Cogent Engineering
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Techno-economic assessment of solar PV/fuel cell
hybrid power system for telecom base stations in
Ghana
Flavio Odoi-Yorke & Atchou Woenagnon |
To cite this article: Flavio Odoi-Yorke & Atchou Woenagnon | (2021) Techno-economic
assessment of solar PV/fuel cell hybrid power system for telecom base stations in Ghana, Cogent
Engineering, 8:1, 1911285, DOI: 10.1080/23311916.2021.1911285
To link to this article: https://doi.org/10.1080/23311916.2021.1911285
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Odoi-Yorke & Woenagnon, Cogent Engineering (2021), 8: 1911285
https://doi.org/10.1080/23311916.2021.1911285
ELECTRICAL & ELECTRONIC ENGINEERING | RESEARCH ARTICLE
Techno-economic assessment of solar PV/fuel
cell hybrid power system for telecom base
stations in Ghana
Received: 15 December 2020
Accepted: 15 March 2021
*Corresponding author: Flavio OdoiYorke, Department of Renewable
Energy Technology, Cape Coast
Technical University, Cape Coast,
Ghana; Center for Renewable Energy,
Cape Coast Technical University, Cape
Coast, Ghanamail
Email: fodoi-yorke@cctu.edu.gh
Reviewing editor:
Akhtar Kalam, Victoria University,
Melbourne, AUSTRALIA
Additional information is available at
the end of the article
Flavio Odoi-Yorke1,2* and Atchou Woenagnon3
Abstract: As the world drives towards a resilient zero-carbon future, it is prudent for
countries to harness their locally available renewable energy resources. This study has
investigated the possibility of deploying a solar PV/Fuel cell hybrid system to power
a remote telecom base station in Ghana. The study aims to lower the levelized cost of
electricity (LCOE) and reduce greenhouse gas emissions produced from the hybrid power
system. Hybrid Optimization Model for Electric Renewable (HOMER) software was used to
conduct the viability analysis. The results show that the LCOE produced by the PV/fuel cell
hybrid system is about 0.222 USD/kWh. This LCOE outshines the current average grid
tariff (0.25 USD/kWh) paid by grid-connected telecom base stations. Moreover, the LCOE
is 67% cheaper than the diesel power system at the site. Likewise, the LCOE is 30%
cheaper compared to a PV/battery/diesel hybrid system. Furthermore, a switch to a PV/
Fuel system saves nearly 43 tCO2/yr and 67 tCO2/yr than PV/battery/diesel and diesel
power systems, respectively. Sensitivity analysis shows that the system LCOE is resilient
to variations in the discount rate and capital subsidies. Based on these findings, off-grid
telecom sites with insufficient wind and biomass resources could opt for a PV/fuel cell
system since it has been shown to be more cost-effective than diesel generating power
systems under locally available market data. The study findings are vital to stakeholders,
decision-makers, policymakers, and investors in Ghana and worldwide to promote low
carbon technologies.
ABOUT THE AUTHOR
PUBLIC INTEREST STATEMENT
Flavio Odoi-Yorke is a Faculty Member at the
Department of Renewable Energy Technology,
Cape Coast Technical University. He has received
his B.Sc. in Physics from Kwame Nkrumah
University of Science and Technology and was
awarded his M.Sc. in Energy Engineering from
Pan African University Institute of Water and
Energy Sciences (Including Climate Change). His
research interests include Renewable Energy
Systems, Energy Modelling, Rural Electrification,
Energy Access & Planning, and Climate Change.
Atchou Woenagnon holds an MSc. in Renewable
Energy Engineering from Regional Maritime
University. Woenagnon is a Professional
Engineer with research interests in Renewable
Energy, Power Systems, and High Voltage
Controls.
Ghana has a plan to increase renewable energy
installed capacity in the national generation mix
to 1,363.63 MW by 2030. Therefore, exploring the
possibility of harnessing all locally available
renewable energy sources could help achieve this
target. Presently in Ghana, base stations located
in remote communities, islands, and hilly sites
isolated from the utility grid mainly depend on
diesel generators for their source of power. This
study presents an analysis on deploying a PV/fuel
hybrid system as a possible substitute for existing
diesel power systems and even grid-connected
base stations. The study has investigated the
resilience of the hybrid system based on selected
critical economic indicators. The study findings
are pertinent to stakeholders, policymakers and
investors towards utilizing low carbon technologies to achieve universal access to energy in
Ghana.
© 2021 The Author(s). This open access article is distributed under a Creative Commons
Attribution (CC-BY) 4.0 license.
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Subjects: Power & Energy; Renewable Energy; Energy & Fuels; Energy; Planning
Keywords: Solar photovoltaics; fuel cell; hybrid power system; telecom base station;
decarbonization; Sustainable Energy
1. Introduction
Electricity is an essential driver for economic growth and development. Thus, a nation’s development depends on the availability of electricity for consumption. The telecom sector relies on
electricity to provide reliable services to potential customers.
The mobile telecom industry is among the strong penetrating businesses with outstanding
improvement in Africa. (Hatsu et al., 2016). Ghana’s mobile telecom market is among the fastestgrowing sectors due to its consistent and stable growth in recent years (Hatsu et al., 2016).
Information, Communication Technology (ICT) contributed about 2.4% to Ghana’s Gross
Domestic Product (GDP) for the year 2018 (Ghana Statistical Service, 2019).
Presently, there is swift attention to enhancing the energy efficiency of communication networks. According to Lambert et al. (2013), global telecommunication networks’ power consumption rate is rising at a rate of 10% annually. ICT network operators account for about 600 TWh of
global electricity consumed. This figure is projected to surge to about 1,700 TWh by 2030 (Humar
et al., 2011). The telecom sector is responsible for its energy usage and greenhouse gases (GHG)
emitted into the environment (Aris & Shabani, 2015). However, the global GHG produced from ICT
matches those of the aviation industry (Postnote, 2008). ICT usage accounted for 0.53% of global
CO2 emissions in 2015 and is expected to contribute about 3% to the global emissions for 2020
(Malmodin & Lundén, 2018; Postnote, 2008).
The mobile network operators (MNO) operating in Ghana are Scancom (MTN), AirtelTigo,
Vodafone Ghana, and Globacom Ghana. The mobile voice subscriptions in Ghana surged from
17,436,949 subscriptions in 2010 to 41,113,131 at the end of June 2019 (NCA, 2020). However, this
rapid surge is faced by expensive electricity for base stations found mostly in remote locations
(Quansah et al., 2017). Furthermore, the rise in mobile voice subscriptions needs communication
infrastructures such as cellular base transceiver stations (BTS) and towers to provide reliable
network coverage in Ghana’s peri-urban and remote areas (NCA, 2010).
The swift increase in electricity demand, depletion of conventional fuels, depleting crude oil
reserves, and environmental pollution has resulted in a keen worldwide interest in renewable
energy (RE) resources for the power production and transportation sectors. Renewable energy is
a perfect remedy for lowering and mitigating global GHG emissions (IRENA, 2015). Renewable
energy is an environmentally friendly source of energy. It can provide reliable, affordable, and
clean electricity for telecom base stations in remote areas lacking access to electricity (TH Energy,
2019). Renewable energy has attracted attention in most industrialized and emerging countries.
Different policies and agreements have been signed to curb conventional fuels and promote
renewable energy resources. The United Nation Framework Convention on Climate Change
(UNFCCC) imposes on countries to protect the climate from hazardous human interference
(UNFCCC, 1992). Also, the Kyoto Protocol enforces nations to reduce and limit GHG emissions by
specific targets (UNFCCC, 2020). These policies and agreements give countries the urge to tackle
the effect of climate change (UNFCCC, 2015). Ghana has drafted policies that promote and attract
the deployment of renewable energy resources for potential investors. These policies make the
country unique, with significant renewable energy regulatory and fiscal policies in Africa (Sakah
et al., 2017). The Government of Ghana Renewable Energy Act 832 encourages developing and
utilizing renewables for power and heat generation to diversify the national energy supply mix
(Government of Ghana, 2011).
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The intermittent nature of some renewable energy resources has impelled the development and
deployment of hybrid power systems (HPS). Generally, HPS consists of not less than two power sources
(e.g., solar/diesel, solar/fuel cell, solar/biomass/hydro, etc.), which work in a standalone or gridconnected form to attain a feasible and consistent power supply system (Aris & Shabani, 2015). HPS
can address power system efficiency, reliability, fuel flexibility, and economics (Bajpai & Dash, 2012).
In Ghana, telecom base stations located in remote communities, islands, and hilly sites with no
access to grid electricity mainly depend on diesel genset for their source of power. The combustion
of diesel emits GHG, pollutes the environment, and negatively affects the climate. Investing in
diesel genset is thrice expensive compared to grid electricity purchase (AfDB, 2016).
Presently, studies on hybrid power systems that incorporate fuel cell technologies exist in literature.
