ArticlePDF Available

Abstract and Figures

Seasonal mismatches between electricity supply and demand is increasing due to expanded use of wind, solar and hydropower resources, which in turn raises the interest on low-cost seasonal energy storage options. Seasonal pumped hydropower storage (SPHS) can provide long-term energy storage at a relatively low-cost and co-benefits in the form of freshwater storage capacity. We present the first estimate of the global assessment of SPHS potential, using a novel plant-siting methodology based on high-resolution topographical and hydrological data. Here we show that SPHS costs vary from 0.007 to 0.2 US$ m −1 of water stored, 1.8 to 50 US$ MWh −1 of energy stored and 370 to 600 US$ kW −1 of installed power generation. This potential is unevenly distributed with mountainous regions demonstrating significantly more potential. The estimated world energy storage capacity below a cost of 50 US$ MWh −1 is 17.3 PWh, approximately 79% of the world electricity consumption in 2017.
This content is subject to copyright. Terms and conditions apply.
ARTICLE
Global resource potential of seasonal pumped
hydropower storage for energy and water storage
Julian D. Hunt 1, Edward Byers 1, Yoshihide Wada 1, Simon Parkinson 1,2, David E.H.J. Gernaat3,4,
Simon Langan 1, Detlef P. van Vuuren 3,4 & Keywan Riahi1
Seasonal mismatches between electricity supply and demand is increasing due to expanded
use of wind, solar and hydropower resources, which in turn raises the interest on low-cost
seasonal energy storage options. Seasonal pumped hydropower storage (SPHS) can provide
long-term energy storage at a relatively low-cost and co-benets in the form of freshwater
storage capacity. We present the rst estimate of the global assessment of SPHS potential,
using a novel plant-siting methodology based on high-resolution topographical and hydro-
logical data. Here we show that SPHS costs vary from 0.007 to 0.2 US$ m1of water stored,
1.8 to 50 US$ MWh1of energy stored and 370 to 600 US$ kW1of installed power
generation. This potential is unevenly distributed with mountainous regions demonstrating
signicantly more potential. The estimated world energy storage capacity below a cost of
50 US$ MWh1is 17.3 PWh, approximately 79% of the world electricity consumption
in 2017.
https://doi.org/10.1038/s41467-020-14555-y OPEN
1International Institute of Applied Systems Analysis (IIASA), Laxenburg, Austria. 2Institute for Integrated Energy Systems, University of Victoria, PO Box 3055
STN CSC Victoria, BC, Canada. 3Copernicus Institute of Sustainable Development, Utrecht University, Heidelberglaan 2, 3584 CS Utrecht, The Netherlands.
4PBL Netherlands Environmental Assessment Agency, Bezuidenhoutseweg 30, 2594 AV Den Haag, The Netherlands. email: hunt@iiasa.ac.at
NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications 1
1234567890():,;
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Whilst a number of energy storage technologies are
being developed to manage electricity grids, most
technologies only full short-term cycles (daily or
shorter). Pumped hydropower storage (PHS) systems are cur-
rently the most mature and widespread method for large-scale
electricity storage16. Global installed PHS electricity generation
capacity is ~165 GW and constitutes the vast majority of elec-
tricity storage worldwide, of which 25 GW have been identied as
mixed plants that are also conventional reservoir-based hydro-
power dams7. Often, PHS is seen as a technology capable of
storing energy for daily or weekly cycles and up to months813;
however, the technology can also operate over annual and pluri-
annual cycles14. Given the current costs reduction in other
technologies offering daily energy storage (particularly batteries),
PHS is anticipated to gain importance as a seasonal energy and
water storage alternative.
A SPHS plant consists of a high-head variation storage reservoir
built in parallel to a major river. During periods of low-energy
demand or high water availability, water is pumped into the
reservoir. Stored water is released from the reservoir generating
electricity when additional electricity generation capacity is
required, or water is scarce. They can be compared to conven-
tional reservoir dams, due to the possibility of regulating the river
ow and increasing the hydropower generation on the hydro-
power dams in cascade15. SPHS plants have lower land require-
ments than conventional hydropower dams, for a comparable
energy and water storage potential, because the off-river reservoir
design permits higher hydraulic heads variations14. SPHS can also
be attractive to deal with the load problems emerging from elec-
tricity consumption and supply seasonal variations and increasing
use of intermittent sources of generation. The storage of water can
also help to overcome water shortage problems. Because storage is
also not near the main river, possible negative impacts of hydro-
power can be better managed (further details in Supplementary
Table 1).
To understand the potential that SPHS can full in future
energy storage requirements, in this paper, we present the rst
comprehensive and globally consistent assessment of SPHS
potential. It presents the results from the SPHS world potential
model, which is an upgrade of the methods that have been used
for estimating global hydropower potential1621. One recent study
investigates the global potential for PHS and assumes the con-
struction of two reservoirs in a closed loop for daily and weekly
operation. They found a global potential of 23 × 106GWh in more
than 600,000 plants, but the project sizes appear to be impractical
or infeasible for seasonal storage or water storage and do not
include detailed cost analysis or water availability22,23 (Supple-
mentary Table 2). We have not included these closed loop sites
because they are designed to store energy and we are looking at
energy and water storage solutions in this paper. Other studies
have been developed to nd the potential for PHS projects in
Europe21,24,25, and Iran26, however, these are regional models also
do not include costs. In this paper, we scan the global landscape
alongside rivers for attractive sites to build articial reservoirs for
water and energy storage purposes with SPHS plants. Here, we
evaluate all land grid points for project suitability at a 15 s reso-
lution (~450 m resolution), using a detailed siting assessment
methodology for developing and costing SPHS projects with
topography, river network, and hydrological data.
Our estimates show that the global technical and economic
potential for water and energy storage with SPHS is vast, but with
an unequal spatial distribution across the world. Considering all
the energy storage projects with the cascade, the total storage
capacity is equivalent to 17,325 TWh, or ~79% of the world
electricity consumption in 2017. Whilst we have considered a
maximum of one SPHS per 1-degree grid square (100 × 100 km),
in some locations a series of SPHS plants in cascade could further
increase the energy storage potential.
Results
The SPHS world potential model identied more than 5.1 million
potential projects, all of which have a xed generation/pumping
capacity of 1 GW. With the intention of eliminating competing
projects and focusing on the best projects per region, the projects
with the lowest costs for water storage (US$ m3), long (US$
MWh1) and short-term (US$ kW1) energy storage, within a
1 arc degree resolution of the globe are presented. This consists of
1457 water storage projects with water storage costs lower than
0.2 US$ m3and 1092 energy storage projects with energy sto-
rage cost lower than 50 US$ MWh1(some of the water projects
consist of the same energy projects).
