Techno-economic Analysis of Hybrid Renewable Energy System for
Hydrogen Production in the Demnate Region of Morocco
IKRAM EL HAJI, MUSTAPHA KCHIKACH, ABDENNEBI EL HASNAOUI
Power Electronics and System Control Lab,
Higher National School of Mines,
Avenue Hadj Ahmed Cherkaoui, B.P: 753, Agdal, Rabat,
MORROCO
Abstract: - This paper investigates the techno-economic feasibility of producing electrical energy for three
villages in the mountains in the Demnate region. The community needs were determined based on the site visit
to identify the electrical load demand in reality. In addition, a site description was done to evaluate the suitable
system to produce the electrical energy. Using the Homer software, two systems were selected to produce
electricity and hydrogen which are described as follows: The first system is constituted of a PV-Generator with
3759 kW, an Autosize Genset generating 300 kW, a DC/ AC converter supplying 317 kw, 800 kW produced by
the electrolyzer, and a hydrogen storage tank with 900 Kg as a capacity. The second system is composed of PV
modules with 3743 kw, seven G3 wind turbines with 3kW, an Autosize Genset generating 300 kw, 323 kW of
power converters, a generic electrolyzer with an output power of 800 kW, and a hydrogen tank with 900 Kg as
capacity. In addition, the financial analysis gives 1.56$/kWh and 1.57$/kWh as the Levelized Cost of Energy
and 15.6 M$ and 15.7 M$ as the Net Present Cost for the first and second systems respectively.
Key-Words: - Hydrogen, techno-economic study, renewable energy systems, energy storage, Morocco,
hydrogen storage, Pv system,, Turbine Wind system, LCOE, NPC.
Received: May 19, 2023. Revised: May 22, 2024. Accepted: June 25, 2024. Published: September 3, 2024.
1 Introduction
Faced with the intermittency of renewable energy
systems (RES), energy storage systems (ESS) are
defined as one of the promising solutions to ensure
the balance between the rural and urban population's
needs and renewable energy intermittent production.
Indeed, several types of ESS have been introduced
in many literatures to solve the previously
mentioned problem including pumped hydro storage
(PHS), compressed air energy storage (CAES),
thermal energy storage (TES), electrostatic and
magnetic energy storage (EMES), and
electrochemical energy storage (ELMES), [1].
Furthermore, numerous studies have been conducted
to investigate the feasibility of using RES with the
ESS option to promote electrical energy access to
cities and rural areas, [2], [3], [4]. The adoption of
ESS to produce electrical energy is highly
recommended by researchers due to the high cost of
grid extension especially for rural and isolated areas.
The ESS are used in multiple types of service
including schools, universities, and hospitals, [5],
[6], [7]. For the reason that the well-managed use of
ESS can highly improve several populations’ lives
by providing electrical energy to health and
education buildings. For instance, in the
Siyambalanduwa region of SIRILANKA, an off-
grid hybrid energy system was designed to electrify
rural areas due to the national grid's non-existence
by using the “HOMER” software tool. Hence, the
selected hybrid system to feed the site with
electricity was composed of PV, wind, and battery
generators with 0.36 $/kWh as a levelized cost of
energy, [8]. Similarly, a case study was conducted
in a village west of China to investigate the techno-
economic feasibility of an off-grid hybrid renewable
energy system using the software tool mentioned.
The optimization results confirm the effectiveness
of the selected hybrid system implementation with
104 kW PV modules, three Wind turbines of 10 kW,
50 kW Biogas fueled Diesel Generator BDG, 331
kWh storage batteries, and 99 kW power converter,
which leads to total independence from the grid
network in this Chinese village, [4].
Off-grid systems have also emerged for mobile
homes as an alternative to grid extension in some
countries, such a case study assessed in IRAN to
feed mobile homes with electricity using the
“TRNSYS” software tool, giving an LCOE of 0.23
$/kWh. The system lacks 2.45%, equivalent to
118 h of required electrical energy, and produces
56% of surplus energy, [9].
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On the other hand, ESS is also used to limit
stability problems in the network when the PV
system is connected to the grid. In particular, grid-
connected to residential PV systems with battery
supercapacitors were designed and modeled to
analyze small signals of the proposed system. As a
result, the ESS has the advantage of providing a
dynamic performance and a rapid response during
the load and PV generation changes, [10]. However,
some disadvantages occur when batteries are used in
the long term. Therefore, using batteries as an
energy storage component requires three to four
times its replacement in case of bad management
and the health and environmental harmfulness
caused by their usage during the expiration period,
[11].
For this reason, and to avoid these
inconveniences, several research studies have been
carried out on alternatives to replace batteries. It has
been found that hydrogen could be an alternative
solution to different storage systems.
