Title: Long Term National Impacts of Statelevel Policies WindPower 2006
1Long Term National Impacts of State-level
PoliciesWindPower 2006
- Nate Blair, Walter Short, Paul Denholm, Donna
Heimiller - National Renewable Energy Laboratory
2Goal 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?
3Contents
- Brief Description of the WinDS Model
- Base Case results
- State-Level Policy Impacts
- No State-Level Policy
- Impact of Penalty Level on RPS Compliance
4WinDS 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
5WinDS Regions
6Wind Resources in WinDS
7WinDS 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?
8General 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
9Base Case Capacity by Wind Class
10Base Case Generation Fractions
11Basecase Wind Capacity in 2050
12Legislation 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 PTCs and ITCs last?
- Frequently Changing Legislation
13Our 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.
14State RPS Assumptions
15State PTC and ITC Assumptions
16Wind Capacity With W/out State Incentives
(WithW/out RD Improvements)
17Delta Wind Consumed in 2030 (MWh) (normal state
incentives - no state incentives)
18Delta Wind Consumed in 2050 (MWh) (normal state
incentives - no state incentives)
19Increased Penalty Values would increase RPS
compliance
20Conclusions
- State-level incentives drive a significant
fraction of the early growth in wind
installations. - In the second decade of the 21st 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
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