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Optimised Hydrogen Production by a Photovoltaic –
Electrolysis System DC/DC Converter and Water–
Flow Controller
Sanae Dahbi*, Abdelhak Aziz, Naima Benazzi
Laboratory of Electrical Engineering and Maintenance
Higher School of Technology
Oujda, Morocco
dahbisanae@hotmail.fr
Mohamed Elhafyani
National School of Applied Sciences
Mohammed First University
Oujda, Morocco
Abstract— In this article, we borrowed a new path for hydrogen
production by adapting the electrolysis to a renewable source
such as photovoltaic (PV) to generate the maximum hydrogen. A
complete modeling of the PV-electrolysis system was developed in
Matlab/Simulink environment. A proton exchange membrane
(PEM) electrolysis is connected to the PV system via a DC/DC
Buck converter with a maximum power point tracking (MPPT)
control which allows the maximization of the power transferred
to the electrolysis and controls the injected water flow in the
electrolysis. Simulation results show firstly as control of water
flow that enters electrolysis depends on power variations caused
by weather changes .On the other hand, the use of a DC/DC buck
converter having a MPPT control allows a better adaptation
between the PV array and electrolysis. This leads to an optimal
functioning photovoltaic-electrolysis system and therefore a
maximum hydrogen production.
Keywords-electrolysis; MPPT; PV; DC/DC converter;
hydrogen; PEM ; water flow
I. INTRODUCTION
One of the most interesting developments of photovoltaic
energy systems is their integration with other energy sources
such as electrolysis to produce hydrogen. Indeed, the
production of hydrogen by electrolysis of water from
electricity supplied by photovoltaic energy allow without
polluting in both to store, transport and reuse this energy. That
is to say compensate its two main disadvantages of being
intermittent and non-storable.
Until now, most research on electrolysis water related to
hydrogen production projects is concentrated on alkaline
electrolysis systems and PEM electrolysis. PEM electrolysis
has a number of advantages over conventional alkaline
electrolysis systems, because of their ecological cleanliness,
simplicity, high efficiency and easy production capacity [1]
[2] [3].
The optimization and modeling of various blocks forming the
photovoltaic-electrolysis system, which aims to get the best
performance from the production of hydrogen, attracted the
attention of many scientists and researchers. In particular,
Garcia-Valverde [4] has optimized the system by coupling the
PV module and the electrolysis through the integration of a
controlled power converter. In other hand, Garrigos [5] has
combined maximum power point tracking and output current
control to optimize the full system such as photovoltaic-
electrolysis and DC/DC converter. Bousquet et al. [6] have
developed an empirical approach to model a regenerative
electrolysis or fuel cell. A dynamic model of PEM electrolysis
was presented and evaluated by Gorgun [7]. Thomas and
Nelson [8] presented an optimization of the efficiency of the
PV-electrolysis system by adapting the voltage and maximum
power of the PV to the voltage of the PEM electrolysis
operation. Marshall [9] has developed a new catalyst for PEM
electrolysis aimed to high hydrogen production.
However, most research has not taken into account the
effect of controlling the water flow to be injected into the
electrolysis, on the performance of hydrogen production and
thereafter on the PV-electrolysis system. This flow control
process is the subject of this article.
In this article we raise the problems of adaptation of the PV
module and the electrolysis and we display two strategies to
improve hydrogen production:
 Optimization of the process of electrolysis by
supplying the electrolysis by a suitable photovoltaic
system by a DC/DC buck converter, having itself a
numerical control maximum power tracking (MPPT).
The assembly allows maximum extraction of the
power delivered by a photovoltaic generator and an
almost totally transfer to the electrolysis.
 The water flow control to be injected into the
electrolysis for maximum hydrogen production while
taking account of the power transferred by the PV
system.
In Section 2, we present a complete and simple modeling
of the PV generator and the PEM electrolysis and then analyze
the results of this modeling. Also describes in thorough way
the control system. Furthermore, simulation results are
provided in Section 3. Finally, some conclusions are drawn in
Section 5.
978-1-4673-7894-9/15/$31.00 ©2015 IEEE
II. PHOTOVOLTAIQUE-ELECTROLYSIS SYSTEM
In this work, we considered that the electrolysis is
connected to the PV system according to the diagram in
“Fig.1”.
 Panel (generator) PV Mutsibuchi-180 type, it consists
of 50 elementary photovoltaic cells and can deliver in
standard test conditions 174W of power, a current of
8.3A under optimum voltage of 24V.
 The adaptation quadripole is an energy buck
converter already dimensioned and designed to
operate at a frequency of 100 KHz.
 An algorithmic unit is developed to pursue the point of
maximum power where we implemented the MPPT
control algorithm known to perturb and observe
(P&O). The result of this program is to generate a
pulse width modulated signal (PWM) with frequency
of 100 KHz and controlling the MOSFET of the
converter. The implemented algorithm allows
adjustment of the duty cycle to pursue the maximum
power point of the PV panel and allows the optimal
operation of the electrolysis.
 PEM electrolysis consists of 7 cells connected in
series with a surface of 10cm². The temperature and
the pressure operating electrolysis are T=80°C and
P=101325 Pa.
Figure 1. Schematic of a PV-electrolysis system
A. PV Modeling
A solar cell is generally represented by a current source
connected in parallel with a diode threshold less than 1V, a
series resistor Rs and a parallel resistor Rp “Fig. 2”. The solar
panel is an association Ns cells in series with Np cells in
parallel, the conversion of solar energy into electrical energy
is expressed by a non-linear relationship between the current I
and the voltage V of the PV panel [2].
.
.
1
..
)..(
.exp...
P
pvSpv
s
P
pvS
PSPHPpv
R
IRV
N
N
ATk
IRVq
NIINI

























