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transcript
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.
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
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 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
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%
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
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.