energies
Article
Tidal Current Power Resources and Influence of
Sea-Level Rise in the Coastal Waters of Kinmen
Island, Taiwan
Wei-Bo Chen 1, *, Hongey Chen 1,2 , Lee-Yaw Lin 1 and Yi-Chiang Yu 1
1
2
*
National Science and Technology Center for Disaster Reduction, New Taipei City 23143, Taiwan;
[email protected] (H.C.); [email protected] (L.-Y.L.); [email protected] (Y.-C.Y.)
Department of Geosciences, National Taiwan University, Taipei 10617, Taiwan
Correspondence: [email protected]; Tel.: +886-2-8195-8612
Academic Editor: Aristides Kiprakis
Received: 2 March 2017; Accepted: 4 May 2017; Published: 9 May 2017
Abstract: The tidal current power (TCP) resource, the impact of TCP extraction on hydrodynamics
and the influence of sea-level rise (SLR) on TCP output in the coastal waters of Kinmen Island (Taiwan)
are investigated using a state-of-the-art unstructured-grid depth-integrated numerical model. The
model was driven by eight tidal constituents extracted from a global tidal prediction model and
verified with time series of measured data for tide level and depth-averaged current. The simulations
showed reasonable agreement with the observations; the skill index was in the excellent (0.71–0.93)
range with regard to simulating tide level and currents. Model predictions indicated that the channel
between Kinmen and Lieyu serves as an appropriate site for deploying the tidal turbines because
of its higher tidal current and deeper water depth. The bottom friction approach was utilized to
compute the average TCP over a spring-neap cycle (i.e., 15 days). Mean TCP reached its maximum
to 45.51 kW for a coverage area of 0.036 km2 when an additional turbine friction coefficient (Ct )
increased to 0.08, and a cut-in speed of 0.5 m/s was used. The annual TCP output was estimated to
be 1.08 MW. The impact of TCP extraction on the change in current is significant, with a maximum
reduction rate of instant current exceeding 60%, and the extent of influence for the average current
is 1.26 km in length and 0.30 km in width for the −0.05 m/s contour line. However, the impact of
TCP extraction on the change in tide level is insignificant; the maximum change in amplitude is only
0.73 cm for the K2 tide. The influence of SLR on the TCP output in Kinmen waters was also estimated.
Modeling assessments showed that due to SLR produces faster tidal current, the annual TCP output
increased to 1.52 MW, 2.01 MW, 2.48 MW and 2.97 MW under the same cut-in speed and coverage
area conditions when SLR 0.25 m, SLR 0.5 m, SLR 0.75 m and SLR 1.0 m were imposed on the model.
Keywords: tidal current power; bottom friction approach; depth-integrated numerical model;
sea-level rise; Kinmen Island
1. Introduction
Global warming is expected to become more intense during this century due to the increasing
emissions of greenhouse gases [1]. The relationship between the burning of fossil fuels and climate
change is becoming more established. Therefore, renewable marine power resources, in the form of
tides, waves, tidal currents and sea temperature (thermal energy), are potential candidates for possible
energy sources [2,3]. The extraction of kinetic energy from tidal currents is a desirable form since it is
predictable, regular, and has a high energy density with low greenhouse gas emissions [4].
Recently, many researchers have made great efforts to identify the most appropriate locations for
the placement of tidal turbines and to assess how much tidal current power (TCP) can be extracted
Energies 2017, 10, 652; doi:10.3390/en10050652
www.mdpi.com/journal/energies
for the placement of tidal turbines and to assess how much tidal current power (TCP) can be
extracted from a specific site [5–7]. Tidal currents are highly dependent on the geographic
characteristics. For instance, a channel with varying cross-sections linking with two large water
bodies is usually rich in TCP [5–9]. In addition, tidal currents can be accelerated in the area around
a headland
tip652
[10–15].
Energies
2017, 10,
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Although tidal turbine operation has less negative influences on the marine environment, the
hydrodynamics of a tidal system, such as tide level and current speed, might change due to the
from
a specific
sitein[5–7].
Tidalsea
currents
are highly
onan
the
geographic
For
extraction
of TCP
a certain
or estuarine
area dependent
[2,16]. Thus,
assessment
ofcharacteristics.
the environmental
instance,
a
channel
with
varying
cross-sections
linking
with
two
large
water
bodies
is
usually
rich
in
impact should be conducted for a turbine farm before the deployment of tidal turbines. Although
TCP
[5–9].
In addition,
tidal
can be
accelerated
in the area
around
global
warming
may be
farcurrents
worse than
thought
and sea-level
rise
(SLR)aisheadland
expectedtip
to[10–15].
accelerate
Although
tidal
turbine
operation
has
less
negative
influences
on
the
marine
environment,
the
over the next century [17,18], few studies have concentrated on estimating the effect of SLR on TCP
hydrodynamics
of
a
tidal
system,
such
as
tide
level
and
current
speed,
might
change
due
to
the
output [19,20].
extraction
of TCP inhydrodynamic
a certain sea ormodel
estuarine
[2,16]. Thus,
the environmental
A numerical
is aarea
powerful
tool an
to assessment
assess the of
distribution
of TCP
impact
should
be
conducted
for
a
turbine
farm
before
the
deployment
of
tidal
turbines.
Although
resources; a two-dimensional model (2D model) is required for shallow coastal waters [7,21,22],
and
global
warming may model
be far worse
than thought
and for
sea-level
rise (SLR)
is expected
to accelerate
a three-dimensional
(3D model)
is required
the deep
sea [2,23,24].
In addition,
two
over
the nextare
century
[17,18],incorporated
few studies have
on estimating
the effect
SLR on
approaches
commonly
into concentrated
numerical models
to simulate
the of
effect
of TCP
TCP
output
[19,20].
extraction on hydrodynamics. The first method is the bottom friction approach, and a 2D model is
A numerical
hydrodynamic
model
a powerful
assess
theisdistribution
of TCP
resources;
generally
employed;
the presence
of is
tidal
turbinestool
in to
the
water
represented
by adding
an
aadditional
two-dimensional
model
(2D
model)
is
required
for
shallow
coastal
waters
[7,21,22],
and
a
bottom friction in the model [25,26]. The second method is the momentum-sink
three-dimensional
model
(3D
model)
is
required
for
the
deep
sea
[2,23,24].
In
addition,
two
approaches
approach, which usually adopts a 3D model; in this model, the momentum is diminished by adding
are
incorporated
into numerical
models to equations
simulate the
effect of
TCP extraction
on
the commonly
TCP extraction
effect terms
in the momentum
[2,23,24].
However,
these two
hydrodynamics.
The
first
method
is
the
bottom
friction
approach,
and
a
2D
model
is
generally
approaches produce similar results [24].
employed;
theIsland
presence
of tidalTaiwan),
turbines located
in the water
is represented
by adding
Kinmen
(Kinmen
just off
the southeastern
coastanofadditional
mainlandbottom
China
friction
in
the
model
[25,26].
The
second
method
is
the
momentum-sink
approach,
which
usually
2
(Figure 1a), covers an area of 153 km and has a population of 135,223 (2017). The Tashan Power
adopts
a 3D
in this
theon
momentum
is diminished
by adding
TCP
extraction
Plant (the
redmodel;
solid circle
in model,
Figure 1b)
Kinmen Island
is a fuel-fired
power the
plant
built
in 1967.
effect
terms
in thegeneration
momentumcapacity
equations
However,
approaches produce
similar
The total
power
of [2,23,24].
the Tashan
Power these
Plant two
is approximately
34 MW.
It is
results
[24].
currently inadequate for meeting the power resource demand for the residents of Kinmen Island.
Kinmen
(Kinmen from
Taiwan),
locatedwaters
just offofthe
southeastern
coast
of considered
mainland China
Therefore,
theIsland
TCP extracted
the coastal
Kinmen
Island has
been
as an
2 and has a population of 135,223 (2017). The Tashan Power
(Figure
1a),
covers
an
area
of
153
km
alternative power generation method because of its lower pollution.
PlantThe
(theobjectives
red solid circle
Figure
1b)ason
Kinmen
is a fuel-fired
power plant
built
in 1967. The
of thisinstudy
are
follows:
(1)Island
investigate
the distribution
of TCP
resources
and
total
power
generation
of the the
Tashan
Plant
is approximately
It isIsland;
currently
find an
appropriate
sitecapacity
for deploying
tidalPower
turbines
in the
coastal waters34
of MW.
Kinmen
(2)
inadequate
for
meeting
the
power
resource
demand
for
the
residents
of
Kinmen
Island.
Therefore,
the
calculate maximum mean TCP output over a spring-neap cycle using a high-resolution
TCP
extracted fromhydrodynamic
the coastal waters
of Kinmen
has been
as an
two-dimensional
model
for theIsland
turbine
site; considered
(3) evaluate
thealternative
impact ofpower
TCP
generation
method
because
of its
lower
pollution.
extraction on
the tide
level and
tidal
current;
and (4) assess the influence of SLR on TCP output.
Figure 1. Locations of: (a) the study area; and (b) tide level and current stations. The cyan area
Figure 1. Locations of: (a) the study area; and (b) tide level and current stations. The cyan area
represents ocean, while white areas are land.
represents ocean, while white areas are land.
2. Materials and Methods
The objectives of this study are as follows: (1) investigate the distribution of TCP resources and find
an
site Model
for deploying the tidal turbines in the coastal waters of Kinmen Island; (2) calculate
2.1.appropriate
Hydrodynamic
maximum mean TCP output over a spring-neap cycle using a high-resolution two-dimensional
hydrodynamic model for the turbine site; (3) evaluate the impact of TCP extraction on the tide level
and tidal current; and (4) assess the influence of SLR on TCP output.