Recently, the interest in green hydrogen
production has been widely increasing. It is
considered a promising key for industrial,
transportation, and residential sectors by the
prediction of its ability to replace fossil fuels.
However, the approach that aims to adopt hydrogen
practically in different sectors, is still lacking
resources and studies to come up with a global view
concerning the future of green hydrogen production
and its use.
To respond to these scientific and industrial
needs, different strategies were proposed by
researchers to enhance effective hydrogen
production. It is classified based on two levels: the
first one depends on the importance of energy
sources such as electrical, biochemical, thermal, and
material used in the production process including
fossil fuels, water, biomass, and water, while the
second depends on the component used during the
production process (electrolyzer …etc.), [12].
Indeed, the hydrogen production method's
performance depends on several criteria that mainly
involve technical, economic, thermodynamic,
environmental, and social criteria. Based on these
aspects, a performance comparison of different
production methods has been conducted in the
literature, [13]. In conclusion, high-temperature
electrolysis provides the highest energy efficiency
while photo fermentation has the lowest energy
efficiency and CO2 emissions. Therefore, the hybrid
thermochemical cycle is the most efficient among
the others in terms of energy efficiency.
Among the various hydrogen production
methods, the one based on renewable energy
sources is the most concerned in the energy
transition phase. Despite its implementing
advantages, it is still insufficient to get a clear road
map in different fields and sectors. Especially in the
African continent is especially known for its huge
diversity and potential for renewable energy
sources, which might make it the main green
hydrogen producer and exporter to the rest of the
world.
So, the right use of this diversity of renewable
resources can guarantee self-satisfaction for
countries that are most dependent on fuels in the
industry sectors. As a result, conducting studies
about the feasibility of hydrogen production and
integrating its technology in African countries is
recommended. Several researchers have studied the
necessary criteria to produce green hydrogen purely
based on RES. In [14], The study claims that Africa
could export 20.90 % of the hydrogen to the
European market due to the potential of available
RE resources 34.88% and the high number of
population’s youth (13.95 %) while the ammonia
production according to the research goes to
20.90%.
Other encouraging studies propose the use of
green hydrogen in the transport sector as a
replacement for fossil fuels by profiting from its
nontoxicity, [15]. The study aims to assess a
techno-economic investigation of a wind-hydrogen
refueling station in seven South African cities. The
station was designed to feed 25 green hydrogen
vehicles daily with 5 tanks for each vehicle. Results
prove the viability of the station with a competitive
price of 6.34 $/kg green hydrogen compared to 8.97
$/kg of fuel price in addition to the CO reduction by
0.133 tons and CO2 emissions by 73.95 tons per
year. Similarly, in Niger, a case study shows the
possibility of using hydrogen to provide electricity
for the transport sector. The total hydrogen
production needed to replace 1% of gasoline and
diesel demand toward 2040 is about 0.0117 Mt,
while the space required to implement the
installation is 5% of the Niger land, [16].
In other regions of the world, like Ningbo in
east China, a combined hydrogen and heating
system based on solar energy was proposed to
constitute an off-grid system that produces
6179 kWh for summer and 3667 kWh for winter
seasons, [17].
Correspondingly, in Belgium, a case study was
conducted to assess the techno-economic feasibility
of using current and future ESS based only on
hydrogen including unique battery systems and
hybrid storage systems (battery and hydrogen). The
first option was not considered a competitive
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solution compared to the other proposed storage
systems, [18].
In one Moroccan city, as illustrated in the
literature [19], a refueling station was designed to
produce 152 kg/day of green hydrogen to supply the
total of electrical taxis with a cost of 9.18 $/kg,
while 30. kg/day with 12.56 $/kg is required to feed
only 20% of taxis with a cost of 12.56 $/ kg. This
research study responds to the Moroccan
government's strategy regarding green hydrogen
production and renewable energy systems adoption
instead of fossil fuels. Therefore, the aim is to
enhance the use of renewable energy systems by 52
% by 2030 [20].
Indeed, the focus on rural areas is highly
recommended when speaking about electrification
availability due to the need to develop these
villages, especially since the off-grid system’s
implementation could be more economical, unlike
the grid extension due to the high distance its
realization becomes more costly. For this reason,
our research work in this paper investigates at the
first stage the financial feasibility of integrating the
off-grid systems technology with hydrogen storage
for 140 families in the Demnate region of Morocco.
In the second stage, the off-gird system is compared
to the grid extension option to identify the most
suitable solution from which the considered region
can benefit economically. Finally, a green hydrogen
load was considered during the modeling and
simulation phase to measure the correspondence
between hydrogen storage and its effective
consumption. This paper's results were found using
the Homer software tools simulation. However, an
on-site visit is crucial to identify the software's
inputs and the system's power source availability
and coherence with the mountains of the Demnate
region. The following sections describe the
methodology followed in this paper.
