Optimal Sizing and Techno-Economic Analysis of Minigrid Hybrid Renewable Energy System for Tourist Destination Islands of Lake Tana, Ethiopia - MDPI

applied
 sciences
Article
Optimal Sizing and Techno-Economic Analysis of Minigrid
Hybrid Renewable Energy System for Tourist Destination
Islands of Lake Tana, Ethiopia
Teketay Mulu Beza , Chen-Han Wu and Cheng-Chien Kuo *

 Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 4,
 Keelung Rd., Taipei 10607, Taiwan; teketay.mulu@bdu.edu.et (T.M.B.); d10907002@mail.ntust.edu.tw (C.-H.W.)
 * Correspondence: cckuo@mail.ntust.edu.tw; Tel.: +886-9-2088-1490; Fax: +886-2-2737-6688

 Abstract: Achieving universal electricity access is a challenging goal for the governments of devel-
 oping countries such as Ethiopia. Extending the national grid to the remotely located, scattered,
 and island populations demands a huge investment. This paper aims to show the techno-economic
 feasibility of minigrid renewable energy system to electrify Kibran Gabriel island in Ethiopia, through
 the execution of simulation, optimization and sensitivity analysis using Hybrid Optimization Models
 for Energy Resources (HOMER Pro) software. The minigrid systems were compared with both diesel
 generation (DG) and grid extension systems. The hybrid photovoltaic (PV)/DG/battery system
 is more economically feasible compared with other minigrid systems, and the best cost-effective
 option is the one including load flow (LF) strategy with 25 kW of PV, 10 kW of DG, 40 kWh of battery,
 



 
 and 5 kW of bi-directional convertor. The optimal PV/DG/Battery system, having levelized cost of
 energy (COE) of USD 0.175/kWh, net present cost (NPC) of USD 119,139 and renewable fraction (RF)
Citation: Beza, T.M.; Wu, C.-H.; Kuo,
C.-C. Optimal Sizing and
 of 86.4%, reduces the pollutant emissions by 33,102 kg/yr compared with the stand-alone DG system.
Techno-Economic Analysis of The optimal minigrid sensitivity to the variations in global horizontal irradiance (GHI), diesel price
Minigrid Hybrid Renewable Energy and load consumption were considered in the sensitivity analysis, and the result shows that the
System for Tourist Destination system will operate reasonably well.
Islands of Lake Tana, Ethiopia. Appl.
Sci. 2021, 11, 7085. https://doi.org/ Keywords: hybrid renewable energy; minigrid; rural electrification; optimal sizing; techno-economic
10.3390/app11157085 analysis; grid-extension cost; sensitivity analysis

Academic Editor: Luis
Hernández-Callejo

 1. Introduction
Received: 25 June 2021
Accepted: 28 July 2021
 Energy poverty is a serious problem that must be addressed for the sustainable de-
Published: 31 July 2021
 velopment of a community. Of different forms of energy, electrical energy is the one that
 has become part and parcel of our lives. Nowadays, electricity access is closely linked to
Publisher’s Note: MDPI stays neutral
 aspects of human development such as healthcare, sanitation, educational access, and em-
with regard to jurisdictional claims in
 ployment rate [1]. That is why it is given priority attention in the sustainable development
published maps and institutional affil- goals (SDGs)—specifically, as stated in SDG-7: access to affordable, reliable, sustainable
iations. and modern energy for all [2]. According to the International Energy Agency (IEA), the
 number of people in sub-Saharan Africa without access to electricity was estimated to be
 580 million in 2019, while the number of people without access to clean cooking facilities
 was estimated to be about 900 million [3]. Similar studies showed that a number of people
 without access to electricity reside in rural areas of sub-Saharan Africa and South Asia [4].
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
 The rural off-grid communities rely heavily on conventional energy resources such as
This article is an open access article
 firewood, animal dung, kerosene, petroleum, and candles. However, these resources have
distributed under the terms and negative consequences on the environment as well for human health [5].
conditions of the Creative Commons The main challenge today is to supply electricity to people who are not yet connected
Attribution (CC BY) license (https:// to the grid in sub-Saharan African countries, such as Ethiopia. There are four possible
creativecommons.org/licenses/by/ solutions to alleviate the problem: (1) grid extension; (2) standalone diesel based power
4.0/). generation (DG); (3) solar home systems (SHS); and (4) islanded minigrid systems (MGS).