Critical components of the SPHS project costs are the dam and
tunnel (Fig. 1a). Tunnel costs increase proportionally with its
length and reduce with generation head. Dam costs increase
proportionally with width and exponentially with height. A high
land-value of 41,000 US$ ha1was assumed in this paper, and it
represents typically 5% of the total project costs. It is important to
emphasize the relatively low land requirement of SPHS in com-
parison to conventional hydropower dams that have smaller
variations of reservoir levels and thus ood more area for the
same water storage capacity. The average level variation of SPHS
projects is 151.7 m for energy storage projects (Supplementary
Table 5).
We use a site in Tibet, China to illustrate the calculations
(Fig. 1b, c). With a 50 m dam height, the energy storage costs are
the highest at 11.7 US$ MWh1. Most of the costs are related to
the tunnel costs (45%), which is 18 km long. The land cost is high
(8%) if compared to the dam costs (7%) because the amount of
water stored per km2is low. Energy storage cost is the lowest for a
150 m dam height. In this case, the tunnel cost is 30%, and dam
costs, 36% and land cost is low (6%) (Supplementary Tables 6 and
7). A further increment in head increases energy storage costs,
mostly because the required water to ll up the reservoir
according to Eq. (3) exceeds the maximum ow extraction from
the river.
Looking at the global potential, the water storage cost with
SPHS varies from 0.007 to 0.2 US$ m3of water stored (Fig. 2a).
This large cost difference is due to the variation in topography
and water availability. The energy storage cost varies from 4.6 to
50 US$ MWh1without including dams in cascade and from 1.8
to 50 US$ MWh1when including them (Fig. 2b, c, respectively).
The water stored in a SPHS plant also benets the dams down-
stream (in cascade). The higher the altitude of the SPHS system,
the more energy it stores for the whole basin. Given that the
SPHS projects proposed in this paper intend to regulate the ow
of the river, if the river has dams downstream the SPHS plant,
they will also generate more electricity with the ow released
from the SPHS plant15. Assuming a cost for natural gas storage
of 1 US$ mcf127 and an electricity generation efciency of 50%,
the cost of energy storage with natural gas is ~6.8 US$ MWh1.
This value is higher than the energy storage with SPHS in
mountainous regions with cascade around the world (Fig. 2c).
The world storage capacity curves are shaded because they
include the cheapest projects and a combination of cheap and
large storage capacity projects.
The cost of 1 GW PHS capacity varies from 370 to 600 US$ kW1
(Fig. 2d). This excludes dam and land costs. The costs are segmented
in different steps due to the variation in length of the tunnel, which
starts at 3 km with additional increments of 3 km. A cost compar-
ison of other short-term energy storage technologies can be found
in ref. 28.
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y
2NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Thepercentageofinow from the tributary river to ll up the
reservoir varies for each project (Fig. 2e). The remaining percentage
consists of the water that is pumped into the SPHS reservoir from
the river below. Three of the proposed projects, over more than
1000 projects, have 100% of the inow coming from the tributary
river. In these cases, a reversible turbine would be interesting only
to allow the project to store energy in daily and weekly cycles,
given that the seasonal cycle is already accomplished with the river
ow.
The land requirement for energy storage varies from 1.2 to
20 km2TWh1(Fig. 2f). This is a result of the high water level
variation in SPHS reservoirs (mean 141 m for water storage and
152 m for energy storage (Supplementary Table 5)). For com-
parison, the average land requirement for hydropower energy
storage in Brazil is around 150 km2TWh129. The low land
requirement of SPHS projects makes it a more social and envir-
onmentally friendly storage alternative when compared with
conventional dams. Large reservoirs with longer storage cycles
usually have lower storage costs than small ones. The storage
cycle will depend on the needs for storage and the storage
potential of the reservoir.
Discussion
Conventional hydropower dams have been built in main river
channels with the intention of managing water resources and
generating low-cost, low-carbon electricity, but often they fragment
ow and ood upstream areas. SPHS plants built adjacent to main
rivers can provide similar water management and energy storage
services while avoiding the large land footprint associated with
conventional hydropower dams. This paper has identied where
SPHS plants could be built and the associated unit costs for energy
and water storage services. The estimated potential is restricted to
mountainous regions with reasonable water availability and high
hydraulic heads supporting cost-efcient SPHS system design.
Signicant potential exists in the lower part of the Himalayas,
Andes, Alps, Rocky Mountains, Northern part of the Middle East,
Ethiopian Highlands, Brazilian Highlands, Central America, East
Asia, Papua New Guinea, the Sayan, Yablonoi and Stanovoy
mountain ranges in Russia, with energy storage costs with cascade
varying from 1.8 to 50 US$ MWh1(Fig. 2c).
SPHS projects are shown to provide multiple income generating
services, for example, a single SPHS project provides water storage
at 0.1 US$ m3, long-term energy storage at 30 US$ MWh1and
short-term energy storage at 600 US$ kW1. Considering that the
need for three storage services are complementary in the SPHS
projects, the costs of these services are substantially reduced14. The
change in cost for each storage service will vary with the need for
storage and the operation of the SPHS plant. Compared with
natural gas storage, this work has shown that there is considerable
potential for SPHS to provide competitive storage, noting that the
gas comparison does not even consider the cost of the gas power
plant so as not to confuse storage with generation.
a
80
14
Median
5% 5%
4%
40%
35% 11%
12
10
8
6
4
2
050 100 150
Dam height (m)
200 250
60
40
Water and energy projects costs (%)
Energy storage costs (USD$/MWh)
20
0
Dam Electric Excavation Land Turbine Tunnel
b
Dam
Tunnel
Reservoir
Power
House
River
cd
138
115
92
69
46
23
20 40 60 80 100 120 140 160 180
1500–2000 2000–2500 2500–3000 3000–3500
4000–4500 4500–5000 5000–55003500–4000
0 km
Fig. 1 Seasonal pumped hydropower storage (SPHS) costs and description. a Water and energy SPHS project cost distribution shows that the most
expensive components tend to be the tunnel and dam. bExample of energy storage cost variation with cascade according to different heights for the
example project in c. The energy storage cost reduces with the increase in dam height due to economies of gains, however, it then increases because the
reservoir becomes larger than the amount of water available to be sustainably stored. cPresentation of selected project in Tibet, China, on a topographic
map, presenting its tunnel in black and reservoir in purple. dZoom in the selected project.
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y ARTICLE
NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications 3
Content courtesy of Springer Nature, terms of use apply. Rights reserved
The needs for energy and water storage with SPHS plants
should be complementary. This is because during the dry season
there will be low volumes of water available to be used for energy
storage. This complementarity is usually the case in high latitude
countries, where during the summer river ow is higher due to ice
melting and energy demand is lower compared to the winter.