2 Hydrogen Project Feasibility and
Natural Constraints Conditions
Most commonly reviewed studies propose the
exploitation of hydrogen in cities for refulling
stations or other sectors. However, the space and
cost are still presenting limitations to promote
hydrogen-optimized production. As for the cost
factor, it can be reduced by developing the
production processes and by increasing the common
interest in industrial sectors to produce efficient
system components with lower costs. For instance,
the PV panels and batteries prices were extremely
high at the first stage of their production era.
However, prices have steadily decreased due to the
large competition and technology development,
especially after several companies have moved to
larger and cheaper land areas. Indeed, off-grid
systems with hydrogen storage for rural areas could
provide a great solution for different problems
including electrical energy access, economic and
demographic growth, and self-dependency.
The Moroccan economy is still primarily based
on the agri-food sector, especially in rural areas.
Therefore, this paperwork aims to investigate the
feasibility of integrating off-grid systems in these
regions worth considering. In the second stage, the
selection of suitable systems configuration to feed
their load demands using Homer software tools. The
paper proposes also the possibility of benefiting
from this promising project in transferring electrical
energy to major cities.
3 Methodology of the Project Study
Practically, three villages in the Demnate region of
Morocco were selected to investigate the techno-
economic feasibility of integrating off-grid systems
with green hydrogen storage. Initially, the region's
metrological conditions and climate variations were
analyzed to choose renewable energy sources
highlighting the systems' required components. The
second phase is the modeling of the system’s
components which involves renewable energy
sources such as PV modules, wind turbines, and
biomass then simulating the whole system to get a
response each time of the year. The third is
optimizing the system by using the Homer software
which is done based on different key factors
including the system’s cost and annual production
LCOE and CNPC.
Figure 1 shows the system components. It
comprises PV modules, wind turbines, biomass,
DC/DC and DC/ AC power converters, and storage
devices.
3.1 The Required Input Data
Input data will be set at the beginning of the project
design and simulation via the mentioned software
tool. They are required to ensure an appropriate and
suitable sizing of the system. The most important
inputs are the load demand and meteorological data.
In fact, by referring to the selected area's load
demand, the system's output ( electricity) can be
predicted so the system design can fit the village's
electrical requirement. In addition, meteorological
data are important to assess a correct analysis of the
village’s renewable energy sources. They provide
specific information concerning the weather change
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and variation yearly, monthly, and seasonally also
which leads to selecting the appropriate type of
renewable energy source to power the system.
Basically, the required meteorological data are solar
irradiation, wind speed, humidity, and rain falling
which are obtained from the Surface Meteorology
and Solar Energy database of NASA (National
Aeronautics and Space Administration) as
illustrated in Figure 2.
Fig 1: model of the hybrid off-grid system for
hydrogen production
3.2 The System Sizing and Simulation Tool
Function
The system’s size and development are carried out
by using HOMER PRO Software. This software is
also used to study the performance of the system
regarding two main factors which are: the NPC and
the LCOE expressed in equations (1), and (2). The
software takes into consideration the available
renewable energy sources of the mentioned areas,
the load demand, the budget of the project, and the
space required for the system installation. In
addition, the HOMER PRO Software tool allows the
detection of all possible options for the system
implementation so that the user can easily compare
the defined cases in terms of cost and performance.
3.3 Determination of Techno-Economic
Indicators and Analysis
The determination of the two main indicators NPC
and LCOE of energy cost are taken into account in
the techno-economic analysis to define which
system is more performant and economical. So, the
LCOE represents the cost of useful electrical energy
produced by the system per kWh, [21]. It is also
considered the major factor in determining the
project feasibility and competitiveness and is
defined as the division of the annualized cost of the
useful produced electrical energy which is
calculated by the following equation (1), [22].
(1)
Where:
LCOE: is the levellized cost of energy ;
Cann, tot: is the system's annualized total cost
expressed in dollars per year;
Epri: is the primary load served (AC and DC) in
kWh/ year;
Edef: is the deferrable load served in kWh/ year;
Egrid, sales: is the entire gird sales in kWh/ year.
The NPC indicator is calculated by the following
equation (2):
(2)
Where :
CNPC: is defined as the total Net Present Cost in $;
CRF: is defined as the capital recovery factor, i is
expressed in %;
Rproj: is the lifetime of the project in years;
Cann, tot: is the system's annualized total cost
expressed in $ per year.
3.4 The Impact of Natural Electrical Energy
Sources Variables
The sensitivity examination consists of studying the
impact of different physical variables on the
modeled system and analyzing the parameter
variations that occur under climate and
environmental changes. In addition, it evaluates the
designed system effect regarding more than one
case as cited in the literature, [4], [22], [23], [24],
which reveals the selected system robustness
through the examination of uncertain variables such
as solar irradiation, biomass, and diesel price, [3]. In
most of the cases, the doubt is considered in the
energy resources and mentioned system
components, [3], [25].