Energies 2017, 10, 652
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2. Materials and Methods
2.1. Hydrodynamic Model
A state-of-the-art unstructured-grid hydrodynamic model called Semi-implicit Cross-scale
Hydroscience Integrated System Model (SCHISM), has been used to simulate tide levels and tidal
currents in the coastal waters of Kinmen Island. SCHISM is a modeling system that is a derivative
product of the original SELFE model [27], with many enhancements and upgrades, including a new
extension to the large-scale eddying regime and a seamless cross-scale capability from the creek to
ocean scale [28].
Similar to the SELFE model, SCHISM is based on an unstructured grid and is
designed for seamless simulation of three-dimensional baroclinic circulation across creek-lakeriver-estuary-shelf-ocean scales. A highly efficient, parallel computing, robust and accurate
semi-implicit finite-element/finite-volume method with an Eulerian-Lagrangian algorithm is
implemented in the SCHISM model to solve Reynolds-averaged Navier-Stokes equations for transport
of heat, salt and tracers. The wetting and drying scheme is naturally incorporated into the model for
inundation studies. Due to their highly flexible frameworks, the SELFE and SCHISM models have
been widely used to solve cross-scale problems: general circulation [29], storm surges [30], tsunami
hazards [31], water quality [32], oil spills [33], sediment transport [34,35], biogeochemistry [36,37],
and assessment of tidal stream energy resources [9,38]. A two-dimensional version of SCHISM,
SCHISM-2D, is employed in this study since Kinmen Island is surrounded by shallow coastal waters
(as shown in Figure 2a). The governing equations of the SCHISM-2D model with hydrostatic form and
Boussinesq approximation in the Cartesian coordinate system are given as follows:
∂η
∂uH
∂vH
+
+
=0
∂t
∂x
∂y
Du
∂
PA
τsx − τbx
= fv −
g(η − αψ̂) +
+
Dt
∂x
ρ
ρH
τsy − τby
Dv
∂
P
= −fu −
g(η − αψ̂) + A +
Dt
∂y
ρ
ρH
(1)
(2)
(3)
where η ( x, y, t) is the free-surface elevation; u( x, y, t) and v( x, y, t) are the depth-averaged velocity
in the x, y direction, respectively; f is the Coriolis factor; g is the acceleration due to gravity; ψ̂ is the
earth’s tidal potential; α is the effective earth elasticity factor; ρ is the density of water; PA ( x, y, t) is the
atmospheric pressure at the free surface; τsx and τsy refer to the wind shear stress in the x, y direction,
respectively; τbx and τby are the bottom shear stress in the x, y direction, respectively; and H = η + h,
where h( x, y) is the bathymetric depth. The formulas of the bottom shear stress are as follows:
τbx = ρ(Cd + Ct )
p
u2 + v2 u
(4a)
τby = ρ(Cd + Ct )
p
u2 + v2 v
(4b)
where Cd is the bottom drag coefficient, which is determined through model validation. Ct is an
additional bottom friction coefficient introduced by tidal turbine. Ct is equal to zero when turbine is
absent; while is greater than zero when turbine is present.
Energies 2017, 10, 652
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Figure 2. (a) Bathymetry; and (b) the unstructured grid of the computational domain.
Figure 2. (a) Bathymetry; and (b) the unstructured grid of the computational domain.
2.2. Calculation of Tidal Current Power
2.2. Calculation of Tidal Current Power
The extractable TCP over a tidal cycle (spring-neap cycle) for a turbine can usually be
The extractable TCP over a tidal cycle (spring-neap cycle) for a turbine can usually be estimated
estimated as follows:
as follows:
11
2
23 23/2
P =P = MρC
e (e (uu 2 +
M ρeCAe A
+ vv2 ) )
(5)(5)
22
where P is the tidal power extraction rate in watts; M is the number of turbines corresponding to
where P is the tidal power extraction rate in watts; M is the number of turbines corresponding to
the maximum average TCP output; Ce is the turbine thrust coefficient; and Ae is the swept area
the maximum average TCP output; C e is the turbine thrust coefficient; and Ae is the swept area
of the turbine. The over-bar above velocity
term indicates the time average over a spring-neap
of the turbine. The over-bar above velocity term indicates the time average over a spring-neap cycle.
cycle. Although Equation (5) has widely been used, the effects of additional bottom friction
Although Equation (5) has widely been used, the effects of additional bottom friction induced by
induced by turbine deployment on hydrodynamics cannot be appropriately represented. Garrett
turbine deployment on hydrodynamics cannot be appropriately represented. Garrett and Cummins
and Cummins [5] and Bryden and Couch [39] proposed that an additional drag term on the flow
[5] and Bryden and Couch [39] proposed that an additional drag term on the flow will arise from the
will arise from the deployment of turbines. The tidal current power output (Pt ) can be evaluated
deployment of turbines. The tidal current power output ( Pt ) can be evaluated considering the
considering the turbine-induced additional bottom friction coefficient
(Ct ) using the bottom friction
turbine-induced
additional bottom friction coefficient ( Ct ) using the bottom friction approach
approach
[9,19,21,25,40]:
Ct
[9,19,21,25,40]:
(6)
Pt = P
Ct + Cd
Ct
Pt =P
3/2
P = ρ(Cd + CtC
)(t u+2C+d v2 ) At
where At is the area covered by the tidal turbine field; 2u and
v are obtained from SCHISM-2D.
2 32
P = ρ ( Cd + Ct ) ( u + v
)
At
(6)
(7)
(7)
2.3. Model Configuration
where At is the area covered by the tidal turbine field; u and v are obtained from SCHISM-2D.
The computational domain covers the entire Kinmen Islands group, including Kinmen and Lieyu,
which are located just off the southeastern coast of mainland China and are surrounded by the Taiwan
2.3. Model Configuration
Strait (Figure 1a). A global gridded bathymetry dataset with a resolution of 30 arc-second obtained
computational
domain
covers
entire(GEBCO)
Kinmen was
Islands
Kinmen
and
from The
the General
Bathymetric
Chart
of thethe
Oceans
usedgroup,
in this including
study. It was
generated
Lieyu,
which are
located just off ship
the southeastern
coastwith
of mainland
China
and aresounding
surrounded
by
by
combining
quality-controlled
depth soundings
interpolation
between
points
the Taiwan
Strait (Figure 1a).
A global
gridded
bathymetry
with aof resolution
of 30
guided
by satellite-derived
gravity
data. The
modeling
domaindataset
is composed
197,020 triangle
arc-second
obtained
from the
General
Bathymetric
the Oceanswas
(GEBCO)
was
this
mesh
grid cells
and 100,714
nodes.
Coarse
mesh withChart
1000 of
m resolution
arranged
to used
open in
ocean
study. It was
byStrait,
combining
depth soundings
with
interpolation
boundaries
in generated
the Taiwan
while quality-controlled
fine mesh with 50ship
m resolution
was used
around
Kinmen
between
sounding
points
by satellite-derived
gravitythe
data.
The bathymetry
modeling domain
is
Island
(Figure
2b). Once
the guided
unstructured
grid was constructed,
gridded
data were
composed ofto197,020
triangle
gridSCHISM-2D
cells and 100,714
nodes.
Coarse
mesh with
1000 of
m
interpolated
each node
(Figuremesh
2a). The
model was
driven
by harmonic
constants
resolution
arranged
to open
boundaries
in
the
Taiwan
Strait,
while
fine
mesh
with
50
m
eight
majorwas
tidal
constituents
(Mocean
,
S
,
N
,
K
,
K
,
O
,
P
,
and
Q
),
which
were
extracted
from
the
2
2
2
2
1
1
1
1
resolution
wastidal
used
around
Kinmen
2b).
Once
unstructured
gridofwas
global
inverse
model,
TPXO
[41,42]. Island
A time(Figure
step of 60
s was
set the
to ensure
the stability
the
constructed,
the conditions
gridded bathymetry
data weremodel
interpolated
to free
eachsurface
node elevation
(Figure 2a).
The
model.
The initial
for the hydrodynamic
are the null
and null
SCHISM-2D
model was driven
by harmonic
constantsare
of not
eight
major tidal
(M2, S2,The
N2,
velocity.
Meteorological
and hydrological
conditions
considered
inconstituents
the current study.
K2, K1, O1, Pwere
1, and
Q1),run
which
were extracted
the global
inverse
tidal
model,inTPXO
[41,42]. A
simulations
only
in barotropic
mode,from
i.e., density
gradients
are
excluded
the model.
time step of 60 s was set to ensure the stability of the model. The initial conditions for the
hydrodynamic model are the null free surface elevation and null velocity. Meteorological and
Energies 2017, 10, 652
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2.4. Model Performance Indicators
Two criteria were used to evaluate the model performance for the simulation of tide level and the
depth-averaged tidal current, which are the mean absolute percentage error (MAPE) and the skill [43].
It should be noted that the MAPE can only be used when there are no zero value among observations.
The optimal value of the skill is 1, indicating perfect performance. A skill value ranging between 0.65
and 1.0 indicates excellent performance. Very good performance is in the range of 0.5–0.65; good
performance is in the range of 0.2–0.5; and a skill value less than 0.2 expresses poor performance [44]:
1 N Oio − Ois MAPE = ∑ × 100
N i =1
Oio n
(8)
2
∑ |Ois − Oio |
i =1
skill = 1 − n o
o 2
∑ Ois − O + Oio − O (9)
i =1
where N is the total number of data points; Ois is the simulation value; Oio is the measured data; and
o
O is the mean value of the measured data.
3. Results
3.1. Model Validation for Tide Level and Tidal Currents
The observational data provided by the Taiwan Central Weather Bureau were used to validate
the hydrodynamic model for predicting tide level and tidal currents (the gauging station locations
are shown in Figure 1b). The date was measured during the winter (from December 2016 to January
2017); this means that the observations are not affected by severe weather conditions (e.g., typhoon).