For instance, Heydari & Askarzadeh (2016) designed a PV/biogas/fuel cell hybrid system for Iran’s
rural electrification. The study used the Loss Power Supply Probability (LPSP) technique to determine
the system’s reliability. It was observed that minimizing fuel cell initial cost makes fuel cell technology
promising for standalone systems. Ghenai et al. (2018) optimized a PV/fuel cell system to electrify
a house located in a desert area. The study aimed to yield a minimum electricity cost by minimizing
GHG emissions. The hybrid system generates a low LCOE of 145 USD/MWh and produces zero CO2
emissions. Singh et al. (2017) examined the financial viability of utilizing a hybrid system to meet the
electrical load demand of an academic research building in Bhopal. The authors used a fuzzy logic
program to estimate component capital and replacement costs and HOMER to size the hybrid system
configuration. The study findings show electricity generation from the hybrid system is about
24,570.72 kWh, which has an LCOE of 0.203 USD/kWh. Özgirgin et al. (2015) designed a solar PV/
fuel cell grid-connected cogeneration hybrid system for a residential home. It was seen that integrating a hybrid power system into existing grid power offers a feasible prospect for powering
standalone houses without polluting the environment. Dursun & Aykut (2019) used HOMER to analyze
a PV/fuel cell/wind turbine hybrid system to power a nursing home in Istanbul. It was estimated the
optimal hybrid system sizing produces a competitive LCOE of 1.306 USD/kWh and an NPC of 607,298
USD. Also, an increase in solar radiation and wind speed strongly affected LCOE. Mohammed et al.
(2014) employed the LPSP concept and HOMER to design a solar PV/fuel cell power system to provide
reliable electricity for Brest. The authors investigated that hybrid systems save about 1,390 kg of CO2
per annum. Furthermore, several works on hybrid power systems have been done to investigate and
address electricity and environmental challenges associated with cellular base stations. Some of
these notable works are summarized in Table 1. Table 2 presents a review of studies on hybrid
systems existing in literature for Ghana. It can be observed that only a few studies on hybrid power
systems have been carried out for telecom base stations application in Ghana. The already existing
studies for Ghana focused mainly on PV, battery, and diesel genset technologies. However, there are
no feasibility studies in the open literature for Ghana that focus on employing solar PV/fuel cell hybrid
systems to power telecom base stations.
This study investigates the viability of deploying solar PV/fuel cell hybrid system to power
telecom base stations in Ghana. Furthermore, the study tests the proposed power system resilience by comparing its technical, economic, and environmental performance to PV/diesel and
diesel power systems. It is believed that the study findings will be valuable for stakeholders,
policymakers, and investors as Ghana drives towards increasing its renewable energy capacity to
1363.63 MW by 2030 (Energy Commission, 2019).
2. Materials and method
2.1. Study area description and location
Buduburam ATC (American Tower Corporation) base station is the study area for this research.
Buduburam is situated in the Gomoa East District in the Central Region of Ghana. The base station
lies at latitude 5°52 N, longitude 0°47 W. The Gomoa East district depends on grid electricity
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Table 1. Related studies on hybrid systems for powering telecom base stations
Author(s)
Sizing Method/
Technique
Hybrid System
Configuration
Location
LCOE
(USD/kWh)
Paudel et al. (2011)
HOMER/MATLAB
Wind/battery/PV
Nepal
0.880
Goel & Ali(2013)
HOMER
PV/wind/diesel/
battery
PV/diesel/battery
PV/wind/battery
India
0.839
0.851
0.963
Kusakana &
Vermaak (2013)
HOMER
PV/battery/wind
South Africa
0.372
Olatomiwa et al.
(2014)
HOMER
PV/diesel/battery
PV/wind/diesel/
battery
PV/battery
Nigeria
0.420
0.448
0.664
Amutha & Rajini
(2015)
HOMER
PV/diesel/fuel cell/
wind/battery
India
0.990
Alsharif et al. (2015)
HOMER
PV/diesel
Malaysia
0.250
Olatomiwa et al.,
2015)
HOMER
PV/wind/diesel/
battery
PV/battery/diesel
Nigeria
0.445
0.409
Quansah et al.
(2017)
HOMER
PV/battery/diesel
Ghana
0.530
Aderemi et al.
(2018)
HOMER/MATLAB
PV/battery/diesel
South Africa
0.218
Babatunde et al.
(2019)
HOMER
PV/diesel/battery
Nigeria
0.750
(75.1%), kerosene lamps (16.4%), and flashlight/torch (5.7%) for lighting (Ghana Statistical Service,
2014). Buduburam ATC base station is isolated from the utility grid. Hence, it relies on diesel genset
for its source of power. Gomoa East district experiences two main rainfall patterns. The first major
pattern occurs between April and July and the minor one between September and November.
Furthermore, it experiences a dry season from December to March (Ghana Statistical Service,
2014). Figure 1 shows the location of Buduburam ATC base station in the context of Ghana.
2.2. Base station electrical load assessment
Primary data for base station electrical loads was collected by auditing electrical equipment/
gadgets/appliances used at the base station. The base station electrical equipment/appliances in
use at the site are summarized in Table 3.
The daily electrical load is computed as follows:
ELoad ¼ ðPrating Þ � ðQty Þ � ðtuse Þ
(1)
where ELoad is the estimated electrical load in kWh/d. Prating represents power rating (W) for the
electrical appliances, Qty represents the total quantity of appliances/equipment, and t represents
usage hours of the electrical appliance/equipment in hr/d.
2.3. Resource assessment
The locally available renewable energy resources available at the study sites are solar, wind, and
biomass. However, the site’s annual average wind speed is about 3.0 m/s, low for substantial wind
power generation. Also, the primary biomass resources available are mainly cassava and plantain
residues. However, crop residues for biogas production require attention. Furthermore, the collection of biomass feedstock for anaerobic digestion would be a challenge to sustain the system.
Thus, hybridizing solar PV and fuel cells is ideal since the other resources are insufficient for reliable
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Table 2. Review of existing studies on hybrid systems for Ghana
Author(s)
Hybrid System
Description
Key
objective
Method/
Technique
Application
Key
Findings
Addo et al. (2014)
PV/wind/battery/
diesel
Design
a hybrid
system for
electrical
power loads
Iterative
algorithm
Supply
electricity for
a group of
villages found
in Bonsaaso
The optimal
configuration
provides
maximum
system
reliability and
minimum
load rejection
over 20 years
of the project.
Adaramola et al.
(2014)
PV/wind/diesel
Perform an
economic
analysis of
PV/wind/
diesel hybrid
system
HOMER
Rural
Electrification
in Southern
Ghana
The hybrid
system has
a very low
LCOE of 0.281
USD/kWh. The
HRES is
resilient to
changes in
wind speed,
global solar
radiation, and
diesel prices.
Adaramola et al.
(2017)
PV/biodiesel
Investigate
the economic
feasibility of
PV/biodiesel
hybrid system
HOMER
Provide WA
East District
with
electricity and
water
demands
The hybrid
system has
a high LCOE
of 0.76 USD/
kWh with
a 0% subsidy.
The LCOE
declines to
0.20 USD/
kWh with
a 100%
subsidy.
However,
customers
would pay up
to 200%
more under
100% subsidy
to maintain
the system.
Quansah et al.(2017)
PV/diesel
Investigate
the technoeconomic
viability of
PV/diesel
hybrid power
HOMER
Power
a remote
base
transceiver
station
PV/diesel
genset hybrid
systems
reduce LCOE
by 48%
compared to
diesel genset
systems. PV/
diesel saves
about 90% of
GHG
emissions.
(Continued)
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Table 2. (Continued)
Author(s)
Hybrid System
Description
Key
objective
Method/
Technique
Application
Key
Findings
Tchao et al. (2017)
Diesel/battery
Assess the
usage of dual
prime
gensets and
hybrid power
systems
Field trial
measurements
Power an offgrid base
transceiver
station
The
maximum
restriction of
genset sizes
can not deter
hybrid
systems from
expanding to
5 rectifier
modules. The
hybrid
system’s
deployment
reduced the
diesel gensets
runtime by
16.55 hours,
saving about
61.70% of
CO2 emission.
Ansong et al.(2017)
PV/diesel/battery/
fuel cell
Conduct
technoeconomic
viability study
of utilizing
hybrid
systems
HOMER
Provide
electricity for
an off-grid
mine located
at Amansie
West
The hybrid
system LCOE
is costeffective and
more than
28% cheaper
than the
agreed tariff
allocated for
mining
companies
operating in
Ghana.
Opoku et al. (2018)
PV/grid
Estimate the
fraction of
solar energy
needed to
meet
daytime airconditioner
energy
demand
Mathematical
Modelling,
Experimental
setup
Power public
and
commercial
offices airconditioners
Using 100%
solar energy
to power the
airconditioners
saves about
3,300 USD
compared to
using 100%
electricity
from the
utility grid.