4 Modeling of Renewable Energy
System’s Components
In the current study, solar and wind are considered
as the main primary sources of renewable energy
systems. Annual Monthly solar radiation and wind
speed data are obtained and simulated with the
HOMER PRO software tool. The evaluation of the
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energy storage systems and resources is explicated
in the following manner:
4.1 Solar Radiation and PV Modules Output
Power
Based on the measured solar radiation and ambient
temperature, The hourly energy output of solar
modules can be computed using the following
calculation, [22]:
(3)
where
YPV [kW]: represents the PV array's related
capacity, or its output power under typical test
circumstances (STC), which consist of radiation of 1
kW/m2, cell temperature of 25 °C with no wind;
fPV: is the PV derating factor;
GT: is the solar radiation incident on the PV array in
the current time step;
GT, STC: is the incident radiation at STC;
: is the temperature coefficient of power;
Tc: is the temperature of the PV cells in the current
time step;
Tc, STC: is the temperature of the PV cells at STC.
According to the NASA website data resources,
The annual average solar irradiation is 5.40
kWh/m2/ day for the three villages.
4.2 Wind Speed and Turbine’s Output
Power
A turbine's main function is to convert the
mechanical wind energy into electrical energy.
Equation (4) represents a wind turbine’s output
power under normal pressure and temperature [3], in
which the wind turbine's rated power, rated velocity,
cut-in velocity, and cut-out velocity are indicated by
the letters Pr, Vr, Vcut-in, and Vcut-out.
According to the diagram shown in Figure 2, the
monthly average wind resource statistics for the
chosen villages are provided from the NASA
resource website. The annual average wind speed in
the considered region is 3.57m/s.
(4)
Where
Pr: is rated power, Vr<v(t)< Vcut-out
Vr: is the rated velocity
Vcut-in: is the cut-in velocity
Vcut-out : is the cut-in velocity
4.3 Hydrogen Energy Storage System
Components
The energy storage system in the three villages is
composed of an electrolyzer and green hydrogen
tank as shown in Figure 1. Indeed, in most common
off-grid systems, the batteries have emerged as
beneficial devices to store the excess of the
produced energy and create equivalence between the
load demand and energy excess during low-demand
periods. In addition, batteries can be used in off-grid
and on-grid systems to reduce the intermediacy of
renewable energy sources. Despite their significant
role in storing energy, the green hydrogen storage
technique has become a major competitor.
4.3.1 Electrolyzer
As a crucial device of the renewable energy
production system, the electrolyzer is considered
one of the most appropriate manner for green
hydrogen production, [26]. It is divided into
multiple types according to the practical usage.
PEM and alkaline electrolyzers are the most
commonly used due to the purity of hydrogen
produced and also due to their low capital cost
compared to other types, [27].
4.3.2 Hydrogen Storage Tank
The produced green hydrogen through an
electrolyzer, is compressed and stored in a tank. The
power required for the green hydrogen compression
is expressed in the equation (5) as follows, [28]:
(5)
Where
ψ: is the polytrophic coefficient;
R: is the gas constant;
T : is the compressor inlet temperature;
Ƞc: is the compressor efficiency;
P1: is the inlet pressure;
P2: is the outlet pressure;
: represents the mass flow rate of the green
hydrogen.
The green hydrogen tank's pressure is defined
below in the equation (6):
(6)
Where
ηtank: is the number of moles of gas in the tank;
Vtank: is the tank's capacity.
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5 Technico-economic Data of the
Studied Region
5.1 Site Description:
The three villages considered for study are TIZI,
IGRDAN, and ASFOULA. They are located in the
Demnate region in the AZILAL province of
Morocco with an altitude of 960 meters above sea
level and geographical coordinates of 29°49'51°N
and 9°22'10°W. The three settlements are home to
140 families. They sit close together in the center of
Montagne far from Marrakech city about 110 Km,
where there are few transportation options and
consequently few people, which impacts the
population’s daily life.
The two main economic activities in these rural
areas are agriculture and livestock husbandry.
They are connected to the grid network.
However, due to the geographical shape site, it
is difficult to maintain a fluent energy flow and
the use of an electrical grid network during the
hot or cold seasons is financially exhausting for
the population due to their low income. For
these reasons, it is very crucial to find other
ways to supply the three villages with cheap
and independent electrical energy sources other
than the grid network. Therefore, the main
purpose of this study is to respond to this
energy issue, based on an on-site visit, the
community's needs and suitable solutions are
selected.
