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Technical, economical and environmental
comparative analysis of a Microgrid using battery
and pumped hydro storage for remote area
electrification in southern Algeria
Bekhti mohammed abderahim
Electrical Engineering Department
University Abdelhamid Ibn Badis
Mostaganem,Algeria
bekhtimohammed20016@gmail.com
Ghomri Leila
Electrical Engineering Department
UniversityAbdelhamid Ibn Badis
Mostaganem,Algeria
leila.ghomri@univ-mosta.dz
Larbi beklaouz hadj
Electrical Engineering Department
UniversityAbdelhamid Ibn Badis
Mostaganem,Algeria
beklaouz@outlook.fr
Abstract—This study aims to analyze the techno-economic
and environmental performance of the hybrid energy system
(HES) to meet the electricity demand of an off-grid community
and the dump load in the Indalek village located in the
southern of Algeria. Different combinations of HES, such as
PV/FC/DG/battery (BESS) and PV/FC/DG/Pumped hydro
storage (PHS), are modeled, analyzed and compared using
HOMER software. The techno-economic environmental
performance analysis has evaluated the net present cost (NPC),
the cost of energy (COE), excess electricity (EE), a fraction of
renewable energy (RF) and CO2 emissions of the different
combinations of HES. The simulation results show that the
BESS hybrid energy system has the best feasibility techno-
economic performance with the least NPC, COE and the
higher EE of $438335.21, $0.1423/KWh, 36222 KW/year,
respectively. On the contrary, the HES with PHS has the
highest fraction of renewable energy of 87.4% and the most
environmentally friendly with 96.43% reduction in CO2
emissions compared to the HES with BESS. Finally, the
sensitivity analysis is performed on the hybrid energy system
with BESS shows that the improvement of the derating factor
with the increase load leads to a lower the COE.
Keywords—Microgrid, hybrid storage, remote area,
economical study, technico-economical analysis, environmental
analysis.
I. INTRODUCTION
The growth of electrical energy demand is expected to
blow up by 30% in 2030, mainly because of the world's
industrial development needs [1]. Although some countries
have made some progress in renewable energy, more than
70% of the world's electricity needs are met by fossil fuels
(oil, gas, and coal) [2]. The demand for electricity is
increasing even in remote areas to ensure people have the
best quality of life possible. The majority of these areas are
powered by diesel generators. Renewable energy sources can
mitigate the environmental and economic impacts of diesel
generators [4]. Since the beginning of 2000, there has been
an increasing interest in the use of various renewable energy
sources such as solar energy, wind energy, wave energy,
geothermal energy, and biomass energy [3]. The production
of electrical energy by renewable energies faces the problem
of intermittency, particularly in the case of solar and wind
energy use. A hybrid power generation system combines
several alternative energy sources (such as solar and wind)
with conventional energy sources (oil, gas, and coal) as well
as energy storage systems (BESS, PHS, and fuel cell (FC))
represents an interesting deal in generating continuous
electricity and meeting various levels of demand in remote
areas. There are several research studies on hybrid energy
systems (HESs) with different storage systems. Moreover,
there are several research literature focus on the techno-
economic analysis environment of HESs with different
storage systems. For example, PV solar, generator diesel
(GD), fuel cell (FC), BESS; PV solar, wind turbine (WT),
GD, PHS; PV, GD, PHS; PV, GD, BESS in [3,5,7].
However, there is a brief review of the literature related to
the HESs in remote areas in the south of Algeria. It is
obvious that the HESs based on PV, GD, fuel cell, BESS,
PHS for remote areas of Algeria where it has not been
studied yet. Thus, the main objective of this paper is as
follows: The technical, economic, and environmental
comparative analysis between the two HESs, such as PV/
GD/ FC/ BESS and PV/ GD/ FC/PHS for supplying the
electricity in the Indalek village in the south of Algeria.
