Integrating Remote Wind Resource: The Role for Energy Storage
Julian Lamy, Granger Morgan, Inês Azevedo
Background
One major challenge of wind power
generation is that it’s time-variable and often
not synchronized with load. Another issue is
that the highest-output wind resources are
located in remote locations, necessitating
transmission investment between generation
sites and load. On-site energy storage
coupled with wind could smooth wind power
variability
and
decrease
required
transmission investment. This project will
present a model to optimize transmission and
energy storage capacity investment for a
wind farm located in in the Upper Midwest.
Different battery technologies are considered
for energy storage such as sodium-sulfur,
advanced Li-Ion and reused Li-Ion batteries
from electric vehicles. The paper relies upon
price data from Midwest Independent System
Operator (MISO) energy markets and wind
data from the National Renewable Energy
Lab’s EWITS study.
Broader Impacts
Currently, 29 States have renewable portfolio
standards that require minimum levels of lowcarbon generation. In some regions, wind
generation could help utilities meet these
targets. Moreover, future federal regulation
and legislation is likely to lead to some form
of required carbon mitigation, further
incentivizing renewable investment. This
research offers a potential solution to
problems with wind generation and provides
insights for managers of how such
investments could be profitable. The model
presented also adds to the optimization
methods literature by offering a very simple,
yet affective application of finite horizon
dynamic programming.
Wind variability and transmission investment
are inescapable challenges to integrating
remote wind capacity into the electricity grid,
however on-site batteries can make wind
projects more economic. Investors should
consider building such projects and
regulators should help facilitate this effort.
The.figure above shows optimal storage
capacity investment for a 100 MW wind farm
under different capital cost assumptions.
Data used were EWITS 2006 ND wind output
and 2010 Illinois Hub MISO LMP prices.
Transmission length modeled at 1600km.
Assumed financing of 7% over 40 years.
Financial Support
This work was supported by the center for
Climate and Energy Decision Making (SES0949710), through a cooperative agreement
between the National Science Foundation
and Carnegie Mellon University.
For more information contact:
Julian Lamy,
jlamy@*, (202) 257-8377
Inês Azevedo,
ilimade@*
Granger Morgan, granger.morgan@*
*@andrew.cmu.edu
Results and Conclusions
Preliminary results suggest that optimal
transmission capacity investment is lower
than the nameplate capacity of the wind
farm, consistent with previous literature [1]
[2]. We find that this optimal level is between
60-80% of nameplate wind capacity. We also
find that optimal storage capacity is 20% of
nameplate wind capacity in our base case
assumptions ($500/KWh storage cost and
>$1000/MW-km
transmission
cost).
Furthermore, energy storage investment is
optimal at costs below ~$700/KWh.
References
[1] Denholm, Paul and Ramteen Sioshansi,
“The value of compressed air energy storage
with wind in transmission constrained electric
power systems,” Energy Policy 37 (2009)
3149–3158.
[2] Pattanariyankool, Sompop and Lester B.
Lave “Optimizing transmission from distant
wind farms,” Energy Policy 38 (2010) 2806–
2815.