Although the northeast monsoon is sometimes stronger in this area in winter, the effects of winter
monsoon winds on tide level and depth-averaged tidal current are not significant. Because the Kinmen
buoy is placed at a location with the water depth of 20–25 m. In addition, the unusual values such as
−9999.0 were also filtered. The simulation period, a total of 29 days, was from 12 December 2016 to
9 January 2017. The first 14 days are designed to confirm that the model results will not be affected by
the initial conditions. Figure 3 shows the model-data comparison for tide level at Suetao (Figure 3a)
and Liaolowan (Figure 3b). Excellent agreement between the simulated and measured time series of
tide level is observed at these two tidal stations. The model performance in the tidal simulations is
illustrated in Table 1. The MAPE and skill values are 17.68% and 0.93 for Suetao and 15.41% and 0.93
for Liaolowan, respectively.
Table 1. Statistical errors of the model-data difference for tide levels and currents. MAPE: mean
absolute percentage error.
Suetau
Variables
Tide level
Current
Liaolowan
Kinmen Buoy
MAPE (%)
Skill
MAPE (%)
Skill
MAPE (%)
Skill
17.68
-
0.93
-
15.14
-
0.93
-
20.57
0.71
-: No data for comparison.
The predictions of the depth-averaged tidal currents for the Kinmen buoy were compared with
the measurements; the comparison results are presented in Figure 4. The results reveal that the
hydrodynamic model faithfully reproduces the peaks and phases of the tidal current. Table 1 indicates
that the MAPE is 20.57%, and the skill score of 0.71 indicates an excellent performance of the tidal current
monsoon winds on tide level and depth-averaged tidal current are not significant. Because the
Kinmen buoy is placed at a location with the water depth of 20–25 m. In addition, the unusual
values such as −9999.0 were also filtered. The simulation period, a total of 29 days, was from 12
December 2016 to 9 January 2017. The first 14 days are designed to confirm that the model results
will not
be10,
affected
by the initial conditions. Figure 3 shows the model-data comparison for6 of
tide
Energies
2017,
652
15
level at Suetao (Figure 3a) and Liaolowan (Figure 3b). Excellent agreement between the simulated
and measured time series of tide level is observed at these two tidal stations. The model
simulations.
bottom
coefficient
(Cd ) was determined
0.002
through
model
validation.
The
performanceThe
in the
tidal drag
simulations
is illustrated
in Table 1. as
The
MAPE
and skill
values
are 17.68%
SCHISM-2D
model
can
therefore
be
practically
applied
to
the
TCP
calculations.
and 0.93 for Suetao and 15.41% and 0.93 for Liaolowan, respectively.
Energies 2017, 10, 652
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Energies 2017, 10, 652
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Figure 3. Mode-data comparison for tide level at: (a) Suetau; and (b) Liaolowan.
The predictions of the depth-averaged tidal currents for the Kinmen buoy were compared with
the measurements; the comparison results are presented in Figure 4. The results reveal that the
hydrodynamic model faithfully reproduces the peaks and phases of the tidal current. Table 1
indicates that the MAPE is 20.57%, and the skill score of 0.71 indicates an excellent performance of
the tidal current simulations. The bottom drag coefficient ( Cd ) was determined as 0.002 through
model validation. The SCHISM-2D model can therefore be practically applied to the TCP
Figure 3. Mode-data comparison for tide level at: (a) Suetau; and (b) Liaolowan.
calculations. Figure 3. Mode-data comparison for tide level at: (a) Suetau; and (b) Liaolowan.
The predictions of the depth-averaged tidal currents for the Kinmen buoy were compared with
the measurements; the comparison results are presented in Figure 4. The results reveal that the
hydrodynamic model faithfully reproduces the peaks and phases of the tidal current. Table 1
indicates that the MAPE is 20.57%, and the skill score of 0.71 indicates an excellent performance of
the tidal current simulations. The bottom drag coefficient ( Cd ) was determined as 0.002 through
model validation. The SCHISM-2D model can therefore be practically applied to the TCP
calculations.
Figure
4. Mode-data
comparison
forfor
thethe
depth-averaged
current
at Kinmen
Buoy.
Figure
4. Mode-data
comparison
depth-averaged
current
at Kinmen
Buoy.
Table 1. Statistical errors of the model-data difference for tide levels and currents. MAPE: mean
The distribution of the average tidal current over a spring-neap cycle (i.e., 15 days) around Kinmen
absolute percentage error.
Island is shown in Figure 5a. A higher current is observed in a narrow channel between Kinmen and
Suetau
Liaolowan
Kinmen
Buoy
Lieyu, with a maximum current
exceeding 2.0 m/s. This
suggests that the area
is appropriate
for the
Variables
MAPE
(%)
MAPE
(%)
MAPE
(%)
Skill
Skill
Skill
deployment of tidal power turbines. Water depths in the range of 20–50 m are also a requirement, in
leveltidal velocity
17.68 [4]. Therefore,
0.93
15.14
additionTide
to high
Figure
5b shows a 0.93
desirable site (gray
box), with
an area
Current
20.57
0.71
2
2
of 35762.44Figure
m (0.036
km
),
depths
greater
than
20
m
and
average
velocity
of
0.43
m/s,
for
deploying
4. Mode-data comparison
for data
the depth-averaged
-: No
for comparison. current at Kinmen Buoy.
the turbines.
Tabledistribution
1. Statistical of
errors
the model-data
difference
tide levels and
currents.
MAPE:
mean
The
the of
average
tidal current
over for
a spring-neap
cycle
(i.e., 15
days)
around
absolute
percentage
error.
Kinmen Island is shown in Figure 5a. A higher current is observed in a narrow channel between
Kinmen and Lieyu, with a Suetau
maximum current exceeding
2.0 m/s. This suggests
that the area is
Liaolowan
Kinmen Buoy
Variables
appropriate for the deployment
turbines.
depths in
the range
20–50 m are
MAPE (%) of tidal
(%) Water
MAPE
(%) of Skill
SkillpowerMAPE
Skill
also a requirement,
tidal velocity
site
Tide level in addition
17.68 to high
0.93
15.14[4]. Therefore,
0.93 Figure 5b- shows a desirable
Current
0.71 velocity
(gray box),
with an area of- 35762.44 m-2 (0.036 km2),- depths greater
than 2020.57
m and average
of 0.43 m/s, for deploying the turbines. -: No data for comparison.
The distribution of the average tidal current over a spring-neap cycle (i.e., 15 days) around
Kinmen Island is shown in Figure 5a. A higher current is observed in a narrow channel between
Kinmen and Lieyu, with a maximum current exceeding 2.0 m/s. This suggests that the area is
appropriate for the deployment of tidal power turbines. Water depths in the range of 20–50 m are
also a requirement, in addition to high tidal velocity [4]. Therefore, Figure 5b shows a desirable site
Energies 2017, 10, 652
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Energies 2017, 10, 652
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Figure 5.5.(a)
(a)Distribution
Distribution
average
current
a spring-neap
cycle
days) Kinmen
around
Figure
of of
thethe
average
current
over over
a spring-neap
cycle (i.e.,
15(i.e.,
days)15around
Figure
5.
(a)
Distribution
of
the
average
current
over
a
spring-neap
cycle
(i.e.,
15
days)
around
Kinmen
Island;
and
(b)
turbine
deployment
site
(gray
box).
Island; and (b) turbine deployment site (gray box).
Kinmen Island; and (b) turbine deployment site (gray box).
3.2. Assessment
Assessment of
of Maximum
Maximum Tidal
Tidal Current Power
Power
3.2.
3.2. Assessment
of Maximum TidalCurrent
Current Power
According to a typical power curve, Robins et al. [45] assumed a cut-in velocity of 0.7 m/s and
According
to atotypical
power
[45] assumed
assumeda acut-in
cut-in
velocity
According
a typical
powercurve,
curve,Robins
Robins et
et al.
al. [45]
velocity
of of
0.70.7
m/sm/s
and and
rated velocity of 2.7 m/s in the evaluation of tidal current power. However, this was an idealized
rated
velocity
of
2.7
m/s
in
the
evaluation
of
tidal
current
power.
However,
this
was
an
idealized
rated velocity of 2.7 m/s in the evaluation of tidal current power. However, this was an idealized
representation of the potential performance of a turbine [46]. To assess the maximum potential TCP
representation
of the
potential
[46].To
Toassess
assess
the
maximum
potential
representation
of the
potentialperformance
performance of
of a turbine
turbine [46].
the
maximum
potential
TCPTCP
output
in
this
study,
the
cut-in
speed
was
therefore
set
to
0.5
m/s
[47]
and
the
rated
velocity
was
not
output
in this
study,
cut-in
speedwas
wastherefore
therefore set to 0.5
and
thethe
rated
velocity
waswas
not not
output
in this
study,
thethe
cut-in
speed
0.5 m/s
m/s[47]
[47]
and
rated
velocity
specified
because
the
average
tidal
currents
did
not
exceed
2.0
m/s
at
the
turbine
site.
specified
because
average
tidalcurrents
currentsdid
did not
not exceed
exceed 2.0
atat
thethe
turbine
site.site.
specified
because
thethe
average
tidal
2.0m/s
m/s
turbine
TheThe
depth-averaged
tidal
currents
were
calculated bybySCHISM-2D.
SCHISM-2D.