5.2 Electrical Loads Assessment Used in the
Study Area
The electrical demand assessment was carried out
based on an on-site study in the village. The three
villages' load demands are divided into three
categories: basic household load, community load,
and commercial load. Since the determination of the
load demand is captured based on seasonal
variations (air conditioning, fans, refrigerator
…etc.), water pumping, schools, and mosques are
all seasonal loads, so the basic household load is
energy-consuming dominant compared to
commercial and community loads. Table 1
(Appendix) shows the daily electrical power
demand seasonally.
Most of the existing household loads are modest
in the study area and don’t require high electrical
energy by using grid extension due to its high cost.
This encourages the integration of an optimized
renewable energy system to respond to the
community needs.
Table 1 (Appendix) illustrates the electrical
power consumption of each household appliance
during one day in the summer and winter seasons.
As noted, one household needs 15,19kWh/day and
14,66kWh/day during winter and summer
respectively. However, the total energy needed for
the three villages is 2127,65 kWh per day and 253
kW as peak electrical power.
5.3 Design Specification and Component
Choice
The designed hybrid renewable energy system is
composed of solar modules and wind turbine
generators as main sources, and the storage unit tank
of hydrogen while the power converter is used to
provide the electricity (current or voltage) for
different load types from DC to AC. The hydrogen
tank serves as a storage unit to guarantee the
stability of the output electrical power given to the
loads. As for the electrolyzer, it uses electricity to
split water into hydrogen and oxygen, while its load
is inserted to measure the efficiency of the hydrogen
tank. Indeed, the grid modules were taken into
consideration in the design phase to compare the
economic impact of off-grid systems with hydrogen
and on-grid systems with hydrogen storage.
Additionally, a generator is inserted as a source of
energy to prevent the problem of renewable energy
source intermediacy. The majority of economic data
input of the designed component is selected from
the HOMER software database. As shown in Figure
1, multiple components were selected to constitute
the architecture of the optimized suggested system.
The following paragraph describes the inserted
parameters of the selected system components.
5.4 Solar Power Generator Modules
The PV power generator is connected to the DC bus
with a lifetime of 25 years. From the HOMER
software database, a generic flat plate PV is selected
with a capital cost of 2500$ for 1 kW, 2500 $ as a
replacement cost while the O&M cost considered is
10$/year. In addition, about 80% is thought to be the
derating factor of each PV panel. Nevertheless, the
number of PV panels opted to generate the power is
determined by the Homer optimizer feature.
5.5 Wind Power Generator Turbine
Like the PV generator selection, the wind turbine
power generator type selection is done by referring
also to the HOMER software database. The wind is
connected to the AC bus. A generic 3 kW (G3) is
selected with a lifetime of 20 years and a hub height
of 17m. The capital cost of one unit of G3 is fixed at
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18000$ while the considered replacement cost is
18000$ and the O&M cost is 180$/year.
(a) Monthly solar Global Horizontal Irradiance changes
b) Monthly wind speed changes
Fig. 2: Diagram of natural energy resources changes
5.6 Generator
An Autosize Genset is selected to provide backup
power in the designed system. It sizes itself
automatically to meet the load requirement. The
initial capital cost and the replacement cost of the
auto-size Genset are equal to 500$/ kW while the
O&M cost is 0.030$/op.hour. The generator is
connected to the DC bus with a lifetime of 1500
operating hours and the minimum load ratio is set to
be 20%.
5.7 Power Converter
The power converter is used to provide the AC
outputs from the DC source to meet the load
requirement. The selected type is a generic system
converter with a lifetime of 15 years. Its efficiency
and relative capacity are 95% and 100%
respectively while the capital and replacement cost
of 1kw is 300$.
5.8 Electrolyzer
The electrolyzer is linked to the DC side, the
selected electrolyzer is a generic electrolyzer with a
15-year lifetime, with a capital cost of 1100$ for one
kW, a replacement cost of 850$, and an O&M cost
of 10 $/year. As for its capacity optimization, it
varies between 0 kw to 800 kW and its efficiency is
approximately 85%. The economic data is obtained
by referring to the literature, [26].
5.9 Hydrogen Tank
A generic tank is selected to store the hydrogen
produced by the designed systems with a lifetime of
25 years. The capital cost of 1kg produced
hydrogen is 1000 $ while its replacement cost goes
to 750 $ and the capacity optimization of the storage
tank varies from zero kg to 900 kg. Its relative size
is set to 50 %.
3,53
4,34
5,25
6,37
7,01 7,4 7,33
6,39
5,69
4,52
3,74 3,21
0
1
2
3
4
5
6
7
8
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Daily Radiation
(kWh/m2/day
Month
3,36
3,71
3,82
3,89 3,85
3,55
3,38 3,38 3,34
3,43
3,58 3,58
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Average wind speed(m/s)
Month
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5.10 Project and Grid Economic
Estimation
This project has estimated that the designed EES
lifetime is managed to be 25 years with an inflation
rate of 2% and a discount rate of 8%. A grid
extension is taken into account to ensure the
reliability of the considered system and to study the
possibility of off-grid system implementation on the
mentioned site. In fact, the grid extension capital
cost is 8000 $/km while the grid power price is 0.10
$/kWh.
