International Journal of Mechanical Engineering and Technology (IJMET)
(IJM
Volume 10, Issue 1, January 2019,
201 pp. 808–820, Article ID: IJMET_10_01_083
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ISSN Print: 0976-6340 and
nd ISSN Online: 0976-6359
0976
© IAEME Publication
Scopus Indexed
SEAWATER BATTERY APPLICATION
APPLICATION FOR
SAILING BOAT APPLICATION
APPLICATION USING
PARTICLE SWARM OPTIMIZATION
OPTIMIZATION BASED
MAXIMUM POWER POINT TRACKING
(Case
Case Study: Madura Strait, The Waters of Madura Island)
Island
Soedibyo, Feby Agung Pamuji,
Pamuji Sjamsjul
amsjul Anam, Mochamad Ashari
Department of Electrical Engineering, Faculty of Electrical Technology
Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Mohamad Ridwan
Department of Electrical Engineering,
Politeknik Elektronika Negeri Surabaya, Indonesia
ABSTRACT
Indonesia has ocean potential energy as a renewable energy source, since around
2/3 of the area consists of water. On the other hand, Indonesian people also work as
fishermen. Seawater battery is one of renewable energy
energy sources proposed in the study.
It is applied in a sailing boat especially for cooling system when fishermen sail for
long time to cool some fish until they arrive in the land and are ready to sell. The
salinity is the most important thing to generate power
power in seawater battery. The value
of it always changes in every location, so the power would be fluctuating. Particle
Swarm Optimization (PSO) is proposed for tracking the maximum power point of
seawater battery. The result shows that PSO succeed to track the maximum power
point in spite of the changes of seawater salinity.
salinity
Key words: Seawater battery, Renewable energy, Particle Swarm Optimization
(PSO), Maximum
mum Power Point Tracking (MPPT).
Cite this Article: Soedibyo, Feby Agung Pamuji, Sjamsjul Anam, Mochamad
Mo
Ashari
and Mohamad Ridwan, Seawater Battery Application For Sailing Boat Application
Using Particle Swarm Optimization Based Maximum Power Point Tracking (Case
Study: Madura Strait, The Waters of Madura Island),
Island) International
ernational Journal of
Mechanical Engineering
ngineering and Technology, 10(1), 2019, pp. 808–820.
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Seawater Battery Application For Sailing Boat Application Using Particle Swarm Optimization Based
Maximum Power Point Tracking (Case Study: Madura Strait, The Waters of Madura Island)
I
1. INTRODUCTION
Solar Indonesia is located south-east
south east Asia. Indonesia has more than 13.000 islands which is
also called as an archipelago
ago country. The waters cover 2/3 of the area of Indonesia, so that is
known as a maritime country. Therefore, Indonesia has more ocean potential energy as
renewable energy sources, such as wave energy, ocean thermal, and tide and tidal power,
which are shown
own in table 1 [1].
TABLE 1 Ocean potential energy sources in Indonesia
No
Energy Source
1
2
3
Wave Energy
Ocean Thermal Energy Conversion
Tide and Tidal Power
Resources
(MW)
1,995.2
41,012
4,800
Seawater battery is one of renewable energy sources utilizing
utilizing one of ocean potentials,
those are seawater minerals. The minerals of seawater are used as the electrolyte to generate
ion transportation, so the electricity can be obtained. Seawater battery has two main parts,
electrolyte and electrodes and in principle,
pr
it is similar to Volta-element.
element. In 80’s, seawater
battery was firstly developed. In 1985 [2], Norwegian Defense Research Establishment
(NDRE) with Alcatel-STK
STK and Marintek develop a power source for an autonomous deep sea
oil well for Statoil. In 1989, undersea water vehicle using aluminum-sea
aluminum sea water battery was
built [3]. Therefore, seawater battery is one of potentials that can be applied for seawater
vehicles. In the study, the seawater battery is applied for sailing boat power source to supply
some
ome equipment, such as lightings and a fishing cooler system. The study is observed in
Madura strait, the waters of Madura Island, since Madura is one of the biggest producers of
salt in Indonesia. In 2015, it is more than 800,000 tons of salt produced in Madura Island [1].
Madura Island
Madura
Strait
Figure 1. Madura Strait, Madura Island
The value of seawater salinity always changes, so the power resulted by seawater battery
would be fluctuating. Therefore, a power point tracker is applied to obtain the maximum
power of seawater battery. There
here are many algorithms used to track the maximum power point
having been studied, such as Perturb and Observe (P&O), Incremental Conductance (IC), and
Fuzzy Logic Control (FLC) [4]-[6],
[4]
In the study, Particle Swarm Optimization (PSO) algorithm is proposed
propos to track the
maximum power point of seawater battery caused by the changes of seawater salinity. PSO is
able to obtain the optimum value through individual interactions in a certain area of search.
