future cost of electricity storage and impact on …...pba –lead-acid battery phs –pumped hydro...
TRANSCRIPT
Future cost of electricity storage and
impact on competitiveness
Oliver Schmidt
28 June 2018 | EU4Energy Policy Forum
Karven 4 Seasons Resort, Sary-Oi, Kyrgyzstan
Storage may have a big impact, but its
future role is perceived as highly uncertain
2
Problem: Uncertainty on role of storage
Source: World Energy Issues Monitor 2017 | Exposing the new energy realities. World Energy Council; 2017.
Critical uncertainty: What keeps you awake at night
Action priority: What keeps you busy at work
Global installed capacity - 2017
While pumped hydro is the most widely
deployed stationary storage technology
3Source: Energy Storage Database, Department of Energy (2017); Global Energy Storage Forecast, 2016-2024, BNEF (2017); https://www.ngk.co.jp/nas/
All data in MW
NaS – Sodium-sulphur Battery
Flow – Flow Battery
PbA – Lead-acid Battery
PHS – Pumped Hydro Storage
Li-ion – Lithium-ion Battery
CAES – Compressed Air Energy Storage
20% added in last 10 years
99% added in last 10 years
Recent cost developments
Investment costs of lithium-ion batteries
have fallen dramatically in recent years
4Sources: Tepper, M. Solarstromspeicher-Preismonitor Deutschland 2016. (Bundesverband Solarwirtschaft e.V. und Intersolar Europe, 2016);
www.solarfixni.co.uk/solarpanelsystems/tesla/; www.tesla.com/powerwall
October 2013 April 2015 October 2016
Average: 3,000 $/kWhcap
Powerwall 1: 1,100 $/kWhcap
Powerwall 2: 500 $/kWhcap
Approach
We need a consistent method to project
cost for multiple technologies
5
Technology
• Cost analyses are focussed on lithium-ion
• A holistic assessment should cover multiple technologies
Scope
• Cost quotes refer to different technology components
• A transparent analysis should clarify reference scope
Method
• Cost projections are made with varying methods
• An objective and consistent method should be chosen
Source: www.flaticon.com
Technologies
Electricity can be stored in multiple ways
6
Electricity
storage
concepts
Mechanical
• Gravitation(e.g. pumped hydro)
• Compression(e.g. compressed air)
• Rotation (e.g. Flywheel)
Electrolysis
Liquid air
Pumped hydro
Supercapacitor
Lithium-ion
Redox-Flow
Technology scope
Cost figures can refer to different scopes
containing not all cost components
7
Module
Source: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrical energy storage based on experience rates. Nat. Energy 2, 17110 (2017)
Cell
Pack
System (ex-works)
Installed system
Consumer electronics
Electric vehicles
Stationary applications
20%
-
30%
65%
100%
-
-
of installed system
of installed system
of installed system
1976
2015
100
1,000
10,000
100,000
0.001 0.01 0.1 1 10 100 1,000
Pro
du
ct
Pri
ce
(U
S$
2015/k
W)
Cumulative Installed Capacity GW)
Method
Experience curves are an objective tool to
model cost reductions for technologies
8
Solar PV (23%, Module)
Source: Liebreich, M. Keynote - Bloomberg New Energy Finance Summit 2016. (Bloomberg New Energy Finance, 2016).
50
100
200
500
1,000
2,000
5,000
10,000
20,000
0.001 0.01 0.1 1 10 100 1,000 10,000
1983 2013
1989 2012
2013
2016
1995
2016
2010
2017
2013
2017
2010
2017
1997
2014
20072015
2008
2015
1956
2014
2004
2015
Pro
du
ct
Pri
ce
(U
S$
2017/k
Wh
cap)
Cumulative Installed Nominal Capacity (GWhcap)
Pumped hydro (Utility, -1±8%)
Lead-acid (Multiple, 4±6%)
Lead-acid (Residential, 13±5%)
Lithium-ion (Electronics, 30±3%)
Lithium-ion (EV, 18±3%)
Lithium-ion (Residential, 15±4%)
Lithium-ion (Utility, 16±3%)
Nickel-metal hydride (HEV, 11±1%)
Sodium-sulfur (Utility, -)
Vanadium redox-flow (Utility, 11±9%)
Electrolysis (Utility, 18±6%)
Fuel Cells (Residential, 18±2%)
Dataset
The experience curve dataset for storage
technologies...