Agyekum & Nutakor
(2020)
PV/wind/battery/
diesel
Reduce the
monopoly
use of fossil
fuels through
the
penetration
of hybrid
power
systems
HOMER
Power
a community
located in
Mankwadze
The hybrid
LCOE is
relatively
expensive
compared to
utility grid
electricity
sold to
household
consumers in
Ghana. The
power system
is resilient to
variations in
fuel cost,
inflation, and
discount
rates.
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Figure 1. Map showing the
location of the study area.
Table 3. List of electrical appliances/equipment for base station load assessment
Power
Ratings
W
Qty
BTS 900 MHZ
2000
1
BTS 1800 MHZ
2000
1
BTS 2600 MHZ
2500
Air Conditioner
1860
Appliance
Inside Lights
Outside Lights
Time of Use
Usage Hours
h/d
Total
kWh/d
00:00–23:00
24
48.00
00:00–23:00
24
48.00
1
00:00–23:00
24
60.21
1
00:00–23:00
24
44.64
9
2
18:00–06:00
12
0.22
50
2
18:00–06:00
12
1.20
Total Energy Consumption 202.27
power generation. However, fuel cells are expensive and still attracting attention on the African
continent, but they have already been tested and deployed in African countries like Kenya and
South Africa (Crouch, 2011). This implies that it is prudent to access its technical and economic
performance in Ghana’s context for future deployment.
Ground data for solar resources was unavailable during this study. Hence, recent solar resource
data was retrieved from the PVGIS-5 geo-temporal irradiation database for Buduburam located at
latitude 5°52 N, longitude 0°47 W. The database provides solar resource data from 2005–2016. The
annual average daily solar irradiation and clearness index available at Buduburam is about
5.56 kWh/m2/day and 0.56. The clearness index determines the clearness of the atmosphere.
The months of June, July, August, and September have a low daily average low solar irradiation
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Daily radiation (kWh/m2/day)
Clearness Index
7
0.7
6
0.6
5
0.5
4
0.4
3
0.3
2
0.2
1
0.1
0
0
Clearness index
Daily Radiation
Figure 2. Clearness index and
solar global horizontal irradiation for Buduburam.
Month
and clearness index, as shown in Figure 2. These low solar irradiation and clearness index values
are due to frequent rain and cloudy atmosphere at Buduburam during that season.
2.4. Hybrid system sizing with HOMER software
In this study, Hybrid Optimization Model for Electric Renewable (HOMER) software is utilized to
model and size the hybrid power system. HOMER was selected because it is one of the most widely
used software to design and analyze hybrid renewable energy systems (Okedu & Uhunmwangho,
2014). HOMER’s powerful optimizing function quickly estimates several hybrid system scenarios.
Furthermore, its optimization and sensitivity analysis algorithms determine several possible system configurations (Okedu & Uhunmwangho, 2014). HOMER is utilized to accomplish three tasks:
simulation, optimization, and sensitivity analysis, as shown in Figure 3. During the simulation,
HOMER models the system by running each system for one year every hour to determine the
power systems that meet the electrical loads and constraints assigned to it. In optimization,
HOMER decides the most cost-effective way to meet the electric load under technical, economic,
and system conditions. Sensitivity analysis helps to investigate the impact of variation in input
parameters on system performance (HOMER Energy, 2016). Figure 3 below displays comprehensive
steps utilized in HOMER software for this study.
2.4.1. Proposed hybrid power system operating strategy
The proposed hybrid power system consists of PV panels, electrolyzer, hydrogen tank, fuel cell,
battery, converter, AC bus, DC bus, and AC and DC loads, as shown in Figure Figure 4. The
electrolyzer uses electricity generated from PV panels to split water into hydrogen and oxygen.
After that, hydrogen tank stores produced hydrogen fuel. The stored hydrogen fuel is injected into
the fuel cell to produce electricity. The PV and fuel cell systems operate concurrently to power the
base station loads. The base station operates 24 h/d; hence, there should be a continuous
electricity supply to meet electrical loads. The PV panels generate electricity to meet electrical
loads but cannot work at night due to sunlight’s unavailability. Also, the PV panels charge the
battery with excess electricity produced. During the night, electricity generated from the fuel cell
meets the electrical loads. The battery bank, which acts as a backup power source, is required to
compensate the fuel cell to meet electrical loads when there is insufficient solar radiation caused
by rains and a cloudy atmosphere in the day.
2.4.2. Hybrid power component specifications and cost details
2.4.2.1. Solar photovoltaic array. HOMER computes the PV array output using equation 2:
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Figure 3. Steps utilized in
HOMER software.
PVoutput ¼ RPV UPV
�
RT
RT;STC
�h
1 þ βp Tc
Tc;STC
�i
(2)
Where Rpv represents PV rated capacity (kW) under standard test conditions (STC), Upv represents
PV derating factor (%), RT is the incident solar irradiation on PV panel (kW/m2), RT ,STC is the incident
solar irradiation at STC (1 kW/m2), βp represents temperature coefficient (%/oC), Tc represents PV
cell temperature (oC), and Tc, STC is the PV cell temperature under STC (25 oC). In this study, PV
panels would be mounted at a fixed angle equal to the study site’s latitude value. The azimuth,
which defines the sloping direction, is 0° west of south. Also, the derating factor responsible for
losses, shading, etc., is taken to be 80%. Furthermore, ground reflectance, which accounts for the
percentage of solar radiation reflected, is taken to be 20%. A typical PV panel lifespan of 25 years is
considered. The PV capital and replacement costs comprise the cost of panels, accessories, wiring,
and labour. Globally, the cost of PV panels has declined drastically over the years due to advancements in solar cell efficiency and the rate at which new projects are being commissioned at a low
absolute cost level (IRENA, 2019). At present, local and multinational companies exist in the
Ghanaian market responsible for supplying PV systems. For this study, the cost of PV panels and
accessories (cables, mounting structure) was obtained by soliciting price quotations from 5 different suppliers and installers in the Ghanaian Market. These suppliers and installers have been
granted a permit from the Energy Commission of Ghana to supply and install PV systems. Per
the data obtained in Figure 5, the average cost of PV panels with accessories was estimated at 745
USD/kW. A 10% margin for installation was added, increasing PV capital cost to 820 USD/kW.
Furthermore, the PV replacement cost is 0 USD/kW because the PV lifetime equals the project
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Figure 4. The layout of the proposed hybrid power system.
Figure 5. Cost of PV panels with
accessories (cables, mounting
structure).
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lifetime. The operation and maintenance cost is 8 USD/kW/year, mainly for cleaning/washing the
PV panels.
2.4.2.2. Diesel genset. The diesel genset consumes diesel to produce electricity. The fuel slope
defines the volume of diesel consumed by the genset to generate electricity. HOMER computes the
fuel consumption rate as follows:
Vc ¼ iAgen þ jBgen
(3)
Where Vc is the volume of diesel consumed by the genset per hour (L), i is the fuel curve intercept
coefficient (L/h/kWrated), Agen is the genset capacity (kW), j represents fuel curve slope (L/h/kW), and
Bgen represents genset power output in kW. The supply and installation cost for diesel genset was
collected from notable local suppliers such as Cummins Ghana, Mantrac Ghana, and C. Woermann
Ghana. Based on information received, the diesel genset capital cost is about 250 USD/kW. The
replacement and O&M costs are about 200 USD/kW and 0.03 USD/h/kW. The price of diesel fuel in
the Ghanaian market was about 0.937 USD/L (GlobalPetrolPrices, 2020) during this study. However,
a 10% margin to cater for transportation and delivery costs increased the price to 1.03 USD/L.
2.4.2.3. Battery and power converter. The battery bank stores DC energy produced from PV panels
and fuel cell systems. This energy meets the base station electrical loads when there are power
shortages from the generating power systems. The battery bank autonomy and battery lifetime
are very critical parameters when sizing the battery bank capacity. HOMER computes the battery
bank autonomy as follows:
Zbatt ¼
�
pmin �
24 hd
Abatt Bnom Cnom 1 100
PLave ðkWh=dÞ
(4)
Zbatt is the battery bank autonomy in years. Abatt represents battery quantity, Bnom represents
battery nominal voltage in V, Cnom is the nominal battery capacity in Ah, Pmin is the battery bank’s
minimum state of charge in %, and PLave is the average primary load in kWh/d. HOMER uses
equation 4 to compute the battery bank lifetime:
�
�
Z Q
Xbatt ¼ min b ls ; Rb;f
(5)
Qth
Xbatt represents the battery bank’s lifetime in years. Zb represents the total quantity of batteries. Qls
represents single battery lifespan throughput, Qth represents yearly battery throughput, and Rbf
represents battery float life. The cost of a battery in the local market is about 200 USD/kWh (AIMS
Power, 2020a; SUKA, 2020a). Hence, a 10% margin for installation was added, increasing the
capital cost to 220 USD/kWh. Also, the battery replacement cost is taken as 200 USD/kWh (AIMS
Power, 2020a; SUKA, 2020a). Proper operating and maintenance (O&M) cost of 5 USD/kWh/year is
considered. The battery has a design lifespan of 10 years with proper maintenance.
