Application of a Simulation Platform for the Study and Experimental

Comparison of PEM Electrolyzer Models

Antonio José Calderón

, Francisco Javier Folgado

, David Calderón

and Isaías González

Department of Electrical Engineering, Electronics and Automation, Universidad de Extremadura,

Avenida de Elvas, s/n, 06006, Badajoz, Spain

Keywords: PEM Electrolyzer, Hydrogen, Renewable Energies, Smart Microgrid, Simulation.

Abstract: In the last decades, hydrogen has been a trend in the energy sector as it has been employed as an energy carrier

in applications based on Renewable Energy Sources (RES). In this context, RES-based smart grids and

microgrids use devices called electrolyzers to generate hydrogen. The implementation of this device in a real

installation faces difficulties due to its complex operation and the diversity of variables involved. Therefore,

a prior study is essential to understand the behavior of these devices and to achieve correct implementation

and management. This paper describes the application of a simulation platform for the study of Proton

Exchange Membrane Electrolyzers (PEMEL), as well as the comparison of the data obtained through

simulation and those reported from an experimental PEMEL operating within a RES-powered smart

microgrid hybridized with green hydrogen. The principle of operation of the simulation platform is presented

together with the models selected for this research. The experimental PEMEL is framed in the operation of

the smart microgrid, where its automation equipment and the interaction between them are described.

Furthermore, the process followed to obtain the simulated and experimental data is detailed. Finally, a case

study is reported where simulated and experimental results are compared.

1 INTRODUCTION

Hydrogen is a gaseous element under ambient

conditions, whose chemical properties give it high

relevance in applications across various fields. In the

field of chemical industry, hydrogen is present in

petroleum refining processes (Manna et al., 2021), as

well as in the production processes of ammonia

(Ishaq et al., 2021; Manna et al., 2021) and urea

(Ishaq et al., 2021). In recent decades, climate

changes resulting from the use of fossil fuels, as well

as the scarcity of these resources and the progressive

increase in global energy demand have driven the

research and development of new technologies for the

utilization of new energy resources such as hydrogen.

The energy characteristics of this element have made

it a promising energy carrier (Abdin et al., 2020) to

address these challenges, fostering the transformation

of production processes to include hydrogen

generation (Ishaq et al., 2022; Tang et al., 2023),

https://orcid.org/0000-0003-2094-209X

https://orcid.org/0000-0001-6010-0685

https://orcid.org/0009-0004-6569-4581

https://orcid.org/0000-0001-5645-3832

storage (Tang et al., 2023), and utilization (Ishaq et

al., 2022) within industries.

Currently, hydrogen has become a revolutionary

trend in the energy sector, driving advancements in

fields such as automotive (Aminudin et al., 2023),

energy transportation (Niermann et al., 2019), as well

as the reduction of fossil fuel consumption

(Potashnikov et al., 2022) and the exploitation of

Renewable Energy Sources (RES) (Sarker et al.,

2023). In the context of RES-based applications, the

current trend leans towards the integration of

hydrogen in systems such as smart grids or

microgrids. In these systems, hydrogen serves as a

supportive element to stabilize short and medium-

term energy fluctuations caused by the variability of

RES (Atlam & Kolhe, 2011). In these applications,

devices called electrolyzers are employed.

Electrolyzers are hydrogen generation devices based

on the electrolysis process. More specifically, in

RES-based systems, the use of Proton Exchange

Calderón, A., Folgado, F., Calderón, D. and González, I.

Application of a Simulation Platform for the Study and Experimental Comparison of PEM Electrolyzer Models.

DOI: 10.5220/0012202800003543

In Proceedings of the 20th Inter national Conference on Informatics in Control, Automation and Robotics (ICINCO 2023) - Volume 2, pages 289-296

ISBN: 978-989-758-670-5; ISSN: 2184-2809

289

Membrane Electrolyzers (PEMEL) is common due to

their features that allow for a rapid response to

variations in input setpoints (Feng et al., 2017).