This work is organized as follows: in section II, we have
described the area of the Indalek village for highlighting the
opportunity of implanting a Microgrid there. In section III,
we have resumed the existing configuration, and material
data information. In section IV, a simulation allowed us to
fix energy cost parameters for various storage configurations,
and in the last section, we performed a sensitivity analysis.
II. SITE DESCRIPTION
The model of the HES in this study was proposed for the
Indalek village. The location of this village is 22.59°N,
5.80°E, 1377 m for latitude, longitude and altitude
respectively. The study under the site has a good level of
solar radiation. It receives an annual average solar radiation
of 7.26 kWh/m2 per day [6]. The solar radiation data for the
study site is extracted from the NASA database [8]. The
maximum and minimum solar radiation levels in this village
are 7.180 KW/m2/day, and 4.10 KW/m2/day in July and
December respectively, as shown the figure 1. The average
total solar radiation per year is 5.90 kWh/m2/day. The
Indalek village is known for the activity of agriculture, and
live stockbreeding; its population is estimated at around 500
Inhabitants which are not completely connected to a grid
utility. The estimates of the load of the unconnected village
to a grid utility include the future energy demand calculated
as a daily primary demand of 640.98 kwh/day for 11 houses
and the dump load of 11.89 kWh/day. The figure 2. Shows
the daily average energy consumption for different seasons
in the Indalek village.
Fig.1. Average solar radiation and clearness index of the Indalek
village per month.
Fig.2. Daily average energy consumption patterns for different seasons
in the Indalek village.
III. HYBRID ENERGY SYSTEM MODELING AND SIZING
Figure 3. is a schematic for a hybrid model of the HES
using BESS and PHS. The HOMER provides detailed
mathematical modeling of the system components as well as
their technical, economic and environmental criteria. Table I
describes the different components of the hybrid energy
system.
Fig.3. Schematic diagram of the HES based on BESS and PHS storage.
A. photovoltaic array modeling
The power output from the PV system is estimated using
the equation (1) [2].
Where, (kW/m2) is the solar irradiation, is the
radiation under standard test conditions (STC) (1 kW/m2),
is the temperature coefficient, and are
the temperature of the PV cell and the temperature of
the PV cell in the standard test conditions ,
respectively.
B. Fuel cell
Fuel cell is used to transfer the chemical fuel (hydrogen)
into electricity. Eq. (2) provides the electric power produced
by the fuel cell [10].
Where is the pile voltage, I is the current, is
the voltage of a single cell, and is the number of cells.
The following Eq. (3) gives the PEM fuel cells ’efficiency
power.
Where is the higher heating value to hydrogen
(120–140 MJ/kg) and (kg/s) is the mass flow rate.
C. Electrolyzer for fuel cell production (H2)
The hydrogen is produced in the Electrolyzer by splitting
water, in hydrogen and oxygen. Power input is needed for
the Electrolyzer to split the water for hydrogen production.
The electrical power consumed by the Electrolyzer is
provided by Eq. (4).
where, is the power consumption of the
Electrolyzer, is the produced hydrogen mass flow rate
(kg/s), and is the gross calorific value (MJ/kg) and
is the efficiency of Electrolyzer.
D. Diesel backup generator
The diesel generator generates electricity by consuming
fuel. The fuel consumption of diesel generator is expressed
by Eq. (5).
where,is fuel consumption in (l/h), is the intercept
coefficient of the fuel curve (0.0165 l/h/kW), is the slope
of the fuel curve (0.267 l/h/kW), is the rated capacity of
generator and is diesel power generation.
E. Pump hydro storage
A pumped hydro storage system builds potential energy
for storing water in a reservoir at a certain height when there
is excess energy. The following Eq. (6) gives the energy
storage capacity of a pumped hydro storage system.
