intl B

ridge,

MI

Am

b.

Bridge,

MI

Gra

nd P

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age,

MN

Noyes,

MN

Roseau,

MN

Intl F

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, M

NB

audett

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MN

Chie

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TP

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MT

Raym

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MT

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MT

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MT

Turn

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MT

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bro

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ND

Dunseith,

ND

Port

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DS

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ND

Colu

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NM

Santa

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NM

Ale

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, N

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NY

Massena,

NY

Fort

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NY

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Falls

, N

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BS

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TX

Colu

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, TX

Conve

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TX

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TX

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Bridge o

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, TX

Eagle

Pass,

TX

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TX

Fort

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, TX

El P

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TX,

leased

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, TX

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s,

TX

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TX

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TX

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TX

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TX

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Pro

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, TX

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in,

TX (

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TX,

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DO

T,

TX,

leased

Derb

y L

ine,

VT

Nort

on,

VT

Beebe P

lain

, V

TA

lburg

Springs

, V

TN

ort

h T

roy V

TW

est

Berk

shire,V

TD

erb

y L

ine,

VT

Beecher

Falls

, V

TC

anaan,

VT

East

Ric

hfo

rd,

VT

Ric

hfo

rd,

VT

Alb

urg

, V

T,

join

t ow

ner

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hgate

Springs 1

, V

TH

ighgate

Springs 2

, V

TH

ighgate

Springs 3

, V

TB

lain

e,

WA

Danvi

lle,

WA

Laurier,

WA

Mata

line F

alls

. W

AO

rovi

lle,

WA

Poin

t R

obert

, W

AS

um

as,

WA

Bla

ine,

WA

Bla

ine,

WA

Kenneth

Ward

, W

A

An

nu

al R

en

ew

ab

le E

ne

rgy D

elive

ry (M

btu

)

Win

d

So

lar

Ve

nt

Pre

he

at

So

lar

Wa

ter

He

atin

g

So

lar

Th

erm

al

Bio

ma

ss G

asifie

r

An

ae

rob

ic

Dig

este

r (M

btu

)

Da

ylig

htin

g

Ph

oto

vo

lta

ics

Initial Cost for Renewable Energy Projects ($) $17,708,833

Annual Electric Savings (kWh/year) 18,956,969

Annual Gas/Fuel Savings (therms/year) 295,241

Annual Cost Savings ($/year) $1,993,263


Rate of Return 11.5%

Percent of Energy From Renewables 15%


New: Monthly REO (example)

Consider 2,200,000 sf office building, 12 floors

Washington DC Climate, Utility Rates, Incentives

Name

Annual Electric

Consumption

(kWh)

Annual Electric

Cost ($)

Annual Steam

Consumption

(therms)

Annual Steam

Cost ($/year)

Example Building 37,721,061 $5,933,523 587,611 $1,385,586

January 2,612,262 $410,909 67,932 $160,183

February 2,786,413 $438,303 61,139 $144,165

March 2,960,563 $465,697 54,346 $128,147

April 3,134,714 $493,091 47,552 $112,128

May 3,308,865 $520,484 40,759 $96,110

June 3,483,016 $547,878 33,966 $80,092

July 3,657,167 $575,272 27,173 $64,073

August 3,517,846 $553,357 37,363 $88,101

September 3,378,525 $531,442 44,156 $104,119

October 3,343,695 $525,963 50,949 $120,138

November 2,856,073 $449,260 57,742 $136,156

December 2,681,922 $421,866 64,535 $152,174


Photovoltaics Details

New: Monthly REO Example

PV rating

(kW)

PV Size

(ft2)

PV Initial Cost

($)

PV

Rebate

($)

PV

Production

Incentive

($/year)

PV State

Tax Credit

($)

PV Federal

Tax Credit

($)

PV Annual

Energy Delivery

(kWh/year)

Capacity

Factor, AC

(%)

PV Annual

Utility Cost

Savings ($)

PV Annual

O&M Cost

($/year)

PV Payback

Period

(years)

5168 330986 $35,502,811 $0.00 $0.00 $0.00 $0.00 6519921 18.7% $1,018,090 $39,120 36.3

Name

PV Annual

Energy Delivery

(kWh)

Capacity

Factor, AC

(%)

PV Annual

Utility Cost

Savings ($)

PV Annual

O&M Cost ($)

January 349552 11.8% $50,531 $2,097

February 365985 13.7% $57,569 $2,196

March 550295 18.6% $86,561 $3,302

April 631689 22.0% $99,365 $3,790

May 726658 24.5% $114,303 $4,360

June 749342 26.2% $117,871 $4,496

July 753902 25.5% $118,589 $4,523

August 696935 23.5% $109,628 $4,182

September 569257 19.9% $89,544 $3,416

October 508163 17.2% $79,934 $3,049

November 330872 11.5% $51,934 $1,985

December 287270 9.7% $42,260 $1,724


0

2000

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18000

Janu

ary

Febr

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Mar

chApr

ilM

ay

June Ju

ly

Aug

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Sep

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Oct

ober

Nov

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Dec

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An

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rgy

(M

btu

)

Electric (Mbtu) Fuels (Mbtu) Photovoltaics (Mbtu)

Wind (Mbtu) Solar Vent Preheat (Mbtu) Solar Water Heating

Solar Thermal (Mbtu) Biomass Gasifier (Mbtu) Anaerobic Digester (Mbtu)

Daylighting (Mbtu) Landfill (Mbtu) Sold to Utility (Mbtu)

New: Monthly REO (example)

Monthly Loads and RE Resources


Monthly REO

Executive

Summary

Economic Summary

Initial Cost for Renewable Energy Projects ($) $51,082,533

Annual Electric Savings (kWh/year) 9,486,000

Annual Gas/Fuel Savings (therms/year) 188,492

Annual Cost Savings ($/year) $1,750,763


Rate of Return 6.8%

Percent Renewables 27.3%

Carbon Dioxide Savings (tons/year) 6,413

Life Cycle Savings ($) $30,544,543

Sizes of Each Technology:

Photovoltaics (kW) 5,168

Wind Energy (kW) 4,447

Solar Ventilation Air Preheat (sf) 26,985

Solar Water Heating (sf) 79,275

Solar Thermal Parabolic Trough (sf) 0

Thermal Storage (therms) 0

Solar Thermal Electric (kW) 0

Biomass Gasification Boiler (MBH) 0

Biomass Gasification Cogen (kW) 0

Biomass Pyrolysis Boiler (MBH) 0

Biomass Pyrolysis Cogen (kW) 0

Biomass Anaerobic Digester (ft3) 0

Biomass Anaerobic Digester Cogen (kW) 0

Skylight Area (sf) 2

Landfill Gas Collection Size (Mbtu/hr) 0

Landfill Gas Cogen (kW) 0

Ground Source Heat Pumps (tons) 0


“It's so much easier to

suggest solutions when you

don't know too much about

the problem.”

- Malcolm Forbes

Thank You!

Andy Walker

Senior Engineer

National Renewable Energy Laboratory

[email protected]

“Simplicity is quite

often the mark of

excellence”

-Allen Bennett, SMDC

mailto:[email protected]

renewable energy optimization...

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