The integration of PEMEL into systems like

microgrids is not immediate due to their complex

operation and the diversity of factors to consider for

proper operation (Folgado et al., 2022). Therefore, it

is necessary to conduct a preliminary study in order

to understand the behavior and operation of these

devices, as well as the key variables involved and

their relationships. This knowledge is crucial for

implementing PEMEL and ensuring safe long-term

behavior and operation, thus preventing the

occurrence of degradation mechanisms that reduce

performance and equipment lifespan (Feng et al.,

2017). To understand the operation of PEMEL,

models are used that describe their electrochemical

behavior and associate their mechanisms with

interrelated variables. In (Falcão & Pinto, 2020), a set

of models described by various authors is reviewed,

examining the relationship between variables such as

voltage, working temperature, working pressure,

current density, and the effects resulting from their

variations.

This paper describes the application of a

simulation platform for the study and comparison of

PEMEL models and an experimental PEMEL

integrated into a prototype smart microgrid powered

by RES and hybridized with green hydrogen. In this

work, the operating principle of the simulator, the

equipment comprising the smart microgrid, and their

interconnection are described, as well as the process

of acquiring simulated and experimental data.

Finally, a case study is presented where the behavior

of the models and the real device is compared under

identical operating conditions.

This work is framed within a Research and

Development (R&D) project focused on the

employment of hydrogen and its exploitation as an

energy carrier through its integration into a larger-

scale industrial or domestic RES-based installation.

Therefore, the results obtained from the prototype

smart microgrid are scalable for the higher-power

system. The motivation for the work described lies in

the employment of the result obtained to subsequently

undertake the design of a digital twin of the

experimental PEMEL.

The structure of the rest of the manuscript is as

follows. Section 2 describes the working principle of

the PEMEL, as well as the model employed and the

operation of the simulation platform. Section 3

explains the operation of the smart microgrid where

the experimental PEMEL is integrated, detailing the

relationship between its elements. Section 4

illustrates the data acquisition process and presents

the case study. Finally, the main conclusions derived

from the research are outlined.

2 PEMEL AND SIMULATION

PLATFORM

This section describes the principle of operation and

structure of PEMEL. Furthermore, a brief

introduction of the models selected for this work is

provided, as well as the working principle of the

simulation platform.

2.1 Working Principle and Structure of

PEMEL

As indicated in the previous section, PEMEL are

hydrogen generation equipment based on the

electrochemical process of electrolysis. This process

involves the separation of a compound into its

fundamental components using an electric current

and a reduction and oxidation reaction. The hydrogen

obtained from this process is often denoted with a

colour that indicates the nature of the target

compound for electrolysis (Ajanovic et al., 2022). For

example, grey, brown, or black hydrogen comes from

the electrolysis of fossil fuels and results in the

emission of carbon dioxide during the process.

Furthermore, the designation green is attributed to

hydrogen derived from RES and characterized by the

absence of pollutant-emitting components.

In RES-powered microgrids, PEMEL are

employed for hydrogen generation from water,

resulting in the production of hydrogen and oxygen in

a clean and eco-friendly process. The reactions taking

place at the anode and cathode of the PEMEL are

defined in Equation (1) and Equation (2),

respectively:

2𝐻



+2𝑒



→𝐻



(1)

𝐻



𝑂→2𝐻



𝑂



+2𝑒



(2)

The electrolysis process resulting from both sub-

reactions is illustrated in Equation (3):

𝐻



𝑂→𝐻



𝑂



(3)

Concerning its structure, the PEMEL comprises a

collection of cells responsible for executing the

electrolysis process. These cells can be

interconnected either in series to form a stack or in

parallel.

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2.2 Selected Models

In order to comprehend the PEMEL behavior, a

comprehensive selection of three models existing in

previous literature has been chosen and integrated

within the simulation platform. The selected models

encompass Equivalent Circuit Models (ECM) that rely

on an electrical diagram, thus facilitating the depiction

of the device's behavior through the establishment of

interrelationships amongst electrical components,

including resistors and power sources.

In (Atlam & Kolhe, 2011) an ECM model for a

PEMEL is presented, starting with the description of

the model for a single PEM cell. Such work describes

the relationship among its key variables, with a

particular emphasis on the effects associated with

voltage variations due to changes in temperature or

operating pressure. Additionally, a scalable model is

proposed for the PEMEL voltage, taking into account

the structure and number of cells that compose the

electrolyzer.