Table I. CHARACTERISTICS OF HYBRID ENERGY SYSTEM
COMPONENTS
Where, is the energy stored in joules. Divide by 3.6 x 106
to convert to KWh;is the density of water, usually
about 1000kg/;
is the volume of the reservoir in
cubic meters;is the head height in meters; is the
efficiency of the energy conversion, and must consider
losses like turbine efficiency, generator efficiency, and
hydrodynamic losses.
F. Battery
The batteries play an important role in the stability of
electrical energy in the hybrid energy system bus. The SOC
of the battery varies between two moments t to t 1 according
to whether the battery is in charge or discharge mode [11].
The following formula is used to calculate the SOC of the
battery:
Where : battery efficiency []; : load power
of the battery [Kw];: bus voltage [Volt].
G. Inverter/converter modeling
an inverter is an electric device linked between two
buses DC and AC buses. The output power of inverter is
determined using Eq. (8), where Pin is the input power to
the inverter and is the inverter’s efficiency (95%) [11].
The HOMER calculates the required capacity of the inverter
based on the energy flow from DC to AC.
H. Net present cost
The net present cost (NPC) of a system is calculated as
the present value of all the costs of installing and operation
the component over the project lifetime, minus the present
value of all the revenues that it earns over the project
lifetime. The NPC is calculated by Eq. (9) [12] where InC,
OpC, FuC, ReC, SaC, and Nc is The initial capital cost,
operating cost, fuel cost, replacement cost, salvage cost, the
number of elements, respectively. A discount factor (DF) is
a ratio used to calculate the present value of an income (a
series of equal yearly cash flows) and based the real interest
rate (%) and the number of years (n).
NPC =
I. Cost of energy
The energy cost is defined as the cost per KWh of the
useful energy produced () by the system over its lifespan
(Ny). The COE is calculated using Eq. (11), where CRF is
the capital recovery factor [13].
COE
J. Carbon emission impact
An analysis of the CEI calculates the amount of carbon
dioxide emissions released from the energy system to the
environment in a specific time. The CEI can be determined
using a formula. (13) based on the annual generated energy
[14]. where Vol (CO2) is the quantity of CO2 emission in
(tCO2/KWh) and is the energy generated using
non-renewable sources (kWh).
(13)
K. Renewable fraction
The Renewable fraction (RF) is the percentage of energy
delivered to the load () from renewable energy sources
(). The RF is expressed using the formula in Eq. (14)
[15].
Components
Type
Size (KW)
Effeciency (%)
Capital cost
($)
Replacement cost ($)
Cost of O &
M($/year)
Lifetime
Solar PV [2]
Generic flat
plate PV
120-160
-
1,176.00
1,176.00
0
25(year)
GD [2]
Generic Medium
Genset
50
-
342.00
342.00
0.050
15000 (Hours)
Fuel cell
[9]
Generic Fuel
Cell
5-20
-
3,000.00
2,500.00
0.080
40000 (Hours)
Electrolyzer
[9]
Generic
Electrolyzer
0-15
85
1,500.00
1,000.00
20.00
15(year)
Hydrogen
tank
[9]
Generic
Hydrogen tank
0-20
-
1,200.00
800.00
15.00
25
BESS [2]
HoppeckeOPz
2000
-
86
276.00
276.00
20.00
10 (year)
PHS [16]
Generic 245kWh
Pumped
Hydro
-
90
22,000.00
500.00
22,000.00
7 (year)
Converter [2]
Generic large,
free converter
95-110
90
341.00
341.00
3.00
15 (year)
IV. SYSTEM SIMULATION
In this study, we have performed the comparison
between two combinations of HESs such as
PV/FC/DG/BESS and PV/FC/DG/PHS are designed to meet
the load demand of the Indalek village. The main objective
of this study is to compare the influence of PHS and BESS
on the HES on the basis of economic indicators (COE,
NPC), technical parameters (EE, RF) and environmental
indicators (CO2 emissions). This study takes into account
the constraints listed in table II.
TABLE II. MODEL CONSTRAINTS
Constraints
Value
Descreption
Maximum annual of
capacity shortage
(%).