TCP
outputs
depth-averaged
tidal
currents
were
calculated
TCP
outputs
werewere
The depth-averaged tidal currents were calculated by SCHISM-2D. TCP outputs
were computed
computed
using
Equations
(6) and
(7);
coveredby
bythe
thetidal
tidal turbine
field
) was 35762.44
computed
using
Equations
andcovered
(7); the
the area
area
covered
( At )( A
was
tm2 35762.44
using
Equations
(6) and
(7); the(6)
area
by
the
tidal turbine
field turbine
(At ) wasfield
35762.44
(0.036 km2 ),
2
2
2
2
m (0.036
kmkm
), and
the
drag
incrementally
increased
from
to
0.24.
m
), and
theturbine
turbine
drag term
term ( Ct )increased
incrementally
from
0.04
to 0.24.
was
Ct Cdwas
Ct to
and
the(0.036
turbine
drag
term
(Ct ) incrementally
fromincreased
0.04
to 0.24.
Ct 0.04
was
added
in
added
in Equations
andthat
(4b),the
thisbottom
means that
thestress
bottom
shearbe
stress
would with
be increased
Equations
(4a)
and
(4b), this (4a)
means
shear
would
increased
increasing
Cin
added
to to
C
d Equations (4a) and (4b), this means that the bottom shear stress would be increased
d
C
,
and
consequently
slow
the
horizontal
velocity
in
the
hydrodynamic
model.
Each
simulation
was
with
increasing
,
and
consequently
slow
the
horizontal
velocity
in
the
hydrodynamic
model.
t
with increasing Ct ,Ctand consequently slow the horizontal velocity in the hydrodynamic model.
carried
out
for
each
value
of
C
.
In
this
way,
the
average
TCP
output
over
a
spring-neap
cycle
increased
t out for each value of C . In this way, the average TCP output over a
Each
simulation
was
carried
Each
simulation
was
carried
out for each value of Ct t . In this way, the average TCP output over a
withspring-neap
increasing C
,
resulting
in
a reduction of the average velocity. There is a limit to the available TCP
t
cycle increased with increasing Ct , resulting in a reduction of the average velocity.
spring-neap
with
increasing
resulting
in athe
reduction
of the
average
velocity.
Ct , but
output
as toocycle
manyincreased
turbines not
only
create drag
also slow
current and
therefore
reduce
the
There is a limit to the available TCP output as too many turbines not only create drag but also slow
There
is
a
limit
to
the
available
TCP
output
as
too
many
turbines
not
only
create
drag
but
also
slow
TCP output [4,17]. The maximum average TCP output is estimated to be 45.51 kW when Ct = 0.08,
the current and therefore reduce the TCP output [4,17]. The maximum average TCP output is
2 and
the estimated
current
therefore
reduce
the TCP
output
[4,17].mThe
maximum
average
TCPis output
is
cut-in
speed and
is
m/s, kW
turbine
area
is 35762.44
the average
velocity
0.33 m/s
to 0.5
be 45.51
whencoverage
Ct = 0.08 , cut-in speed is 0.5 m/s, turbine coverage area is 35762.44
estimated
to
be
45.51
kW
when
,
cut-in
speed
is
0.5
m/s,
turbine
coverage
area
is
35762.44
(as
shown
in
Figure
6).
This
indicates
that
the
annual
TCP
output
was
estimated
to
be
1.11
MW
C
=
0.08
t
m2 and the average velocity is 0.33
m/s (as shown in Figure 6). This indicates that the annual TCP
(45.51
kW
×
365/15/1000
=
1.11
MW)
theshown
turbine deployment
site. indicates
The results at
shown
in Figure 6
m2 and
the
average
velocity
is
0.33
m/sat
(as
6)./1000
This
the
output was estimated to be 1.11
MW
( 45.51 in
the annual
turbineTCP
kWFigure
× 365 /15
= 1.11 MW )that
are
similar
to
those
of
other
studies
for
the
calculations
of
TCP
output
using
numerical
models
output
was estimated
to be shown
1.11 MW
( 45.51
) at the
turbine
365 /15to/1000
MW studies
deployment
site. The results
in Figure
6 kW
are ×similar
those= 1.11
of other
for
the or
theoretical
methods
[5,9,19,21].
deployment
site.
Theoutput
results
shown
in Figure
similar methods
to those[5,9,19,21].
of other studies for the
calculations
of TCP
using
numerical
models6 orare
theoretical
calculations of TCP output using numerical models or theoretical methods [5,9,19,21].
Figure 6. Average TCP and its corresponding average current over a spring-neap cycle (i.e., 15 days)
Figure 6. Average TCP and its corresponding average current over a spring-neap cycle (i.e., 15 days) at
at the turbine deployment site.
the turbine deployment site.
Figure 6. Average TCP and its corresponding average current over a spring-neap cycle (i.e., 15 days)
at the turbine deployment site.
Energies 2017, 10, 652
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3.3. Influence of Tidal Current Power Extraction on Hydrodynamics
3.3. Influence
Influence of
of Tidal
TidalCurrent
CurrentPower
PowerExtraction
Extractionon
onHydrodynamics
Hydrodynamics
3.3.
TCP extraction may alter the hydrodynamics (e.g., tide level and currents) over an area where
TCP extraction
extraction may
may alter the
the hydrodynamics
hydrodynamics (e.g.,
(e.g., tide level
level and
and currents)
currents) over
over an
an area
area where
where
TCP
the turbines
are deployed.alter
To understand
the impacts oftide
turbine operation
on tidal dynamics,
time
the
turbines
are
deployed.
To
understand
the
impacts
of
turbine
operation
on
tidal
dynamics,
time
the turbines
are deployed.
Toofunderstand
the currents
impacts were
of turbine
operation
tidal
dynamics,
time
series
and spatial
differences
tide level and
compared
for anonarea
with
and without
series and
and spatial
spatial differences
differences of
of tide
tide level
level and
and currents
currents were
were compared
compared for
for an
an area
areawith
with andwithout
without
series
turbines.
Due to C
produced
the maximum
mean TCP
, Figure 7 depicts
a tidaland
water level
t = 0.08 produced the maximum mean TCP, Figure 7 depicts a tidal water level
turbines.
Due
to
C
=
0.08
t 0.08 produced the maximum mean TCP, Figure 7 depicts a tidal water level time
turbines. Due to Ct =
time series for Ct = 0 and Ct = 0.08 at the turbine site. The turbine-induced tide level change is
time series
the turbine
site.
The turbine-induced
tidechange
level change
is
series
for Ct for
= 0Cand
Cand
= 0.08
the at
turbine
site. The
turbine-induced
tide level
is minor;
Ct =at
0.08
t =0 t
minor;
the
difference
is
difficult
to
distinguish
in
Figure
7.
The
spatial
distribution
of
tide
level
the
difference
is difficultistodifficult
distinguish
in Figure 7.inThe
spatial
tide level differences
is
minor;
the difference
to distinguish
Figure
7. distribution
The spatial of
distribution
of tide level
differences
is shown
in Figure
8a.difference
The tide level
difference
atobtained
each node
was
obtained
fromlevel
the
shown
in
Figure
8a.
The
tide
level
at
each
node
was
from
the
average
tide
differences is shown in Figure 8a. The tide level difference at each node was obtained from the
average
tide level over
a spring-neap
cycle for
minus
that for Ct in
. The
differences
in
= 0.08
over
a spring-neap
Ct = 0.08 minus
The differences
average
tide level
t = 0.
average
tide level cycle
over afor
spring-neap
cycle that
for Cfor
minus
that for Ct ==0the
differences
in
0 . The
Ct t =C0.08
the
average
and
in
the
spatial
distribution
are
negligible,
between
Ct =tide
0.08 level
and Cbetween
spatial
distribution
are
negligible,
although
an
enlargement
of
the
C
=
0.08
C
=
0
t = 0 in the
the average tide level between Ct t = 0.08 and Ct t = 0 in the spatial distribution are negligible,
turbine site
shown in Figure
although
anisenlargement
of the8b.
turbine site is shown in Figure 8b.
although an enlargement of the turbine site is shown in Figure 8b.
Figure 7. Comparison of the time series of tide level between Ct = 0.0 and Ct = 0.08 at the turbine
Figure 7.7. Comparison
Comparison of
of the
the time
time series
series of
oftide
tidelevel
levelbetween
betweenCC
andCtC=
at the
the turbine
turbine
Figure
0.08 at
t t== 0.0 and
t = 0.08
deployment
site.
deployment
site.
deployment site.
Figure 8. (a) Spatial distribution of tide level (average tide level over a spring-neap cycle)
Figure8.8.(a)(a)
Spatial
distribution
of tide (average
level (average
tide
over a spring-neap
cycle)
Figure
Spatial
distribution
of tide
tide level
overlevel
a spring-neap
cycle) differences
differences
between
Kinmen
waters;
and (b) an enlarged
view of
Ct = 0.0 and
Ct = level
0.08 around
differences
between
and
around
Kinmen
waters;
and
(b)
an
enlarged
view
Ctt ==0.0
Ct =Kinmen
0.08
between C = 0.0 and C
0.08 around
waters; and (b) an enlarged view of the turbine site.of
the turbinet site.
the turbine site.
a very
reduction
in the tidal
Figure
9 demonstrates
TCP extraction
extractionproduced
produced
a noticeable
very noticeable
reduction
incurrent.
the tidal
current.
Figure 9a
TCP extraction produced a very noticeable reduction in the tidal current. Figure 9
time
series
of
the
depth-averaged
current
for
C
=
0
and
C
=
0.08
at
the
turbine
site.
The
maximum
t current for
t
demonstrates a time series of the depth-averaged
and
at the turbine site.
demonstrates a time series of the depth-averaged current for CCt t ==00 and CCt t ==0.08
at the turbine site.
0.08 waters;
instant
tidal
current
exceeded
1.1
m/s
when
the
turbines
are
absent
in
the
coastal
it
The maximum instant tidal current exceeded 1.1 m/s when the turbines are absent in however,
the coastal
The reduced
maximum
instant
tidal
current
exceeded
1.1
m/s when
the
turbines
are
absentnoting
in thethat
coastal
was
to
68%
due
to
the
presence
of
tidal
turbines
(i.e.,
C
=
0.08).