In (Awasthi et al., 2011), the model for a PEMEL

operating at high temperature and pressure conditions

(90 °C and 70 bar) is described. This model

investigates the internal aspects that influence the

PEMEL's operation, including factors such as partial

pressures of water and hydrogen for the determination

of the PEMEL voltage.

In the study of (Guilbert & Vitale, 2019) a

dynamic analysis of a three-cell PEMEL is

performed, resulting in an ECM model. This research

illustrates the relationship between key variables of

the PEMEL, such as power consumption, input

current, voltage, and efficiency. Furthermore, the

dynamic response of the stack voltage to variations in

the input current is demonstrated.

The selected models have been employed while

preserving their configuration parameters. Thus, the

aim is to comprehend the operation of each model in

its original state, without introducing any alterations

that may disrupt its behavior throughout the

simulation process or the comparison of results with

other models or the experimental PEMEL.

2.3 Simulation Platform

The selected models have been implemented in a

simulation platform that enables the individualized

study of the behaviour of each model, as well as a

comparison of the obtained results within a single

tool. The simulation platform has been implemented

in MATLAB software. The following MATLAB

features/tools have been employed for this purpose:

Simulink, App Designer, and the MATLAB

workspace. The operational principle of the platform

is founded on the interactions and synergies among

these tools.

Simulink is an environment dedicated to the design

and simulation of models and systems. This tool has

been utilized to implement the selected models and to

execute the simulations. App Designer, on the other

hand, is a MATLAB toolbox specifically designed for

the development of Graphical User Interfaces (GUI).

This toolbox has been employed to create a GUI that

serves as a control interface for the simulator and as a

platform for the visualization of the simulations.

Finally, the MATLAB workspace has been used as a

connection bridge between the other environments,

facilitating communication and data exchange. The

diagram in Figure 1 illustrates the tools utilized in the

operation of the simulation platform, as well as the

diverse interactions among them.

Figure 1: Simulation platform. Interactions between tools.

To facilitate the management of the simulation

platform, users are provided with a GUI that

operates based on navigation across various tabs.

The GUI initiates by displaying a main tab,

comprising buttons that grant access to the specific

tabs of each model, as well as a tab dedicated to the

comparison of model results. Furthermore, each

model tab includes an additional tab devoted to the

visualization of simulation results through graphical

representations.

In (Gaspar et al., 2021), a detailed description of

the operation, design and structure of the simulation

platform employed in this work is provided, along

with the integrated GUI and its implementation.

3 SMART MICROGRID AND

EXPERIMENTAL PEMEL

Section 3 describes the Smart microgrid where the

experimental PEMEL is framed, detailing the

equipment involved and their interactions. Moreover,

Application of a Simulation Platform for the Study and Experimental Comparison of PEM Electrolyzer Models

291

the technical specifications of the experimental

PEMEL used in this work are detailed, as well as the

auxiliary equipment, hardware, software and

communications employed for its correct operation.

3.1 Smart Microgrid

The experimental PEMEL under study in this work is

integrated into a prototype smart microgrid powered

by RES and hybridized with hydrogen. The smart

microgrid consists of two systems. Firstly, there is the

main generation and storage system, composed of a

set of photovoltaic (PV) panels and a Lithium-Ion

(Li-Ion) battery.

The hydrogen-based support system comprises a

generation system employing a PEMEL, a storage

system by means of metal hydride tanks, and an

electrical generation system based on a PEM Fuel

Cell (PEMFC). The PEMEL and PEMFC are

connected to DC/DC converters in order to adjust the

voltage setpoints of these devices with the central DC

bus, whose voltage level is managed by the battery.

Lastly, a programmable electronic load is

available to simulate different load profiles, thus

generation an energy demand within the system.

The diagram in Figure 2 illustrates the

components of each system that constitute the smart

microgrid, as well as the interaction between them.

Figure 2: Component of the prototype smart microgrid.

The operation of the smart microgrid is as

follows. The PV panels generate the required current

to meet the energy demand imposed by the

programmable electronic load. If there is an excess of

electrical production beyond the energy demand, the

remaining current is stored in the Li-Ion battery. If the

State of Charge (SoC) of the battery exceeds an upper

threshold, the surplus energy is transferred to the

PEMEL for the generation of green hydrogen. This

hydrogen is stored in the metal hydride tanks. In the

event that the energy demand from the load exceeds

the production from the PV panels, and the SoC of the

battery is below a minimum threshold, the PEMFC is

activated to generate electricity from the stored

hydrogen. This ensures the required electrical current

is supplied to the load.

