Abstract

This paper provides a study of the potential impacts of climate change on intermittent renewable energy resources and storage requirements for grid reliability and resource adequacy. Climate change models and available regional data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed within a specific U.S. southwest service area as a case study. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources. Results for the extreme climate change scenario show that the projected wind power may decrease by ∼13% due to projected decreases in wind speed. Projected solar power may decrease by ∼4% due to decreases in irradiance and increases in temperature. Uncertainty in these climate-induced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in round-trip efficiency. The hourly energy balance among electrical load, generation, and storage was calculated throughout the year. The annual loss of load expectation (LOLE) was found to increase from ∼0 days/year to a median value of ∼2 days/year due to potential reductions in renewable energy resources caused by climate change and decreased battery performance. Significantly increased battery storage was required to reduce the LOLE to desired values of 0.2 days/year.

References

1.
Solaun
,
K.
, and
Cerdá
,
E.
,
2019
, “
Climate Change Impacts on Renewable Energy Generation. A Review of Quantitative Projections
,”
Renewable Sustainable Energy Rev.
,
116
, p.
109415
.
2.
Gernaat
,
D. E. H. J.
,
de Boer
,
H. S.
,
Daioglou
,
V.
,
Yalew
,
S. G.
,
Müller
,
C.
, and
van Vuuren
,
D. P.
,
2021
, “
Climate Change Impacts on Renewable Energy Supply
,”
Nat. Clim. Change
,
11
(
2
), pp.
119
125
.
3.
Russo
,
M. A.
,
Carvalho
,
D.
,
Martins
,
N.
, and
Monteiro
,
A.
,
2022
, “
Forecasting the Inevitable: A Review on the Impacts of Climate Change on Renewable Energy Resources
,”
Sustainable Energy Technol. Assess.
,
52
, p.
102283
.
4.
Ayli
,
U. E.
,
Özgirgin
,
E.
, and
Tareq
,
M.
,
2021
, “
Solar Chimney Power Plant Performance for Different Seasons Under Varying Solar Irradiance and Temperature Distribution
,”
ASME J. Energy Resour. Technol.
,
143
(
6
), p.
061303
.
5.
Addo-Binney
,
B.
,
Besada
,
W.
, and
Agelin-Chaab
,
M.
,
2022
, “
Analysis of an Integrated Thermal Energy System for Applications in Cold Regions
,”
ASME J. Energy Resour. Technol.
,
144
(
1
), p.
012104
.
6.
Houchati
,
M.
,
Beitelmal
,
A. H.
, and
Khraisheh
,
M.
,
2022
, “
Predictive Modeling for Rooftop Solar Energy Throughput: A Machine Learning-Based Optimization for Building Energy Demand Scheduling
,”
ASME J. Energy Resour. Technol.
,
144
(
1
), p.
011302
.
7.
Yang
,
P.
, and
Najafi
,
H.
,
2022
, “
A Comparative Study of Multi-Stage Approaches for Wind Farm Layout Optimization
,”
ASME J. Energy Resour. Technol.
,
144
(
10
), p.
101302
.
8.
Harang
,
I.
,
Heymann
,
F.
, and
Stoop
,
L. P.
,
2020
, “
Incorporating Climate Change Effects Into the European Power System Adequacy Assessment Using a Post-Processing Method
,”
Sustainable Energy Grids Netw.
,
24
, p.
100403
.
9.
Phillips
,
N.
,
Reiman
,
M.
,
Brunton
,
D.
,
Gutierrez
,
S.
, and
Heslop
,
J.
,
2021
,
PNM 2020–2040 Integrated Resource Plan
,
Public Service Company of New Mexico
,
Albuquerque, NM
. https://www.pnmforwardtogether.com/irp, Accessed January 29, 2021.
10.
Burrows
,
S. M.
,
Maltrud
,
M.
,
Yang
,
X.
,
Zhu
,
Q.
,
Jeffery
,
N.
,
Shi
,
X.
,
Ricciuto
,
D.
, et al
,
2020
, “
The DOE E3SM v1.1 Biogeochemistry Configuration: Description and Simulated Ecosystem-Climate Responses to Historical Changes in Forcing
,”
J. Adv. Model. Earth Syst.
,
12
(
9
), p.
e2019MS001766
.
11.
Eyring
,
V.
,
Bony
,
S.
,
Meehl
,
G. A.
,
Senior
,
C. A.
,
Stevens
,
B.
,
Stouffer
,
R. J.
, and
Taylor
,
K. E.
,
2016
, “
Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) Experimental Design and Organization
,”
Geosci. Model Dev.