The converter converts DC output from PV and fuel cell to AC output to meet the base station AC loads.
The converter has an efficiency of 95% and a lifespan of 15 years. A converter’s cost in the local market is
about 315 USD/kW (AIMS Power, 2020b; SUKA, 2020b). A 10% margin for installation increased the
capital cost to 347 USD/kW. The replacement and O&M costs are 315 USD/kW and 7 USD/kW/yr.
2.4.2.4. Fuel cell unit. Fuel cells are energy conversion devices that operate electrochemically to
produce DC electrical current. The Fuel cell absorbs hydrogen and oxygen in the air to generate
electricity, water, and heat (Crouch, 2011). HOMER models a fuel cell as a generator that generates
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DC electricity using hydrogen and oxygen (HOMER Energy, 2016). The fuel slope defines the fuel
(hydrogen) volume consumed by the fuel cell to generate electricity. The fuel consumption rate is
calculated using equation 5: (HOMER Energy, 2016)
Fc ¼ kYgen þ sPgen
(6)
Where Fc represents the amount of fuel consumed by the fuel cell in an hour (L), k represents fuel
curve intercept coefficient (L/h/kWrated), Ygen represents the fuel cell rated capacity in kW,
s represents fuel curve slope (L/h/kW). Pgen represents the power output in kW. The electrolyzer
breakdowns water into hydrogen and oxygen. Subsequently, a storage tank is used to store
hydrogen. Currently, there are no local suppliers for (electrolyzer, hydrogen tank, fuel cell) in the
Ghanaian market since the technology is now attracting attention in the African market. In this
study, the fuel cell, electrolyzer, and hydrogen tank cost details were retrieved from
a comprehensive review of notable works on fuel cell systems worldwide, as shown in Table 4.
Table 5 presents a summary of input technical parameters for HOMER simulation. Table 6 summarizes the component cost, as discussed above.
2.4.3. Economic and project input parameters
Economic indicators such as the inflation rate and discount rate play a central role in renewable
energy projects’ feasibility. HOMER uses the inflation rate and the discount rate to estimate the
project annualized cost, NPC, capital recovery fraction, etc. The discount rate at the Central Bank of
Ghana stood at 12% at the time of this study (Bank of Ghana, 2020a). Also, the inflation rate of 10%
was used (Bank of Ghana, 2020b). A typical project lifetime of 25 years is considered. A project fixed
capital cost of 10,000 USD is assumed for acquiring land and control panel (regulate the flow of
Table 4. Review of cost for fuel cell, electrolyzer, and hydrogen tank for HOMER simulation
Electrolyzer
Capital Cost
UDS/kW
Replacement Cost
USD/kW
O&M Cost
USD/yr
Source
1000
667
5
(Kebede & Bekele, 2018)
1500
1200
20
(Dursun & Aykut, 2019)
1000
1000
10
(Mohammed et al., 2014)
3500
3500
35
(Cotrell & Pratt, 2003)
770
770
15
(IRENA, 2019)
Capital Cost
USD/kW
Replacement Cost
USD/kW
O&M Cost
USD/hr/kw
3000
2000
0.02
(Kebede & Bekele, 2018)
3000
2500
0.02
(Dursun & Aykut, 2019)
4500
4500
0.10
(Cotrell & Pratt, 2003)
450
400
0.15
(Isa et al., 2016)
1200
1200
0.05
(Ansong et al., 2017)
Capital Cost
USD/kg
Replacement Cost
USD/kg
O&M Cost
USD/yr
1300
867
13
(Kebede & Bekele, 2018)
1100
950
20
(Dursun & Aykut, 2019)
1320
165
15
(Cotrell & Pratt, 2003)
1300
1200
15
(Isa et al., 2016)
Fuel Cell
Hydrogen Tank
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Table 5. Summary of technical input parameters for sizing optimal hybrid system
Parameter
Value
Electrical Load
Daily DC load
156.21 kWh/d
DC load factor
0.79
DC peak load
8.20 kW
Daily AC load
46.06 kWh/d
AC peak load
2.50 kW
AC load factor
0.77
Solar PV
Sizes selected for simulation
10–100 kW
Lifetime
25 years
Derating factor
80%
PV module efficiency
18.33%
Nominal operating cell temperature
45°C
−0.390 %/oC
Temperature coefficient
Panel Slope
Azimuth
Ground reflectance
5.52º
º
0 west of south
20%
Electrolyzer
Sizes selected for simulation
2–50 kW
Efficiency
85%
Lifetime
20 years
Hydrogen Tank
Sizes selected for simulation
Relative to tank size
Lifetime
2–50 kW
10 %
25 years
Fuel Cell
Sizes selected for simulation
Lifetime
2–30 kW
50,000 hrs
Minimum load ratio
25%
Fuel curve intercept
0.01 kg/hr/kWrated
Fuel curve slope
0.025 kg/hr/kWoutput
Lower heating value
120 MJ/kg
Density of hydrogen
0.09 kg/m3
Battery
Battery initial state of charge (SOC)
100%
Minimum SOC
40%
Roundtrip efficiency
80%
Lifespan
10 years
Converter
Converter efficiency
Lifespan
95%
15 years
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Table 6. Summary of components cost for simulation
Component
Capital Cost
Replacement Cost
O&M Cost
PV Panels
820 USD/kW
0 USD/kW
8 USD/kW/yr
Fuel Cell
2800 USD/kW
2500 USD/kW
0.04 USD/h/kW
Electrolyzer
1000 USD/kW
1000 USD/kW
12 UDS/kW/yr
Hydrogen Tank
1050 USD/kg
1000 USD/kg
18 USD/kg/yr
Battery
220 USD/kWh
200 USD/kWh
5 USD/kWh/yr
Diesel genset
250 USD/kW
200 USD/kW
0.03 USD/hr
Converter
347 USD/kW
315 USD/kW
7 USD/kW/yr
energy from PV and fuel cell). An additional project fixed O&M cost of 100 USD/yr is estimated for
maintaining the control panel.
2.4.4. Key economic metrics
In this study, total Net Present Cost (NPC) and levelized cost of electricity (LCOE) are key economic
metrics essential for decision making. The total net present cost refers to the sum of components
costs (capital, replacement, and operating and maintenance) minus revenues over the project lifespan (HOMER Energy, 2016). HOMER calculates the NPC for a project as follows:
TNPC ¼
Ca;t
CRFði; Plifetime Þ
(7)
where Ca,t represents the total annualized cost, i represents real interest rate per annum (measured from
discount rate), Plifetime represents project lifetime, and CRF(i,N) represents capital recovery factor.
The CRF(i,N) is computed as follows:
CRFði; NÞ ¼
ið 1 þ i Þ N
ð 1 þ iÞ N
1
(8)
where i represents the annual real interest rate, and N represents project lifetime.
The levelized cost of electricity (LCOE) is the cost of electricity ($/kWh) produced by the system
(HOMER Energy, 2016). HOMER calculates the LCOE using equation 8:
LOCE ¼
Total annualized cost ð$Þ
Electrical load served ðkWhÞ
(9)
2.4.5. System constraints
System constraints are conditions set for the hybrid power system to meet. HOMER rejects feasible
power systems that refuse to meet the stated requirements, thus, omitted in the HOMER optimization results. In this study, the key selected system constraints are operating reserve, minimum
renewable fraction, and minimum annual capacity shortage. Operation reserve is the excess
operating capacity that meets the unexpected surge in electricity demand or decline in PV
power output. For this study, 10% of the hourly electricity demand and 25% of PV power output
are specified for operating reserve to guarantee consistent electricity supply for the base station.
The minimum renewable fraction is 100%. Also, the annual capacity shortage, which accounts for
the total electricity shortage expected to occur during the year, is taken as 0–0.5%.