Appl. Sci. 2021, 11, 7085. https://doi.org/10.3390/app11157085 https://www.mdpi.com/journal/applsci

Appl. Sci. 2021, 11, 7085 2 of 22

 Grid extension is relatively reliable in power quality but it is a very expensive alterna-
 tive for delivering electricity access to remotely located, scattered and island populations.
 The DG system is the other option for electricity access for rural off-grid communities.
 However, diesel fuel transportation, pollutant emissions during power generation, high
 operating costs, and harmful effects on human health and the environment have made
 this option unfavorable [4]. SHS is the third option which has been used in rural off-grid
 communities. It is a portable and low-cost system with limited electrification capabilities to
 support large loads [6]. SHS basically delivers electricity for lighting and charging. How-
 ever, the economic value SHS injects into the community is very limited due to the capacity
 of power delivery [7]. Compared to the first three technologies, MGS have been deemed a
 better choice because of their potential to enable electrification beyond subsistence level
 living. In addition, the hybrid minigrid systems are considered a cost-effective alternative
 for the rural off-grid communities [8].
 In the sector of renewable energies, the increase in electrical energy generated by
 wind and solar was relatively the fastest. For example, the global solar PV installed
 capacity rosed from less than 1 GW in 2000 to 227 GW in 2015 [9,10]. Similarly, the globally
 installed capacity of wind power increased from 59 GW in 2005 to 433 GW in 2015 [9].
 However, optimal sizing and techno-economic analysis of hybrid minigrid systems for
 rural communities have been the main issue for many scholars. The related literature is
 discussed below.
 Emad et al. [11] made a review of the computational methods for the planning of
 hybrid renewable microgrids. The paper addressed the uncertainties in solar and wind
 energy resources and gives good insights for future researchers in this regard. Suman
 et al. [12] conducted a study to optimize an off-grid PV/wind/biogenerator system inte-
 grated with diesel and a storage system using hybrid particle swarm optimization and a
 grey wolf optimizer. Ko et al. [13] proposed an energy storage system model combined
 with PV system to explore the impact of incentives on power plant operations. Similarly, a
 hybrid energy management system for islanded networked microgrids considering battery
 energy storage and wasted energy was discussed in [14]. Bahramara et al. [15] presented
 a review of optimal planning tools considering investment and operation costs, meeting
 technical and emission constraints, and optimal sizing renewables. On the other hand,
 Rana et al. [16] proposed a novel peak load shaving algorithm for an isolated PV/battery
 microgrid system. However, excess energy, peak load handling, initial capital cost and op-
 timal sizing are still controversial in PV/battery systems. The optimal sizing of an off-line
 microgrid system using multiobjective simulated annealing particle swarm optimizer was
 proposed in [17]. However, the study mainly considers batteries and diesel generators to
 increase system reliability.
 Oladigbolu et al. [18] carried out a comparative analysis of hybrid renewable power
 system for off-grid rural electrification in Nigeria. According to the analysis a hybrid
 hydro/PV/wind/diesel/battery system with 77.4% renewable fraction was proposed for
 that specific site. Odou et al. [19] tried to optimize a hybrid off-grid renewable power
 system for rural communities in Benin, and the PV/diesel/battery system was the least
 costly system identified in the analysis. The study also indicated a 70% battery size
 reduction compared to PV/battery system. A co-optimization scheme using the Lagrange
 multiplier method for distributed energy resource planning in community microgrids was
 carried out in [20]. The study optimized the total annualized cost at the maximum fuel
 saving. Gebrehiwot et al. [21] proposed an off-grid hybrid power system for the village
 named Golbo II, in Ethiopia. According to this study, the PV/wind/diesel/battery system
 with a cost of energy of USD 0.207/kWh was the optimal solution. Similar studies taking
 into consideration the load demand and the environmental conditions of specific sites have
 been conducted in [12,22–24].