It
is
worth
the
t
waters; however, it was reduced to 68% due to the presence of tidal turbines (i.e., Ct = 0.08 ). It is
waters; however,
was reduced
to 68%was
due77%
to the
of tidalbetween
turbinesCt(i.e.,
It is
Ct = 0.08
decrease
in the timeit average
tidal current
for presence
the comparison
= 0 and
Ct =). 0.08
worth noting that the decrease in the time average tidal current was 77% for the comparison
(as
shown
in Figure
6). decrease
Figure 10a
spatial tidal
distribution
tidal
worth
noting
that the
in exhibits
the timetheaverage
current difference
was 77% of
forthe
theaverage
comparison
between Ct = 0 and Ct = 0.08 (as shown in Figure 6). Figure 10a exhibits the spatial distribution
current
cycle
Ct = in
0.08
minus6).CtFigure
= 0. The
of the
is 0.30 km
betweenover
and Ct = 0.08
(as for
shown
Figure
10aextent
exhibits
theinfluence
spatial distribution
Ct =a0spring-neap
difference
of 0.13
the average
tidalfor
current
overm/s
a spring-neap
for km
minus
. The
0.08
in
length and
in width
the −0.10
contour line,cycle
and 1.26
length
andCC
0.30
in
t = 0 km
difference
of the km
average
tidal current
over a spring-neap
cycle
for CCt t ==in
minus
. The
0.08
t =0
extent of the influence is 0.30 km in length and 0.13 km in width for the −0.10 m/s contour line, and
extent of the influence is 0.30 km in length and 0.13 km in width for the −0.10 m/s contour line, and
Energies
2017,
10,
652
Energies
Energies 2017,
2017, 10,
10, 652
652
999 of
of
15
of 15
15
1.26
1.26 km
km in
in length
length and
and 0.30
0.30 km
km in
in width
width for
for the
the −0.05
−0.05 m/s
m/s contour
contour line
line (as
(as shown
shown in
in Figure
Figure 10b).
10b). The
The
width
for
the
−
0.05
m/s
contour
line
(as
shown
in
Figure
10b).
The
installment
of
turbines
not only
installment
of
turbines
not
only
significantly
retards
the
tidal
current
but
also
affects
a
certain
area
installment of turbines not only significantly retards the tidal current but also affects a certain
area
significantly
retards
the tidal current
adjacent
TCP
site.
adjacent to
to the
the
TCP extraction
extraction
site. but also affects a certain area adjacent to the TCP extraction site.
Figure
9.
Comparison
time
series
of
the
current
between
and
at the
turbine
0.0
= 0.08
Figure 9.
9. Comparison
Comparison time
time series
series of
ofthe
thecurrent
currentbetween
betweenCt C
andCC
the turbine
turbine
t =
C=
0.0 and
Figure
0.08 at
at the
tCtt== 0.08
t =0.0
deployment
site.
deployment
site.
deployment site.
Figure
Figure 10.
10. (a)
(a) Spatial
Spatial distribution
distribution of
of current
current (average
(average current
current over
over aa spring-neap
spring-neap cycle)
cycle) differences
differences
Figure 10. (a) Spatial
distributionaround
of current
(average
current
over
a spring-neap
cycle)
differences
between
and
Kinmen
waters;
and
(b)
an
enlarged
view
of
the
turbine
=
0.0
C
=
0.08
between C
and
around
Kinmen
waters;
and
(b)
an
enlarged
view
of
the
turbine
t
t
C = 0.0
Ct =0.08
0.08around Kinmen waters; and (b) an enlarged view of the turbine
between Ct t= 0.0 and Ct =
site.
site.
site.
3.4. Influence of Sea-Level Rise on Tidal Current Power Output
3.4.
3.4. Influence
Influence of
of Sea-Level
Sea-Level Rise
Rise on
on Tidal
Tidal Current
Current Power
Power Output
Output
According to the Intergovernmental Panel on Climate Change (IPCC) AR5 report, the sea levels
According to
the Intergovernmental
Panel
on Climate
Change
(IPCC)
AR5
report, the
Panel
Change
(IPCC)
AR5
the sea
sea
couldAccording
rise 0.26 mtotothe
0.54Intergovernmental
m for RCP 2.6; 0.32
m toon
0.62Climate
m for RCP
4.5; 0.33
m to
0.62report,
m for RCP6.0;
levels
could
rise
0.26
m
to
0.54
m
for
RCP
2.6;
0.32
m
to
0.62
m
for
RCP
4.5;
0.33
m
to
0.62
m
for
levels
could
rise
0.26
0.54 mby
for2100
RCP[48].
2.6; 0.32
m to 0.62
for RCP
4.5;on
0.33
m to
0.62 m
for
and
0.45
m to
0.81
mm
fortoRCP8.5
Therefore
the m
effects
of SLR
TCP
output
were
RCP6.0;
and
0.45
m
to
0.81
m
for
RCP8.5
by
2100
[48].
Therefore
the
effects
of
SLR
on
TCP
output
RCP6.0;
and
0.45
m
to
0.81
m
for
RCP8.5
by
2100
[48].
Therefore
the
effects
of
SLR
on
TCP
output
assessed by conducting the scenario simulations for SLR 0.25 m, SLR 0.5 m, SLR 0.75 m and SLR 1.0 m.
were
assessed
by
conducting
the
simulations
for
SLR
m,
0.5
SLR 0.75
and
were
assessedthat
by the
conducting
the scenario
scenario
simulations
forregion
SLR 0.25
0.25
m, SLR
SLR
0.5 m,
m,
0.75 m
m and
and
We
assumed
tidal dynamics
outside
of the study
do not
change.
AllSLR
boundary
SLR
1.0
m.
We
assumed
that
the
tidal
dynamics
outside
of
the
study
region
do
not
change.
All
SLR
1.0
m.
We
assumed
that
the
tidal
dynamics
outside
of
the
study
region
do
not
change.
bathymetry conditions are kept constant except for increasing the water depth by 0.25 m, 0.5 m, 0.75All
m
boundary
and
bathymetry
conditions
are
kept
constant
except
for
increasing
the
water
depth
boundary
and the
bathymetry
conditions are
keptand
constant
except for increasing
the water approach
depth by
by
and
1.0 m over
entire computational
domain
open boundaries.
This straightforward
0.25
m,
m,
m
m
entire computational
domain
and
This
0.25been
m, 0.5
0.5
m, 0.75
0.75
m and
andto1.0
1.0
m over
over the
the
domain
and open
open boundaries.
boundaries.
This
has
widely
adopted
investigate
the entire
effectscomputational
of SLR on coastal
hydrodynamics
and tidal energy
straightforward
approach
has
been
widely
adopted
to
investigate
the
effects
of
SLR
on
coastal
straightforward
approach
has
been
widely
adopted
to
investigate
the
effects
of
SLR
on
coastal
resources [19,44,49,50]. TCP outputs were also calculated by Equations (6) and (7) with an incremental
hydrodynamics
and
TCP
2
hydrodynamics
and tidal
tidal energy
energy resources
resources [19,44,49,50].
[19,44,49,50].
TCP outputs
outputs were
were also
also calculated
calculated by
by
C
t , a cut-in speed of 0.5 m/s and At of 35762.44 m ; the depth-averaged tidal currents were obtained
2; the
Equations
(6)
and
(7)
with
an
incremental
,
a
cut-in
speed
of
0.5
m/s
and
of
3
5762.44
m
2
A
C
Equations
(6) andof(7)
with an incremental Ctt , a cut-in speed of 0.5 m/s and Att of 35762.44 m ; the
from
the outputs
SCHISM-2D.
depth-averaged
tidal
currents
were
from
the
depth-averaged
tidal currents
were obtained
obtained
fromcorresponding
the outputs
outputs of
oftoSCHISM-2D.
SCHISM-2D.
Figure 11 illustrates
the average
TCP outputs
different Ct values. The maximum
Figure
11
illustrates
the
average
TCP
outputs
corresponding
to
different
values.
Figure
illustrates
the average
TCPkW,
outputs
corresponding
to 121.94
different
values.
The
average
TCP11
output
is evaluated
to be 62.64
82.43 kW,
102.12 kW and
kWCCfor
SLR 0.25The
m,
t
t
maximum
average
TCP
output
evaluated
to
be
82.43
kW,
and
121.94
kW
SLR
0.5 m, 0.75
m and
SLR
1.0 m.is
sea
level,
the102.12
annualkW
TCP
output
increased
maximum
average
TCP
output
isCompared
evaluatedto
topresent-day
be 62.64
62.64 kW,
kW,
82.43
kW,
102.12
kW
and
121.94
kW for
for
SLR
0.25
m,
SLR
0.5
m,
0.75
m
and
SLR
1.0
m.
Compared
to
present-day
sea
level,
the
annual
TCP
to
1.52
MW,
2.01
MW,
2.48
MW
and
2.97
MW
under
the
SLR
0.25
m,
SLR
0.5
m,
SLR
0.75
m
and
SLR
SLR 0.25 m, SLR 0.5 m, 0.75 m and SLR 1.0 m. Compared to present-day sea level, the annual TCP
output
increased
to
2.01
MW,
2.48
MW
and
MW
the
SLR
m,
SLR
0.5
1.0
m scenarios,
respectively.
This
means
TCP due
the0.25
faster
output
increased
to 1.52
1.52 MW,
MW,
2.01
MW,that
2.48SLR
MWproduces
and 2.97
2.97higher
MW under
under
theto
SLR
0.25
m,tidal
SLRcurrent
0.5 m,
m,
SLR
0.75
m
and
SLR
1.0
m
scenarios,
respectively.