 

(1)
Where I is the PV generated current, V is PV generated
voltage, IPH is light-generated current (photo-current), Is is
saturated diode current, q is unsigned electron charge, A is an
ideal factor, (varies between 1.2 and 5), k is Boltzmann’s
constant and Tc is the absolute cell temperature.
B. Electrolysis Modeling
1) Water Electrolysis Principle
Electrolysis of water is dissociation of water molecules into
hydrogen and oxygen. A potential is applied across the
electrochemical cell to cause electrochemical reactions at two
electrodes. The scheme shown in "Fig.3" shows the
fundamental principle of electrolysis water.
Figure 2. Equivalent circuit of a solar cell
The main part of the PEM water electrolysis is the
membrane electrode assembly MEA. The perfluorosulfonic
acid polymer such as Nafion has been widely used as a
membrane for electrolysis of water, due to its intrinsic
properties: excellent chemical and mechanical stability and
high proton conductivity [10] [11] [12] [13].
For the anode, the catalysts based on Pt-IrO² alloy are
relatively stable and more practical as an anode electro-
catalyst compared to the platinum, which shows significant
overvoltage and platinum/ruthenium (Pt/Ru) that is not stable
and corrodes under oxygen evolution [14].
For the cathode, platinum offers the best performance and
commonly used for the electrolysis of water [9] [15].
The water introduced at the anode is dissociated into oxygen,
protons and electrons. The reaction at the anode can be
expressed as follows:
H2O (l) ½ O2(g) +2H+
+2e- (2)
Under an electric field, the protons are entrained through the
PEM to the cathode where they combine with electrons
coming from the external circuit to form hydrogen gas:
2H+
+ 2e- H2(g) (3)
Therefore, the overall reaction of this decomposition can be
written as:
H2O (l) H2(g) +1/2O2 (g) (4)
Figure 3.Fundamental principle of electrolysis water.
2) Electrochemical Voltage of a PEM Electrolysis Cell
When the current is applied to the PEM cell, the voltage of
total operation of the electrolytic cell can be represented as the
sum of the Nernst voltage Erev, overvoltage at the cathode ηc
and anode ηa, overvoltage due to the membrane ηm and
interfacial overvoltage ηI “Fig.4”.
E=Erev+ηa-ηc +ηm+ηI (5)
Where the Nernst potential Erev is given empirically by [16]:
)log(
4
3.2)298(109.023.1 22
23
OHrev PP
F
RT
TE   (6)
Figure 4. Voltage (V) as a function of current density (A) for a PEM
electrolysis cell operating at 80◦C
The overvoltage’s due to cathode, anode and membrane
resistance is given by: [14]
)
2
(sinh
.
0
1
A
A
I
I
F
TR 

(7)
)
2
(sinh
.
0
1
C
C
I
I
F
TR 

(8)
(9)
Where IA0 is the anode exchange current [A], Ic0 is the cathode
exchange current [A], LB is the thickness of PEM, σB is
conductivity of the electrolyte.
The interfacial overvoltage ƞI is the production of the
interfacial resistance RI and current I.
ηI=RI.I (10)
3) Modeling of PEM electrolysis cell
“Fig.5” illustrates the electrolysis process which is
represented by an equivalent electrical circuit consisting of a
series of resistors and a back electromotive force.
A separate derivation overvoltage confers resistance
corresponds to anode, cathode and polymer electrolyte
exchange membrane.
2
0
0 )(
4
1
1)2(
.
A
A
A
I
I
FI
TR
R


(11)
Figure 5. The equivalent circuit for the water electrolysis process
2
0
0 )(
4
1
1)2(
.
C
C
C
I
I
FI
TR
R


(12)
.
)(
B
B
m
L
R


(13)
And RI=RI (14)
4) The mass flow
The mass of hydrogen produced at the cathode is
proportional to the amount of current passed through the
electrolyte according to the second Faraday law:
FH
n.F
M
m 
.t.I.nc
2
 (15)
With:
mH2 = mass of hydrogen formed to the electrode (in kg)
nc = number of cells
M = molar mass of hydrogen (in kg.mole-1)
I = current through the electrolysis (in A)
t = time of electrolysis (sec)
n = number of electrons per mole of product formed
F = Faraday's number (F = 96 485 C/mol)
ŋF = Faraday efficiency is the ratio between the actual value
and the maximum theoretical amount of hydrogen produced in
the electrolysis. The faradic efficiency can be calculated as:








2
5.7509.0
5.96 II
F  (16)
.
)( I
L
B
B
m

 
In a PV system, the output power depends on the weather
conditions (rapidly changing), then, it would not be wise to
use directly the quantity of water to be electrolyzed. Our
approach focuses on the flow of water introduced into the
electrolysis taking into account the quickly changing
conditions. In previous work [17], we have shown that the
flow of hydrogen produced can be expressed in the form:
n.F
nM
t
m
m FcH
H
....I
.
2
2


(17)
According to “(4)“ .The amount of hydrogen produced is
given by the following relationship:
.
2
92


 OH
H
m
m (18)
We posing
.
.9
.
M
Fn
C 
.The amount of hydrogen produced is
given by the following relationship:
F
c
OH
C
nI
m .
.
.
2 

(19)
In addition, the electric power P available for ectrolyzing
according to the scheme of "Fig.1" is:
IVP .. (20)
Using “(19)”, “(20)”.
F
c
OH
VC
nP
m .
.
.
.
2 

(21)
This relation shows that the water flow is proportional to
the electrical power available. Hence the necessities to control
the water flow to be introduced into the electrolysis.
We have shown that the production of hydrogen is
proportional on one hand to the electrolysis current, and the
other hand to the water flow to be injected into the
electrolysis. Further water flow is proportional to the converter
output power “(17)” “(18)” “(21)”. A control system is
necessary for extracting the maximum photovoltaic power that
will lead undoubtedly to an optimized electrolysis operation
and consequently a maximum hydrogen production.
C. Maximum Power Point Tracking Converter
“Fig.6” shows the flowchart of the type of MPPT control
system developed in this work. This is a technical MPPT
based on P&O algorithm with a variable step size and an
acceleration mechanism [18]. This algorithm is in charge to
find a simple and effective way to improve the accuracy of the
place of maximum power point MPP, and the acceleration of
the system to quickly reach this point. This technique also
adjusts the optimum voltage of the PV panel to the cell voltage
of the electrolysis.
III. EVALUATION OF SIMULATION RESULTS
We simulated the production of hydrogen by a
photovoltaic system using a Buck power converter controlled
by the aforementioned MPPT control and supplying PEM
electrolysis.
The modelization and sizing of PEM electrolysis is made
exactly in a manner to consume all the power produced by the
PV system.
The complete diagram of the PV-electrolysis system is
shown in “Fig.7”.The assembly simulation is conducted in the
Matlab/Simulink. Modeling physical components of PV is
made by the Simscape language and modeling of the digital
part is done by the S-Function CMEX tool using the
programming language C.
Figure 6. Flowchart of the P&O algorithm with a variable step size and an
acceleration mechanism
The solar radiation signal input from the photovoltaic
generator is shown in “Fig.8”. The buck converter equipped
with MPPT control, extracts the maximum power and the
current of photovoltaic module “Fig.9” and “Fig.10” and
transfers them to the electrolysis for:
 Control the water mass flow to be injected into the
electrolysis
 To produce the maximum amount of hydrogen in the
form of mass flow depending on the sunlight.
Figure 7. Modeling of photovoltaic-electrolysis system in Matlab/Simulink
Figure 8. Solar irradiance
Figure 9 . Output power of the PV panel transferred to the electrolysis
The "Fig.11" and "Fig.12" represent the results of
simulations of the water mass flow injected into the
electrolyzer and the mass flow of hydrogen produced during
the different phases of solar radiation. We simulated these two
quantities in a direct coupling of the PV module to the
electrolysis, but also during the coupling of the two systems
by introducing the DC-DC power converter equipped with its
control algorithm (indirect coupling). It appears that:
The water flow follows the variation of the power extracted
from the PV panel following variations illumination. This
proves that the water flow to be introduced into the
electrolysis depends only on the power provided by the
photovoltaic source PV and afterwards of sunlight.
Furthermore by:
 The flow of hydrogen produced simultaneously tracks
the water flow; it confirms the importance of
controlling the flow of water injected into the
electrolysis for maximum hydrogen production.
 The quantity of water injected into the electrolysis is
most important during the indirect coupling than to
direct coupling with an equal amount of radiation.
Note then, by adopting the process of producing hydrogen
using the PV module, the electrolysis, the DC-DC converter
and controlling the amount of water is obtained a significant
improvement in overall system performance. This
improvement concerns first of maximizing the power supplied
by the PV module, and eventually an increase in the
production of hydrogen through of the water flow control
injected into the electrolysis. This leads to optimum operation
of the electrolysis and therefore a higher production of
hydrogen compared to a direct coupling.