9Source: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrical energy storage based on experience rates. Nat. Energy 2, 17110 (2017)
System Pack Module Battery
50
100
200
500
1,000
2,000
5,000
10,000
20,000
0.001 0.01 0.1 1 10 100 1,000 10,000
Pro
du
ct
Pri
ce
(U
S$
2017/k
Wh
cap)
Cumulative Installed Nominal Capacity (GWhcap)
Pumped hydro (Utility, -1±8%)
Lead-acid (Multiple, 4±6%)
Lead-acid (Residential, 13±5%)
Lithium-ion (Electronics, 30±3%)
Lithium-ion (EV, 18±3%)
Lithium-ion (Residential, 15±4%)
Lithium-ion (Utility, 16±3%)
Nickel-metal hydride (HEV, 11±1%)
Sodium-sulfur (Utility, -)
Vanadium redox-flow (Utility, 11±9%)
Electrolysis (Utility, 18±6%)
Fuel Cells (Residential, 18±2%)
System Pack Module Battery
Investment cost projection – Capacity-based
... shows that battery storage investment
cost will reach cost of pumped hydro
10
System Pack Module Battery
Source: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrical energy storage based on experience rates. Nat. Energy 2, 17110 (2017)
200-330
125-200
Price ranges
130
Investment cost projection – Time-based
Resulting time-based cost projections could
be used to compare technologies, but
11
0
200
400
600
800
1,000
1,200
1,400
2015 2020 2025 2030 2035 2040
Pro
du
ct
Pri
ce
(U
S$
2015/k
Wh
cap)
Lithium-ion (Utility, 16±4%, System)
Experience Rate uncertainty
+ Growth Rate uncertainty
280 $/kWh
390 $/kWh
220 $/kWh
Apple ≠ Orange
12
Cost and performance parameters
Electricity storage technologies differ in
many cost and performance parameters
Cost Performance
Investment cost Cost to construct technology
overnight (total vs specific)
Nominal power
capacity
Maximum amount of power
generated
Construction
time
Actual duration of technology
construction
Discharge
duration
Maximum duration to discharge
energy at maximum power
Replacement
cost
Cost to replace technology
components
Nominal / Usable
energy capacity
Maximum amount of energy stored
Usable amount of energy stored
Replacement
interval
Time interval at which technology
component replacement is required
Depth-of-
discharge
Maximum energy that can be used
without severely damaging the store
O&M cost Cost of operating and maintaining
operability of technology
Cycle life Number of full charge-discharge
cycles before end of usable life
Charging cost Cost for energy to technology with
energy
Calendar life Number of years before end of
usable life (even at no operation)
Disposal cost /
Residual value
Cost to dispose of the technology at
its end-of-life (can be negative)
Degradation Loss in usable energy capacity
Discount rate Rate at which future cost / revenues
of technology are discounted
Round-trip
efficiency
Proportion of energy discharged
over energy required to charge store
13
LCOS Formula
Levelised cost of storage (LCOS) consider
all cost and performance parameters
14
The discounted cost of a “MWh” discharged from the storage device
𝐿𝐶𝑂𝑆$
𝑀𝑊ℎ=𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡 + 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑐𝑜𝑠𝑡 + 𝐷𝑖𝑠𝑝𝑜𝑠𝑎𝑙 𝑐𝑜𝑠𝑡
𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒𝑑
• Investment cost
• Construction time
• Replacement cost / interval
• Charging cost
• O&M cost
• Round-trip efficiency
• Depth-of-discharge
• Annual cycles
• Cycle life
• Calendar life
• Degradation
• End-of-life cost or
residual value
Electricity storage applications
Applications affect storage operation, so
LCOS analysis must be application-specific
