1. Long Term National Impacts of State- level Policies WindPower 2006 Nate Blair, Walter Short, Paul Denholm, Donna Heimiller National Renewable Energy Laboratory

2. Goal of Analysis Attempting to answer the following questions –What impact will state-level incentives have on wind capacity growth in the near future and the distant future? –How are state-level policies shaping the dispersal of wind deployment across the country ? This effect interacts with dispersal due to capacity value increase with greater dispersal. –Could higher penalties promote greater compliance with RPS? And how high should they be?

3. Contents Brief Description of the WinDS Model Base Case results State-Level Policy Impacts –No State-Level Policy –Impact of Penalty Level on RPS Compliance

4. 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

5. WinDS Regions

6. Wind Resources in WinDS

7. WinDS is Designed to Address the Principal Market Issues for Wind Access to and cost of transmission –Class 4 close to the load or class 6 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?

8. 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 4 levels of regions – wind 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 All major power technologies – hydro, gas CT, gas CC, 4 coal technologies, nuclear, gas/oil steam Electricity storage capability

9. Base Case Capacity by Wind Class

10. Base Case Generation Fractions

11. Basecase Wind Capacity in 2050

12. Legislation Leaves Modeling Questions How long is the final RPS fraction to be maintained? What is the penalty for non-compliance with an RPS? –“standard utility enforcement” = $ ??? What RPS fraction is from wind? How long will PTC’s and ITC’s last? Frequently Changing Legislation

13. Our Modeling Assumptions for Incentives State Incentives based on DSIRE database and other sources. If no duration given, assumed incentive lasts throughout the simulation. Assumed complete RPS compliance for affected utilities – either by purchasing renewables or paying the penalty –Munis and coops frequently exempted Fraction that must be met by wind determined exogenously –Based on viability of wind resource and other state renewable resources (solar, biomass, etc.) Assumed that RPS requirements can be met by wind generation transmitted in from other states.

14. State RPS Assumptions

15. State PTC and ITC Assumptions

16. Wind Capacity With & W/out State Incentives (With&W/out R&D Improvements)

17. Delta Wind Consumed in 2030 (MWh) (normal state incentives - no state incentives)

18. Delta Wind Consumed in 2050 (MWh) (normal state incentives - no state incentives)

19. Increased Penalty Values would increase RPS compliance

20. Conclusions State-level incentives drive a significant fraction of the early growth in wind installations. In the second decade of the 21 st century, current incentives will most likely not continue to be a primary factor in new wind growth. Enhanced incentives and the spread of incentives to new states could continue to spur wind energy growth. Higher penalty amounts and enforcement are critical to reaching expected RPS penetration levels. Continued work on including additional state-level incentives and updating existing incentives is necessary for more precise near-term forecasts.

21. 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.