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3. Results and discussion
3.1. Electrical load and load profile for Buduburam ATC base station
Figure 6 displays the Buduburam ATC base station hourly load profile. The total electrical load
demand for Buduburam ATC base station DC and AC loads are estimated at 156 kWh/d and 46.056
kWh/d. Therefore, the base station’s total electricity demand is about 202.056 kWh/d. It can be
observed that DC and AC loads have a peak load of 6.5 kW and 1.98 kW. Also, DC loads have
a constant load profile throughout the day. The DC loads are mainly consumed by the base
transceiver stations (BTS) at the site, which operate 24 hr/d throughout the year unless they
develop a fault and become non-functional. Moreover, for AC loads, there is a slight variation in
the hourly load profile. The AC loads have a constant load of 1.98 kW from 18:00 to 5:00, mainly
dominated by air-conditioner and lighting systems. Correspondingly, in the hours of 6:00–17:00, AC
loads exhibit a constant load profile of 1.86 kW. The air-conditioner consumes 97%, outside lights
(2.6%), and inner lights (0.4%) of the total AC loads. The base station works 24/7, therefore,
weekday loads and weekend loads are assumed to be the same throughout the year. HOMER
simulation allows adding of daily and hourly noise random variation into the load profile. In this
study, a 10% day to day in a time step of 15% of random variability was added to the hourly load
profile. This increased the DC peak load from 6.5 kW to 8.2 kW and the AC peak load from 1.98 kW
to 2.77 kW, as shown in Figure 7. This random variation would account for an unexpected rise in
electricity demand to ensure a continuous supply of power for the base station.
3.2. HOMER simulation and optimization results
This study proposes a PV/fuel cell hybrid system to power a remote base station. However, the
base station is already powered by a diesel genset to meet its daily electricity demand. For this
study, an alternative power system, namely, PV/diesel/battery, is modelled in conjunction with the
site’s diesel power system. The technical, economic, and environmental performance of these
power systems is compared to that of the proposed system. This aims to justify and test the
viability, resilience, and competitive advantage of the PV/Fuel cell system to PV/battery/diesel and
diesel-only power systems. Table 7 presents HOMER results for the power systems. The results are
presented and analyzed for three power systems considered. It can be observed that the optimal
hybrid system sizing configuration for PV/fuel cell that meets the base station desired loads
comprises PV panels (79 kW), fuel cell (6 kW), battery (144 kWh), electrolyzer (30 kW), hydrogen
tank (30 kg) and converter (3 kW). Likewise, the PV/battery/diesel system comprises PV panels
(35 kW), battery (145 kWh), diesel genset (16 kW), and a converter (8 kW). Finally, adopting
DC Loads
Figure 6. Buduburam ATC base
station hourly load profile.
AC Loads
7
6
Load (kW)
5
4
3
2
1
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour of Day
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Figure 7. Screenshot of modelled PV/Fuel cell hybrid system
using HOMER.
a diesel-only system requires a diesel genset capacity of 16 kW and a converter capacity of 8 kW.
The total electricity production ranges from 160.838 MWh/yr for PV/fuel cell, 88. 242 MWh/yr for
PV/diesel/battery and 80.64 MWh/yr for diesel genset only. Diesel genset power system produces
no electricity excess. However, PV/diesel/battery and PV/fuel cell electricity excesses are 1.7%
(6.902 MWh/yr) and 20% (32.351 MWh/yr), respectively. From the technical point of view, the
three power systems can meet the base station loads.
From Table 7, the Buduburam base station diesel genset is expected to run for 8,760 hours and
produce about 69,400 kg/yr of CO2 emissions. However, opting for PV/diesel/battery reduces the
genset operating hours by about 85% and reduces CO2 emissions by 62% compared to the dieselonly system. Based on global concern about reducing CO2 emissions to mitigate climate change,
deploying a PV/Fuel cell hybrid system emits no emissions, but it saves about 27 tCO2/yr than a PV/
battery/diesel system and 67 tCO2/yr than a diesel power system. These CO2 savings can contribute to the Government of Ghana’s agenda on carbon savings of about 11 MtCO2 by 2030 as
drafted in the Ghana Renewable Energy Master Plan (Energy Commission, 2019). Also, it is
supported by Ghana’s Renewable Energy Act 832, which promotes the utilization of locally
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Table 7. HOMER optimum results for hybrid power systems
PV/Fuel Cell
PV/diesel/battery
PV capacity (kW)
Parameter
79
35
-
Fuel cell capacity (kW)
6
-
-
Battery capacity (kWh)
144
145
-
Diesel genset capacity
(kW)
-
16
16
30
-
8.06
Hydrogen tank (kg)
Converter capacity (kW)
Diesel only
2.75
7.79
Electrolyzer (kW)
30
-
-
Dispatch Strategy
Load following
Load following
Cycle charging
656,985
NPC (USD)
326,193
436,396
LCOE (USD/kWh)
0.222
0.296
0.466
Operating Cost (USD/yr)
7,043
18,505
32,596
185,712
67,278
6,796
0
10,201
26,510
100
60
0
Initial Capital (USD)
Fuel Cost (USD/yr)
Renewable Fraction (%)
Generator hours (hrs)
-
1,296
8,760
73.7
73
65
Electricity Production
(kWh/yr)
160,838
88,242
80,164
Excess Electricity (kWh/
yr)
32,351
6,902
0
Capacity Shortage (kWh/
yr)
Unmet Load (kWh/yr)
50.9
1.87
0.224
CO2 emission (kg/yr)
0
26,704
69,400
Carbon Monoxide (kg/yr)
0
167
433
Sulfur Oxide (kg/yr)
0
65
170
Nitrogen Oxide (kg/yr)
0
157
407
available renewable energy resources to cut down greenhouse emissions (Government of Ghana,
2011). This is a potential footprint for Ghana towards decarbonization for the telecom sector
across the country.
From a purely economic standpoint, the two economic metrics for decision making are NPC and
LCOE. Concerning Table 7, PV/Fuel cell NPC is 30% lower than PV/diesel/battery and 67% lower than
diesel-only. Also, the PV/fuel cell has the lowest LCOE (0.222 USD/kWh), although it has the highest
initial capital (185,712 USD). The LCOE is only 29% lower than PV/battery/diesel but 71% lower than
the diesel-only power system (current power system). Additionally, PV/Fuel cell initial capital cost is
about 94% higher than PV/batter/diesel and almost 186% higher than diesel-only power systems. The
operating cost for PV/Fuel is 90% and 129% lower than PV/diesel and diesel power systems. In Ghana,
the Public Utilities Regulatory Commission (PURC) categorizes telecom base stations connected to the
national grid under the special load tariff—low voltage (SLT-LV) sector. The approved average electricity tariff for this sector is about 0.25 USD/kWh as of October 2020 (PURC, 2020). The LCOE generated
from PV/fuel is about 12% cheaper than the average current tariff (0.25 USD/kWh) paid by gridconnected telecom stations. Key observations can be gleaned from similar studies that incorporate
PV and fuel cells, as discussed above. For instance, this hybrid system LCOE (0.222 USD/kWh) is nearly
comparable to the LCOE (0.145 USD/kWh) for a study in UAE (Ghenai et al., 2018). However, the authors
excluded battery banks in the hybrid system, which could have increased the system cost to impact
the LCOE. Likewise, a study in India with an LCOE (0.203 USD/kWh) (Singh et al., 2017) is comparable to
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system LCOE. Moreover, the system LCOE outshines the LCOE (1.306 USD/kWh) for a study conducted
in Istanbul (Dursun & Aykut, 2019). Furthermore, significant observations can be gleaned from similar
studies on hybrid systems for powering base stations in Table 1. It can be seen that most of the studies
focused on the utilization of PV, battery, diesel components to the telecom sites. However, the study
that comprises PV/battery/wind/fuel cell was conducted in India, and the LCOE is about 0.99 USD/kWh
(Amutha & Rajini, 2015), which is far above the LCOE estimated in this study. Nevertheless, other LCOE
estimated for telecom sites that are comparable to the current study LCOE are as follows: 0.372 USD/
kWh in South Africa (Kusakana & Vermaak, 2013), 0.205 USD/kWh in Malaysia (Alsharif et al., 2015),
and 0.218 USD/kWh in South Africa (Aderemi et al., 2018). A study on PV/diesel/battery hybrid systems
for a telecom base station estimated an LCOE of 0.53 USD/KWh (Quansah et al., 2017) for Ghana’s
case. This system LCOE is expensive compared to the LCOE generated from this study. Globally, the
LCOE generated from low carbon generation technologies has declined and is gradually becoming
lower than fossil fuel generation costs. Also, renewable energy costs have continually declined in
recent years (International Energy Agency, 2020). The PV/fuel cell system LCOE is cost-effective, and
telecom sites can opt to shift to this technology. Though it has a high initial cost, it is more costeffective and lucrative than PV/diesel/battery and diesel-only systems in the long term.
3.2.1. PV/fuel cell hybrid system performance
Table 8 presents electricity generation and consumption by the hybrid power system. The annual
electricity production from this hybrid system is about 160.838MWh/yr, which comprises 132.151
MWh/year (82.2%) from solar PV panels and 28.687 MWh/yr (17.8%) from the fuel cell. About 52%
of electricity generation from PV serves the electrolyzer to split water into hydrogen and oxygen.