15Source: The Economics of Battery Storage, RMI, 2015
LCOS – Bill Management
Lithium-ion to become more competitive
than flow batteries for bill management
16
Power Capacity 1 MW
Discharge duration 4 hours
Annual cycles 500
Charging cost 100 $/MWh
Vanadium redox-flow Lead-acid Sodium-sulfur Lithium-ion
LC
OS
in U
S$
2018/M
Wh
0
200
400
600
800
1,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
200
400
600
800
1,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
100
200
300
400
500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
200
400
600
800
1,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
200
400
600
800
1,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
LCOS – Resource Adequacy (Seasonal)
Pumped hydro, compressed air and
hydrogen compete for seasonal storage
17
Power Capacity 1,000 MW
Discharge duration 700 hours
Annual cycles 3
Charging cost 50 $/MWh
Pumped hydro Compressed air Hydrogen Vanadium redox-flow
LC
OS
in U
S$
2018/M
Wh
0
2,000
4,000
6,000
8,000
10,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
2,000
4,000
6,000
8,000
10,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
2,000
4,000
6,000
8,000
10,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
0
500
1,000
1,500
2,000
2,500
3,000
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
2,000
4,000
6,000
8,000
10,000
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
700.00 PHS PHS 700.00 H2 H2
8.00 CAES CAES PHS PHS PHS 8.00 Lithium Lithium Lithium Lithium VRFB
4.00 Lithium Lithium Lithium Lithium PHS PHS 4.00 Lithium Lithium Lithium Lithium VRFB VRFB
2.00 Lithium Lithium Lithium Lithium VRFB PHS 2.00 Lithium Lithium Lithium Lithium VRFB VRFB
1.00 Lithium Lithium Lithium Lithium Lithium VRFB 1.00 Lithium Lithium Lithium Lithium Lithium VRFB
0.50 Lithium Lithium Lithium Lithium Lithium Lithium Lithium 0.50 Lithium Lithium Lithium Lithium Lithium Lithium Lithium
0.25 Lithium Lithium Lithium Lithium Lithium Lithium FlywheelFlywheel 0.25 Lithium Lithium Lithium Lithium Lithium Lithium FlywheelFlywheel
1 10 50 100 500 1000 5000 10000 1 10 50 100 500 1000 5000 10000
Dis
ch
arg
e d
ura
tio
n
(ho
urs
)
Cycles p.a.Cycles p.a.
Summary
Overall, increasing dominance of Lithium-
ion for majority of applications by 2030
20
15
700.00 PHS PHS 700.00 H2 H2
8.00 CAES CAES PHS PHS PHS 8.00 Lead Lead Lead Lead H2
4.00 CAES CAES CAES PHS PHS PHS 4.00 Lead Lead Lead Lead VRFB VRFB
2.00 CAES CAES CAES CAES PHS PHS 2.00 Lead Lead Lead Lead VRFB VRFB
1.00 CAES CAES CAES CAES PHS PHS 1.00 Lead Lead Lead Lead VRFB VRFB
0.50 CAES CAES CAES CAES CAES PHS PHS 0.50 Lead NaS NaS NaS NaS VRFB Flywheel
0.25 CAES CAES CAES CAES CAES PHS FlywheelFlywheel 0.25 NaS NaS NaS NaS NaS NaS FlywheelFlywheel
1 10 50 100 500 1000 5000 10000 1 10 50 100 500 1000 5000 10000
Cycles p.a.
Dis
ch
arg
e d
ura
tio
n
(ho
urs
)
Cycles p.a.
20
20
20
30
700.00 PHS PHS 700.00 H2 H2
8.00 CAES CAES PHS PHS PHS 8.00 Lithium Lithium Lithium Lithium VRFB
4.00 CAES CAES CAES PHS PHS PHS 4.00 Lithium Lithium Lithium Lithium VRFB VRFB
2.00 CAES CAES CAES CAES PHS PHS 2.00 NaS NaS NaS NaS VRFB VRFB
1.00 CAES CAES CAES CAES PHS PHS 1.00 NaS NaS NaS NaS VRFB VRFB
0.50 NaS NaS NaS NaS VRFB PHS PHS 0.50 NaS NaS NaS NaS VRFB VRFB Flywheel
0.25 NaS NaS NaS NaS NaS NaS FlywheelFlywheel 0.25 NaS NaS NaS NaS NaS NaS FlywheelFlywheel
1 10 50 100 500 1000 5000 10000 1 10 50 100 500 1000 5000 10000
Cycles p.a. Cycles p.a.