Figure 10. Output current of the PV panel transferred to the electrolysis
Figure 11 . Water flow injected into the PEM electrolysis with and without
controlled DC/DC.
Figure 12 . Hydrogen flow produced by the PEM electrolysis with and
without DC/DC controlled
VI. CONCLUSION
In this work, we presented the modeling of various
components of the PV-electrolysis system (PEM electrolysis,
PV, DC/DC buck converter). We have given particular
attention to the electrical modeling of chemical phenomena
that occur in electrolysis for integrated it in an electrical
environment. So we introduced between the PV module and
the electrolysis a DC-DC buck converter type with a digital
control algorithm to prosecute the maximum power (MPPT),
and ensuring the transfer of this power to electrolysis in order
to produce hydrogen.
Simulation results show that the coupling between the
PEM water electrolysis and the PV panel via a DC/DC buck
converter, controlled by an MPPT algorithm and a water flow
controller in the electrolysis, leads to an improvement on
maximization of the power drawn from the PV module on one
hand, and on the other hand maximizing the amount of
hydrogen produced in the electrolysis. This has the effect an
overall improvement in hydrogen production system designed.
REFERENCES
[1] Ni. Meng, M. K. H. Leung, D. Y. C. Leung, “Energy and exergy
analysis of hydrogen production by a proton exchange membrane (PEM)
electrolyzer plant,” J. Energy Conversion and Management, vol. 49, pp.
2748-2756, October 2008.
[2] O. F. Selamet, F. Becerikli, M. D. Mat, Y. Kaplan, “ Development and
testing of a highly efficient proton exchange membrane (PEM)
electrolyzer stack,” Int. J. Hydrogen Energy, vol. 36 , pp. 11480-
11487, August 2011.
[3] M. Carmo, D. L. Fritz, J. Mergel, D. Stolten, “A comprehensive review
on PEM water electrolysis,” Int. J. Hydrogen Energy, vol. 38, pp. 4901-
4934, April 2013.
[4] R. Garcıa-Valverdea, C. Miguela, R. Martınez-Bejarb, A. Urbinaa,
“Optimized photovoltaic generatore water electrolyser coupling through
a controlled DC/DC converter,” Int. J. Hydrogen Energy, vol. 33, pp
5352-5362, October 2008.
[5] A. Garrigos, J. L . Lizan, J. M. Blanes, R. Gutierrez, “Combined
maximum power point tracking and output current control for a
photovoltaic-electrolyser DC/DC converter,” Int. J. Hydrogen Energy,
vol. 39, pp. 20907–20919, December 2014.
[6] S. Busquet, C. E. Hubert, J. Labbe, D. Mayer, R. Metkemeijer, “A new
approach to empirical electrical modeling of a fuel cell, an electrolyser
or a regenerative fuel cell,” J. Power Sources, vol. 134, pp. 41-48,
July 2004.
[7] H. Gorgun, “Dynamic modelling of a proton exchange membrane
(PEM) electrolyzer,” Int. J. Hydrogen Energy, vol. 31, pp. 29–38,
January 2006.
[8] L. G. Thomas, A. K. Nelson ,”Optimization of solar powered Hydrogen
production using photovoltaic electrolysis devices,” Int. J. Hydrogen
Energy, vol. 33, pp. 5931 –5940 , November 2008.
[9] A. Marshall,1, B. Børresen, G. Hagen, M. Tsypkin, R. Tunold,
“Hydrogen production by advanced proton exchange membrane (PEM)
water electrolysers—Reduced energy consumption by improved
electrocatalysis,” J. Energy ,vol. 32, pp. 431–436, April 2007.
[10] W. Smith, “The role of fuel cells in energy storage,” J. Power Sources,
vol. 86 , pp. 74-83, March 2000.
[11] A. Leonida, J. McElroy, T. Nalette, “ Hydrogen-oxygen proton-
exchange membrane fuel cells and electrolyzers, ”J. Power Sources,
vol. 29,pp 399-412, February 1990.
[12] L. L. Swette, A. B. LaConti, S. A. McCatty, “Proton-exchange
membrane regenerative fuel cells,” J. Power Sources, vol. 47, pp. 343-
351, January 1994.
[13] T. Loroi , K. Yasuda, Z. Siroma , N. Fujiwara, Y. Miyazaki , “Thin film
electrocatalyst Layer for unitized regenerative polymer electrolyte fuel
cells,” J. Power Sources, vol. 112, pp. 583–587, November 2002.
[14] G. D. Bessarabovb, R. Dattaa, P. Choi, ”A simple model for solid
polymer electrolyte (SPE) water electrolysis,” J. Solid State Ionics, vol.
175, pp. 535–539, November 2004.
[15] K. Onda, T. Murakami, T. Hikosaka, M. Kobayashi, R. Notu, K. Ito, ”
Performance analysis of polymer-electrolyte water electrolysis cell at a
small-unit test cell and performance prediction of large stacked cell,” J.
Electrochemical Society, vol. 149, pp. A1069-A1078, June 2002.
[16] D. M. Bernardi, M. W. Verbrugge, ”A Mathematical model of the solid
polymer-electrolyte fuel cell,” J. Electrochemical Society, vol. 139, pp.
2477- 2491, April 1992.
[17] S. Dahbi, A. Aziz, N. Benazzi, M. Elhafyani, H. Zahboune, “Toward
a new method to improving hydrogen production by an adaptive
photovoltaic system,” The 2nd International Renewable and
Sustainable Energy Conference (IRSEC’14), Ouarzazate, Morocco,
October 2014.
[18] S. Dahbi, A. Aziz, N. Benazzi, M. Elhafyani, N. Benahmed, “
Advanced MPPT controller based on P&O algorithm with variable
step size and acceleration mechanism for solar photovoltaic system,”
Mediterranean Conference on Information & Communication
Technologie (MedICT’15), Saidia, Morocco, May 2015.