The remaining 48% meets the DC and AC loads during the daytime. Electricity production from PV
yields a levelized cost of 0.029 USD/kWh. The PV panels rated capacity is 79 kW. It has a mean
output of 15.1 kW and a capacity factor of 18.4%. The rated capacity of the fuel cell is 6 kW. It has
a mean and minimum power output of 5.84 kW and 2.42 kW. The fuel cell’s capacity factor is
54.6% at a fixed generation cost of 0.54 USD/hr. The fuel cell consumes 1,071 kg of hydrogen with
a specific hydrogen consumption of 0.0373 kg/kWh. Also, it consumes 2.93 kg of hydrogen per day
(about 0.122 kg of hydrogen per hour). It has an operating time of 4,622 hrs/yr.
The overall electricity generated from this hybrid system is consumed as follows: AC loads
(16.773 MWh/yr), DC loads (57.006 MWh/yr), and electrolyzer (50.885MWh/yr.). About 3.823
MWh/yr of electricity is lost during energy conversion in the battery and converter systems.
Figure 8 displays the monthly electricity generated from PV panels and fuel cell. It can be seen
that there is variation in electricity generated by each power system throughout the year. For
instance, the months of June—September has low power produced from PV panels and fuel cells.
This is due to low solar irradiation and clearness index at Buduburam, mainly caused by frequent
rains and cloudy atmosphere during that season which likely to affect PV and fuel cell power
output
Table 8. Electricity produced and consumed
Component
Electricity Produced
MWh/yr.
Electricity Consumed
MWh/yr.
PV Panels
132.151
AC loads
16.773
Fuel Cell
28.687
DC loads
57.006
-
-
Electrolyzer
50.885
-
-
Excess electricity
32.351
-
-
Losses
Total
160.838
Total
3.823
160.838
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Fuel Cell
Figure 8. PV and fuel cell
monthly electricity generation.
PV Panels
Average Electricity Production (kW)
25
20
15
10
5
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Month
3.2.2. Economic analysis
The solar PV/fuel cell hybrid system has a total NPC, initial capital, and operating cost of 326,193
USD 185,712 USD and 7,043 USD/yr, respectively, as presented in Table 7. Figure 9 shows the cost
breakdown for all components. It can be observed that the battery component has the highest
NPC ($90,178.57), followed by PV ($77,386.30), fuel cell ($63,213.13), electrolyzer ($60,075.83),
hydrogen tank ($42,271.20), other ($11,994.67) and converter ($1,993.64) respectively. Also, it can
be seen that capital cost contributes to 54% of the total NPC. The PV panels are the most
expensive component, contributing 34% to the hybrid system’s capital cost. Next is the battery
(17.5%) and the hydrogen tank (16.5%). The remaining component’s contribution to capital cost is
as follows: electrolyzer (16%), fuel cell (9%), other (cost for acquiring land and control panel) (5%),
and converter (1%).
Replacement cost contributes about 26% to the project total NPC. Replacement cost emanates
from components such as fuel cell, battery, electrolyzer, and converter. The battery bank has the
highest replacement cost of 49%. The remaining component’s contribution to replacement cost is
as follows: fuel cell (25%), electrolyzer (25%), and converter (1%). Hydrogen tank and PV panels
have no replacement because their lifetime equals the project lifetime (25 yrs). Operating cost has
the lowest cost contribution to the project total NPC. The hybrid system’s operating cost emanates
from fuel cell (33%), battery (20%), PV panels (18%), hydrogen tank (15%), electrolyzer (10%),
others (3%), and converter (1%).
3.3. Sensitivity analysis
Sensitivity analysis was carried out on critical parameters to envisage its impact on the optimal
hybrid system NPC and LCOE. This would help check the hybrid system’s resilience for decisionmaking. The key selected parameters are the discount rate and capital subsidy.
The discount rate is the interest rate at which money is borrowed from local and international
banks. It measures the present value of future cash flows from the project. Figure 10 displays the
impact of the discount rate on the system NPC and LCOE. It can be seen that the LCOE decreases
with a decrease in the discount rate. There is almost a positive linear relationship between the
discount rate and LCOE. As the discount rate decreases from 12% to 10%, the system LCOE
decreases by about 30%, but NPC increases by about 24%. With a lower discount of 4%, the
LCOE reduces by 71%, and the NPC increases by 64%. Similarly, the LCOE rises by 21%, and NPC
decreases by 14% when the discount increases to 14%. These sensitive changes are due to the
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Capital Cost
Figure 9. Cost breakdown for
components.
Replacement Cost
Operating & Maintenance Cost
1,00,000
90,000
80,000
NPC $
70,000
60,000
50,000
40,000
30,000
20,000
10,000
0
Fuel Cell
Battery
Hydrogen Converter
Tank
Other
Electrolyser
PV
Component
NPC ($)
Figure 10. Effect of discount
rate on NPC and LCOE.
LCOE ($/kWh)
6,00,000
0.3
0.28
5,00,000
NPC ($)
4,00,000
0.24
0.22
3,00,000
0.2
2,00,000
0.18
LCOE ($/kWh)
0.26
0.16
1,00,000
0.14
0
0.12
4
6
8
10
12
Discount rate %
14
16
system’s total annualized being affected by the discount rate. The annualized cost decreases with
the decreasing discount rate, thus, causing the LCOE to fall. Generally, capital-intensive technologies are sensitive to variations in the discount rate. However, a relatively high upfront cost
technology could be more vulnerable to business uncertainties, thus increasing financing costs
(International Energy Agency, 2020). Although the PV/fuel system is capital-intensive, it is resilient
to discount rate fluctuations is significant. Moreover, the discount rate’s impact on the system
would enable stakeholders and investors to break even on the project to gain appropriate investment returns. Hence, local and international banks should grant stakeholders and investors a low
discount rate to attract this system’s deployment to yield a cost-effective LCOE for customers.
The effect of initial capital subsidies was accessed using the base case discount rate (12%) and
inflation (10%). The initial capital is the total cost required to commence the project. However,
renewable energy projects are capital intensive, which is likely to discourage stakeholders from
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NPC ($)
Initial Capital ($)
LCOE ($/kWh)
0.25
3,50,000
0.222
3,00,000
0.2
0.190
2,50,000
0.158
0.15
2,00,000
$
0.126
1,50,000
0.094 0.1
LCOE ($/kWh)
Figure 11. Effect of capital
subsidy on NPC and LCOE.
1,00,000
0.05
50,000
0
0
25
50
75
Capital subsidy %
100
deployment. Subsidizing the initial capital cost by either a local or international donor agency would
help attract the system’s deployment by stakeholders since the high upfront cost is sometimes
a barrier. Figure 11 displays the effect of the capital subsidy on the system NPC and LCOE. It can be
seen that almost a linear relationship exists between the capital subsidy and the LCOE. A donor agency
providing a 50% initial capital subsidy reduces both NPC and LCOE by 29%. A 100% fund for the entire
initial investment cost significantly reduces the system LCOE by 59%. The results indicate that the
hybrid system LCOE is more sensitive to capital subsidy and is attractive and cost-effective compared
to LCOE paid by grid-connected base stations. Therefore, donor agencies could play a pivotal role in
assisting stakeholders in deploying this system by providing funds to cut down initial capital costs. This
would aid stakeholders in reducing CO2 emissions to achieve a carbon-neutral environment. Also, the
capital subsidies would encourage grid-connected telecom sites to go off-grid to reduce grid dependency and increase renewable energy capacity in the national energy mix.
4. Conclusions
The depletion of fossil fuel reserves and high greenhouse gas emissions from fossil fuel combustion has compelled a global need to transit to cleaner energy systems like solar PV, wind turbines,
hydropower, fuel cells, etc. This study presents an analysis of a solar PV/fuel cell hybrid system to
power a base station located at Budumburam, in the Central Region of Ghana. HOMER was used to
perform a complete parametric analysis of the system. The NPC and LCOE were selected as the
principal economic indicators. The hybrid system’s technical, economic, and environmental performance was compared to PV/diesel/battery and diesel power systems.
From the study results, these findings are gleaned. The existing base station diesel power system
initial capital ($6,796) is low compared to PV/diesel/battery ($67,278) and PV/fuel/cell ($185,712).
However, PV/Fuel operating cost is 90% and 129% lower than PV/diesel/battery and diesel power
systems. The LCOE generated from PV/fuel is only 29% lower than PV/battery/diesel but 71% lower
than the diesel power system (current power system). Moreover, this LCOE is about 12% cheaper
than the current average tariff (0.25 USD/kWh) paid by grid-connected telecom stations. Even at
a lower discount rate of 6%, PV/fuel cell yields an LCOE of 0.149 USD/kWh, which is about 50%
lower than the grid tariff. Deploying a PV/fuel cell system would cause the base station to save
about 27 tCO2/yr than the PV/diesel/battery power system and 67 tCO2/yr than a diesel power
system. This is a footprint for the Government of Ghana (GoG) towards decarbonization for the
telecom industry. Sensitivity analysis shows that the PV/fuel system is sensitive to changes in the
discount rate. Although the system has a high upfront cost, its economic feasibility is evident in its
lower LCOE and zero CO2 emissions. Presently, this technology is new in Ghana. However, subsidizing the initial capital would drastically reduce the system NPC and LCOE to make it more
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attractive and lucrative. This would probably attract stakeholders to consider this system’s deployment to increase renewable energy penetration in Ghana.