PSO is also proven to avoid the system trapped in a local
local optimum. Therefore, PSO is used as
a Maximum Power Point Tracker (MPPT) method in the study.
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2. SEAWATER BATTERY MODEL [7]-[8]
2.1. Seawater Battery Principle
A volta-element is the main principle concept of seawater battery, where it has two main
components inside of the battery, electrodes (cathode and anode) and electrolyte. The
electrolyte allows cathode and anode to transport some ions, in one direction as they charge or
in the other direction as they discharge (deliver the elctricity). The electrolyte from seawater
contains various components such as sodium, sulfur, chloride, etc. Seawater components are
shown in figure. 2.
Figure 2. Seawater components
During charge discharge process, the ion transport and chemical reactions occur. When
the battery is charged, Na+ ions are extracted and transported to the negative electrode, while
the electrons are transferred from cathode to anode through electro-dialysis chemical
reactions. When a load is connected to the battery, the electrons would be transferred from
anode to cathode. The chemical reactions are shown in figure. 3.
(a)
(b)
Figure 3 Chemical reactions of sea water battery; (a) charge (b) disharge
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Seawater Battery Application For Sailing Boat Application Using Particle Swarm Optimization Based
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2.2. Seawater Battery Model
Nernst equation is used to model the proposed seawater battery which is shown in eq. 1.
R.T  γ sea c sea 
E = N m .α
ln 

(1)
z.F  γ c river 
 river 
The potential of the battery, or known as electromotive force, E, is determined by the
number of membranes, Nm, and some constants, such as R is the universal constant {8.31
K/(mol/K)}, T is absolute temperature (K), z is the valence of the ions, F is Faraday constant
(96485 C/mol), γ is activity coefficient, and csea and criver are sea water and river water
concentration respectively.
Similar to the other types of battery, sea water battery also has the internal resistance,
called Rohm, which is depending on the number of membranes, called Rohmic, and the material
used as the electrodes, called Relectrode, which usually varies from 1 to 100 Ωm2.According to
the condition Rohm of sea water battery is shown in eq. 2.


(2)
= N m  R AEM + R CEM + h sea + h river  +
R
Ohmic
2  1 − β
1− β
2
ε .κ
2
sea
ε .κ
river


R
electrodes
Resistance area (Ωm2) is defined as RAEM and RCEM. h defines the distance of inter
membrane electrode (m), while K is the conductivity of electrolyte (S/m).
The electrical equivalent circuit of sea water battery according to the electromotive force
(E) and its internal resistance is illustrated in figure. 3.
Figure 4 Seawater battery equivalent circuit
The internal voltage (Rohmic) causes voltage drop in the terminal of sea water battery. The
condition is shown in eq. 3.
Vbat = E − ROhmic . j
(3)
2
Where j is current density (A/m ) flowing through each electrode of the battery terminal.
j=
I
A
(4)
A is area of each electrode (m2). If eq. 3 is substitute with eq. 4, the current flowing can be
expressed as.
I=
( E − V bat )
ROhmic
.A
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3. PARTICLE SWARM OPTIMIZATION BASED MPPT FOR SEA
WATER BATTERY
In Particle Swarm Optimization (PSO) was firstly proposed by J. Kennedy and C.
Eberhart in 1995 [9]. PSO is one of artificial algorithms which is inspired by individual
interactions in a group of animals, such as swarm of birds, school of fish, etc. PSO has proven
successfully to optimize various mathematical functions, so it interests many researchers to
develop especially in engineering.
Particles in PSO represent the possible solutions. In this study, the output of PSO is set a
duty cycle of MPPT circuit. It is used to set so that the power supplied by seawater battery is
able to be transferred optimally to the load. The particles are represented as =
( , , ,…,
). Of those particles, it is chosen the best particle, called, pbest, which is
recorded and represented as = ( , , , … ,
). Then, among pbest values, it is obtained
a global best value, gbest. The position and the velocity of the particles are updated in every
iteration using eq. 10 and 11 respectively.
=
=
+
( )(
−
)+
()
−
+
(10)
(11)
In every updating the particles, there needs random value between 0 and 1, which is
obtained by a function rand(). c1 and c2 are constant parameters, while w is an inertia weight.
and
are velocity and position of a ith particle respectively. The complete flowchart of
PSO algorithm can be seen in fig. 5.