,
9
(
5
), pp.
1937
1958
.
12.
Golaz
,
J.-C.
,
Caldwell
,
P. M.
,
Roekel
,
L. P. V.
,
Petersen
,
M. R.
,
Tang
,
Q.
,
Wolfe
,
J. D.
,
Abeshu
,
G.
, et al
,
2019
, “
The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution
,”
J. Adv. Model. Earth Syst.
,
11
(
7
), pp.
2089
2129
.
13.
Tebaldi
,
C.
,
Debeire
,
K.
,
Eyring
,
V.
,
Fischer
,
E.
,
Fyfe
,
J.
,
Friedlingstein
,
P.
,
Knutti
,
R.
, et al
,
2021
, “
Climate Model Projections From the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6
,”
Earth Syst. Dyn.
,
12
(
1
), pp.
253
293
.
14.
Craig
,
M. T.
,
Cohen
,
S.
,
Macknick
,
J.
,
Draxl
,
C.
,
Guerra
,
O. J.
,
Sengupta
,
M.
,
Haupt
,
S. E.
,
Hodge
,
B.-M.
, and
Brancucci
,
C.
,
2018
, “
A Review of the Potential Impacts of Climate Change on Bulk Power System Planning and Operations in the United States
,”
Renewable Sustainable Energy Rev.
,
98
, pp.
255
267
.
15.
Craig
,
M. T.
,
Carreño
,
I. L.
,
Rossol
,
M.
,
Hodge
,
B.-M.
, and
Brancucci
,
C.
,
2019
, “
Effects on Power System Operations of Potential Changes in Wind and Solar Generation Potential Under Climate Change
,”
Environ. Res. Lett.
,
14
(
3
), p.
034014
.
16.
Losada Carreño
,
I.
,
Craig
,
M. T.
,
Rossol
,
M.
,
Ashfaq
,
M.
,
Batibeniz
,
F.
,
Haupt
,
S. E.
,
Draxl
,
C.
,
Hodge
,
B.-M.
, and
Brancucci
,
C.
,
2020
, “
Potential Impacts of Climate Change on Wind and Solar Electricity Generation in Texas
,”
Clim. Change
,
163
(
2
), pp.
745
766
.
17.
Haupt
,
S. E.
,
Copeland
,
J.
,
Cheng
,
W. Y. Y.
,
Zhang
,
Y.
,
Ammann
,
C.
, and
Sullivan
,
P.
,
2016
, “
A Method to Assess the Wind and Solar Resource and to Quantify Interannual Variability Over the United States Under Current and Projected Future Climate
,”
J. Appl. Meteorol. Climatol.
,
55
(
2
), pp.
345
363
.
18.
Mearns
,
L.
,
McGinnis
,
S.
,
Korytina
,
D.
,
Arritt
,
R.
,
Biner
,
S.
,
Bukovsky
,
M.
,
Chang
,
H.-I.
, et al
,
2017
, “
The NA-CORDEX Dataset, version 1.0
,” NCAR Climate Data Gateway, Boulder CO.
19.
Skamarock
,
W.
,
Klemp
,
J.
,
Dudhia
,
J.
,
Gill
,
D.
,
Barker
,
D.
,
Wang
,
W.
,
Huang
,
X.-Y.
, and
Duda
,
M.
,
2008
,
A Description of the Advanced Research WRF Version 3, UCAR/NCAR, 1002 KB 2008-06
.
20.
Chen
,
L.
,
2020
, “
Impacts of Climate Change on Wind Resources Over North America Based on NA-CORDEX
,”
Renewable Energy
,
153
, pp.
1428
1438
.
21.
Pryor
,
S. C.
,
Barthelmie
,
R. J.
,
Bukovsky
,
M. S.
,
Leung
,
L. R.
, and
Sakaguchi
,
K.
,
2020
, “
Climate Change Impacts on Wind Power Generation
,”
Nat. Rev. Earth Environ.
,
1
(
12
), pp.
627
643
.
22.
Crook
,
J. A.
,
Jones
,
L. A.
,
Forster
,
P. M.
, and
Crook
,
R.
,
2011
, “
Climate Change Impacts on Future Photovoltaic and Concentrated Solar Power Energy Output
,”
Energy Environ. Sci.
,
4
(
9
), pp.
3101
3109
.
23.
Folini
,
D.
,
Dallafior
,
T. N.
,
Hakuba
,
M. Z.
, and
Wild
,
M.