The study findings are incredibly vital for stakeholders, policymakers, and investors to guide investment and deployment of PV/fuel cell power systems for Ghana’s telecom base stations. Though the
upfront cost is high, stakeholders could be sensitized to understand the long-term profit of deploying
renewable energy systems. The authors encourage the Ghana National Communication Authority to
partner stakeholders to consider a hybrid system of this nature since the GoG has a target of saving 11
MtCO2 by 2030 (Energy Commission, 2019). Lastly, the authors encourage local and international
banks to provide stakeholders, investors, and decision-makers with attractive incentives and packages
not limited to a low discount rate, grants, tax credits, and loan programs to attract the deployment of
a standalone renewable hybrid system of this nature. Future studies should focus on setting up
a prototype to validate HOMER’s technical results. Likewise, further studies should focus on using
measured ground data for solar irradiation to yield more precise and realistic simulation findings.
Acknowledgements
The authors are grateful to the team in charge of the
Buduburam ATC base station for their sincere support
during data collection for electrical load assessment.
Funding
The authors received no direct funding for this research.
Author details
Flavio Odoi-Yorke12
E-mail: fodoi-yorke@cctu.edu.gh
ORCID ID: http://orcid.org/0000-0002-7270-0159
Atchou Woenagnon3
E-mail: woenagnon@gmail.com
1
Department of Renewable Energy Technology, Cape
Coast Technical University, Cape Coast, Ghana.
2
Center for Renewable Energy, Cape Coast Technical
University, Cape Coast, Ghana.
3
Department of Marine Engineering, Regional Maritime
University, Accra, Ghana.
Citation information
Cite this article as: Techno-economic assessment of solar
PV/fuel cell hybrid power system for telecom base stations
in Ghana, Flavio Odoi-Yorke & Atchou Woenagnon, Cogent
Engineering (2021), 8: 1911285.
References
Adaramola, M. S., Agelin-Chaab, M., & Paul, S. S. (2014).
Analysis of hybrid energy systems for application in
southern Ghana. Energy Conversion and
Management, 88(2014), 284–295. http://10.1016/j.
enconman.2014.08.029
Adaramola, M. S., Quansah, D. A., Agelin-Chaab, M., &
Paul, S. S. (2017). Multipurpose renewable energy
resources based hybrid energy system for remote
community in northern Ghana. Sustainable Energy
Technologies and Assessments, 22, 161–170. https://
doi.org/10.1016/j.seta.2017.02.011
Addo, E. O. K., Asumadu, J., & Okyere, P. Y. (2014). Optimal
design of renewable hybrid energy system for
a village in Ghana. Proceedings of the 2014 9th IEEE
Conference on Industrial Electronics and Applications,
ICIEA 2014, 1520–1526, https://doi.org/10.1109/
ICIEA.2014.6931410.
Aderemi, B. A., Daniel Chowdhury, S. P., Olwal, T. O., &
Abu-Mahfouz, A. M. (2018). Techno-economic feasibility of hybrid solar photovoltaic and battery energy
storage power system for a mobile cellular base
station in Soshanguve, South Africa. Energies, 11(6),
1572. https://doi.org/10.3390/en11061572
AfDB. (2016). African economic outlook 2016: Special
theme: Sustainable cities and structural
transformation. [Online]. https://www.afdb.org/filead
min/uploads/afdb/Documents/Publications/AEO_
2016_Report_Full_English.pdf
Agyekum, E. B., & Nutakor, C. (2020). Feasibility study and
economic analysis of stand-alone hybrid energy system for southern Ghana. Sustainable Energy
Technologies and Assessments, 39(January), 100695.
https://doi.org/10.1016/j.seta.2020.100695
AIMS Power. (2020a). 12V 100Ah deep cycle battery heavy
duty. Retrieved June 22, 2020, from https://www.
aimscorp.net/agm-12v-100ah-deep-cycle-batteryheavy-duty.html
AIMS Power. (2020b). 1000 watt pure sine power inverter
12 volt ETL listed to UL 458. Retrieved August 27,
2020, from https://www.aimscorp.net/1000_Watt_
Pure_Sine_Power_Inverter_12_Volt.html
Alsharif, M. H., Nordin, R., & Ismail, M. (2015). Energy
optimisation of hybrid off-grid system for remote
telecommunication base station deployment in
Malaysia. EURASIP Journal on Wireless
Communications and Networking, 2015(1). https://
doi.org/10.1186/s13638-015-0284-7
Amutha, W. M., & Rajini, V. (2015). Techno-economic evaluation of various hybrid power systems for rural
telecom. Renewable and Sustainable Energy Reviews, 43,
553–561. https://doi.org/10.1016/j.rser.2014.10.103
Ansong, M., Mensah, L. D., & Adaramola, M. S. (2017).
Techno-economic analysis of a hybrid system to
power a mine in an off-grid area in Ghana.
Sustainable Energy Technologies and Assessments, 23
(September), 48–56. https://doi.org/10.1016/j.seta.
2017.09.001
Aris, A. M., & Shabani, B. (2015). Sustainable power supply
solutions for off-grid base stations. Energies, 8(10),
10904–10941. http://doi:10.3390/en81010904
Babatunde, O. M., Denwigwe, I. H., Babatunde, D. E.,
Ayeni, A. O., Adedoja, T. B., & Adedoja, O. S. (2019).
Techno-economic assessment of photovoltaic-diesel
generator-battery energy system for base transceiver
stations loads in Nigeria. Cogent Engineering, 1–19.
https://doi.org/10.1080/23311916.2019.1684805
Bajpai, P., & Dash, V. (2012). Hybrid renewable energy
systems for power generation in stand-alone applications: A review. Renewable and Sustainable Energy
Reviews, 16(5), 2926–2939. https://doi.org/10.1016/j.
rser.2012.02.009
Bank of Ghana. (2020a). Monthly interest rates. Retrieved
June 23, 2020, from https://www.bog.gov.gh/eco
nomic-data/interest-rates
Page 22 of 25
Odoi-Yorke & Woenagnon, Cogent Engineering (2021), 8: 1911285
https://doi.org/10.1080/23311916.2021.1911285
Bank of Ghana. (2020b). Bank of Ghana monetary policy
report inflation outlook and analysis. [Online]. https://
www.bog.gov.gh/monetary_policy_rpts/inflationoutlook-and-analysis-report-may-2020
Cotrell, J., & Pratt, W. (2003). Modeling the feasibility of using
fuel cells and hydrogen internal combustion engines in
remote renewable energy systems preprint. [Online].
https://www.nrel.gov/docs/fy03osti/34043.pdf
Crouch, M. (2011). Fuel cell systems for base stations : Deep
dive study. An exploration of the current and future
potential of fuel cell systems to provide green power for
the telecoms industry. [Online]. https://www.gsma.
com/mobilefordevelopment/wp-content/uploads/
2012/04/Fuel_Cell_Report_for_fomatting1.pdf
Dursun, B., & Aykut, E. (2019). An investigation on wind/
PV/fuel cell/battery hybrid renewable energy system
for nursing home in Istanbul. Proceedings of the
Institution of Mechanical Engineers, Part A: Journal of
Power and Energy, 233(5), 616–625. http://doi:10.
1177/0957650919840519
Energy Commission. (2019). Ghana renewable energy master plan. [Online]. http://www.energycom.gov.gh/files/
Renewable-Energy-Masterplan-February-2019.pdf
Ghana Statistical Service. (2014). 2010 population and
housing census Gomoa. District analytical report. East
district. [Online]. http://www2.statsghana.gov.gh/doc
files/2010_District_Report/Central/GOMOAEAST.pdf
Ghana Statistical Service. (2019). Rebased 2013–2018
annualgross domesticproduct. April 2019 edition.
[Online]. http://www.statsghana.gov.gh
Ghenai, C., Salameh, T., & Merabet, A. (2018). Technicoeconomic analysis of off grid solar PV/Fuel cell
energy system for residential community in desert
region. International Journal of Hydrogen Energy, 45
(20), 11460–11470. https://doi.org/10.1016/j.ijhy
dene.2018.05.110
GlobalPetrolPrices. (2020). Ghana diesel prices. Retrieved
May 28, 2020, from https://www.globalpetrolprices.
com/Ghana/diesel_prices
Goel, S., & Ali, S. M. (2013). Hybrid energy systems for off-grid
remote telecom tower in Odisha, India. International
Journal of Ambient Energy, 36(3), 116–122. https://doi.
org/10.1080/01430750.2013.823110
Government of Ghana. (2011). Renewable energy act
2011: Act 832. [Online]. 1–27, http://energycom.gov.
gh/files/RENEWABLEENERGYACT2011(ACT832).pdf
Hatsu, S., Mabeifam, U. M., & Paitoo, P. C. (2016).