Dis
ch
arg
e d
ura
tio
n
(ho
urs
)
All technologies Excl. PHS & CAES
Increased PV self-consumption
Analysis – Competitiveness
LCOS analysis also allows analysing
competitiveness of electricity storage
19
Frequency regulation
50Hz
Competitiveness – Frequency regulation
Recent investments in storage to provide
balancing services show that...
20Source: https://www.energy-storage.news/news/siemens-to-deploy-market-based-grid-balancing-battery-for-german-utility
50Hz
0
50
100
150
200
250
2012 2013 2014 2015 2016 2017
No
min
al P
ow
er
Cap
acit
y (
MW
)
Utility-scale battery capacity
0
200
400
600
800
1,000
1,200
-
20
40
60
80
100
120
140
160
180
200
2010 2015 2020 2025 2030 2035 2040
Pro
du
ct
Pri
ce
(U
S$
2015/k
Wh
cap)
An
nu
al
Ca
pa
cit
y C
os
t (U
S$
2017/k
Wyr)
Time
Lithium-ion (Utility, 16±4%)
Experience Rate uncertainty
+ Growth rate uncertainty
Primary frequency control prices
Competitiveness – Frequency regulation
... frequency regulation is a business case
for electricity storage
21
Timespan
Source: Own Analysis; D.P. Svoboda, D.R. Schemm, M. Bartelt, Aufbruch in den Regelenergiemarkt?, Energ. Manag. (August 2015) 28.
Competitiveness – Increased PV self-consumption
The market for home storage appears
poised for growth...
22Source: www.tesla.com/powerwall; L. Goldie-Scot, Global Energy Storage Forecast 2016-24, Bloomberg New Energy Finance, 2016.
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
2015 2017 2019 2021 2023
Cu
mu
lati
ve
in
sta
lla
tio
ns (
MW
h)
Time
Short duration balancing
Peaking capacity
Renewable energy integration
Transmission Level
Distribution Level
Behind-the-meter: PV + storage
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
1.40
1.50
2010 2015 2020 2025 2030 2035 2040
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
Pro
du
ct
Pri
ce
(U
S$
2017/k
Wh
cap)
Le
veli
sed
co
st
of
sto
rag
e (
US
$2017/k
Wh
e) Lithium-ion (Residential, 15±4%)
Experience Rate Uncertainty
+ Growth Rate uncertainty
Retail Power
Competitiveness – Increased PV self-consumption
Still, residential batteries are unlikely to
make economic sense in GER before 2030
23
Timespan
Source: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrical energy storage based on experience rates. Nat. Energy 2, 17110 (2017)
410
Concept
Electricity storage can provide multiple
services in parallel, i.e. “benefit-stacking”
24
Value ($)
Investment
costIncreased
PV self-
consump-
tion
End-user
service
System
service
Utility
service
Utility
service
System
service
End-user
service
Increased
PV self-
consump-
tion
Source: Own analysis.
Benefit-stacking in the UK
Benefit-stacking is a reality for subsidy-free
battery projects in the United Kingdom…
25
0
200
400
600
800
1,000
1,200
-
20
40
60
80
100
120
140
160
180
200
2015 2020 2025 2030 2035 2040
Pro
du
ct
Pri
ce
(U
S$
2015/k
Wh
cap)
An
nu
al
Ca
pa
cit
y C
os
t (U
S$
2017/k
Wyr)
Time
Lithium-ion (Utility, 16±4%)
Experience Rate uncertainty
+ Growth rate uncertainty
Timespan
Enhanced
frequency
response
Capacity
provision
Network
charge
avoidance
Source: Own analysis.
…through the combination of three
different electricity storage services
26
Electricity storage applications
Source: The Economics of Battery Storage, RMI, 2015
Policy measures
Low-cost policy measures can enable
benefit-stacking
27
A. Adjust technical standards to open markets for storage technologies (frequency response: reduce minimum bidding sizes, allow assets operating in dispersed fleets)
B. Amend competition regulation to allow combined value streams (example: “unbundling” prohibits simultaneous revenues from generation and transmission)
C. Develop consistent legal definition of ‘electricity storage’ to ascertain that storage can serve as generation, transmission/distribution and consumption support simultaneously
Stephan, A., Battke, B., Beuse, M. D., Clausdeinken, J. H., & Schmidt, T. S. (2016). Limiting the public cost of stationary battery deployment by combining applications. Nature Energy, 1(June), 16079.