Appl. Sci. 2021, 11, 7085 3 of 22

 In accordance with worldwide trends, the Government of Ethiopia has set key targets
 for its energy sector, with the goal of providing electric power to all citizens by the end of
 2030 [25]. The government has a vision to provide high quality energy services to all sectors
 of the economy, as well as to export power to neighboring countries via the East African
 Power Pool [26]. Renewable energy sources such as hydropower, photovoltaics, wind, and
 geothermal energy have been identified as promising possibilities for Ethiopia’s energy
 security and environmental management in order to mitigate the harmful consequences
 of climate change [26,27]. However, rural electrification in the remote areas and small
 islands of Ethiopia through grid extension demands a huge capital investment because of
 the dispersed population, and difficult geographic terrain. According to the IEA, African
 energy outlook 2019 special report, Ethiopia has an electricity access rate of only 45%;
 nearly 60 million people do not have access to electricity [28]. Only 11% of the population
 has access to electricity through decentralized solutions, mainly from stand-alone diesel
 and PV.
 Considering the research gaps and the real problem on the ground at the specified site,
 the authors proposed optimal sizing and techno-economic analysis of the minigrid hybrid
 renewable energy system in comparison with grid-extension and diesel power generation
 for Kibran Gabriel island of Ethiopia. In addition to the optimal minigrid system, e.g.,
 other alternative configurations, the pollutant emission gases that can be reduced, the
 optimal system sensitivity to the variations of GHI, load consumption and diesel price are
 addressed in the analysis.
 The remainder of this paper is organized as follows: Section 2 describes materials
 and methods, whereas in Section 3 resources and demand of the case study are presented.
 Minigrid hybrid system discerptions, and component cost and financial assumptions are
 discussed in Sections 4 and 5, respectively. The simulation results and discussion are
 provided in Section 6, then a brief conclusion follows in Section 7.

 2. Materials and Methods
 This study mainly aims to show the techno-economic viability of the minigrid system
 for Kibran Gabriel island. Using HOMER Pro software, the feasible configurations and
 system sizing for the optimal system were carried out. The required data for simulation
 analysis were acquired from multiple sources: the weather data of the island was obtained
 from NASA surface meteorology and solar energy database integrated in HOMER Pro [29].
 In addition, the load data, diesel fuel price, interest rate and inflation rate, grid extension
 cost, and e-market surveys for equipment costs were required for the analysis.
 • The load profile of the island was estimated and categorized into primary loads
 (power is required at a specific time) and deferrable loads (power is required but time
 is flexible).
 • Since the island is not fully electrified yet, in the simulation analysis, electrifying the
 island with diesel generator was considered as a reference for other comparisons.
 Despite the pollution, the economic feasibility of diesel power generation relative to
 grid-extension cost was also considered for further comparisons.
 • We considered different feasible configurations of PV/wind/battery, PV/wind/diesel/
 battery, PV/battery, and PV/diesel/battery systems compared with the stand-alone
 DG system, and finally the optimal system was determined.
 • Once the optimal system was determined, sensitivity analysis was carried out to
 observe the effects of the variation of important parameters such as global horizontal
 irradiation, diesel fuel price, and load consumption on the optimal system.
 • Finally, the optimal size and techno-economically feasible configuration were de-
 termined. The minimum LCOE, and NPC, the total emissions reduced (compared
 with stand-alone diesel system), RF, capacity shortage fraction, and BGED and other
 parameters were computed.

Appl.Sci.
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 11,7085
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 of2222

 Description of Simulation Software
 Description of Simulation Software
 HOMER Pro software was developed by US National Renewable Energy Laboratory
 HOMER Pro software was developed by US National Renewable Energy Laboratory
 (NREL). The software is a powerful tool for designing, analyzing and planning of
 (NREL). The software is a powerful tool for designing, analyzing and planning of minigrid
 minigrid systems to determine the optimal size of system components through carrying
 systems to determine the optimal size of system components through carrying out techno-
 out techno-economic
 economic analysis [29].analysis
 Figure 1[29]. Figure
 depicts the1HOMER
 depicts the
 Pro HOMER Pro
 simulation simulation
 process process
 architecture
 architecture
 diagram. diagram.