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Dahbi2015

  • 1. Optimised Hydrogen Production by a Photovoltaic – Electrolysis System DC/DC Converter and Water– Flow Controller Sanae Dahbi*, Abdelhak Aziz, Naima Benazzi Laboratory of Electrical Engineering and Maintenance Higher School of Technology Oujda, Morocco dahbisanae@hotmail.fr Mohamed Elhafyani National School of Applied Sciences Mohammed First University Oujda, Morocco Abstract— In this article, we borrowed a new path for hydrogen production by adapting the electrolysis to a renewable source such as photovoltaic (PV) to generate the maximum hydrogen. A complete modeling of the PV-electrolysis system was developed in Matlab/Simulink environment. A proton exchange membrane (PEM) electrolysis is connected to the PV system via a DC/DC Buck converter with a maximum power point tracking (MPPT) control which allows the maximization of the power transferred to the electrolysis and controls the injected water flow in the electrolysis. Simulation results show firstly as control of water flow that enters electrolysis depends on power variations caused by weather changes .On the other hand, the use of a DC/DC buck converter having a MPPT control allows a better adaptation between the PV array and electrolysis. This leads to an optimal functioning photovoltaic-electrolysis system and therefore a maximum hydrogen production. Keywords-electrolysis; MPPT; PV; DC/DC converter; hydrogen; PEM ; water flow I. INTRODUCTION One of the most interesting developments of photovoltaic energy systems is their integration with other energy sources such as electrolysis to produce hydrogen. Indeed, the production of hydrogen by electrolysis of water from electricity supplied by photovoltaic energy allow without polluting in both to store, transport and reuse this energy. That is to say compensate its two main disadvantages of being intermittent and non-storable. Until now, most research on electrolysis water related to hydrogen production projects is concentrated on alkaline electrolysis systems and PEM electrolysis. PEM electrolysis has a number of advantages over conventional alkaline electrolysis systems, because of their ecological cleanliness, simplicity, high efficiency and easy production capacity [1] [2] [3]. The optimization and modeling of various blocks forming the photovoltaic-electrolysis system, which aims to get the best performance from the production of hydrogen, attracted the attention of many scientists and researchers. In particular, Garcia-Valverde [4] has optimized the system by coupling the PV module and the electrolysis through the integration of a controlled power converter. In other hand, Garrigos [5] has combined maximum power point tracking and output current control to optimize the full system such as photovoltaic- electrolysis and DC/DC converter. Bousquet et al. [6] have developed an empirical approach to model a regenerative electrolysis or fuel cell. A dynamic model of PEM electrolysis was presented and evaluated by Gorgun [7]. Thomas and Nelson [8] presented an optimization of the efficiency of the PV-electrolysis system by adapting the voltage and maximum power of the PV to the voltage of the PEM electrolysis operation. Marshall [9] has developed a new catalyst for PEM electrolysis aimed to high hydrogen production. However, most research has not taken into account the effect of controlling the water flow to be injected into the electrolysis, on the performance of hydrogen production and thereafter on the PV-electrolysis system. This flow control process is the subject of this article. In this article we raise the problems of adaptation of the PV module and the electrolysis and we display two strategies to improve hydrogen production:  Optimization of the process of electrolysis by supplying the electrolysis by a suitable photovoltaic system by a DC/DC buck converter, having itself a numerical control maximum power tracking (MPPT). The assembly allows maximum extraction of the power delivered by a photovoltaic generator and an almost totally transfer to the electrolysis.  The water flow control to be injected into the electrolysis for maximum hydrogen production while taking account of the power transferred by the PV system. In Section 2, we present a complete and simple modeling of the PV generator and the PEM electrolysis and then analyze the results of this modeling. Also describes in thorough way the control system. Furthermore, simulation results are provided in Section 3. Finally, some conclusions are drawn in Section 5. 978-1-4673-7894-9/15/$31.00 ©2015 IEEE