3.2 Experimental PEMEL

The green hydrogen generation system consists of a

six-cell PEM stack and a set of ancillary sensors and

actuators that facilitate data acquisition and

operational control of the PEMEL. Figure 3 illustrates

the appearance of the experimental PEMEL, which

has been equipped with a temperature sensor and a

fan to regulate the working temperature. Table 1

provides the main technical specifications of the

experimental PEMEL.

Figure 3: Experimental PEMEL appearance.

Table 1: Main technical specifications of the experimental

PEMEL

Number of cells 6 cells in series

flow rate generated 250 ml/min; 15 l/h

purity

99.9999 %

Input current Up to 8 A

Working temperature 25 to 50 ºC

Working pressure Up to 6 bar

In Table 2, a series of measured variables and

control signals for the operation of the PEMEL are

listed, along with the components used for their

measurement or actuation.

To centralize and manage data from the

experimental PEMEL, a Programmable Logic

Controller (PLC) is employed, which, in turn, sends

this information to a dedicated SCADA system for

real-time monitoring of the hydrogen generation

system. The SCADA has been implemented using

LabVIEW software, a specialized programming

environment for designing such systems. The

communication and data exchange between the PLC

and SCADA have been resolved through the Open

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Table 2: Measured variables and control signals for the

operation of the PEMEL. Devices employed for

measurement/actuation.

Measured variables /

control signals

Devices

Voltage (V) Potentiometer

Input current (A) Hall effect sensor

Working temperature (ºC) PT-100

Working pressure (bar) Pressure sensor

Ambient temperature (ºC) PT-100

Hydrogen flow rate

(mL/min)

Thermal Mass Flow

Mete

Water purge Electrovalve

Feed water level

Electro-optical level

senso

ON/OFF power supply

PEMEL

DC Relay

Platform Communications (OPC) protocol,

specifically using its Data Access (DA) variant,

which is widely used for data exchange in industrial

environments (González et al., 2019). Additionally,

the SCADA allows storing the visualized data in an

Excel spreadsheet. The diagram in Figure 4 depicts

the data flow from the PEMEL to its visualization in

the SCADA, indicating the equipment, processes, and

communication protocols involved.

Figure 4: Flow data from PEMEL. Centralization,

management and visualization.

4 RESULTS

This section details the results obtained from the

application of the simulation platform. For this

purpose, the conditions of the case study conducted

are described, and a graphical comparative analysis of

the behaviour of the models and the experimental

PEMEL is conducted. Finally, conclusions are

presented based on the results displayed.

4.1 Case Study

In order to perform a comparative analysis between

the models and the experimental PEMEL, it is

imperative to establish precise conditions for

conducting the experimental tests. Subsequently, the

measured experimental conditions will be replicated

in the simulator to obtain results under comparable

conditions. The conditions set for the experimental

tests are as follows:

First, the experimental PEMEL starts from an idle

state, performing an ascending path in the input

current from 0 A to 8 A, with 0.2 A intervals and a

settling time of 1 min.

Secondly, the experimental tests are conducted at

atmospheric pressure (1 bar). This condition is

imposed due to the technical limitations of the

experimental PEMEL installation, which hampers a

direct measurement of the pressures at the cathode and

anode of the equipment. These pressures are required

for the model of (Awasthi et al., 2011), so the PEMEL

is operated at atmospheric pressure to maintain a fixed

value for these variables. Furthermore, there is a

specific interest in studying the isolated behavior of the

experimental PEMEL, independent of any interaction

with the other components of the installation. To

achieve this, the PEM stack is disengaged from the

storage system, facilitating the release of the generated

hydrogen into the atmosphere.

The aim of this study is to acquire information from

the measured variables in order to construct the chara-

cteristic curves that depict the behavior of the PEMEL.