Inter-tropical regions with abundant hydropower generation also
have complementarity, where during the wet season there is high
water availability and hydropower generation. However, there are
regions and countries where the need for energy and water sto-
rage is not complementary, for example, in the inter-tropical
regions without hydropower generation, where the summer and
wet season is the period with highest electricity demand due to air
conditioning. In cases where energy and water storage need are
0.2
0.175
0.15
0.125
0.1
0.075
0.05
0.025
0.007
50
40
30
20
10
4.6
1 10 100 1000 10,000
Water storage costs (US$ m–3)Water storage costs (US$ m–3)
b
c
1 10 100 1000 10,000
100
50
10
1
1 10 100 1000 10,000 100,000
Energy storage cost
with natural gas
a
d
ef
>20
15
10
5
0.8
Energy storage costs without cascade (US$ MWh–1)
Energy storage costs without cascade (US$ MWh–1)
50
40
30
20
10
1.8
600
550
500
450
400
370 0 200 400 600 800 1000 1200 1400 1600 1800 2000
600
550
500
450
400
350
100
80
60
40
20
0
Percentage of reservoir that is filled with the tributary river inflow (%)
Energy storage installed capacity (GW)
Energy storage capacity without cascade (TWh)
Energy storage capacity with cascade (TWh)
World generation
in 2017
1
0.2
0.1
0.01
0.001
Energy storage cost
with natural gas
Energy storage costs (US$ kW–1 installed) Energy storage costs (US$ kW–1installed)
Water storage capacity (km3)
100
50
10
1
Flooded area/energy storage (km2 TWh–1)
Energy storage costs without cascade (US$ MWh–1)
Energy storage costs without cascade (US$ MWh–1)
1
1
1
1
1
North America
Africa Asia Australia Europe
Central America South America World
Fig. 2 Seasonal pumped hydropower storage world cost and ooded area maps. a Water storage costs and capacity curve in km3.bEnergy storage
without considering hydropower plants in cascade costs and capacity curve in US$ MWh1.cEnergy storage considering hydropower plants in cascade
costs and capacity curve in US$ MWh1.dAdditional generation capacity costs and capacity curve in US$ kW1.ePercentage of the reservoir that is lled
with the river inow into the SPHS reservoir. fAverage land requirement for energy storage in different basins.
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y
4NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications
Content courtesy of Springer Nature, terms of use apply. Rights reserved
not complementary, SPHS should not be considered as an energy
and water storage alternative.
Given that this is the rst global assessment for SPHS, the
model was developed with the intent of focusing on its technical
potential. Other restrictions that impact socio-economic feasi-
bility, such as population, land use, biodiversity, transmission, etc.
were not included in this work with the intent of presenting the
existing potential and not its viability. Regional studies such as,
Rogeau et al. 21 already tried to eliminate irrelevant sites due to
conicts with existing land use.
With the needs for reducing CO
2
emissions to mitigate the
impacts of climate change, SPHS provides short-term and long-
term energy storage services allowing the development of 100%
renewable energy grids. SPHS also increases water security in
regions with unsuitable topography for conventional dams, high
evaporation, and sedimentation rates. It is, thus, a prominent
alternative for sustainable development on a worldwide scale.
Methods
Global model. To assess the global potential of SPHS, our methodology integrates
ve critical components, which are: topography, river network and hydrology data,
infrastructure cost estimation and project design optimization. SPHS project
suitability mainly depends on the topography, distance to a river and water
availability, which together determine the technical potential. Additional con-
textual factors, such as distance from energy demand and associated transmission
infrastructure losses and associated costs, determine the economic feasibility.
Whilst previous studies have used similarly high-resolution topography for con-
ventional reservoir dams estimation16, the possibility of storing water and energy
by pumping water to a reservoir parallel to a major river has not been globally
assessed. Since storage potential and infrastructure costs are highly dependent on
the topography, our new spatially explicit approach identies numerous technically
feasible candidate sites and provides estimates of costs.
Details of the SPHS world potential model framework are explained step-by-
step in Fig. 3and Supplementary Tables 35. The model goes through each grid cell
location delineated at a 15resolution, implementing a detailed siting assessment
that accounts for topography and hydrology in the calculation of project-level
costs. The model performs the stages as follows. First, it looks for a river with
reasonable owrate up to 30 km away from a reservoir (Fig. 3c), second it checks if
a dam up to 250 m high can be built from the grid cell (Fig. 3d), third it removes
projects with competing dams (Fig. 3e), fourth it nds the ooded side of the dam
and creates the reservoir (Fig. 3f), fth it calculates the volume and ooded areas,
sixth it compares the size of the storage site with the water available for storage
(Fig. 3g), seventh it estimates the costs of the dam, tunnel, turbine, generator,
excavation and land, eighth it estimates water and energy storage costs (Fig. 3i).
SPHS reservoirs in this study are operated to reduce the seasonality and
interannual river ow variations, to regulate the ow of the river. If the river ow is
already constant, then the water available for storage in the SPHS reservoir will be
zero, as it would deregulate the ow of the river. The hydrological data were used to
restrict the size of the storage reservoirs, according to water availability. This
guarantees that there will be water available to ll up the storage reservoir without
having a considerable impact on the overall river ow. Additionally, conservative
storage values are assumed to reduce the impact of the SPHS plant in the river ow.
The maximum volume of the reservoir equals to 11% of the annual river ow, from
which the need for storage is divided by seasonal storage needs and inter-annual
storage needs. This value was selected with the intent of reducing the
environmental impact of storage on the overall river ow. On average, the water
available for storage in SPHS reservoirs in this model equals to 7.7% of the annual
river ow (Supplementary Fig. 1).
Data collection. The SPHS World Potential Model provides a near-global scale
potential (56°S60°N). The excluded area is due to unavailable Shuttle Radar
Topography Mission (SRTM) topographic data. The topographic data applied is
SRTM30 and has 3resolution. The resolution is decreased to 15, assuming the
centre point, to reduce modelling time and to combine with the river network
data. The river network data assumed the Strahler methodology in Global-scale
river network (GRIN)31, which is derived from the SRTM data and has 15
resolution. The topographic and river Strahler data are then combined with the
hydrological data taken from the PCR-GLOBWB32 global hydrological model,
which are derived into annual discharge, seasonal, and inter-annual variations. We
use methods to optimize the number and diameter of the tunnels33 and for cost-
estimation34 procedures, which are further explained in Supplementary Tables 2
and 3.