  • 2. II. PHOTOVOLTAIQUE-ELECTROLYSIS SYSTEM In this work, we considered that the electrolysis is connected to the PV system according to the diagram in “Fig.1”.  Panel (generator) PV Mutsibuchi-180 type, it consists of 50 elementary photovoltaic cells and can deliver in standard test conditions 174W of power, a current of 8.3A under optimum voltage of 24V.  The adaptation quadripole is an energy buck converter already dimensioned and designed to operate at a frequency of 100 KHz.  An algorithmic unit is developed to pursue the point of maximum power where we implemented the MPPT control algorithm known to perturb and observe (P&O). The result of this program is to generate a pulse width modulated signal (PWM) with frequency of 100 KHz and controlling the MOSFET of the converter. The implemented algorithm allows adjustment of the duty cycle to pursue the maximum power point of the PV panel and allows the optimal operation of the electrolysis.  PEM electrolysis consists of 7 cells connected in series with a surface of 10cm². The temperature and the pressure operating electrolysis are T=80°C and P=101325 Pa. Figure 1. Schematic of a PV-electrolysis system A. PV Modeling A solar cell is generally represented by a current source connected in parallel with a diode threshold less than 1V, a series resistor Rs and a parallel resistor Rp “Fig. 2”. The solar panel is an association Ns cells in series with Np cells in parallel, the conversion of solar energy into electrical energy is expressed by a non-linear relationship between the current I and the voltage V of the PV panel [2]. . . 1 .. )..( .exp... P pvSpv s P pvS PSPHPpv R IRV N N ATk IRVq NIINI                             (1) Where I is the PV generated current, V is PV generated voltage, IPH is light-generated current (photo-current), Is is saturated diode current, q is unsigned electron charge, A is an ideal factor, (varies between 1.2 and 5), k is Boltzmann’s constant and Tc is the absolute cell temperature. B. Electrolysis Modeling 1) Water Electrolysis Principle Electrolysis of water is dissociation of water molecules into hydrogen and oxygen. A potential is applied across the electrochemical cell to cause electrochemical reactions at two electrodes. The scheme shown in "Fig.3" shows the fundamental principle of electrolysis water. Figure 2. Equivalent circuit of a solar cell The main part of the PEM water electrolysis is the membrane electrode assembly MEA. The perfluorosulfonic acid polymer such as Nafion has been widely used as a membrane for electrolysis of water, due to its intrinsic properties: excellent chemical and mechanical stability and high proton conductivity [10] [11] [12] [13]. For the anode, the catalysts based on Pt-IrO² alloy are relatively stable and more practical as an anode electro- catalyst compared to the platinum, which shows significant overvoltage and platinum/ruthenium (Pt/Ru) that is not stable and corrodes under oxygen evolution [14]. For the cathode, platinum offers the best performance and commonly used for the electrolysis of water [9] [15]. The water introduced at the anode is dissociated into oxygen, protons and electrons. The reaction at the anode can be expressed as follows: H2O (l) ½ O2(g) +2H+ +2e- (2) Under an electric field, the protons are entrained through the PEM to the cathode where they combine with electrons coming from the external circuit to form hydrogen gas: 2H+ + 2e- H2(g) (3) Therefore, the overall reaction of this decomposition can be written as: H2O (l) H2(g) +1/2O2 (g) (4) Figure 3.Fundamental principle of electrolysis water.
  • 3. 2) Electrochemical Voltage of a PEM Electrolysis Cell When the current is applied to the PEM cell, the voltage of total operation of the electrolytic cell can be represented as the sum of the Nernst voltage Erev, overvoltage at the cathode ηc and anode ηa, overvoltage due to the membrane ηm and interfacial overvoltage ηI “Fig.4”. E=Erev+ηa-ηc +ηm+ηI (5) Where the Nernst potential Erev is given empirically by [16]: )log( 4 3.2)298(109.023.1 22 23 OHrev PP F RT TE   (6) Figure 4. Voltage (V) as a function of current density (A) for a PEM electrolysis cell operating at 80◦C The overvoltage’s due to cathode, anode and membrane resistance is given by: [14] ) 2 (sinh . 0 1 A A I I F TR   (7) ) 2 (sinh . 0 1 C C I I F TR   (8) (9) Where IA0 is the anode exchange current [A], Ic0 is the cathode exchange current [A], LB is the thickness of PEM, σB is conductivity of the electrolyte. The interfacial overvoltage ƞI is the production of the interfacial resistance RI and current I. ηI=RI.I (10) 3) Modeling of PEM electrolysis cell “Fig.5” illustrates the electrolysis process which is represented by an equivalent electrical circuit consisting of a series of resistors and a back electromotive force. A separate derivation overvoltage confers resistance corresponds to anode, cathode and polymer electrolyte exchange membrane. 2 0 0 )( 4 1 1)2( . A A A I I FI TR R   (11) Figure 5. The equivalent circuit for the water electrolysis process 2 0 0 )( 4 1 1)2( . C C C I I FI TR R   (12) . )( B B m L R   (13) And RI=RI (14) 4) The mass flow The mass of hydrogen produced at the cathode is proportional to the amount of current passed through the electrolyte according to the second Faraday law: FH n.F M m  .t.I.nc 2  (15) With: mH2 = mass of hydrogen formed to the electrode (in kg) nc = number of cells M = molar mass of hydrogen (in kg.mole-1) I = current through the electrolysis (in A) t = time of electrolysis (sec) n = number of electrons per mole of product formed F = Faraday's number (F = 96 485 C/mol) ŋF = Faraday efficiency is the ratio between the actual value and the maximum theoretical amount of hydrogen produced in the electrolysis. The faradic efficiency can be calculated as:         2 5.7509.0 5.96 II F  (16) . )( I L B B m   