All three barriers can be removed at low costs
Key messages
Summary
28
1. Investment cost of battery storage technologies will reach cost of
pumped hydro.
2. Levelised cost of storage (LCOS) is the metric to be used to
compare technologies.
3. Lithium-ion will be most cost-effective in most applications except
when long discharge and/or many cycles are required.
4. Electricity storage is expensive, but versatile. Thus, benefit-stacking
is the holy grail to profitability and system benefits.
Oliver Schmidt | PhD Researcher in Energy StorageGrantham Institute - Climate Change and the EnvironmentImperial College London, Exhibition Road, London SW7 2AZTel: +44 (0) 7934548736Email: [email protected]: www.storage-lab.com
Questions?
Non-PHS vs PHS
Global storage capacity is again growing
quickly to ensure VRE integration
30
Positive market and policy trends supported annual growth of over 50% for non-
pumped hydro storage. Near-term storage needs will remain answered by PHS.
Source: Tracking Clean Energy Progress 2017. International Energy Agency (2017).
Medium-term outlook for non-PHS storage - Power
Non-PHS capacity growth will mostly be
required to integrate self-generated PV
31
-
5
10
15
20
25
30
35
40
45
50
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Cu
mu
lati
ve
po
we
r c
ap
ac
ity (
GW
)
Behind-the-meter: PV + storage
Other
Behind-the-meter: C&I demand charges
Distribution Level
Transmission Level
Renewable energy integration
Peaking capacity
Short duration balancing
Source: Global Energy Storage Forecast, 2016-2024, BNEF (2017)
Applications vs Technologies
Application requirements can be met by
different energy storage technologies
32Source: Energy Technology Perspectives 2014, International Energy Agency (2014).
New technologies are constantly being
developed
33
Technologies
0.001 0.01 0.1 1 10 100 1,000 10,000
Cumulative Installed Nominal Capacity (GWhcap)
Pumped hydro (Utility, -1±8%)
Lead-acid (Multiple, 4±6%)
Lead-acid (Residential, 13±5%)
Lithium-ion (Electronics, 30±3%)
Lithium-ion (EV, 18±3%)
Lithium-ion (Residential, 15±4%)
Lithium-ion (Utility, 16±3%)
Nickel-metal hydride (HEV, 11±1%)
Sodium-sulfur (Utility, -)
Vanadium redox-flow (Utility, 11±9%)
Electrolysis (Utility, 18±6%)
Fuel Cells (Residential, 18±2%)
Sanity Check – Raw material cost
Raw material costs suggest that these cost
projections are not infeasible
34
System Pack Module Battery
109 87 72 52 51
20 15 14 12 10
100
1,000
Ra
w M
ate
ria
l C
os
t (U
S$
2017/k
Wh
cap)
1995
2011
2010
2017
1997
2014
2004
2015
50
100
200
500
1,000
2,000
5,000
10,000
20,000
0.001 0.01 0.1 1 10 100 1,000 10,000
Pro
du
ct
Pri
ce
(U
S$
2015/k
Wh
cap)
Cumulative Installed Nominal Capacity (GWhcap)
Lithium-ion (Electronics, 30±3%)
Lithium-ion (EV, 18±3%)
Nickel-metal hydride (HEV, 11±1%)
Fuel Cells (Residential, 18±2%)
However, experience rates of immature
technologies can be highly uncertain
35
Uncertainty Check
Source: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrical energy storage based on experience rates. Nat. Energy 2, 17110 (2017)
Storage materials – reserve base
36Source: Own analysis
ESOI of different storage technologies
37
Application-specific LCOS account for all
relevant cost and performance parameters