This
means
that
SLR
produces
higher
TCP
due
at
the
turbine
site
in
the
coastal
waters
of
Kinmen
Island
(Figure
12).
SLR 0.75 m and SLR 1.0 m scenarios, respectively. This means that SLR produces higher TCP due to
to
the
the faster
faster tidal
tidal current
current at
at the
the turbine
turbine site
site in
in the
the coastal
coastal waters
waters of
of Kinmen
Kinmen Island
Island (Figure
(Figure 12).
12).
Energies 2017, 10, 652
Energies 2017, 10, 652
10 of 15
10 of 15
Energies 2017, 10, 652
11 of 15
According to the numerical experiments conducted in Section 3.4, the maximum average TCP
was increased with SLR because a higher sea level produces faster tidal currents (as shown in
Figure 12). The momentum equations in Equations (2) and (3) can be used to explain this
phenomenon. The last term on the right-hand side of Equations (2) and (3) shows that the
horizontal velocities, u( x, y, t ) and v( x, y, t ) , are proportional to the total water depth ( H = η + h )
when the wind shear stresses ( τ sx and τ sy ) are excluded in the model. In other words, deeper water
depth (i.e., SLR) leads to faster tidal currents if the bottom drag coefficient remains constant. Lopes
and Dias [53] estimated the impacts of SLR on tidal dynamics for the Ria de Aveiro lagoon in
Portugal, using the ELCIRC 2D model. Chen and Liu [9] assessed the influences of SLR on tidal
Figure
11. Average
a spring-neap
cycle
(i.e.,
days)
for
present-day
sea
level,
sea-level
rise
Figure
11.
Average
TCPTCP
overover
a spring-neap
(i.e.,
1515
days)
for
present-day
level,
sea-level
rise
energy
output
for the
Taiwan
Strait.
The cycle
same
findings
were
also
found insea
their
studies,
suggesting
(SLR)
0.25
m,
SLR
0.5
m,
SLR
0.75
m
and
SLR
1.0
m,
and
its
corresponding
C
.
t
(SLR)SLR
0.25produces
m, SLR 0.5faster
m, SLR
0.75currents
m and SLR
1.0consequently
m, and its corresponding
Ct . output.
that
tidal
and
increases TCP
4. Discussion and Future Work
The effect of TCP extraction on the change in tide level is difficult to determine in the time
series and spatial difference figures (Figures 7 and 8). To quantify TCP extraction impact on tide
level change, harmonic analysis was conducted to extract the main eight tidal components for Ct = 0
(without TCP output) and Ct = 0.08 (with maximum mean TCP output) at the turbine site. Table 2
lists the amplitudes and phases of eight tidal constituents for Ct = 0 and Ct = 0.08 . The maximum
changes in amplitude and phase caused by turbines are only 0.73 cm and 0.77° for the K2 tide,
respectively. The change of tide level for TCP extraction is ignored in both qualitative and
quantitative analyses. Yang and Wang [51] compared the tide level changes of a tidal channel with
and without turbines. They found that TCP extraction had a minor influence on the tidal elevations.
Defne et al. [2] assessed the effects of TCP extraction on water level for an estuarine area, they
concluded that both the decrease in the maximum water level and the increase in the minimum are
kept below 0.05 m. Chen et al. [38] estimated the influences of TCP extraction on water level for the
Figure
12. Average
tidal
current over
aapproach.
spring-neapTheir
cyclestudy
(i.e., 15
days) found
for present-day
sea
level,
Taiwan
Strait
the
momentum
sink
results
that TCP
extraction
at
Figure
12. using
Average
tidal
current over
a spring-neap
cycle (i.e.,
15 days)
for present-day
sea level,
SLR
SLR 0.25 m, SLR 0.5 m, SLR 0.75 m and SLR 1.0 m, and its corresponding Ct .
a specific
could
significantly
tidalitscurrent,
but the
0.25 m,farm
SLR 0.5
m, SLR
0.75 m and affect
SLR 1.0the
m, and
corresponding
Ct .change in tidal amplitude and
tidal phase could be neglected. Plew and Stevens [52] also suggested that introducing turbines in
Uehara etand
al.Future
[54]
model
to investigate
tidal
andthrough
tide-dependent
theDiscussion
numerical
model
hasused
only aa two-dimensional
minor influence on
the difference
in water
level
the Tory
4.
Work
changes
in
the
northwest
European
shelf
seas
over
the
last
twenty
thousand
years.
They
adopted
Channel. This phenomenon might be due to the water level simulations are mainly determined
by
The effect ofto
TCP
extraction
on theof
change
inocean-tide
tide level is
difficult to
determine
in
the time of
series
two
approaches
consider
the
effect
future
variability
on
the
open
boundary
the
the tide elevations specified at open boundaries.
and
spatial difference
figures
(Figures
7 and
8). To state;
quantify
extraction
impact
on tide level
numerical
model. One
is fixed
to the
present
theTCP
other
is variable
according
to achange,
global
harmonic
analysis
was
conducted
to
extract
the
main
eight
tidal
components
for
C
=
0 (without
paleotidal
They found
that of
theeight
M2 amplitude
only increases
byand
1.0 Ct
m =(0.9–1.9
m) turbine
in
the west
Table model.
2. Amplitudes
and phases
tidal constituents
for Ct = 0.00
0.08 at tthe
TCP
output)
and
(with maximum
output)
at the
turbinechanges
site. Table
2 liststides
the
t = 0.08twenty
of the
Sea
through
thousand mean
years. TCP
Although
more
realistic
in shelf
siteCeltic
yielded
byC
harmonic
analysis.
amplitudes
and
phases
of
eight
tidal
constituents
for
C
=
0
and
C
=
0.08.
The
maximum
changes
in
t
t
during ten thousand years can be obtained in this way, the variation of tidal amplitude
might be
o)
Amplitude
(m)
Phase
(
◦
amplitude
and
phase
turbines
are onlyto0.73
cm and
for the K
tide, respectively.
The
Constituent
small Tidal
100 years
from caused
now. It by
would
be sensible
assume
that0.77
the change
of2 tidal
amplitudes from
Ct = 0.00
Ct = 0.08
Ct = 0.00
Ct = 0.08
change
of
tide
level
for
TCP
extraction
is
ignored
in
both
qualitative
and
quantitative
analyses.
Yang
2017 to 2100 is ignorable. Therefore, we compared the TCP output between present-day sea level
M2
2.4714
2.4678
114.5893
114.8391
and
compared the tide
level changes
of a tidal
channel
and without
turbines.
They
and Wang
future [51]
SLR
boundary
conditions
in the
model.with
However,
modeling
assessment
S2 using the same0.7518
0.7474
159.1727
159.7660
found
thathydrodynamics
TCP extractionmight
had a minor
influence
the tidal projections
elevations. of
Defne et al. [2]variations
assessed the
of future
be more
faithful on
if accurate
for
N2
0.5004
0.4987
97.1582 future tide97.4440
effects
of
TCP
extraction
on
water
level
for
an
estuarine
area,
they
concluded
that
both
the
decrease
in
model boundary
available.
0.2227
138.5008
139.2686
K2 conditions are0.2300
the maximum
water
level
and
the
increase
in
the
minimum
are
kept
below
0.05
m.
Chen
et
al.
[38]
0.5387 a series of 0.5422
165.6684
K1 Green [19] conducted
Pelling and
numerical experiments
to assess the165.0175
SLR influence
estimated
theOinfluences
TCPof
extraction
water
level for
Taiwan
Strait using
the
momentum
1
0.3885
0.3878
124.8016
124.7191
on TCP output
for the of
Gulf
Maine. Inontheir
study,
SLRthe
was
implemented
according
to two
1 Their study results
0.0765
0.0719
124.7396
125.4009
P
sink
approach.
found
that
TCP
extraction
at
a
specific
farm
could
significantly
approaches. The first approach was to increase the water depth over the entire model domain and
Q1current,
0.0644
0.0634 (referred
102.4989
affect
tidal
but on
thethe
change
amplitude
and tidal
phase
neglected.
Plew
allow the
low-lying
elements
landintotidal
be flooded
to 102.3196
as
the could
‘floodbe
run’).
The second
method was the same as the first except that no area was allowed to be flooded (referred to as the
‘no-flood run’). They found that the no-flood run produced higher maximum power output than
the flood run for the Minas Passage. This is because TCP became dissipated when new
shallow-water areas were created in the flood run. The difference in maximum TCP output is only
8.7% between these two approaches for the Minas Passage. Ward et al. [49] used the flood run
Energies 2017, 10, 652
11 of 15
and Stevens [52] also suggested that introducing turbines in the numerical model has only a minor
influence on the difference in water level through the Tory Channel. This phenomenon might be due to
the water level simulations are mainly determined by the tide elevations specified at open boundaries.
Table 2. Amplitudes and phases of eight tidal constituents for Ct = 0.00 and Ct = 0.08 at the turbine site
yielded by harmonic analysis.
Phase (o )
Amplitude (m)
Tidal Constituent
M2
S2
N2
K2
K1
O1
P1
Q1
Ct = 0.00
Ct = 0.08
Ct = 0.00
Ct = 0.08
2.4714
0.7518
0.5004
0.2300
0.5387
0.3885
0.0765
0.0644
2.4678
0.7474
0.4987
0.2227
0.5422
0.3878
0.0719
0.0634
114.5893
159.1727
97.1582
138.5008
165.6684
124.8016
124.7396
102.3196
114.8391
159.7660
97.4440
139.2686
165.0175
124.7191
125.4009
102.4989
According to the numerical experiments conducted in Section 3.4, the maximum average TCP was
increased with SLR because a higher sea level produces faster tidal currents (as shown in Figure 12).