Figure 5 Complete flowchart of PSO algorithm
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Seawater Battery Application For Sailing Boat Application Using Particle Swarm Optimization Based
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4. PROPOSED DC-DC CONVERTER FOR SEAWATER BATTERY
APPLICATION
The converter proposed for seawater battery application is high step up zeta converter with
coupled inductor and capacitor multiplier. Zeta converter is usually designed to provide either
step up or step down operation. Two inductors, a series capacitor and a diode are usually used
in the conventional zeta converter. By using coupled inductor, it can reduce the dimension of
power supply and the capacitor multiplier is to increase the step up ratio the output for further
is a Wind Turbine system consisting of a turbine, Permanent Magnet Synchronous Generator
(PMSG) with Uncontrolled Rectifier and converter Boost
Figure 6. Zeta converter with coupled inductor and capacitor multiplier
Figure 7 Simplified circuit model of the coupled inductor and capacitor multiplier zeta converter
Zeta converter is configured from a coupled inductor L1, with primary side N1 connected
to C1 and D1 to recycling the leakage energy from inductor N1. The secondary side of N2 is
connected to C2 and D2. To simplify the analysis, fig 6 can be modeled as shown in fig 7.
The coupled inductor and capacitor multiplier zeta converter has some advantages, those
are 1) the leakage energy of the coupled inductor can be recycled, so the efficiency will be
increased; 2) to step up the output voltage is used both coupled inductor ration and capacitor
multiplier, so it increases the efficiency of voltage ratio conversion; and 3) the DC input from
seawater battery can be isolated during the non-operation condition.
4.1. Converter Circuit Analysis
To obtain voltage required to supply some loads from seawater battery in a fishing boat, the
zeta converter is operated in CCM (Continuous Conduction Mode). There are five operation
scheme modes of the zeta converter, which can be found in [5]. In CCM operation mode,
there are only two modes used and the leakage inductances of the primary and secondary
inductors are ignored. The modes used in the operation are shown as follows:
1). when switch S1 is “On”, C1, C2, secondary winding N2 and Lk2 are series connected to the
input Vin. The energy from N2 flows and charges C3 through D3, while
energized by the input Vin. During this condition, it can be described that:
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Lm and Lk1 are
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Soedibyo, Feby Agung Pamuji, Sjamsjul Anam, Mochamad Ashari and Mohamad Ridwan
V Lm = V in
(12)
V N 2 = nV in
(13)
2). when switch S1 is “Off”, the inductor Lm releases the stored energy to the C1
simultaneously and C2 through the inductances of primary and secondary sides. In this mode,
only diode D1 and D2 are conducting. The stored energy in capacitor C3 is discharged to the
load R. During this condition, it can be formulated that:
V Lm=−V C1
(14)
V N 2 =−V C 2
(15)
The equation of a voltage balance on the inductor Lm can be written as follows:
D Ts
Ts
∫ V indt + ∫ −V C 1dt = 0
0
(16)
DTs
D Ts
Ts
∫ n .V indt + ∫ −V C 2dt = 0
0
(17)
D Ts
where the voltages of capacitor C1 and C2 are obtained from the following equations:
V C1 =
D
V in
1− D
(18)
nD
V in
1− D
(19)
V C2 =
During the switch S1 “On”, the output voltage can be calculated as follows:
V 0 = V in +V C1 +V N 2 +V C 2
V 0 = V in +
(20)
D
1+ n
nD
V =
V in + nV in +
V in
1− D
1− D in 1 − D
(21)
Therefore, the voltage gain of the zeta converter is:
G=
1+ n
1− D
(22)
5. SIMULATION RESULT
The model of seawater battery and MPPT algorithm are simulated using PSIM software. The
output of seawater battery is connected to a buck-boost converter to track the maximum
power of seawater battery before it is transferred to the load. The results and analysis are then
presented. Table 2 and 3 shows the parameters used in this study. Fig. 8 shows all diagram of
seawater battery system and its MPPT.
The seawater battery in this study is designed to have power output around 1 kW. The
simulation was done in two cases. The first case is tracking the maximum power with
constant salinity, and the second is tracking with the changes of salinity. The result is
discussed below.