Site selection model and engineering design. The site selection model is
divided into nine main stages (Supplementary Table 4). Initially, the topographic
data are combined with the river Strahler data, which is a numerical measure of
its branching complexity and was derived from the same topographic data. The
higher the Strahler stream order value the more tributary rivers (branches)
deliver water to the given part of the river31. The two are compared at the same
resolution to identify rivers within the topographic data and to estimate the
length of the tunnels connecting the upper reservoir and the lower reservoir in
the river. The river Strahler data are also used to reduce the amount of SPHS
projects developed within a given area and reduce the modelling time. Rivers
with small river Strahler stream order have low river ows, which results in
unviableSPHSprojectswithsmallgeneration capacities. A minimum river
Strahler stream order of 7 is selected because the river has a considerable number
of tributary rivers connected to it, which results in a relatively large and constant
river ow.
For each land grid cell at a latitude between 60° N and 56° S (point under
analysis (PUA)), the model searches for rivers with sufcient discharge (river
Strahler stream order 7) within 130 km of distance, which consists of the tunnel
length. If a large river is found, the model attempts to build dams of 50, 100, 150,
200 and 250 m height, along four axes (NS, WE, NWSE, NESW) and with a
maximum length of 7.2 km (Supplementary Table 4 (L4)). If the topography allows
the construction of such dams, it veries whether the PUA is the lowest point of the
dam (if it is not, the process stops with the intention of not repeating the same
project). Using the surrounding topography and observing limits to the maximum
ooded area of the reservoir, the model identies the side with the largest storage
volume. Subsequently, the reservoir water level is varied to determine the ooded
area vs. level and storage volume vs. level curves. This is done by subtracting the
volume of land and water with the reservoir at a given level by the volume of land
and water with the reservoir at its minimum level. Project costs are estimated using
the equations presented in the ref. 34. The cost is divided in dam, tunnel,
powerhouse excavation, pump-turbine, electro-technical equipment and land costs.
More details on the assumptions for the cost estimate are presented in
Supplementary Table 3. In the analysis, the water storage capacity of the SPHS
projects is limited according to the water availability of the main river. The
maximum water storage capacity is limited to 11% of the annual river ow, which
is a small portion of the river ow and results in a small impact to the river. If the
storage capacity is much higher than the amount of water available, the estimated
cost of storage increases, as a section of the reservoir will never ll up. The project
costs are then compared with the hydrology of the river to nd the water and
energy storage costs with Eqs. (4) and (5).
Storage dimensioning and cost. The seasonal and interannual variability of river
discharge used in the Hydrological Analysis Stage is calculated with the Eqs. (1)
and (2). They are important to calculate the water available for storage in the SPHS
reservoir, with the objective of producing a constant river ow. If the river has no
seasonal variation, then the water available for storage would be equal to zero. This
is because, if the SPHS deregulates the ow of the river, the hydropower potential
of the dams in cascade or the water supply downstream could be negatively
affected.
SV¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Pm2Mð
qm
qsÞ2
Nm
r
qs
if SV>1!SV¼1
fð1Þ
IV¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Py2Yð
qy
qsÞ2
Ny
r
qs
if IV>1!IV¼1fð2Þ
where, S
V
is the seasonal variation index, I
V
is the interannual variation index,
qmis
the river ow of a given m month,
qyis the average river ow of a given year,
qsis
the average river ow over y years, N
m
is the number of months, N
y
is the number
of years.
The costs of water and energy storage services calculated in the Estimate Storage
Cost stage vary according to the annual river ow, the seasonal and interannual
variation indexes. These hydrological parameters have three main purposes. Firstly,
they intend to guarantee that there will be sufcient water in the river to be stored
in the upper reservoir. Secondly, the need for water and energy storage should not
have a substantial detrimental impact on the river ow. Thirdly, the water storage
potential intends to regulate the ow of the river and produce a constant ow of
water, reducing its seasonality and interannual variations.
Using the values calculated for S
V
and I
V
(Supplementary Fig. 2) and the
percentage of river annual discharge available for storage (Supplementary Fig. 1),
the water available for storage Q
A
(Eq. (3)) is calculated by
QA¼Q´ðSV´0:1Þ´ð1þðIV´0:1ÞÞ ð3Þ
where Q
A
is the water available for storage in km3yr1,Qis the river annual
discharge in km3yr1.
The variation of the water and long-term energy storage costs with the water
available for storage is presented in Eq. (4). The costs for additional short-term
energy storage are presented in Eq. (5). For more details on Eqs. (1)(5) please refer
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y ARTICLE
NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications 5
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Legend:
Data input
Data output
Dam screening
Dam height 50 m
Reservoir side
and flooding
River screening
River Strahler
stream order > 7
Reservoir
storage
capacity
Estimate
project cost
Estimate
storage cost
Can’t find
Can’t find river
with 7 Strahler
Select point
under analysis
(PUA)
Identify dams
with height 250
m
Can’t find dams
shorter than 7.2 km
Lowest point of
the dam
Yes
PUA is not the lowest
point of the dam
Yes
Yes
Reservoir,
hydrology
comparison
Topographic data (SRTM), 15 s resolution
River network Strahler data (GRIN), 15 s resolution
Reservoir larger
than 1625 km
2
flood other side
Increase tunnel
length in 3 km
up to 30 km No
a
a
b c
b
e
d
e
f
g
h i j
h
Identify rivers with
higher Strahler
(up to 12)
Hydrological data (PCR-GLOBWB), 6 mins resolution
j
If both sides larger
than 1625 km
2
River Strahler 7
Iguaçu River
Uruguay River
Paraná
River
Antas River
Jacuí River
SPS tunnels
All SPHS projects developed in
South Brazil, 15 s resolution
Cheapest SPHS projects in 1 deg resolution
SPHS project and main components
g
dc
Energy storage costs with cascade (US$ MWh
–1
)
50
40
30
20
10
1.8
i
f
Height (m)
1000–1050
1250–1300
1050–1100
1300–1350
1100–1150
1350–1400
1150–1200
1400–1450
1200–1250
1450–1500
Shortest and
selected dam
Dam longer than
7.2 km, discated
Possible dam
but not selected
River
Proposed
tunnel
Point under analysis (PUA)
Look for river
close to PUA
If this point is
higher than the
PUA, flood this side
If the PUA is the lowest point
of the shortest dam, it is used
to create a reservoir
1350
1375
1325
Altitude (m)
1300
1275
1250
1225
1200
0 2.5 5.0
Lenght (km)
7.5
Check if the points
surrounding the
flooded areas
are lower than the
reservoir height
and flood it
If the reservoir is bigger
than 1625 km2, flood the
other side of the dam
Fig. 3 Seasonal pumped hydropower storage (SPHS) world potential model framework. a Topographical data input from the Shuttle Radar Topography
Mission (SRTM)30.bRiver network Strahler data input from the Global River Network (GRIN)31.cFinding rivers close to the SPHS site. dLooking for
possible dams. eLimiting the number of proposed SPHS projects. fCreating and nding reservoirs. gHydrological data input32.hRepresentation of a
possible SPHS project in the Zambezi river basin. iCheapest SPHS projects in 1-degree resolution. jLocation with several SPHS projects proposed.