The momentum equations in Equations (2) and (3) can be used to explain this phenomenon. The last
term on the right-hand side of Equations (2) and (3) shows that the horizontal velocities, u( x, y, t) and
v( x, y, t), are proportional to the total water depth (H = η + h) when the wind shear stresses (τsx and
τsy ) are excluded in the model. In other words, deeper water depth (i.e., SLR) leads to faster tidal
currents if the bottom drag coefficient remains constant. Lopes and Dias [53] estimated the impacts of
SLR on tidal dynamics for the Ria de Aveiro lagoon in Portugal, using the ELCIRC 2D model. Chen and
Liu [9] assessed the influences of SLR on tidal energy output for the Taiwan Strait. The same findings
were also found in their studies, suggesting that SLR produces faster tidal currents and consequently
increases TCP output.
Uehara et al. [54] used a two-dimensional model to investigate tidal and tide-dependent changes in
the northwest European shelf seas over the last twenty thousand years. They adopted two approaches
to consider the effect of future ocean-tide variability on the open boundary of the numerical model.
One is fixed to the present state; the other is variable according to a global paleotidal model. They
found that the M2 amplitude only increases by 1.0 m (0.9–1.9 m) in the west of the Celtic Sea through
twenty thousand years. Although more realistic changes in shelf tides during ten thousand years can
be obtained in this way, the variation of tidal amplitude might be small 100 years from now. It would
be sensible to assume that the change of tidal amplitudes from 2017 to 2100 is ignorable. Therefore, we
compared the TCP output between present-day sea level and future SLR using the same boundary
conditions in the model. However, modeling assessment of future hydrodynamics might be more
faithful if accurate projections of future tide variations for model boundary conditions are available.
Pelling and Green [19] conducted a series of numerical experiments to assess the SLR influence on
TCP output for the Gulf of Maine. In their study, SLR was implemented according to two approaches.
The first approach was to increase the water depth over the entire model domain and allow low-lying
elements on the land to be flooded (referred to as the ‘flood run’). The second method was the same
as the first except that no area was allowed to be flooded (referred to as the ‘no-flood run’). They
found that the no-flood run produced higher maximum power output than the flood run for the Minas
Passage. This is because TCP became dissipated when new shallow-water areas were created in the
flood run. The difference in maximum TCP output is only 8.7% between these two approaches for
the Minas Passage. Ward et al. [49] used the flood run method to investigate the impact of SLR on
tidal dynamics for the European shelf; they also suggested that different way to implement SLR in the
model shown a significant effect on response of tide. Although the flood run approach is much more
realistic than the no-flood run approach, we can only adopt the latter due to the scarcity of accurate
Energies 2017, 10, 652
12 of 15
topography data and land-use data for Kinmen Island and Lieyu Island. In other words, we can
suppose that an actual average maximum TCP might be 41.55 kW (45.51 × (1 − 0.087) = 41.55 kW)
in the Kinmen coastal waters if the flood run were used.
Due to the amount of TCP output is small and semi-diurnal intermittency of tidal current at the
turbine deployment site in the Kinmen coastal waters; it might be possible to conduct storage into
the supergrid [15,55]. Besides, Neill et al. [56] proposed that optimization of the TCP and finding
the optimal site for parallel development for relative low number of arrays are import for large scale
exploitation of TCP and should be conducted in the future work. In addition, Lewis et al. [57] found
that the wave-current interaction could potentially alter tidal currents and should be included in
hydrodynamic models in future studies.
Using a combination of Equations (5) and (7) to obtain the number of turbines is too simple when
maximum mean TCP output was given. Myers and Bahaj [58] and Mestres et al. [59] suggested that
the separation between both rows is taken as 10 times the dimeter of the tidal turbine rotor and the
inter-lateral turbine separation 2.5 times the diameter. The configuration of tidal turbine array should
be carefully considered before the construction of tidal turbine farm; however this requires further
examination, which is beyond the scope of this paper.
5. Conclusions
The hydrodynamics in the coastal waters of Kinmen Island have been simulated using a
state-of-the-art unstructured-grid depth-integrated numerical model, SCHISM-2D. The simulations
were verified with tide level and depth-averaged tidal current measurements, showing a reasonable
agreement with the observations. The validated model was then applied to evaluate TCP resources and
appropriate sites for deploying tidal turbines around the coastal waters of Kinmen Island. A narrow
channel between Kinmen and Lieyu was found to be a suitable area for turbine deployment because of
its higher mean tidal current. The site has an area of 0.036 km2 , depth greater than 20 m and average
velocity of 0.43 m/s, making it suitable as a tidal current turbine farm. The bottom friction approach
was employed to calculate the mean TCP over a spring-neap cycle. The maximum average TCP output
is estimated as 45.51 kW when the additional turbine friction coefficient Ct = 0.08, cut-in speed is
0.5 m/s and average velocity is 0.33 m/s. The impacts of TCP extraction on hydrodynamics were also
estimated. The TCP extraction effect can be ignored for tide level but shows a significant reduction
in tidal currents. We found that the installation of turbines not only retarded tidal currents but also
affected a certain area near the TCP extraction site. Four SLR scenarios, SLR 0.25 m, SLR 0.5 m, SLR
0.75 m and SLR 1.0 m, were conducted to investigate the influence of SLR on TCP output. Compared to
the present-day sea-level condition, the annual TCP output increased to 1.52 MW, 2.01 MW, 2.48 MW
and 2.97 MW for SLR 0.25 m, SLR 0.5 m, SLR 0.75 m and SLR 1.0 m, respectively, due to the faster
tidal current. Acceptable simulations of tidal dynamics for the coastal waters of Kinmen Island were
accomplished in this study, however, there are still many uncertainties associated with tidal current
simulations, and TCP calculation should be further considered in the future.
Acknowledgments: This research was funded by the Ministry of Science and Technology (MOST), Taiwan, grant
No. MOST 105-2625-M-865-002. The authors would like to thank the Central Weather Bureau, Taiwan, for
providing the measurements, and Joseph Zhang of the Virginia Institute of Marine Science, College of William &
Mary, for kindly sharing his experiences of using the numerical model.
Author Contributions: Hongey Chen, Lee-Yaw Lin, Yi-Chiang Yu and Wei-Bo Chen conceived the study, and
Wei-Bo Chen performed the model simulations. The final manuscript has been read and approved by all authors.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Solomon, S.; Qin, D.; Manning, M.; Chen, Z.; Marquis, M.; Averyt, K.B.; Tignor, M.; Miller, H.L. Climate
Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2007.
Energies 2017, 10, 652
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
13 of 15
Defne, Z.; Hass, K.A.; Fritz, H.M. Numerical modeling of tidal currents and the effects of power extraction
on estuarine hydrodynamics along the Georgia coast, USA. Renew. Energy 2011, 36, 3461–3471. [CrossRef]
Lewis, M.J.; Angeloudis, A.; Robins, P.E.; Evans, P.S.; Neill, S.P. Influence of storm surge on tidal range
energy. Energy 2017, 122, 25–36. [CrossRef]
Lewis, M.; Neill, S.P.; Robins, P.E.; Hasheme, M.R. Resource assessment for future generations of tidal-stream
energy arrays. Energy 2015, 83, 403–415. [CrossRef]
Garrett, C.; Cummins, P. The power potential of tidal currents in channels. Proc. R. Soc. A 2005, 461,
2563–2572. [CrossRef]
Polagye, B.; Kawase, M.; Malte, P. In-stream tidal energy potential of Puget Sound, Washington. Proc. Inst.
Mech. Eng. Part A 2009, 223, 571–587. [CrossRef]
Walkington, I.; Burrows, R. Modelling tidal stream power potential. Appl. Ocean Res. 2009, 31, 239–245.
[CrossRef]
Chen, W.-B.; Liu, W.-C.; Hsu, M.-H. Modeling assessment of tidal current energy at Kinmen Island, Taiwan.
Renew. Energy 2013, 50, 1073–1082. [CrossRef]
Chen, W.-B.; Liu, W.-C. 2017 Assessing the influence of sea level rise on tidal power output and tidal energy
dissipation near a channel. Renew. Energy 2017, 101, 603–616. [CrossRef]
Carballo, R.; Iglesias, G.; Castro, A. Numerical model evaluation of tidal stream energy resources in the Ria
de Muros (NW Spain). Renew. Energy 2009, 34, 1517–1524. [CrossRef]
Xia, J.; Falconer, R.A.; Lin, B. Numerical model assessment of tidal stream energy resources in the Severn
Estuary, UK. Proc. Inst. Mech. Eng. Part A 2010, 224, 969–983. [CrossRef]
Blunden, L.S.; Bahaj, A.S.; Aziz, N.S. Tidal current power for Indonesia? An initial resource estimation for
the Alas Strait. Renew. Energy 2013, 49, 137–142. [CrossRef]
Chen, Y.; Lin, B.; Lin, J.; Wang, S. Effect of stream turbine array configuration on tidal current energy
extraction near an island. Comput. Geosci. 2015, 77, 20–28. [CrossRef]
Robins, P.E.; Neill, S.P.; Lewis, M.J.; Ward, S.L. Characterising the spatial and temporal variability of the
tidal-stream energy resources over the northwest European shelf seas. Appl. Energy 2015, 147, 510–522.
[CrossRef]
Easton, M.C.; Woolf, D.K.; Bowyer, P. The dynamics of an energetic tidal channel, the Pentland Firth, Scotland.
Cont. Shelf Res. 2012, 48, 50–60. [CrossRef]
Neill, S.P.; Jordan, J.R.; Couch, S.J. Impact of tidal energy converter (TEC) arrays on the dynamics of headland
sand. Renew. Energy 2012, 37, 387–397. [CrossRef]
Church, J.A.; White, N.J. A 20th century acceleration in global sea-level rise. Geophys. Res. Lett. 2006, 33,
L01602. [CrossRef]
Woodworth, P.; Gehrels, W.; Nerem, R. Nineteenth and twentieth century changes in sea level. Oceanography
2011, 24, 80–93. [CrossRef]
Pelling, H.E.; Green, A.M. Sea level rise and tidal power plants in the Gulf of Maine. J. Geophys. Res. Ocean.