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Table 2 Simulation parameters
Nm
610
Alpha
0.97
R
8.3
T
300
Z
1
F
96458
Gsea
1
Csea
30 – 32
Griv
1
Criv
0.5
Seawater Battery
Parameters
PSO Parameters
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0.12
1.2
Zeta Converter
Parameters
L
5 mH
C
1000 uF
RL
10 Ω
freq
20 kHz
duty cycle
0 – 90 %
In the first case, the salinity is set 30 PSU (Practical Salinity Unit) as the lowest value.
This value is referred to the average of Indonesia’s ocean salinity. Fig 9 and 10 show the
result of tracking process, power and duty cycle result respectively, while fig.11 shows the
output voltage of MPPT. It is kept to be constant as 340 volt, since it could be converted to
AC 220V/50 Hz later.
Figure 9 Power output of MPPT (salinity = 30)
According to the simulation result, PSO algorithm can track the maximum power of
seawater battery when the salinity is 30 PSU. The output of PSO is to set duty cycle value
which is used to control the switching mechanism of buck-boost converter, so the maximum
power is obtained. The result shows that the average maximum power obtained is 1010 watt
with average duty cycle is 91.5% and output voltage is 342 volt. Based on the transferred
power DC theory, the power transferred to the load when the resistance of the load is the same
value as the series resistance of the battery, which is the internal resistance in this case.
Therefore, buck-boost converter is responsible for changing the impedance to get the
maximum power through the switching mechanism. The switching mechanism is determined
using PSO algorithm by tracking the maximum power obtained. According to the simulation
result, it can be said that PSO is able to track the maximum power of seawater battery.
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Figure 10 Duty cycle tracking to obtain the maximum power of seawater battery
Figure 11 Output voltage of MPPT designed
The second case was designed by changing the salinity value. Fig. 12 shows the change of
the salinity. It is designed to change between 30 – 33 PSU.
Figure 12 The change of salinity
Figure 13 and 14 show the power output and the best duty cycle respectively accordance
with the change of salinity. When the salinity goes down, the power output also decreases.
However, the decrease of power caused by salinity does not change significantly. The average
power output with the change of salinity is obtained as 1014 watt. This value is enough for
satisfying a cold storage and some lighting if it is implemented for a fishing boat [10]. The
output voltage is also kept with average value 342 volt. That is able to be converted to AC
220 V/50 Hz later to supply AC load. The value of duty cycle is same as the value of the
previous case, which is 91.4 %. The duty cycle is not affected though the salinity changes.
Once the duty cycle is obtained, it can be used for any other conditions.
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Figure 13 Power output (according to the change of salinity)
Figure 14 Duty cycle tracking (according to the change of salinity)
Figure 15 The output voltage (according to the change of salinity)
6. EXPERIMENTAL RESULTS
The converter and algorithm designed was implemented and tested in the laboratory. Beside
the power output, the concern is that the output voltage should be constant. To test the
converter is by providing the fluctuating input voltage to the converter. The input voltage is
set as the output of seawater battery, between 40 to 45 volt as the change of seawater salinity.
Figure 16 shows the block diagram of experimental test. Modified zeta converter is applied to
keep the voltage constant on DC link bus.
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Seawater Battery Application For Sailing Boat Application Using Particle Swarm Optimization Based
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Figure 16 Block diagram of experimental test
Figure 17 shows the implementation of the converter with coupled inductor. The output
voltage toward the input voltage applied. The converter is tested by giving the variable input
voltage as resulted by seawater battery. The output is kept to be a constant voltage.
Figure 17 Hardware implementation of the converter
Figure 18 Output voltage of the converter
Figure 18 shows the result of hardware implementation. According to the experimental
result, the converter can keep the output voltage as 340 volt with the change of input voltage.
The ripple of the output voltage reaches around 10 volt or about 3% error output voltage. This
value is not concerned since it is lower than 10%.
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7. CONCLUSION
According to the study of maximum power point tracking of seawater battery, it can be
concluded that PSO can track the maximum power of seawater battery very well with average
power output as 1014 watt when the salinity is changed from 30 – 33 PSU. Moreover, the
output voltage is able to be kept constant with the average value of 342 volt; since it can be
used to supply an inverter with the output voltage 220 V/50 Hz for AC loads. The change of
salinity does not influence the tracking process to get power around 1 kW. PSO is still able to
track the maximum power point in spite of the change of salinity. The implementation result
shows that the converter can keep the output voltage to be a constant while the input voltage
is changing. The future research is to add an inverter to the system in order to be directly
applied for a fishing boat cooling system.
ACKNOWLEDGEMENTS
This work was supported by Superior Research-2018, Institut Teknologi Sepuluh Nopember,
RISTEK DIKTI, Indonesia.
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