,
2017
, “
Trends of Surface Solar Radiation in Unforced CMIP5 Simulations
,”
J. Geophys. Res. Atmos.
,
122
(
1
), pp.
469
484
.
24.
Haupt
,
S. E.
,
Kosović
,
B.
,
Jensen
,
T.
,
Lazo
,
J. K.
,
Lee
,
J. A.
,
Jiménez
,
P. A.
,
Cowie
,
J.
, et al
,
2018
, “
Building the Sun4Cast System: Improvements in Solar Power Forecasting
,”
Bull. Am. Meteorol. Soc.
,
99
(
1
), pp.
121
136
.
25.
Huber
,
I.
,
Bugliaro
,
L.
,
Ponater
,
M.
,
Garny
,
H.
,
Emde
,
C.
, and
Mayer
,
B.
,
2016
, “
Do Climate Models Project Changes in Solar Resources?
,”
Sol. Energy
,
129
, pp.
65
84
.
26.
Chen
,
L.
,
2021
, “
Uncertainties in Solar Radiation Assessment in the United States Using Climate Models
,”
Clim. Dyn.
,
56
(
1
), pp.
665
678
.
27.
Jackson
,
N. D.
, and
Gunda
,
T.
,
2021
, “
Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States
,”
Appl. Energy
,
302
, p.
117508
.
28.
Jiménez
,
P. A.
,
Alessandrini
,
S.
,
Haupt
,
S. E.
,
Deng
,
A.
,
Kosovic
,
B.
,
Lee
,
J. A.
, and
Monache
,
L. D.
,
2016
, “
The Role of Unresolved Clouds on Short-Range Global Horizontal Irradiance Predictability
,”
Mon. Weather Rev.
,
144
(
9
), pp.
3099
3107
.
29.
Wang
,
M.
,
Ullrich
,
P.
, and
Millstein
,
D.
,
2020
, “
Future Projections of Wind Patterns in California with the Variable-Resolution CESM: a Clustering Analysis Approach
,”
Clim. Dyn.
,
54
(
3
), pp.
2511
2531
.
30.
Millstein
,
D.
,
Solomon-Culp
,
J.
,
Wang
,
M.
,
Ullrich
,
P.
, and
Collier
,
C.
,
2019
, “
Wind Energy Variability and Links to Regional and Synoptic Scale Weather
,”
Clim. Dyn.
,
52
(
7
), pp.
4891
4906
.
31.
National Renewable Energy Laboratory
, “
Wind Prospector
,” 2012 2021, https://maps.nrel.gov/wind-prospector.
32.
International Electrotechnical Commission
,
2005
, “
Wind Turbines – Part 1: Design Requirements
,”
International Standard
.
33.
Kalmikov
,
A.
,
Dykes
,
K.
, and
Araujo
,
K.
,
Wind Power Fundamentals
,
MIT
,
Cambridge, MA
, https://web.mit.edu/windenergy/windweek/Presentations/Wind%20Energy%20101.pdf
34.
King
,
J.
,
Clifton
,
A.
, and
Hodge
,
B. M.
,
2014
, “
Validation of Power Output for the WIND Toolkit
,”
National Renewable Energy Laboratory
, Report No. NREL/TP-5D00-61714, Golden, CO, https://www.nrel.gov/docs/fy14osti/61714.pdf
35.
Holmgren
,
W. F.
,
Hansen
,
C. W.
, and
Mikofski
,
M. A.
,
2018
, “
pvlib Python: A Python Package for Modeling Solar Energy Systems
,”
J. Open Source Softw.
,
3
(
29
), p.
884
.
36.
Sengupta
,
M.
,
Xie
,
Y.
,
Lopez
,
A.
,
Habte
,
A.
,
Maclaurin
,
G.
, and
Shelby
,
J.
,
2018
, “
The National Solar Radiation Data Base (NSRDB)
,”
Renewable Sustainable Energy Rev.
,
89
, pp.
51
60
.
37.
Preger
,
Y.
,
Barkholtz
,
H. M.
,
Fresquez
,
A.
,
Campbell
,
D. L.
,
Juba
,
B. W.
,
Romàn-Kustas
,
J.
,
Ferreira
,
S. R.
, and
Chalamala
,
B.
,
2020
, “
Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling Conditions
,”
J. Electrochem. Soc.
,
167
(
12
), p.
120532
.
38.
Spotnitz
,
R.
,
2003
, “
Simulation of Capacity Fade in Lithium-Ion Batteries
,”
J. Power Sources
,
113
(
1
), pp.
72
80
.
You do not currently have access to this content.