2013, 118, 2863–2873. [CrossRef]
Tang, H.S.; Kraatz, S.; Qu, K.; Chen, G.Q.; Aboobaker, N.; Jiang, C.B. High-resolution survey of tidal energy
towards power generation grid and influence of sea-level-rise: A case study at coast of New Jersey, USA.
Renew. Sustain. Energy Rev. 2014, 32, 960–982. [CrossRef]
Karsten, R.; McMillan, J.; Lickley, M.; Haynes, R. Assessment of tidal current energy in the Minas Passage,
Bay of Fundy. Proc. Inst. Mech. Eng. Part A 2008, 222, 493–507. [CrossRef]
Draper, S.; Houlsby, G.; Oldfield, M.; Borthwick, A. Modeling tidal energy extraction in a depth-averaged
coastal plain. In Proceedings of the 8th European Wave and Tidal Energy Conference, Uppsala, Sweden,
7–10 September 2009.
Hasegawa, D.; Sheng, J.; Greenburg, D.A.; Thompson, K.R. Far-field effects of tidal energy extraction in
the Minas Passage on tidal circulation in the Bay of Fundy and Gulf of Maine using a nested-grid coastal
circulation model. Ocean Dyn. 2011, 61, 1845–1868. [CrossRef]
Yang, Z.; Wang, T.; Copping, A.E. Modeling tidal stream energy extraction and its effect on transport
processes in a tidal channel and bay system using a three-dimensional coastal ocean model. Renew. Energy
2013, 50, 605–613. [CrossRef]
Sutherland, G.; Foreman, M.; Garrett, C. Tidal current energy assessment for Johnstone Strait, Vancouver
Island. Proc. Inst. Mech. Eng. Part A 2007, 221, 147–157. [CrossRef]
Energies 2017, 10, 652
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
14 of 15
Atwater, J.; Lawrence, G. Power potential of a split channel. Renew. Energy 2010, 35, 329–332. [CrossRef]
Zhang, Y.; Baptista, A.M. SELFE: A semi-implicit Eulerian-Lagrangian finite-element mode for cross-scale
ocean circulation. Ocean Model. 2008, 21, 71–96. [CrossRef]
Zhang, Y.; Ye, F.; Stanev, E.V.; Grashorn, S. Seamless cross-scale modelling with SCHISM. Ocean Model. 2016,
102, 64–81. [CrossRef]
Zhang, Y.; Ateljevich, E.; Yu, H.S.; Wu, C.H.; Yu, J.C.S. A new vertical coordinate system for a 3D
unstructured-grid model. Ocean Model. 2015, 85, 16–31. [CrossRef]
Bertin, X.; Li, K.; Roldan, A.; Zhang, Y.J.; Breilh, J.F.; Chaumillion, E. A modeling-based analysis of the
flooding associated with Xynthia, central Bay of Biscay. Coast. Eng. 2014, 94, 80–89. [CrossRef]
Zhang, Y.; Witter, R.; Priest, G.R. Tsunami-tide interaction in 1964 Prince William Sound tsunami. Ocean Model.
2011, 40, 246–259. [CrossRef]
Chen, W.; Liu, W. Investigating the fate and transport of fecal coliform contamination in a tidal estuarine
system using a three-dimensional model. Mar. Pollut. Bull. 2017, 116, 365–384. [CrossRef] [PubMed]
Azevedo, A.; Oliverira, A.; Fortunato, A.B.; Zhang, Y.; Baptista, A.M. A cross-scale numerical modeling
system for management support of oil accidents. Mar. Pollut. Bull. 2014, 80, 132–147. [CrossRef] [PubMed]
Pinto, L.; Fortunato, A.B.; Zhang, Y.; Oliverira, A.; Sancho, F.E.P. Development and validation of a
three-dimensional morphodynamic modelling system. Ocean Model. 2012, 57–58, 1–14.
Chen, W.-B.; Liu, W.-C.; Hsu, M.-H.; Hwang, C.-C. Modelling investigation of suspended sediment transport
in a tidal estuary using a three-dimensional model. Appl. Math. Model. 2015, 39, 2570–2586. [CrossRef]
Rodrigues, M.; Oliveira, A.; Queiroga, H.; Fortunato, A.B.; Zhang, Y.J. Three-dimensional modeling of the
lower trophic levels in the Ria de Aveiro (Portugal). Ecol. Model. 2009, 220, 1274–1290. [CrossRef]
Rodrigues, M.; Oliveira, A.; Guerreior, M.; Fortunato, A.B.; Menaia, J.; David, L.M.; Cravo, A. Modeling fecal
contamination in the Aljezur coastal stream (Portugal). Ocean Dyn. 2011, 61, 841–856. [CrossRef]
Chen, W.B.; Liu, W.C.; Hsu, M.H. Modeling evaluation of tidal stream energy and the impacts of energy
extraction on hydrodynamics in the Taiwan Strait. Energies 2013, 6, 2191–2203. [CrossRef]
Bryden, I.G.; Couch, S. ME1-marine energy extraction: Tidal resource analysis. Renew. Energy 2006, 31,
133–139. [CrossRef]
Blanchfield, J.; Garrett, C.; Wild, P.; Rowe, A. The extractable power from a channel linking a bay to the open
ocean. Proc. Inst. Mech. Eng. Part A 2008, 222, 289–297. [CrossRef]
Egbert, G.D.; Erofeeva, S.Y. Efficient inverse modeling of barotropic ocean tides. J. Atmos. Ocean. Technol.
2002, 19, 183–204. [CrossRef]
Egbert, G.D.; Erofeeva, S.Y.; Ray, D.R. Assimilation of altimetry data for nonlinear shallow-water tides:
Quarter-diurnal tides of the Northwest European Shelf. Cont. Shelf Res. 2010, 30, 668–679. [CrossRef]
Willmott, C. On the validation of models. Phys. Geogr. 1981, 2, 184–194.
Chen, W.; Chen, K.; Kuang, C.; Zhu, D.; He, L.; Mao, X.; Liang, H.; Song, H. Influence of sea level rise on
saline water instruction in the Yangtze River Estuary, China. Appl. Ocean Res. 2016, 54, 12–25. [CrossRef]
Robins, P.E.; Neill, S.P.; Lewis, M.J. Impact of tidal-stream arrays in relation to the natural variability of
sedimentary processes. Renew. Energy 2014, 72, 311–321. [CrossRef]
Neill, S.P.; Litt, E.J.; Couch, S.J.; Davies, A.G. The impact of tidal stream turbines on large-scale sediment
dynamics. Renew. Energy 2009, 34, 2803–2812. [CrossRef]
Thiebaut, M.; Sentchev, A.; Schmitt, F.G. Assessing the turbulence in a tidal estuary and the effect of
turbulence on marine current turbine performance. In Progress in Renewable Energies Offshore; Guedes, S., Ed.;
Taylor & Francis Group: London, UK, 2016.
Intergovernmental Panel on Climate Change (IPCC). Working Group I Contribution to the IPCC Fifth Assessment
Report; IPCC: Geneva, Switzerland, 2013.
Ward, S.; Green, J.; Pelling, H. Tides, sea-level rise and tidal power extraction on the European shelf.
Ocean Dyn. 2012, 62, 1153–1167. [CrossRef]
Blanton, J. Energy dissipation in a tidal estuary. J. Geophys. Res. Ocean Atmos. 1969, 74, 5460–5466. [CrossRef]
Yang, Z.; Wang, T. Modeling the effects of tidal energy extraction on estuarine hydrodynamic in a stratified
estuary. Estuar. Coast. 2015, 38 (Suppl. 1), S187–S202. [CrossRef]
Plew, D.R.; Stevens, C.L. Numerical modelling of the effect of turbines on currents in a tidal channel-Tory
Channel, New Zealand. Renew. Energy 2013, 57, 269–282. [CrossRef]
Energies 2017, 10, 652
53.
54.
55.
56.
57.
58.
59.
15 of 15
Lopes, C.L.; Dias, J.M. Influence of mean sea level rise on tidal dynamics of the Ria de Aveiro lagoon,
Portugal. J. Coast. Res. 2014, 70, 574–579. [CrossRef]
Uehara, K.; Scourse, J.D.; Horsburgh, K.J.; Lambeck, K.; Purcell, A.P. Tidal evolution of the northwest
European shelf seas from the last glacial maximum to the present. J. Geophys. Res. 2006, 111, C09025.
[CrossRef]
Neill, S.P.; Hashemi, M.R.; Lewis, M.J. Tidal energy leasing and tidal phasing. Renew. Energy 2016, 85,
580–587. [CrossRef]
Neill, S.P.; Hashemi, M.R.; Lewis, M.J. Optimal phasing of the European tidal stream resource using the
greedy algorithm with penalty function. Energy 2014, 73, 997–1006. [CrossRef]
Lewis, M.J.; Neill, S.P.; Hashemi, M.R.; Reza, M. Realistic wave conditions and their influence on quantifying
the tidal stream energy resource. Appl. Energy 2014, 136, 495–508. [CrossRef]
Myers, L.E.; Bahaj, A.S. An experimental investigation simulating flow effects in first generation marine
current energy convert arrays. Renew. Energy 2012, 37, 28–36. [CrossRef]
Mestres, M.; Grino, M.; Sierra, J.P.; Mosso, C. Analysis of the optimal development location for tidal energy
converts in the mesotidal Ria de Vigo (NW Spain). Energy 2016, 115, 1179–1187. [CrossRef]
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