Modeling the Penetration of Wind Energy Into the U.S. Electric Market

Presentation to CNLS 26th Annual Conference

August 16, 2006

Walter Short, Nate Blair, Paul Denholm, Donna Heimiller

Contents

• Wind Energy in the U.S. Electric System

• Brief Description of the WinDS Model

• Results

• Issues

Wind Energy in the U.S. Electric System

• 9.1 GW of existing U.S. wind capacity (1%)

• 2.4 GW added in 2005– Incentivized by

• 1.9 cents/kWh federal production tax credit

• State mandates, e.g. Renewable Portfolio Standards

• Clean, renewable– Impeded by

• Transmission availability• System integration of a

variable resource• Recent rise in wind turbine

capital costs ($1600/kW)

For details about state-specific wind projects, see the links below.

Wind Resources

>5000 GW of onshore capacity>3000 GW of offshore capacity

The U.S. DOE EIA Uses its National Energy Modeling System to Project

Future Wind Energy Potential

– 13 large electric regions– No new transmission– No cost or limits on use of

transmission within regions– Can’t accurately capture

wind correlation between regions

– Wind considered a mature technology (1% learning rate on capital costs and capacity factors)

– Wind capacity value< 20%– Eliminates 91% of U.S.

wind resource base

0

10

20

30

40

50

60

70

80

90

2000 2005 2010 2015 2020 2025 2030

Win

d C

apac

ity

(GW

)

PTC 2015

CSA (S.139)

Hi RE

AEO2005 Ref

EIA’s NEMS Could Not Address Questions for the DOE Wind Research Program

• Access to and cost of transmission– Light wind close to the load or high speed wind far away?– How much wind can be transmitted on existing lines?– Will wind penetrate the market if it must cover the cost of

new transmission lines?– Will offshore wind close to seaboard loads penetrate?

• Resource Variability– How does wind capacity credit change with penetration?– How do ancillary service requirements increase with wind

market penetration– How much would dispersal of wind sites help?– Is on-site storage cost effective?

WinDS Model(Wind Deployment Systems Model)

A multi-regional, multi-time-period model of capacity expansion in the electric sector of the U.S.Designed to estimate market potential of wind energy in the U.S. for the next 20 – 50 years under different technology development and policy scenarios

WinDS Regions

Transmission in WinDS

General Characteristics of WinDS• Linear program cost minimization for each of 26 two-year

periods from 2000 to 2050

• Sixteen time slices in each year: 4 daily and 4 seasons

• 5 levels of regions – wind supply/demand, power control areas, RTOs, NERC areas, Interconnection areas

• Existing and new transmission lines

• 5 wind classes (3-7), onshore and offshore shallow and deep

• All major power technologies – hydro, gas CT, gas CC, 4 coal technologies, nuclear, gas/oil steam

• State-level incentives

• Fed by extensive GIS input data bases

• Stochastic treatment of wind resource variability – planning reserves, operating reserves, surplus wind

WinDS Logic FlowGIS

Wind resourcesConventional plant locationsTransmission lines

LP Optimizer

EIA – Electric loads, Fuel prices, Plant costs

Update LP coefficients

t=now

T= 2050?no

yes

t=t+2

Stop

∂ capacity credit/ ∂W∂ oper reserve/ ∂W∂ wind surplus/ ∂WRetirements

Minimize PV of CostsSubject to:Gens > Loads + lossess

Cap > Peak *(1+RM)Regional energy balances

Base Case Electricity Capacity

Base Case Capacity by Wind Class

Base Case Key Inputs• Wind R&D-driven

Cost/Performance improvements

• 8% wind learning rate

• 1.9 cent/kWh PTC through 2007

• No carbon caps/tax

• Gas prices

Class 5 Wind Resource

0200400600800

10001200

Cap

ital

Cost

($/

kW)

.

00.10.20.30.40.5

Cap

acit

y F

acto

r .

Natural Gas Price - Base Case

02468

10

2000 2010 2020 2030 2040 2050

$/M

MB

tu .

Source: AEO 2005, DOE/EIA

High Gas Prices Do Not Increase Wind Penetration in the Long Term

050

100150200

250300

2000 2020 2040 2060

GW

Hi Gas Price

Base Case

010

203040

5060

2005 2010 2015 2020

GW

$100/ton Carbon Case - Capacity

$100/ton Carbon Case - Generation

$100/ton Carbon – No New NukesCapacity

Production Tax Credit Extension

A PTC Extension to 2020 Could Result in 20% of Generation from Wind by 2020

0%

5%

10%

15%

20%

25%

2000 2010 2020 2030 2040 2050

Win

d F

ract

ion

of

Gen

erat

ion

WinDS - Basecase

WinDS- PTC to 2010 &Rampdown to 2020

4.1%

20%

* PTC to 2010 with ramp down by 2020

Regional Wind Installations by 2020 with PTC*

Major Modeling Issues in WinDS

• Transmission– Load modeling/loop flow– Multiple interchanges

• Non-economic factors/siting– Environmental – emissions, views, birds, bats, radars

• Competitive technologies– Conventional fuels/technologies– Other renewables

• Electric industry dynamics – Restructuring– RTO’s

• Model scope – electric loads, fuel prices, • Linear Programming Optimization

New Website (documentation and results) at:http://www.nrel.gov/analysis/winds

Backup slides follow

Annual Electric Generating Capacity Additions

Fossil, Nuclear and Non-Hydro Renewables

0

2

4

6

8

10

12

14

16

18

Gig

aWat

ts

Coal Natural Gas Nuclear Non-Hydro Renewable

Natural Gas:

63 GW in 2002

Coal declines

CAAAGas increases

PIFUA changed

PURPA

CC Efficiency

Low price through deregulation

Nuclear emerges

Technology available

“Too cheap to meter”

Gas declines

PIFUA prohibits

Nuclear declines

3-Mile Island (1979)

Chernobyl (1986)

WinDS Constraints on Wind Transmission

Supply/demand regions

Existing transmission line

New wind transmission line

Class x wind

Class y wind

New transmission line

PCA 1

PCA 2

Disclaimer and Government License

This work has been authored by Midwest Research Institute (MRI) under Contract No. DE-AC36-99GO10337 with the U.S. Department of Energy (the “DOE”). The United States Government (the “Government”) retains and the publisher, by accepting the work for publication, acknowledges that the Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for Government purposes. 

Neither MRI, the DOE, the Government, nor any other agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe any privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the Government or any agency thereof. The views and opinions of the authors and/or presenters expressed herein do not necessarily state or reflect those of MRI, the DOE, the Government, or any agency thereof.