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y
6NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications
Content courtesy of Springer Nature, terms of use apply. Rights reserved
to the Supplementary Table 2.
CW¼CP
WS
;CEwc ¼CP
ERwc
WR
WS
;CEwoc ¼CP
ERwoc
WR
WS
if WR<Q
A!WS¼WR
if QA<W
R<2QA!WS¼QAþ0:5WR
if WR>2QA!WS¼1:5QA
8
>
<
>
:ð4Þ
where C
W
is the cost of water storage in US$ km3,C
P
is the cost of the project (i.e.
dam, tunnel, turbine, electrical equipment, excavation, and land) in US$, W
s
is the
water storage capacity adjusted by the water availability in km3,C
Ewoc
is the cost of
long-term energy storage excluding the cascade in US$ MWh1,C
Ewc
is the cost of
long-term energy storage including the cascade in US$ MWh1,W
R
is the water
storage capacity of the reservoir developed in the model in km3,E
Rwc
and E
Rwoc
are
the energy storage capacity of the reservoir developed in the model with and
without cascade in MWh, respectively.
CGW ¼CPGW
Gð5Þ
where, C
GW
is the cost of additional generation capacity in US$ kW1,C
PGW
is the
cost of additional generation capacity (i.e. tunnel, turbine, electrical equipment,
excavation) in billion US$, Gis the generation capacity in GW (xed to be 1 GW
for all SPHS plants proposed).
Reporting summary. Further information on research design is available in
the Nature Research Reporting Summary linked to this article.
Data availability
The data that support the plots within this paper and other ndings of this study are
available from the corresponding author upon reasonable request.
Code availability
The code is available from the corresponding author upon reasonable request.
Received: 11 June 2019; Accepted: 13 January 2020;
References
1. International Energy Agency. Technology Roadmap: Energy Storage
(International Energy Agency, 2014).
2. Rehman, S., Al-Hadhrami, L. M. & Alam, M. M. Pumped hydro energy storage
system: a technological review. Renew. Sustain. Energy Rev. 44, 586598 (2015).
3. USA Department of Energy & Sandia National Laboratories. DOE Global
Energy Storage Database.https://www.energystorageexchange.org/ (2019).
4. International Renewable Energy Agency (IRENA). Renewable Energy Statistics
2019 (International Renewable Energy Agency (IRENA), 2019).
5. International Hydropower Association. Pumped Storage Tracking Tool https://
www.hydropower.org/hydropower-pumped-storage-tool (International
Hydropower Association, 2019).
6. Kelman, R. & Harrison, D. Integrating renewables with pumped hydro storage
in Brazil: a case study. HAL hal-021477, pre-print (2019).
7. International Renewable Energy Agency (IRENA). Renewable power
generation costs in 2014.Renewable power generation costs. doi:10.1007/
SpringerReference_7300 (2015).
8. International Electrotechnical Commission. Electrical Energy Storage: White
Paper (International Electrotechnical Commission, 2011).
9. Renewable Energy Association. Energy storage in the UK: An Overview
(Renewable Energy Association, 2016).
10. Akhil, A. et al. DOE/EPRI 2013 Electricity Storage Handbook in Collaboration
with NRECA. (Sandia National Laboratories, Albuquerque, 2013).
11. World Energy Council. World Energy Resources: E-Storage (World Energy
Council, 2016).
12. Luo, X., Wang, J., Dooner, M. & Clarke, J. Overview of current development in
electrical energy storage technologies and the application potential in power
system operation. Appl. Energy 137, 511536 (2015).
13. International Energy Agency. Technology Roadmap: Hydrogen and Fuel Cells
(International Energy Agency, 2015).
14. Hunt, J., Byers, E., Riahi, K. & Langan, S. Comparison between seasonal
pumped-storage and conventional reservoir dams from the water, energy and
land nexus perspective. Energy Convers. Manag. 166, 385401 (2018).
15. Hunt, J. D., Freitas, M. A. V. & Pereira Junior, A. O. Enhanced-pumped-
storage: combining pumped-storage in a yearly storage cycle with dams in
cascade in Brazil. Energy 78, 513523 (2014).
16. Gernaat, D. E. H. J., Bogaart, P. W., Vuuren, D. P., van, Biemans, H. &
Niessink, R. High-resolution assessment of global technical and economic
hydropower potential. Nat. Energy 2, 821828 (2017).
17. Zhou, Y. et al. A comprehensive view of global potential for hydro-generated
electricity. Energy Environ. Sci. 8, 26222633 (2015).
18. Hoes, O. A. C., Meijer, L. J. J., Van Der Ent, R. J. & Van De Giesen, N. C.
Systematic high-resolution assessment of global hydropower potential. PLoS
ONE 12, e0171844 (2017).
19. Petheram, C., Gallant, J. & Read, A. An automated and rapid method for
identifying dam wall locations and estimating reservoir yield over large areas.
Environ. Model. Softw. 92, 189201 (2017).
20. van Vliet, M. T. H. et al. Multi-model assessment of global hydropower and
cooling water discharge potential under climate change. Glob. Environ. Chang.
40, 156170 (2016).
21. Rogeau, A., Girard, R. & Kariniotakis, G. A generic GIS-based method for
small Pumped Hydro Energy Storage (PHES) potential evaluation at large
scale. Appl. Energy 197, 241253 (2017).
22. Lu, B., Stocks, M., Blakers, A. & Anderson, K. Geographic information system
algorithms to locate prospective sites for pumped hydro energy storage. Appl.
Energy 222, 300312 (2018).
23. Stocks, M. et al. A Global Atlas of Pumped Hydro Energy Storage. Australian
Renewable Energy Agency. https://nationalmap.gov.au/renewables/#share=s-
oDPMo1jDBBtwBNhD (2019).
24. Lacal-Arántegui, R., Fitzgerald, N. & Leahy, N. Pumped-hydro Energy Storage:
Potential for Transformation from Single Dams. JRC Scientic and Technical
Reports (Australian Renewable Energy Agency, 2012).
25. Gimeno-Gutiérrez, M. & Lacal-Arántegui, R. Assessment of the European
potential for pumped hydropower energy storage based on two existing
reservoirs. Renew. Energy 75, 856868 (2015).
26. Ghorbani, N., Makian, H. & Breyer, C. A GIS-based method to identify
potential sites for pumped hydro energy storagecase of Iran. Energy 169,
854867 (2019).