4.2 Comparative Analysis

In order to perform the comparison of the obtained

results, the characteristic curves of the models and the

experimental PEMEL are grouped together and

presented with a common legend. Firstly, the curves of

the models are denoted by the name of the first author

of the original research. For example, the model from

(Atlam & Kolhe, 2011) is referred to as "Atlam."

Additionally, a colour code is followed for each curve,

using blue for Atlam, orange for Awasthi, grey for

Guilbert, and yellow for the experimental PEMEL.

4.2.1 I-V Curve

The relationship between the input current (I) and the

voltage of the PEMEL (V) forms the I-V characteristic

curve, which is the main curve that describes the

behavior of the equipment. This curve can be

segmented into two operating regions. Initially, there

is a current range spanning from 0 to 0.5 A, where the

Application of a Simulation Platform for the Study and Experimental Comparison of PEM Electrolyzer Models

293

voltage exhibits a significant increase, eventually

stabilizing at an initial operating value. Subsequently,

the I-V curve enters the nominal operating region,

which extends from 0.5~1 A to 8 A. Within this

region, the curve assumes a linear trajectory, with its

slope varying based on the working temperature and

pressure. Figure 5 illustrates the I-V curves for the

various models as well as the experimental PEMEL.

Figure 5: I-V curve.

In the mentioned figure, it can be observed that all

curves follow the behavior described earlier. There is

an initial current range with an initial operating

voltage, followed by a linear operating range. For the

model curves, the initial voltage starts around 9 V,

followed by a distinct and pronounced increase.

The curves of Atlam and Awasthi exhibit similar

values, tracing a parabolic trajectory where the

voltage rises with the increase in input current,

reaching a maximum of 19 V at 8 A. This trajectory

is influenced by the increase in working temperature

resulting from the operating time and input current

consumed by the PEMEL.

The Guilbert curve follows a linear trajectory with

a constant increment, reaching a maximum voltage of

approximately 15 V. In this model, the voltage

calculation is independent of the operating

temperature, indicating that the voltage increase is

solely due to the increase in input current.

On the other hand, the experimental curve shows

a sudden increase in voltage, acquiring a higher value

than the Atlam and Awasthi curves for low current

ranges (0 to 2.5 A). In the nominal operating range,

the I-V curve presents a lower slope than the curves

of the models, resulting in approximate coincident

values between 3 and 6 A. Finally, similar to the

Guilbert model, the curve reaches a maximum value

of approximately 15 V.

4.2.2 I-P Curve

The total consumed power (P) is directly proportional

to I and V. This variable encompasses both the useful

power employed by the PEMEL during the

electrolysis process and the dissipated or lost power

during the operation of the device. Figure 6 illustrates

the I-P characteristic curve for the simulated models

and the experimental PEMEL.

Figure 6: I-P curve.

In this figure, the direct relationship between P

and I can be observed, where the value of P exhibits

an increasing trend with increments in I. Furthermore,

the trajectory and value of P in each curve are

determined by the value of V. Similar to Figure 5, the

maximum values of the curves are initially reached by

the Atlam and Awasthi models. The minimum values

of P are represented in the figure through the Guilbert

curve. Finally, the I-P curve of the experimental

PEMEL reflects intermediate values compared to

those shown by the model curves.

4.2.3 P-v

Curve

The hydrogen flow rate generated by the PEMEL

) is directly proportional to the consumed power.

The P-v

characteristic curve, depicted in Figure 7,

illustrates the relationship between the amount of

product generated by the electrolyzer and the total

energy consumption required.

Figure 7: P-v

curve.

As observed in the figure, each curve exhibits a

distinct trajectory. This occurrence is attributed to the

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dependence of P on V, resulting in a relationship

between the V-I and P-v

curves.

Regarding the models, the Guilbert, Atlam, and

Awasthi curves exhibit a pronounced parabolic

trajectory, with the Guilbert curve demonstrating the

maximum v

values for a given current point. As

for the experimental PEMEL, its curve follows a

more linear path, reflecting the minimum values

among the plotted curves. The figure illustrates how

the nominal v

value (Table 1) is attained at a power

value of 100 W.

4.2.4 I- η Curve

The efficiency of the PEMEL (η) is an indicator that

reflects the overall operating performance of the

equipment, encompassing all aspects that affect its

operation. This parameter is determined by the ratio

of the useful power employed in electrolysis and the

total consumed power. Figure 8 depicts the I-η

characteristic curve, illustrating the evolution of

efficiency as a function of the input current.