38
Formula
𝐿𝐶𝑂𝑆$
𝑀𝑊ℎ=
𝐶𝑎𝑝𝑒𝑥 + σ𝐶𝑎𝑝𝑒𝑥𝑅1 + 𝑟 𝑅∗𝑇𝑟
#𝑐𝑦𝑐𝑙𝑒𝑠 ∗ 𝐷𝑜𝐷 ∗ 𝐶𝑛𝑜𝑚_𝑒 ∗ 𝜂𝑅𝑇 ∗ σ𝑛=1𝑁 1 + 𝐷𝑒𝑔 𝑛
1 + 𝑟 𝑛
+σ𝑛=1𝑁 𝑂𝑝𝑒𝑥
1 + 𝑟 𝑛+𝑇
#𝑐𝑦𝑐𝑙𝑒𝑠 ∗ 𝐷𝑜𝐷 ∗ 𝐶𝑛𝑜𝑚_𝑒 ∗ 𝜂𝑅𝑇 ∗ σ𝑛=1𝑁 1 + 𝐷𝑒𝑔 𝑛
1 + 𝑟 𝑛
+
𝐷𝑖𝑠𝑝𝑜𝑠𝑎𝑙1 + 𝑟 𝑁+1
#𝑐𝑦𝑐𝑙𝑒𝑠 ∗ 𝐷𝑜𝐷 ∗ 𝐶𝑛𝑜𝑚_𝑒 ∗ 𝜂𝑅𝑇 ∗ σ𝑛=1𝑁 1 + 𝐷𝑒𝑔 𝑛
1 + 𝑟 𝑛
+𝑃𝑒𝑙η𝑅𝑇
Capex:
Capexr:
Opex:
Disposal:
Pel:
r:
Cnom_e:
DoD:
N:
#cycles:
Deg:
n:
Tr:
R:
Tc
Investment cost ($)
Replacement cost ($)
Operating cost ($)
Disposal cost ($)
Power cost ($/kWhel)
Discount rate (%)
Nominal capacity (MWh)
Depth-of-discharge (%)
Lifetime (years)
Full cycles per year (#)
Annual degradation (%)
Period (year)
Replacement interval (years)
Replacement number (#)
Construction time (years)
Note: Construction time and self-discharge not explicitly
considered for simplification; these parameters affect capex
and period, and discharged energy respectively.
Energy storage technologies contain a
number of components
39
Technology components
Source: Lazard’s Levelized Cost of Storage Analysis 2017
Battery SystemEnergy
System
Applications – Detail
Modelled applications cover entire
spectrum of performance requirements
40
Energy arbitrage
Primary response
Secondary response
Tertiary response
Peaker replacement
Black start
T&D upgrade deferral
Congestion mgmt
Bill mgmt
Power quality
Power reliability
0
1
2
3
4
5
6
7
8
9
10
1 10 100 1,000 10,000
Dis
ch
arg
e d
ura
tio
n (
ho
urs
)
Cycles p.a. (#)
Seasonal
storage
700
Infeasible
(insufficient hours
per year)
1 MW 10 MW 100 MW
Overview 1
LCOS and technology dominance in
modelled electricity storage applications
41
Primary response
Secondary response
Tertiary response
Black start
T&D upgrade deferral
Congestion mgmt
Power quality
Power reliability
0
1
2
3
4
5
6
7
8
9
10
1 10 100 1,000 10,000
Dis
ch
arg
e d
ura
tio
n (
ho
urs
)
Annual cycles (#)
700
0
500
1,000
1,500
2,000
2,500
3,000
3,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
2,000
4,000
6,000
8,000
10,000
12,000
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
600
700
800
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
3,000
3,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
3,000
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
50
100
150
200
250
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
20
40
60
80
100
120
140
160
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
Overview 2
LCOS and technology dominance in
modelled electricity storage applications
42
0
500
1,000
1,500
2,000
2,500
3,000
3,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
2,000
4,000
6,000
8,000
10,000
12,000
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
100
200
300
400
500
600
700
800
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
3,000
3,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
500
1,000
1,500
2,000
2,500
3,000
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
50
100
150
200
250
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
0
20
40
60
80
100
120
140
160
0%
20%
40%
60%
80%
100%
2015 2020 2025 2030 2035 2040 2045 2050
LC
OS
in
US
$2018/M
Wh
Pro
bab
ilit
y
Seasonal storage Power reliability T&D deferral Bill management
Black start Tertiary response Peaker replacement Energy arbitrage
Power quality Congestion management Secondary response Primary response