1
The maximum allowable value of
the capacity shortage fraction.
Load in current time
step (%).
10
The system must maintain
sufficient spare capacity to handle
a sudden 10% increase in load.
Annual peak load
(%).
10
The percentage of primary peak
load (AC) to the desired operating
reserve at each time step.
Solar power output
(%).
25
The power of the PV generator is a
percentage of the required
operating reserve at each time
step.
A. Result and discussion
The optimized results of two HESs such as System I:
PV/FC/DG/BESS and System II: PV/FC/ DG/PHS are
presented in the table III.
TABLE III. COMPARISON OF OPTIMIZATION RESULTS FOR
DIFFERENT HESS CONFIGURATIONS
Characteristics
System I :
PV/FC/DG/BESS
System II :
PV/FC/DG/PHS
COE ($/KWh)
0.1423
0.1681
NPC ($)
438335.21
517922.65
Fuel cell (KW)
5
5
PV panels (KW)
160
160
Diesel generator (kW)
50
50
Electrolyzer (KW)
5
5
Hydrogen tank (Kg)
10
10
PHS (KWh)
1017
Battery (KWh)
686
Converter (KW)
25.3
25.5
Production (KWh/yer)
324242
322750
Excess electricity
(KWh/yr)
36222 (11.2%)
29357 (9.1%)
(%)
86.8
87.4
CO2 (Kg/yr)
23297
22467
1) Energy production : Fig 4. shows the power
generated by PV, FC and GD for the system I and system II
throughout the year to meet the 652.87kWh per day demand
of the Indalek village. The energy production by PV, FC and
GD of system I is high at system II, which estimated 324242
(kWh/year) and 322750 (kWh/year) respectively. This
explains the influence of BESS on system performance
where the annual productivity of BESS is higher than PHS
because the response time of BESS is very quickly in a very
short time (power density), which makes its performance
better compare to PHS, which has a high energy density.
Fig.4. Monthly average electric production from HES two systems: (a)
PV/FC/DG/BESS, (b) PV/FC/DG/ PHS.
2) Economic analysis :The net present costs of all
components of the two HESs are shown in table IV. The net
present cost of the solar PV system, inverter, Electrolyzer
and hydrogen tank is the same for System I and System II,
while the net present cost of the diesel generator and fuel cell
of System II is lower than System I. System II has the
highest net present cost ($517922.65), while System I have
the lowest net present cost ($438335.21). The costs of energy
are $0.1423, $0.1681 for the system I and system II
respectively. The cost of energy of System II is higher than
the cost of energy of the System I because of the capital cost
and the replacement cost of PHS is higher than BESS,
therefore the net present cost and the cost of energy of
System II are higher than System I. The figure 5. Shows that
System I is better than System II in economic terms after the
comparative analysis of the NPC and COE for both systems.
TABLE IV. THE NET COSTS OF ALL COMPONENTS OF TWO
HESs
Components
System I
System II
NPC ($)
NPC ($)
PV
188160
188160
Fuel cell
2549
2487.02
GD
56438.19
59042.68
Battery
117011
/
PHS
/
194056
Electrolyzer
10514.86
10514.86
Hydrogen
13939.13
13939.13
converter
49723.02
49723.02
System
438335.21
517922.65
Fig.5. Economic comparison of the two HESs: (a) NPC ($), (b) COE
($/kWh).
3) Technical analysis : In this study, the technical
performance of the two HESs is based on two parameters:
the RF and the EE. figure 6. Clarifies the technical
performance of the two HESs. System I have the RF value
up to 86.8% and the EE of 36222kWh/year (11.2%), on the
other hand system II has the RF of 87.4% and the EE of
29357 kWh/year (9.1%). The RF of system II is higher than
the RF of the system I due to the high nominal capacity of
the PHS which allows to integrate a lot of renewable energy
compared with BESS in the system I. The EE of the system I
is higher compared to system II because the throughput of
BESS is higher than the PHS, this explains the lower COE in
the system I. It is noticed in the figure 6, both systems can
easily cope with sudden load variations and future increase in
load demand.