6 Results
Based on the data inserted into the HOMER
software program and by referring to its selected
system’s components, including the consumption
rate of energy, the simulation was carried out to
study the suitable system to feed the considered
region with a clean environment and low-price
electrical energy for the next 25 years.
The obtained simulation results are responding
to the load demand requirement, with 2127,65 kWh
per day, and peak power of 253 kW, and a separate
hydrogen load to manage the efficiency of hydrogen
storage, giving two major options both of which are
off-grid systems with an analysis of the grid
extension.
6.1 First Option
The first alternative system architecture is depicted
in Table 2. The optimized system is constituted of a
power source PV-Generator with 3759kW and
300kW provided by the Autosize Genset generator
whereas the DC/ AC power converter supplies about
317kW of electrical energy for loads and finally
800kW is produced by the generic electrolyzer
while the hydrogen tank storage capacity reaches
900Kg.
As expressed in equations (1) and (2), the
determined LCOE revealed in Table 2 of the system
is 1.56$/kWh and the NPC cost is 15.6M$.
Moreover, Figure 3 illustrates the cost summary for
each component while Table 3 provides more
details by indicating the different charges of each
component including its capital cost, replacement
cost, O&M cost, fuel cost, salvage cost, the total
cost of the component and finally the total cost of
the whole system configuration. As a result, the
generic flat plate of the PV generator is indicated as
the most expensive component in this system
architecture while the cheapest component is the
power system converter. However, by focusing on
the electrical energy production presented in Figure
4, it is clearly shown that the mentioned PV
generator provides about 92.5% of the total energy
production while the Autosize Genset generates
only 7.53% of the total energy supplied to the load.
So, the majority of the electrical energy is generated
by PV sources (generic flat plate PV) which justifies
the high cost of PV generators compared to the
other renewable energy system components.
Table 2. System Configuration for the first option
Component
System configuration
Size
Unit
PV- Generator
3759
kW
Autosize Genset-
Generator
300
kW
Power Converter
317
kW
Electrolyzer
800
kW
hydrogen tank capacity
900
kg
LCOE
1.56
$/kW
h
Dispatch strategy
Homer Cycle
Charging
Under typical working conditions, the output
load is supplied by the PV power generator, and any
extra energy is delivered into the electrolyzer to
produce hydrogen. According to the results
presented in Table 4, the AC primary load consumes
21.8% of the energy produced while 78.2% of the
energy is consumed by the electrolyzer. Moreover,
based on the high energy consumption rate of the
electrolyzer, 59960 kg of green hydrogen is
produced per year as described in Table 5.
To evaluate the effectiveness of green hydrogen
storage and the possibility of using its tank to feed
electricity to other loads, hydrogen is taken into
account. The measurement shows that the hydrogen
load consumption reaches 60338kg/year with no
excess.
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Fig. 3: Diagram of the system components summary cost
Table 3. Detailed cost of the system architecture
Component
Capital ($)
Replacement ($)
O&M ($)
Fuel ($)
Salvage ($)
Total ($)
Autosize Genset
150000.00
625805.93
626299.39
2089868.79
1018.12
3490955.99
Generic Electrolyzer
880000.00
288506.20
103420.13
0.00
54299.78
1217626.56
Generic flat plate PV
9396378.47
0.00
485887.30
0.00
0.00
9882265.77
Hydrogen Tank
900000
0.00
0.00
0.00
0.00
900000
System Converter
95229.43
40403.35
0.00
0.00
7604.32
128028.47
Total System
11421607.90
954715.49
1215606.83
2089868.79
62922.22
15618876.79
Fig. 4: Distribution of electrical power generation
Table 4. Electrical energy consumption
Table 5. Electrolyzer production capacity
Consumption
kWh/yr
%
AC Primary Load
776592
21.8
Electrolyzer Consumption
2782458
78.2
Total
3559050
100
Production
kg/yr
%
Electrolyzer
59961
100
Reformer
0
0
Total
59961
100
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Fig. 5: Net Present Cost of the grid extension compared with the off-grid option
6.1.1 Grid Extension
Figure 5 presented below depicts the comparison of
(NPC) between off system and the grid extension
depending on the grid distance. The obtained
curves demonstrate that the cost of an off-grid
system is constant even if the grid extension
distance increases. However, the cost of grid
extension is consequently increasing with the grid
extension distance. For distances below the break-
even point (1451.56 km), the grid extension cost is
lower than the off-grid system cost. Otherwise, the
grid extension is very expensive for distances
above the break-even point.