Figure 8: I- η curve.

In the figure, it can be observed that the efficiency

of the experimental PEMEL remains around 50%

within the nominal current range. On the other hand,

the Guilbert curve estimates a maximum efficiency of

around 60%, while the Atlam and Awasthi curves

indicate an efficiency of approximately 40%.

The trajectory and form of these curves exhibit a

reflection of the I-V curves depicted in Figure 5,

owing to the dependence of η on P, and consequently

on V. In fact, it can be observed that the experimental

PEMEL curve and the curves of the Atlam and

Awasthi models uphold similar values within the

current range of 3 to 6 A, close to those presented in

Figure 5.

4.3 Discussion

Following the results shown in the previous section,

a series of conclusions can be drawn about the

behaviour of the models and the experimental

PEMEL.

Firstly, the characteristic curves that define the

behaviour of the PEMEL are closely linked to the

evolution of V during its operation. This fact reaffirms

the importance of the I-V curve as the main

characteristic curve of the device. The voltage level

of the PEMEL conditions the total power consumed

and, therefore, the hydrogen production and the

efficiency of the equipment. Therefore, the

trajectories of the I-P, P-v

and I-η curves are

modified by the shape of the I-V curve.

Regarding the simulated models, the plotted

characteristic curves illustrate a remarkable

difference between the Guilbert model and the Atlam

and Awasthi models. On the one hand, Atlam and

Awasthi present curves with values close to each

other due to their similar dependence on temperature

and working pressure. However, a slight difference is

observed in these curves, because the Awasthi model

considers the partial pressures at the cathode and

anode, as well as the variations in the ambient

temperature surrounding the PEMEL. The Guilbert

model, on the contrary, describes the behaviour of the

PEMEL independently of the temperature and

operating pressure of the equipment, which results in

an I-V curve with a more linear trajectory and lower

values with respect to V.

Common to all models, the values of v

shown

in Figure 7 illustrate an over-estimation of hydrogen

generation, reaching values much higher than those

indicated in the technical specifications of the

equipment. This leads to the future need to modify the

models in order to adjust their behaviour to the

technical limitations of the experimental PEMEL.

In relation to the experimental PEMEL, the

behaviour of this device resembles those described by

the Atlam and Awasthi models for nominal current

range of 3 to 6 A. This range is contained within the

operating current limits of the experimental PEMEL

during the operation of the prototype smart microgrid.

Due to the above, and in order to design a model

of the experimental PEMEL in the future, the Guilbert

model is excluded and the Atlam and Awasthi models

are chosen as possible base models.

5 CONCLUSIONS

This paper has presented the application of a

simulation platform for the study of PEMEL models,

along with an experimental comparison using a

PEMEL integrated into a prototype smart microgrid

hybridized with green hydrogen. The operational

Application of a Simulation Platform for the Study and Experimental Comparison of PEM Electrolyzer Models

295

principle of PEMEL has been described.

Subsequently, the operation of the simulation

platform has been illustrated, and the available

models within it have been presented. Regarding the

experimental PEMEL, its operation within the smart

microgrid has been framed, including a description of

the components comprising the microgrid and the

installation implemented around the experimental

PEMEL. The automation and supervision system

applied to acquire and visualize experimental data has

also been described. Finally, a case study has been

illustrated through the comparison of characteristic

curves of the PEMEL for the simulated models and

the equipment in the microgrid.

In terms of future research aligned with this study,

one potential avenue involves leveraging the

simulation platform to adjust the characteristic

parameters of the available models. The objective is

to attain a model that accurately represents the

behavior of the experimental PEMEL in order to

develop a digital twin for the device. Another future

endeavour entails utilizing the insights gained from

comparing the obtained results. This knowledge can

be applied to effectively integrate a PEMEL into

larger-scale industrial or residential installations

based on RES.

ACKNOWLEDGEMENTS

This project was supported by MCIN with funding

from European Union NextGenerationEU (PRTR-

C17.11) and by the Junta de Extremadura with

funding from European Regional Development

Funds (FEDER).

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