Fig.6. Electrical system performance for the two HESs.
4) Environmental analysis: The main environmental
risk factors are due to the conventional generator through its
greenhouse gas (GHG) emissions during the combustion of
fuel in the generator. The HES produces the lowest
percentage of GHG. The amounts of CO2, carbon monoxide
(CO), sulfur dioxide (SO2), nitrogen oxide (NOx), unburned
hydrocarbons (UHC), and particulate matter (PM) determine
the carbon footprint of each system. The figure 7. Shows the
GHG emissions emitted by the two HESs. System II has less
environmental impact than system I in terms of carbon
footprint. The CO2 amounts of system II and system I are
22467 kg/year, 23297 kg/year respectively. The reduction of
CO2 in system II due to the renewable fraction is high in this
system compared with the system I, which reduces fuel
consumption and improves the environment in the Indalek
village. Moreover, CO, UHC, SO2 and Nox from system II
are lower than system I.
Fig.7. Greenhouse gas (GHG) emissions released from of two HES.
V. SENSITIVITY ANALYSIS
The technical-economical performance of the system I is
better than system II and his environmental impact is a
higher than system II, but it is acceptable. System I is better
to supply electricity in the Indalek village. The sensitivity
analysis is necessary to investigate the performance of the
system I, because the Indalek village is exposed sandstorms
in the summer. The objective of this analysis is to know the
influence of the derating factor and the load increase on the
cost of energy in the system I. The sensitivity analysis
parameters in the table V.
TABLE V. Sensitivity analysis paramètres of the system I
sensitivity
The derating factor (%)
Electrical load (kWh/d)
75
641
88
641
75
833.247
88
833.247
The figure 8. Shows the influence of the derating factor
with the increasing load on the cost of energy in the system I.
the cost of energy is reduced from 0.141$/KWh to
0.135$/KWh respectively in the case the load is fixed at 641
kWh/d and vary the derating factor from 75% to 88%. In
addition, in the case, the load is varied from 641 KWh/d to
833.27 kWh/d and the derating factor is varied from 75% to
88% respectively, the cost of energy is reduced from
0.131$/KWh to 0.129$/KWh. The improvement of the
derating factor increases the energy production of solar
panels, consequently reducing the cost of energy.
Fig.8. Influence of improving the derating factor and the increasing
load in the cost of energy in system I.
VI. CONCLUSION
This study presents the techno-economic environmental
analysis between the two HESs, such as PV/FC/DG/BESS
and PV/FC/DG/PHS to supply the electricity demand for an
off- grid community and the dump load in Indalek village in
southern Algeria. This analysis evaluates the NPC, COE, RF,
EE and CO2 of the two HESs using HOMER software. The
sensitivity analysis is also performed to know the
performance of HES selected. The simulation results show
that the NPC, COE and RF for PV/FC/DG/BESS
(NPC=$438371, COE= $0.1423$/KWh and RF=86.8%) are
lower than those of PV/FC/DG/PHS (NPC=$517922.65,
COE= $0.1681/KWh and RF=87.4%). The
PV/FC/DG/BESS has the highest EE (36222kWh/year) and
the PV/FC/DG/PHS has the lowest EE (29357 kWh/year).
The PV/FC/DG/PHS is the more environmentally friendly
with CO2 emissions of 22467 Kg/year compared with the
PV/FC/DG/BESS with CO2 emissions of 23297 Kg/year.
The sensitivity analysis is performed on the
PV/FC/DG/BESS shows a lower the COE when increase the
electrical load and the improvement of the derating factor.
In the continuation of this work, we will explore other
storage means such as fuel cells, flywheels for reducing cost
investments, and to gain a total autonomy of the Microgrid,
and obviously we will develop a management method for
optimizing the use of the cost storage.
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