6.2 Second Option
The second proposed option designed to produce
electrical power in the considered region, shown in
Table 6, is a system combined of 3743kw of PV
generator, seven G3 (3kW) wind turbine generator,
300kW of Autosize Genset, 323kW of power
system converter, 800 kW of generic electrolyzer
and 900kg of hydrogen storage tank.
Table 6. System Configuration
Component
System Configuration
Unit
Size
Generic flat plate PV
kW
3743
Generic 3kw
7
Autosize Genset
kW
300
Power System
converter
kW
323
Generic E electrolyzer
kW
800
Hydrogen Tank
kg
900
Dispatch
Homer CC
The financial analysis obtained in Table 7. The
LCOE of the system is about 1.57$ while the NPC
of the system reaches 15.7M$. It also specifies the
cost of each component used in the system such as
the capital cost, replacement cost, O&M cost, fuel
cost, salvage cost, the individual component’s total
cost, and finally the whole system's total cost.
Indeed, according to the diagram of the NPC of
each component shown in Figure 6, it is noticed
that the generic flat plate PV generator is the most
expensive followed by the Autosize Genset.
However, the domination of PV generators in
electricity production in the two cases (unlike the
wind generator) is due to the meteorological
conditions in the DEMNATE region where the
solar irradiation is higher than the wind speed, in
addition to the geographical situation of the region
which is generally mountain and due to the facility
of its implementation, unlike wind generators, all
these conditions favor the effectiveness and use of
PV generators. As a result of the study, according
to Figure 7 and Table 8, the electrical energy
produced by the three generators: PV, Autosize
Genset, and wind turbines are respectively
6587092kwh/year, 536280kwh/year and 9599
kwh/year which represent 92.3%, 7.52%, and
0.135% of the total energy production respectively.
Therefore, 31.8 % of the energy is generated only
by renewable energy systems and delivered to the
loads. The Ac primary load consumes about
21.8% while 78.2% is consumed by the electrolyzer
as shown in Table 9.
Consequently, according to the results obtained
in Table 10, the green hydrogen production through
the electrolyzer is 59961 kg per year. The
consumption of green hydrogen load during one
year reaches 60337 kg per year likewise the
quantity revealed in Table 11 with no hydrogen
excess, which means that it responds to load
demand with 60337kg, including the AC primary
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load served by the basic renewable energy system
proposed.
Table 7. The detailed cost of the system architecture
Fig. 6: Diagram of the system component’s summary cost for the second option
Fig. 7: Distribution of monthly electrical power generation
Table 8. Electrical energy production
Production
kWh/yr
%
Generic flat plate PV
6587092
92.3
Autosize Genset
536280
7.52
Generic 3 kW
9599
0.135
Total
7132972
100
Table 9. Electrical energy consumption
Consumption
kWh/yr
%
AC Primary Load
776592
21.8
Electrolyzer Consumption
2782487
78.2
Total
3559079
100
Table 10. Electrolyzer production
Production
kg/yr
%
Electrolyzer
59961
100
Reformer
0
0
Total
59961
100
Component
Capital ($)
Replacement
($)
O&M($)
Fuel($)
Salvage($)
Total($)
Autosize Genset
150000
625669.40
626066.70
2083072.79
(1137.90 $)
3483670.99
Generic 3 kW
126000
40169.73
16288.67
0.00
22638.22$
159820.18
Generic
Electrolyzer
880000
288506.20
103420.13
0.00
54299.78
1217626.56
Generic flat plate
PV
9356513.82
0.00
483826.01
0.00
0.00
9840339.83
Hydrogen tank
900000
0.00
0.00
0.00
0.00
900000
System converter
96770.32
41057.11
0.00
0.00
7727.36
130100
Total System
11509284.14
995402.44
1229601.51
2083072.79
85803.26
15731557.63
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Table 11. Hydrogen Consumption
Consumption
kg/yr
%
Hydrogen load
60337
100
Total
60337
100
Fig. 8: Diagram of the NPC of the grid extension compared with the off-grid for second option
(a) First option
(b) Second option
Fig. 9: Diagram of monthly green hydrogen load served and electrolyzer Output
These results prove the ability of rural areas to
play an important hub in clean and economic
energy to generate and store large quantities of
PV- hydrogen production to be used and exported
to other areas like cities.
6.2.1 The Grid Extension of the Second Option
As previously explained in the first option, Figure 8
illustrated below depicts the comparison of the
NPC between off-grid system and the grid
extension depending on the grid distance grid
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extension. It displays that the grid extension
distance is proportionally increasing while the off-
grid system cost is constant and does not depend on
the grid extension distance. For distances below the
break-even point (1426.76 km), the grid extension
cost is lower than the off-grid system. Otherwise,
the grid extension is very expensive for distances
above the break-even point.