Infrastructure sharing among Ghana’s mobile telecommunication networks: Benefits and challenges.
American Journal of Networks and Communications, 2
(2), 35–45. http://doi:10.11648/j.ajnc.20160502.14
Heydari, A., & Askarzadeh, A. (2016). Techno-economic
analysis of a PV/biomass/fuel cell energy system
considering different fuel cell system initial capital
costs. Solar Energy, 133, 409–420. https://doi.org/10.
1016/j.solener.2016.04.018
HOMER Energy. (2016, August). HOMER pro version 3.7
user manual. [Online]. http://www.homerenergy.com/
pdf/HOMERHelpManual.pdf
Humar, I., Ge, X., Xiang, L., & Jo, M. (2011). Rethinking
energy—Efficiency models of cellular networks with
embodied energy. IEEE Network, 25(2), 40–49. http://
doi:10.1109/MNET.2011.5730527
International Energy Agency. (2020). Projected costs of
generating electricity 2020 edition. [Online]. https://
www.iea.org/reports/projected-costs-of-generatingelectricity-2020
IRENA. (2015).REthinking energy: Renewable energy and
climate change. [Online]. http://www.irena.org/-/
media/Files/IRENA/Agency/Publication/2015/IRENA-_
REthinking_Energy_2nd_report_2015.pdf
IRENA. (2019). Renewable power generation costs in 2019.
[Online]. https://www.irena.org/-/media/Files/IRENA/
Agency/Publication/2020/Jun/IRENA_Power_
Generation_Costs_2019.pdf
Isa, N. M., Das, H. S., Tan, C. W., Yatim, A. H. M., & Lau, K. Y.
(2016). A techno-economic assessment of
a combined heat and power photovoltaic/fuel cell/
battery energy system in Malaysia hospital. Energy,
112, 75–90. https://doi.org/10.1016/j.energy.2016.06.
056
Kebede, H. M., & Bekele, G. B. (2018). Feasibility study of
PV-wind-fuel cell hybrid power system for electrification of a rural village in Ethiopia. Journal of
Electrical and Computer Engineering, 2018. https://
doi.org/10.1155/2018/4015354
Kusakana, K., & Vermaak, H. J. (2013). Hybrid renewable
power systems for mobile telephony base stations in
developing countries. Renewable Energy, 51,
419–425. https://doi.org/10.1016/j.renene.2012.09.
045
Lambert, S., Van Heddeghem, W., Vereecken, W., Colle, D.,
& Pickavet, M. (2013). Worldwide electricity consumption of communication networks. 790(2010),
[Online]. http://dx.doi.org/10.1364/OE.20.00B513
Malmodin, J., & Lundén, D. (2018). The electricity consumption and operational carbon emissions of ICT
network operators 2010–2015. [Online]. https://www.
diva-portal.org/smash/get/diva2:1177210/
FULLTEXT01.pdf
Mohammed, O. H., Amirat, Y., Benbouzid, M., & Elbast, A.
(2014). Optimal design of a PV/Fuel cell hybrid power
system for the city of Brest in France. [Online].
119–123. https://hal.archives-ouvertes.fr/hal01023490
NCA. (2010). Government of Ghana guidelines for the
deployment of communications towers. [Online].
https://www.nca.org.gh/assets/Uploads/
Communications-Towers-Guidelines3.pdf
NCA. (2020). Telecom voice subscription. Retrieved
January 01, 2020, from https://www.nca.org.gh/
industry-data-2/market-share-statistics-2/telecomvoice
Okedu, K. E., & Uhunmwangho, R. (2014). Optimization of
renewable energy efficiency using HOMER.
International Journal of Renewable Energy Research,
4(2), 421–427. https://doi.org/10.1234/ijrer.v4i2.1231.
g6294
Olatomiwa, L., Mekhilef, S., Huda, A. S. N., & Sanusi, K.
(2015). Techno-economic analysis of hybrid PV–diesel–battery and PV–wind–diesel–battery power systems for mobile BTS: The way forward for rural
development. Energy Science & Engineering, 3(4),
271–285. https://doi.org/10.1002/ese3.71
Olatomiwa, L. J., Mekhilef, S., & Huda, A. S. N. (2014).
Optimal sizing of hybrid energy system for a remote
telecom tower: A case study in Nigeria. 2014 IEEE
Conference on Energy Conversion (CENCON 2014),
September, 243–247, https://doi.org/10.1109/
CENCON.2014.6967509.
Opoku, R., Mensah-Darkwa, K., & Samed Muntaka, A.
(2018). Techno-economic analysis of a hybrid solar
PV-grid powered air-conditioner for daytime office
use in hot humid climates– A case study in Kumasi
city, Ghana. Solar Energy, 165(February), 65–74.
https://doi.org/10.1016/j.solener.2018.03.013
Özgirgin, E., Devrim, Y., & Albostan, A. (2015). Modeling
and simulation of a hybrid photovoltaic (PV)
module-electrolyzer-PEM fuel cell system for
micro-cogeneration applications. International
Journal of Hydrogen Energy, 40(44), 15336–15342.
http://doi:10.1016/j.ijhydene.2015.06.122
Page 23 of 25
Odoi-Yorke & Woenagnon, Cogent Engineering (2021), 8: 1911285
https://doi.org/10.1080/23311916.2021.1911285
Paudel, S., Shrestha, J. N., Neto, F. J., Ferreira, J. A. F., &
Adhikari, M. (2011). Optimization of hybrid PV/wind
power system for remote telecom station. 2011
International Conference on Power and Energy
Systems, ICPS 2011, X, 1–11. https://doi.org/10.1109/
ICPES.2011.6156618.
Postnote. (2008). ICT and CO2 emissions, December 2008
Number 319 Parliamentary Office of Science &
Technology. (319), 1–4. [Online]. https://www.parlia
ment.uk/documents/post/postpn319.pdf
PURC. (2020). Public Utilities Regulation Commission
(PURC) electricity and water tariff [Online]. http://
www.purc.com.gh/purc/sites/default/files/purc_q4_
electricity_and_water_tariff_2020.pdf
Quansah, D. A., Woangbah, S. K., Anto, E. K.,
Akowuah, E. K., & Adaramola, M. S. (2017). Technoeconomics of solar pv-diesel hybrid power systems
for off-grid outdoor base transceiver stations in
Ghana. International Journal of Energy for a Clean
Environment, 18(1), 61–78. https://doi.org/10.1615/
InterJEnerCleanEnv.2017019537
Sakah, M., Amankwah, F., Katzenbach, R., & Gyamfi, S.
(2017). Towards a sustainable electrification in
Ghana: A review of renewable energy deployment
policies. The Indian Journal of Surgery, 79(April),
544–557. https://doi.org/10.1016/j.rser.2017.05.090
Singh, A., Baredar, P., & Gupta, B. (2017). Technoeconomic feasibility analysis of hydrogen fuel cell
and solar photovoltaic hybrid renewable energy system for academic research building. Energy
Conversion and Management, 145, 398–414. https://
doi.org/10.1016/j.enconman.2017.05.014
SUKA. (2020a). DEEP CYCLE ROCKET 12V 100AH. Retrieved
June 22, 2020, from http://suka.com.gh/ecommerce/
product-category/batteries
SUKA. (2020b). 1.5KVA-24V inverter. Retrieved July 20,
2020, from https://suka.com.gh/ecommerce/product/
axpert-1-5kva-24-inverter
Tchao, E. T., Agyekum, K. A. P., & Diawuo, K. (2017).
Techno-Economic evaluation of power systems for
off-grid telecommunications infrastructure in remote
locations in Ghana. Communications on Applied
Electronics, 7(7), 22–27. https://doi.org/10.5120/
cae2017652694
TH Energy. (2019). Huge potential for renewables in the telecom sector. Retrieved September 06, 2020, from https://
www.th-energy.net/2019/02/25/huge-potential-forrenewables-in-the-telecom-sector/#:~:text=Poweringtelecom-towers-with-renewables,costs-for-operationand-maintenance.&text=It-has-become-obvious-that,
energy-solutions-is-therefore-huge
UNFCCC. (1992). United Nations framework convention on
climate change. [Online]. https://unfccc.int/files/
essential_background/background_publications_
htmlpdf/application/pdf/conveng.pdf
UNFCCC. (2015). Paris agreement. [Online]. https://unfccc.
int/files/essential_background/convention/applica
tion/pdf/english_paris_agreement.pdf
UNFCCC. (2020). What is the Kyoto protocol? Retrieved
August 20, 2020, from https://unfccc.int/kyoto_protocol
Page 24 of 25
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