  • 4. In a PV system, the output power depends on the weather conditions (rapidly changing), then, it would not be wise to use directly the quantity of water to be electrolyzed. Our approach focuses on the flow of water introduced into the electrolysis taking into account the quickly changing conditions. In previous work [17], we have shown that the flow of hydrogen produced can be expressed in the form: n.F nM t m m FcH H ....I . 2 2   (17) According to “(4)“ .The amount of hydrogen produced is given by the following relationship: . 2 92    OH H m m (18) We posing . .9 . M Fn C  .The amount of hydrogen produced is given by the following relationship: F c OH C nI m . . . 2   (19) In addition, the electric power P available for ectrolyzing according to the scheme of "Fig.1" is: IVP .. (20) Using “(19)”, “(20)”. F c OH VC nP m . . . . 2   (21) This relation shows that the water flow is proportional to the electrical power available. Hence the necessities to control the water flow to be introduced into the electrolysis. We have shown that the production of hydrogen is proportional on one hand to the electrolysis current, and the other hand to the water flow to be injected into the electrolysis. Further water flow is proportional to the converter output power “(17)” “(18)” “(21)”. A control system is necessary for extracting the maximum photovoltaic power that will lead undoubtedly to an optimized electrolysis operation and consequently a maximum hydrogen production. C. Maximum Power Point Tracking Converter “Fig.6” shows the flowchart of the type of MPPT control system developed in this work. This is a technical MPPT based on P&O algorithm with a variable step size and an acceleration mechanism [18]. This algorithm is in charge to find a simple and effective way to improve the accuracy of the place of maximum power point MPP, and the acceleration of the system to quickly reach this point. This technique also adjusts the optimum voltage of the PV panel to the cell voltage of the electrolysis. III. EVALUATION OF SIMULATION RESULTS We simulated the production of hydrogen by a photovoltaic system using a Buck power converter controlled by the aforementioned MPPT control and supplying PEM electrolysis. The modelization and sizing of PEM electrolysis is made exactly in a manner to consume all the power produced by the PV system. The complete diagram of the PV-electrolysis system is shown in “Fig.7”.The assembly simulation is conducted in the Matlab/Simulink. Modeling physical components of PV is made by the Simscape language and modeling of the digital part is done by the S-Function CMEX tool using the programming language C. Figure 6. Flowchart of the P&O algorithm with a variable step size and an acceleration mechanism The solar radiation signal input from the photovoltaic generator is shown in “Fig.8”. The buck converter equipped with MPPT control, extracts the maximum power and the current of photovoltaic module “Fig.9” and “Fig.10” and transfers them to the electrolysis for:  Control the water mass flow to be injected into the electrolysis  To produce the maximum amount of hydrogen in the form of mass flow depending on the sunlight.
  • 5. Figure 7. Modeling of photovoltaic-electrolysis system in Matlab/Simulink Figure 8. Solar irradiance Figure 9 . Output power of the PV panel transferred to the electrolysis The "Fig.11" and "Fig.12" represent the results of simulations of the water mass flow injected into the electrolyzer and the mass flow of hydrogen produced during the different phases of solar radiation. We simulated these two quantities in a direct coupling of the PV module to the electrolysis, but also during the coupling of the two systems by introducing the DC-DC power converter equipped with its control algorithm (indirect coupling). It appears that: The water flow follows the variation of the power extracted from the PV panel following variations illumination. This proves that the water flow to be introduced into the electrolysis depends only on the power provided by the photovoltaic source PV and afterwards of sunlight. Furthermore by:  The flow of hydrogen produced simultaneously tracks the water flow; it confirms the importance of controlling the flow of water injected into the electrolysis for maximum hydrogen production.  The quantity of water injected into the electrolysis is most important during the indirect coupling than to direct coupling with an equal amount of radiation. Note then, by adopting the process of producing hydrogen using the PV module, the electrolysis, the DC-DC converter and controlling the amount of water is obtained a significant improvement in overall system performance. This improvement concerns first of maximizing the power supplied by the PV module, and eventually an increase in the production of hydrogen through of the water flow control injected into the electrolysis. This leads to optimum operation of the electrolysis and therefore a higher production of hydrogen compared to a direct coupling. Figure 10. Output current of the PV panel transferred to the electrolysis