As presented in Figure 9, the monthly variation
of the hourly amount of the hydrogen load served
and the electrolyzer output during the period
between June and July. For both cases, the
electrolyzer output exceeds 15kg/hr especially in
the duration of July. As for the provided green
hydrogen load, it is generally less or equal to the
electrolyzer output. Therefore, the hydrogen load is
fully supplied through the electrolyzer, including
the AC primary load which is powered by the Off-
grid system without involving electrolyzer
consumption and hydrogen production. It could be
considered an exportation spot for other cities when
there is no need for hydrogen load in rural areas.
On the other hand, the designed off-grid system has
proved its ability to feed the AC primary load and
to produce simultaneously 15 kg/hr for
accumulating the hydrogen in the storage tank.
7 Discussion
To evaluate the accuracy of the result, a
comparison between current results and literature
results is done. The designed systems in this paper
prove the feasibility of powering three villages with
electricity using PV modules, auto-size generators,
and wind turbines. Both systems rely on the PV
modules as the main generator of electricity and
green hydrogen. Similarly, the LCOH of the energy
production in the Dakhla region based on the PV
plants reaches 17 cents / Kwh, [29]. In [5], the
author studies the off-grid hybrid renewable energy
system implementation with hydrogen storage. The
LCOE represents 2.34 $/kWh which is higher than
the LCOE found in this study (1.57 $/kWh and
1.56$/kWh for the first and second systems).
8 Conclusion
Studying the feasibility of integrating an off-grid
system with hydrogen generation is extremely
important to guarantee fluent electrical energy in
cities and rural areas. The African continent has a
qualified potential for renewable energy sources
that could upgrade the economic and social aspects
of African countries if it is well exploited. The
Moroccan government, by announcing the road
map towards renewable energy systems integration,
have already given the start of the new energy
transition in different areas of the country. In the
same context, some efforts have been made to give
importance to green hydrogen production. This
paperwork examines the feasibility of integrating
RES with hydrogen production in rural areas. It
aims to compare between the grid extension and
off-grid system integration in the considered area
“DAMNETE” region by using the HOMER
software tool to modulate and simulate the
optimized system and based an on-site visit, the
load was determined. The simulation results prove
the possibility of implementing two off-grid
systems with hydrogen generation. The first system
is constituted of a PV generator, an electrolyzer, a
green hydrogen storage tank, system of power
converter while the second system takes into
account the integration of seven G3 wind turbines.
Both systems have effectively fed the AC primary
load while the electrolyzer consumes the rest of the
produced energy to produce the green hydrogen
with an LCOE lower than 1.6$/kWh.
The hydrogen load is fed completely with
15kg/hour, which allows exporting the excess
amount not needed in rural areas. As a result of the
study, due to the geographical conditions of the
region, a PV generator is more recommended than
a wind turbine because of its high productivity and
the high solar irradiation compared to the wind
speed. Therefore, the large space of rural areas can
be exploited to build green hydrogen production
centers and helps also reduce the economic and
demographical pressure. From a perspective, it is
recommended to implement the designed systems
in the current study in reality to validate the results.
Index of Abbreviations
RES renewable energy systems
ESS energy storage systems
PHS pumped hydro storage
CAES compressed air energy storage
TES thermal energy storage
EMES electrostatic and magnetic energy storage
ELMES electrochemical energy storage
LCOE levelized cost of energy
NPC Net Present Cost
O&M Operating and maintenance expenses
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Acknowledgment:
This work was supported by the national center for
scientific and technical research of Morocco,
through the Research Excellence Grant Program.
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APPENDIX
Table 1. Daily electrical power consumption of one household
Load of household appliances
Power
rating
(W)
N°. In use
Summer (March to
October)
Winter (November to
February)
Operating
time (h/day)
Wh/day
Operating
time (h/day)
Wh/day
Light
85
9
10
7650
11
8415
Table fan
45
1
2
90
0
0
Iron
1400
1
0,25
350
0,15
210
Computer
200
1
5
1000
5
1000
TV
200
1
6
1200
6
1200
Refrigerator
125
1
24
3000
24
3000
Water pump
1750
1
0,75
1312,5
0,75
1312,5
Mobile charger
5
4
3
60
3
60
Total power (W)
14662,5
15197,5
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
- EL HAJI Ikram: Conceptualization,
Methodology, Software, Formal analysis, Data
curation, Writing – original draft, Visualization.
- Kchikach Mustapha: Writing – original draft,
Writing – review & editing, Visualization,
Project administration.
- Abdennebi EL hasnaoui: Supervision, Project
administration.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors declare that they have no known
competing financial interests or personal
relationships that could have appeared to influence
the work reported in this paper.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.e
n_US
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