27. Federal Energy Regulatory Commission. Current State of and Issues
Concerning Underground Natural Gas Storage (Federal Energy Regulatory
Commission, 2004).
28. Zakeri, B. & Syri, S. Electrical energy storage systems: a comparative life cycle
cost analysis. Renew. Sustain. Energy Rev. 42, 569596 (2015).
29. Hunt, J. D., Freitas, M. A. V. D. & Pereira Junior, A. O. A review of seasonal
pumped-storage combined with dams in cascade in Brazil. Renew. Sustain.
Energy Rev.70, 385398 (2017).
30. Jarvis A., H. I. Reuter, A. Nelson, E. G. Hole-lled Seamless SRTM Data V4
(International Centre for Tropical Agriculture (CIAT), 2008).
31. Schneider, A. et al. Global scale river network extraction based on high-
resolution topography and constrained by lithology, climate, slope, and
observed drainage density. Geophys. Res. Lett. 44, 27732781 (2017).
32. Wada, Y., Graaf, I. & van Beek, L. High-resolution modeling of human and
climate impacts on global water resources. J. Adv. Model. Earth Syst. 8,
735763 (2016).
33. Rognlien, L. Pumped Storage Development in Øvre. MSc thesis, Norwegian
University of Science and Technology, Otra, Norway (2012).
34. SWECO Norge A. S. Cost base for hydropower plants (with a generating
capacity of more than 10,000 kW). Norwegian Water Resources and Energy
Directorate (Jan Slapgård, 2012).
Acknowledgements
We would like to thank CAPES/BRAZIL for the research grant as part of the CAPES/
IIASA Postdoctoral Programme.
Author contributions
J.D.H. conceived the idea, developed the modelling techniques and led the manuscript
writing, E.B. contributed to modelling and to the concept, Y.W. and D.E.H.J.G. devel-
oped the hydrological datasets used in the paper, S.P. contributed to the model and
references, S.L. contributed to the water availability restriction to the model and refer-
ences, D.P.V. and K.R. perfected the idea with valuable inputs. All authors contributed to
the manuscript.
Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/s41467-
020-14555-y.
Correspondence and requests for materials should be addressed to J.D.H.
Peer review information Nature Communications thanks Anne Jost and Rafael Kelman
for their contribution to the peer review of this work. Peer reviewer reports are available.
Reprints and permission information is available at http://www.nature.com/reprints
Publishers note Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional afliations.
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y ARTICLE
NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the articles Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
articles Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this license, visit http://creativecommons.org/
licenses/by/4.0/.
© The Author(s) 2020
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-14555-y
8NATURE COMMUNICATIONS | (2020) 11:947 | https://doi.org/10.1038/s41467-020-14555-y | www.nature.com/naturecommunications
Content courtesy of Springer Nature, terms of use apply. Rights reserved
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... For short-term energy storage (up to a few days), a wide range of technologies is available, including batteries and thermo-mechanical storage [51] . In contrast, chemical energy storage is one of the few alternatives for long-term, seasonal energy storage [51,52] , the other main option being pumped hydropower [53] . Even though pumped hydropower may be a potential solution for low-cost energy storage in some naturally suited areas [53] , the energy density of such systems is low, and pumped hydropower heavily depends on the availability of large natural water formations. ...
... In contrast, chemical energy storage is one of the few alternatives for long-term, seasonal energy storage [51,52] , the other main option being pumped hydropower [53] . Even though pumped hydropower may be a potential solution for low-cost energy storage in some naturally suited areas [53] , the energy density of such systems is low, and pumped hydropower heavily depends on the availability of large natural water formations. ...
... A wide range of technologies is available for short-term energy storage, including batteries and thermo-mechanical storage, typically up to a few days [51] . Chemical energy storage and pumped hydropower are the main alternatives for seasonal energy storage [51][52][53] . Even though pumped hydropower is a potential solution for low-cost energy storage in naturally suited areas [53] , the energy density of such systems is low, and pumped hydropower heavily depends on the availability of large natural water formations. ...
Thesis
Full-text available
This PhD thesis presents an investigation into plasma-catalytic ammonia synthesis in a dielectric barrier discharge (DBD) plasma reactor. Ammonia (NH3) can be synthesized from hydrogen gas (H2) and nitrogen gas (N2). Ammonia has current applications as intermediate for the fertilizer industry and the chemical industry. About 45% of the current pure hydrogen demand in industry is used for ammonia production. Future applications of ammonia include its use as zero-carbon fuel and as hydrogen carrier. Thus, ammonia may play a significant role in a decarbonized energy landscape.
... Additionally, the widespread use of batteries in power systems and mobility applications raises concerns about the sustainability of the usage of materials for batteries [7,8]. Gravity energy storage, such as mountain gravity energy storage [9][10][11] or PHS can provide long-term, seasonal energy storage in mountainous areas [12][13][14][15][16][17][18][19]. However, there is no other option for storing a significant amount of electrical energy economically in areas without mountains, except for converting electricity to other fuels (such as hydrogen or synthetic fuels) with low efficiency and high capital cost. ...
... Additionally, the widespread use of batteries in power systems and mobility applications raises concerns about the sustainability of the usage of materials for batteries [7,8]. Gravity energy storage, such as mountain gravity energy storage [9][10][11] or PHS can provide long-term, seasonal energy storage in mountainous areas [12][13][14][15][16][17][18][19]. However, there is no other option for storing a significant amount of electrical energy economically in areas without mountains, except for converting electricity to other fuels (such as hydrogen or synthetic fuels) with low efficiency and high capital cost. ...
Preprint
Full-text available
The globe is witnessing a significant energy transformation with an increasing proportion of variable energy sources like wind and solar on the grid. To enable a seamless integration of these renewable energy sources, energy storage solutions are required. This paper presents a novel energy storage strategy based on the compression and decompression of air between two floating storage vessels in the deep ocean. Compressed air seesaw energy storage is expected to cost between 10 and 50 USD/kWh for electric energy storage and between 800 and 1,500 USD/kW for the installed power capacity. Seesaw is an interesting alternative to pumped hydro and hydrogen for providing long-term energy storage cycles in regions close to the deep sea. Keywords: long-duration energy storage, utility energy storage, innovation, compressed air energy storage, carbon-neutral world, offshore wind. Highlights  A creative, environmentally friendly option for seasonal energy storage.  The energy storage investment cost for Seesaw ranges from 10-50 USD/kWh.  The installed capacity cost for Seesaw ranges from 800 and 1,500 USD/kW.  The global potential of Seesaw is evaluated.  A case study in Tokyo for offshore wind power storage.
... Batteries can only cover the short-term energy storage demand (Kusko and Dedad 2007). Today, the dominating technology for long-term electrical storage is pumped hydro (Hunt et al. 2020;Richter et al. 2020). ...