  • 6. Figure 11 . Water flow injected into the PEM electrolysis with and without controlled DC/DC. Figure 12 . Hydrogen flow produced by the PEM electrolysis with and without DC/DC controlled VI. CONCLUSION In this work, we presented the modeling of various components of the PV-electrolysis system (PEM electrolysis, PV, DC/DC buck converter). We have given particular attention to the electrical modeling of chemical phenomena that occur in electrolysis for integrated it in an electrical environment. So we introduced between the PV module and the electrolysis a DC-DC buck converter type with a digital control algorithm to prosecute the maximum power (MPPT), and ensuring the transfer of this power to electrolysis in order to produce hydrogen. Simulation results show that the coupling between the PEM water electrolysis and the PV panel via a DC/DC buck converter, controlled by an MPPT algorithm and a water flow controller in the electrolysis, leads to an improvement on maximization of the power drawn from the PV module on one hand, and on the other hand maximizing the amount of hydrogen produced in the electrolysis. This has the effect an overall improvement in hydrogen production system designed. REFERENCES [1] Ni. Meng, M. K. H. Leung, D. Y. C. Leung, “Energy and exergy analysis of hydrogen production by a proton exchange membrane (PEM) electrolyzer plant,” J. Energy Conversion and Management, vol. 49, pp. 2748-2756, October 2008. [2] O. F. Selamet, F. Becerikli, M. D. Mat, Y. Kaplan, “ Development and testing of a highly efficient proton exchange membrane (PEM) electrolyzer stack,” Int. J. Hydrogen Energy, vol. 36 , pp. 11480- 11487, August 2011. [3] M. Carmo, D. L. Fritz, J. Mergel, D. Stolten, “A comprehensive review on PEM water electrolysis,” Int. J. Hydrogen Energy, vol. 38, pp. 4901- 4934, April 2013. [4] R. Garcıa-Valverdea, C. Miguela, R. Martınez-Bejarb, A. Urbinaa, “Optimized photovoltaic generatore water electrolyser coupling through a controlled DC/DC converter,” Int. J. Hydrogen Energy, vol. 33, pp 5352-5362, October 2008. [5] A. Garrigos, J. L . Lizan, J. M. Blanes, R. Gutierrez, “Combined maximum power point tracking and output current control for a photovoltaic-electrolyser DC/DC converter,” Int. J. Hydrogen Energy, vol. 39, pp. 20907–20919, December 2014. [6] S. Busquet, C. E. Hubert, J. Labbe, D. Mayer, R. Metkemeijer, “A new approach to empirical electrical modeling of a fuel cell, an electrolyser or a regenerative fuel cell,” J. Power Sources, vol. 134, pp. 41-48, July 2004. [7] H. Gorgun, “Dynamic modelling of a proton exchange membrane (PEM) electrolyzer,” Int. J. Hydrogen Energy, vol. 31, pp. 29–38, January 2006. [8] L. G. Thomas, A. K. Nelson ,”Optimization of solar powered Hydrogen production using photovoltaic electrolysis devices,” Int. J. Hydrogen Energy, vol. 33, pp. 5931 –5940 , November 2008. [9] A. Marshall,1, B. Børresen, G. Hagen, M. Tsypkin, R. Tunold, “Hydrogen production by advanced proton exchange membrane (PEM) water electrolysers—Reduced energy consumption by improved electrocatalysis,” J. Energy ,vol. 32, pp. 431–436, April 2007. [10] W. Smith, “The role of fuel cells in energy storage,” J. Power Sources, vol. 86 , pp. 74-83, March 2000. [11] A. Leonida, J. McElroy, T. Nalette, “ Hydrogen-oxygen proton- exchange membrane fuel cells and electrolyzers, ”J. Power Sources, vol. 29,pp 399-412, February 1990. [12] L. L. Swette, A. B. LaConti, S. A. McCatty, “Proton-exchange membrane regenerative fuel cells,” J. Power Sources, vol. 47, pp. 343- 351, January 1994. [13] T. Loroi , K. Yasuda, Z. Siroma , N. Fujiwara, Y. Miyazaki , “Thin film electrocatalyst Layer for unitized regenerative polymer electrolyte fuel cells,” J. Power Sources, vol. 112, pp. 583–587, November 2002. [14] G. D. Bessarabovb, R. Dattaa, P. Choi, ”A simple model for solid polymer electrolyte (SPE) water electrolysis,” J. Solid State Ionics, vol. 175, pp. 535–539, November 2004. [15] K. Onda, T. Murakami, T. Hikosaka, M. Kobayashi, R. Notu, K. Ito, ” Performance analysis of polymer-electrolyte water electrolysis cell at a small-unit test cell and performance prediction of large stacked cell,” J. Electrochemical Society, vol. 149, pp. A1069-A1078, June 2002. [16] D. M. Bernardi, M. W. Verbrugge, ”A Mathematical model of the solid polymer-electrolyte fuel cell,” J. Electrochemical Society, vol. 139, pp. 2477- 2491, April 1992. [17] S. Dahbi, A. Aziz, N. Benazzi, M. Elhafyani, H. Zahboune, “Toward a new method to improving hydrogen production by an adaptive photovoltaic system,” The 2nd International Renewable and Sustainable Energy Conference (IRSEC’14), Ouarzazate, Morocco, October 2014. [18] S. Dahbi, A. Aziz, N. Benazzi, M. Elhafyani, N. Benahmed, “ Advanced MPPT controller based on P&O algorithm with variable step size and acceleration mechanism for solar photovoltaic system,” Mediterranean Conference on Information & Communication Technologie (MedICT’15), Saidia, Morocco, May 2015.