Concentrating Solar Deployment Systems (CSDS) A New Model for Estimating U.S. Concentrating Solar Power Market Potential Nate Blair, Walter Short, Mark Mehos, Donna Heimiller National Renewable Energy Laboratory
Dec 14, 2015
Concentrating Solar Deployment Systems (CSDS)
A New Model for Estimating U.S. Concentrating Solar Power
Market Potential
Nate Blair, Walter Short, Mark Mehos, Donna Heimiller
National Renewable Energy Laboratory
Goal of Analysis• Build a new capability to examine future market
penetration for concentrating solar power– Extend capabilities of Wind Deployment System (WinDS)
• Attempting to answer the following questions– When will concentrating solar power strongly enter the
market under business-as-usual conditions?– What regions of the southwestern U.S. are most likely to see
significant CSP market penetration?– Is an extension of the current investment tax credit (ITC) or a
wind-type production tax credit (PTC) provide greater acceleration of market penetration?
– What impact do the expected, improved costs due to research and development have on market penetration?
– What is the sensitivity of deployment to general cost reductions?
CSDS Model(Concentrating Solar Deployment System)
A multi-regional, multi-time-period model of capacity expansion in the electric sector of the U.S. focused on renewables.
Designed to estimate market potential of solar energy in the U.S. for the next 20 – 50 years under different technology development and policy scenarios
General Characteristics of CSDS• 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– Capacity factors for each timeslice determined by hourly simulation
• 4 levels of regions – solar supply/demand, power control areas, NERC areas, Interconnection areas
• Existing and new transmission lines
• 5 wind classes (3-7), onshore and offshore shallow and deep
• 5 solar classes (6.75 kW/m2/day to 8 kw/m2/day)
• All major power technologies – hydro, gas CT, gas CC, 4 coal technologies, nuclear, gas/oil steam
• Conventional costs and fuel prices from EIA’s Annual Energy Outlook 2005
Current CSP Input Assumptions
• SEGS Type Trough Plant– Typical 100 MW plant sizing– 6 hours of thermal storage– Prescribed capacity factor based on plant as
modeled in Excelergy (NREL CSP specific model) for various solar resource levels
– Costs (capital, fixed O&M, Variable O&M) from Excelergy for different locations
– Assume cost reductions in line with DOE goals– 8% learning rate– Independent Power Producer (IPP) financing
Base Case Capacity by Generator Type
0
250
500
750
1000
1250
1500
1750
2000
2250G
W
Conc. Solarnuclearoil-gas-steamCoal-IGCCCoal-newCoal-no scrubCoal-w/scrubGas-CCGas-CTHydroTotal Wind
Base Case Capacity by Solar Class
0
10
20
30
40
50
60
2000
2004
2008
2012
2016
2020
2024
2028
2032
2036
2040
2044
2048
GW
Class 5 (7.75 - 8.06 kW/m2/day)
Class 4 (7.50 - 7.74 kW/m2/day)
Class 3 (7.25 - 7.49 kW/m2/day)
Class 2 (7.00 - 7.24 kW/m2/day)
Class 1 (6.75 - 6.99 kW/m2/day)
Base Case CSP by Transmission Type
0
10
20
30
40
50
60
2000
2004
2008
2012
2016
2020
2024
2028
2032
2036
2040
2044
2048
GW
Used For In-region LoadNew Grid Lines Between RegionsExisting Grid between Regions
Base Case Generation Fractions
0%
20%
40%
60%
80%
100%
2000
2004
2008
2012
2016
2020
2024
2028
2032
2036
2040
2044
2048
TW
h
CSP
nuclear
o-g-s
Coal-IGCC
Coal-new
Coal-old-2
Coal-old-1
Gas-CC
Gas-CT
Hydro
wind shallow
wind onshore
Impact of CSP R&D Improvements
0
10
20
30
40
50
60C
SP
Cap
acit
y (G
W)
Base Case
No R & D Improvements
Impact of Reduced Cost Scenario
Reduced Cost Trajectory Sensitivity
0
10
20
30
40
50
60
70
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
CS
P C
apac
ity (
GW
)
100%90%80%70%60%50%40%
Cheaper Capital and O&M Costs
Extension of Investment Tax Credit (ITC)
0
10
20
30
40
50
6020
0020
0220
0420
0620
0820
1020
1220
1420
1620
1820
2020
2220
2420
2620
2820
3020
3220
3420
3620
3820
4020
4220
4420
4620
4820
50
Cap
acit
y (G
W)
Base Case (30% ITC to 2007, 10% thereafter)
Extend 30% ITC to 2012 (10% thereafter)
Extend 30% ITC to 2017 (10% thereafter)
Extension of Production Tax Credit (ITC)
0
10
20
30
40
50
60
70
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
CS
P C
apac
ity (
GW
)
Base Case (30% ITC to 2007, 10% thereafter)
PTC to 2012 (18 $/MWH, no ITC)
PTC to 2050 (18 $/MWH, no ITC)
Conclusions
• A tool was created for modeling CSP capacity growth and examine various scenarios while accounting for transmission needs.
• CSP will contribute a share of future electric generation in our Base Case scenario and increase that share with various policy enhancements.
• Increased R&D leading to further reductions in cost are vital to CSP market penetration.
• CSP deployment is very cost sensitive because the resource is geographically focused and relatively close to load centers.
• Appropriate incentives are necessary to help assure a more sustained technology expansion.– Extending the Investment Tax Credit past 2007 will
dramatically increase the generation from CSP.– Implementing a Production Tax Credit for CSP similar to the
PTC for wind has a minimal or negative impact on CSP deployment until costs drop significantly.
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.