... For example, it may increase generation during a heatwave or provide black-start capabilities after a severe storm. Pumped hydro also has the potential to serve seasonal storage needs [95]. ...
Article
Full-text available
Political decarbonisation commitments and outcompeting renewable electricity costs are disrupting energy systems. This foresight study prepares stakeholders for this dynamic, reactive change by examining visions that constitute a probable, plausible and possible component of future energy systems. Visions were extrapolated through an expert review of energy technologies and Australian case studies. ‘Probable–Abundant’ envisages a high penetration of solar and wind with increased value of balancing services: batteries, pumped hydro and transmission. This vision is exemplified by the South Australian grid, where variable and distributed sources lead generation. ‘Plausible–Traded’ envisages power and power fuel exports given hydrogen and high-voltage direct-current transmission advances, reflected by public and private sector plans to leverage rich natural resources for national and intercontinental exchanges. ‘Possible–Zero’ envisages the application of carbon removal and nuclear technologies in response to the escalating challenge of deep decarbonisation. The Australian critical minerals strategy signals adaptations of high-emission industries to shifting energy resource values. These visions contribute a flexible, accessible framework for diverse stakeholders to discuss uncertain energy systems changes and consider issues from new perspectives. Appraisal of preferred futures allows stakeholders to recognise observed changes as positive or negative and may lead to new planning aspirations.
Article
The energy mix in Nepal is currently dominated by the traditional and inefficient use of biomass (66.54%) and fossil fuels (27.24%), and energy poverty remains extremely high. This paper reviews relevant literature to provide an overview of the current renewable energy status and energy mix in Nepal, and to discuss prospects for the country to achieve a sustainable energy transition. Nepal‐specific papers from peer‐reviewed sources and other agency and academic reports were included insofar as these discussed renewable energy and provided recommendations for policy‐making on sustainable energy and related development goals. Despite the rapidly falling cost of solar photovoltaic, the share of modern renewable energy in Nepal is currently less than 3%. On this basis, and given the country's sustainable energy goals, we conclude that favorable and aggressive policies and strategies are needed to support adoption of clean energy in Nepal, comprised of a high share of solar generation equipped with battery storage, and balanced with storage such as off‐river pumped hydropower technology.
Article
Seawater batteries are unique energy storage systems for sustainable renewable energy storage by directly utilizing seawater as a source for converting electrical energy and chemical energy. This technology is a sustainable and cost‐effective alternative to lithium‐ion batteries, benefitting from seawater‐abundant sodium as the charge‐transfer ions. Research has significantly improved and revised the performance of this type of battery over the last few years. However, fundamental limitations of the technology remain to be overcome in future studies to make this method even more viable. Disadvantages include degradation of the anode materials or limited membrane stability in aqueous saltwater resulting in low electrochemical performance and low Coulombic efficiency. The use of seawater batteries exceeds the application for energy storage. The electrochemical immobilization of ions intrinsic to the operation of seawater batteries is also an effective mechanism for direct seawater desalination. The high charge/discharge efficiency and energy recovery make seawater batteries an attractive water remediation technology. Here, the seawater battery components and the parameters used to evaluate their energy storage and water desalination performances are reviewed. Approaches to overcoming stability issues and low voltage efficiency are also introduced. Finally, an overview of potential applications, particularly in desalination technology, is provided. Seawater batteries enable simultaneous energy storage and water desalination. This review summarizes the recent advances in seawater batteries in energy storage and seawater desalination and analyses the relationship between the component and performance of seawater batteries. Such combined energy/water devices have great promise for sustainable technologies beyond lithium.
Article
Full-text available
Renewable energy (RE) is the key element of sustainable, environmentally friendly, and cost-effective electricity generation. An official report by International Energy Agency (IEA) states that the demand on fossil fuel usage to generate electricity has started to decrease since year 2019, along with the rise of RE usage to supply global energy demands. Researches on RE technologies are continuously growing in order to enhance the performance of RE generation, especially in term of energy conversion efficiency. The aim of this review paper is to understand and study further the current RE technologies such as solar energy, hydro energy, wind energy, bioenergy, geothermal energy, and hydrogen energy. Several hybrid RE technologies have been also studied and compared, to improve the overall performance of RE in generating electricity. Lastly, suggestions are provided for the purpose to solve and overcome the challenges and limitations of RE technologies in terms of economy, technical, and energy conversion efficiency.
Article
China's hydropower, with a total installed capacity of over 390 GW, is currently considered to be the most reliable flexibility resources to support the grid integration of wind and solar power with a total planned capacity of over 1200 GW. Fully exploiting hydropower flexibility is of great practical significance to China. This paper preliminarily evaluates the feasibility of transforming cascade hydropower stations to a large-scale cascade hydropower energy storage system (LCHES) via adding a pumping station between two adjacent upstream and downstream reservoirs. The pumping station can utilize excess electricity to recycle water potential energy between the two linked reservoirs. Taking cascade hydropower stations of a large hydro-wind-solar clean energy base (HWSCEB) in China as the case study, a simulation model is developed to simulate annual operation of LCHES at hourly resolution. The simulation results for the multi-year average representative year (2017) indicate that LCHES can effectively reduce the energy loss of HWSCEB, and store excess electricity of power grid during valley-electricity-price periods to realize price arbitrage; the overall efficiency of LCHES is approx.65%; LCHES is economically feasible only when the pumping station efficiency is greater than 55%. The performances of LCHES are further verified in different typical years.
Article
Full-text available
Pumped hydro energy storage (PHES) is the most widespread and mature utility-scale storage technology currently available and it is likely to remain a competitive solution for modern energy systems based on high penetration of solar PV and wind energy. This study estimates the technical potential of PHES in Iran through automatised GIS-based models based on four topologies. Two topologies focus on the transformation of existing reservoirs while the third topology which is developed based on permanent rivers of the country offers more alternative sites. The fourth topology assesses the potential of seawater PHES plants as a potential solution for regions characterised by freshwater scarcity. The TOPSIS method is applied to the discovered feasible sites to integrate an economic sensitivity into the evaluation process. Results show that Iran has a favourable topography for PHES and the technical potential of the studied topologies reaches up to 5108 GWh from 250 discovered sites, compared to the existing 5.1 GWh PHES capacity, while a maximum distance of 20 km is considered between reservoirs of a PHES plant.
Article
Full-text available
Pumped hydro energy storage is capable of large-scale energy time shifting and a range of ancillary services, which can facilitate high levels of photovoltaics and wind integration in electricity grids. This study aims to develop a series of advanced Geographic Information System algorithms to locate prospective sites for off-river pumped hydro across a large land area such as a state or a country. Two typical types of sites, dry-gully and turkey's nest, are modelled and a sequence of Geographic Information System-based procedures are developed for an automated site search. A case study is conducted for South Australia, where 168 dry-gully sites and 22 turkey's nest sites have been identified with a total water storage capacity of 441 gigalitres, equivalent to 276 gigawatt-hours of energy storage. This demonstrates the site searching algorithms can work efficiently in the identification of off-river pumped hydro sites, allowing high-resolution assessments of pumped hydro energy storage to be quickly conducted on a broad scale. The sensitivity analysis shows the significant influences of maximum dam wall heights on the number of sites and the total storage capacity. It is noted that the novel models developed in this study are also applicable to the deployments of other types of pumped hydro such as the locations of dry-gully and turkey's nest sites adjacent to existing water bodies, old mining pits and oceans.
Article
Full-text available
Hydropower is the most important renewable energy source to date, providing over 72% of all renewable electricity globally. Yet, only limited information is available on the global potential supply of hydropower and the associated costs. Here we provide a high-resolution assessment of the technical and economic potential of hydropower at a near-global scale. Using 15”×15” discharge and 3”×3” digital elevation maps, we built virtual hydropower installations at >3.8 million sites across the globe and calculated their potential using cost optimization methods. This way we identified over 60,000 suitable sites, which together represent a remaining global potential of 9.49 PWh yr⁻¹ below US$0.50 kWh⁻¹. The largest remaining potential is found in Asia Pacific (39%), South America (25%) and Africa (24%), of which a large part can be produced at low cost (<US$0.10 kWh⁻¹). In an ecological scenario, this potential is reduced to 5.67 PWh yr⁻¹.
Article
Full-text available
The increasing share of weather-dependent renewable energies in power systems creates a need for energy storage technologies to reduce the impacts of variable production. The most mature technology to store energy on the grid remains Pumped Hydro Energy Storage (PHES). The potential of high-energy sites has already been assessed in Europe by the EU JRC, considering mostly dams and reservoirs from global European databases which include only massive water bodies. This paper focuses on estimating the potential for small-PHES, proven to have lower environmental impact and an positive impact on grid balance and reliability. A generic method is designed, able to evaluate a global PHES storage capacity at large scale. It considers both existing lakes and natural depressions suitable to be filled for PHES purposes. The volume of filled lakes is estimated using the surrounding topography. The method is organized so that the “heavy” calculations, i.e. sink detection, volume evaluation, constraints verification, etc. are run only once. Consequently, the actual potential estimation phase only includes fast calculations and can be integrated in a loop for carrying out a sensitivity analysis. The proposed method is then applied considering France as a test case. Suitable environmental, land-use and structural constraints are applied to eliminate irrelevant sites. The analysis leads to an estimated value of the small-PHES potential in France, which ranges from 14 GWh when only existing lakes are considered to 33 GWh when lakes and depressions are considered. These estimations represent respectively 8% and 18% of the current hydro storage capacity in France. Thanks to a global sensitivity analysis, factors like the maximum distance between lakes, the maximum altitude of the sites, and the distance to the electrical grid are shown to have the most influence on the global evaluated potential, which is further sensitized. Lastly, another application is suggested that makes it possible to select the connections to be built first within a restricted area, based on a cost-per-energy-like approach. It uses the connections between reservoirs detected at large geographical scale.
Article
Full-text available
To improve the representation of surface and groundwater flows, global land surface models rely heavily on high-resolution digital elevation models (DEMs). River pixels are routinely defined as pixels with drainage areas that are greater than a critical drainage area (Acr). This parameter is usually uniform across the globe, and the dependence of drainage density on many environmental factors is often overlooked. Using the 15” HydroSHEDS DEM as an example, we propose the calibration of a spatially variable Acr as a function of slope, lithology, and climate, to match drainage densities from reference river networks at a 1:50,000 scale in France and Australia. Two variable Acr models with varying complexities were derived from the calibration, with satisfactory performances compared to the reference river networks. Intermittency assessment is also proposed. With these simple tools, river networks with natural heterogeneities at the 1:50,000 scale can be extracted from any DEM.
Article
Full-text available
Population growth, increasing energy demand and the depletion of fossil fuel reserves necessitate a search for sustainable alternatives for electricity generation. Hydropower could replace a large part of the contribution of gas and oil to the present energy mix. However, previous high-resolution estimates of hydropower potential have been local, and have yet to be applied on a global scale. This study is the first to formally present a detailed evaluation of the hydropower potential of each location, based on slope and discharge of each river in the world. The gross theoretical hydropower potential is approximately 52 PWh/year divided over 11.8 million locations. This 52 PWh/year is equal to 33% of the annually required energy, while the present energy production by hydropower plants is just 3% of the annually required energy. The results of this study: all potentially interesting locations for hydroelectric power plants, are available online.
Article
Renewable sources of energy are providing an increasing share of the electricity generation mix, but their intermittency drives a need for energy storage. At the same time, water resources are increasingly scarce due to changes in demand, such as from population growth, supply side pressures such as climate change and governance challenges relating to poor management. Large storage reservoirs are used for water management and for energy storage. However, some existing and proposed hydropower reservoirs require vast areas of land and have considerable social and environmental impacts. Growing concerns on water and energy storage from a water-energy-land nexus approach motivated this study. Our objective is to compare how energy and water storage services, such as hydropower generation, electricity grid and water management, are provided with Seasonal Pumped-Storage (SPS) and Conventional Reservoir Dams (CRD) plants. Our case study region is Brazil, a country with extensive hydropower capacity and development plans, for which we compare the cost, land requirement and social impacts between CRD and potential SPS plants. Whilst seasonal pumped-storage have higher capital costs than conventional reservoir dams, given the much lower land requirements and evaporative losses, they are a valuable water and energy storage alternative especially in locations with plain topography and high evaporation. Results show that if Sobradinho CRD was built today it would result in a $USD 1.46 billion loss, on the other hand, Muquém SPS plant would result in a $USD 0.67b revenue.
Article
Global demand for water, food and energy has seen the construction and planning of large dams continue at a steady pace in many parts of the world. However, the process of ‘exhaustively’ examining all potential dams sites within an area as part of an initial scoping study is still largely undertaken using manual methods. This paper describes DamSite, a series of novel algorithms that construct ‘virtual’ dam walls at every pixel along every channel within a catchment, including saddle dams where required by the terrain. By repetitively calculating dam and reservoir dimensions, reservoir yield and dam costs along a river network and for incrementally higher dam walls at each location it is possible to identify both optimal dam wall locations and optimal dam wall height at a given location. The DamSite model was tested in two catchments in northern Australia and accurately pin-pointed previously identified potential dam locations.