 Input Parameters Output

 Load Profiles Feasible System Category

 Net Present Cost

 Resource Availability and Cost of Energy
 Meteorological data
 Total Capital Cost
 HOMER Analysis

 Emissions

 Economic and

 Technical data Renewable Fraction

 Capacity Shortage Fraction

 Optimization constraints
 Excess Energy Fraction

 Figure1.1.HOMER
 Figure HOMERPro
 Proanalysis
 analysisarchitecture
 architecturediagram.
 diagram.

 3.3.Resources
 ResourcesandandDemand
 DemandAssessment
 Assessmentof
 ofthe
 theCase
 CaseStudy
 Study
 3.1. Site Description
 3.1. Site Description
 Kibran
 KibranGabriel
 Gabrielisisone
 oneof
 ofLake
 LakeTana
 Tanaislands
 islandslocated
 located11
 11km
 kmNorth
 NorthWest
 WestofofBahir
 BahirDar
 Dar
 city, Ethiopia [30] with latitude 11.6516◦ and longitude 37.3644◦ . Lake Tana is one of the
 city, Ethiopia [30] with latitude 11.6516° and longitude 37.3644°. Lake Tana is one of the
 UNESCO world biosphere reserve sites in Ethiopia, registered on 19 June 2015 [31]. It is
 UNESCO world biosphere reserve sites in Ethiopia, registered on 19 June 2015 [31]. It is
 the home of 37 islands, of which 20 have Ethiopian Orthodox churches and monasteries.
 the home of 37 islands, of which 20 have Ethiopian Orthodox churches and monasteries.
 Kibran Gabriel is endowed with historical and religious heritages that make it the most
 Kibran Gabriel is endowed with historical and religious heritages that make it the most
 popular tourist destination among the Lake Tana islands. However, the communities living
 popular tourist destination among the Lake Tana islands. However, the communities liv-
 on the island do not have access to electricity. Negligible SHS and portable diesel generators
 ing on the island do not have access to electricity. Negligible SHS and portable diesel gen-
 are used during holidays. The major economic activities practiced are agriculture, fishery
 erators are used during holidays. The major economic activities practiced are agriculture,
 and sightseeing. The geographic location is indicated in Figure 2 below.
 fishery and sightseeing. The geographic location is indicated in Figure 2 below.

Appl. Sci. 2021, 11, 7085 5 of 22
Appl. Sci. 2021, 11, 7085 5 of 22
 Appl. Sci. 2021, 11, 7085 5 of 22

 Google Earth, Image ©2021Maxar Technologies
 Google Earth, Image ©2021Maxar Technologies

 Figure
 Figure 2.2.Geographic
 Figure2. Geographiclocation
 Geographic location of
 locationof Kibran
 ofKibran Gabriel
 KibranGabriel island.
 Gabrielisland.
 island.

 3.2.
 3.2.Global
 3.2. GlobalHorizontal
 Global HorizontalIrradiation
 Horizontal Irradiationand
 Irradiation andWind
 and WindSpeed
 Wind Speed
 Speed
 Providing
 Providingthe
 Providing the latitude
 thelatitude
 latitudeandand
 and longitude
 longitude
 longitude ofofof Kibran
 Kibran
 Kibran Gabriel
 Gabriel
 Gabriel island
 island
 island to
 to HOMER
 to HOMER HOMER Pro
 Pro soft-
 soft-
 Pro software,
 ware,
 GHI
 ware, GHI
 and
 GHI and
 wind wind
 andspeed speed
 wind data
 speed data
 ofdata
 NASAof NASA can
 can be can
 of NASA be
 found found via
 via Internet
 be found Internet connection.
 connection.
 via Internet According
 connection. According
 to the
 According
 to
 tothe
 data data
 dataobtained,
 obtained,
 the daily
 dailyaverage
 daily average
 obtained, GHI isGHI
 average 5.94 is
 GHI is5.94
 5.94kWh/m
 kWh/m 2 /day.22/day.
 kWh/m As As
 Asdepicted
 depicted
 /day. in
 inFigure
 in Figure
 depicted 3, the 3,
 Figure 3,the
 daily
 the
 daily
 averageaverage
 GHI GHI
 for for
 each each
 month month
 varies varies
 from from
 the the
 minimumminimum5.05 5.05
 daily average GHI for each month varies from the minimum 5.05 kWh/m /day in Julyto
 kWh/m kWh/m 2
 2 /day2/day
 in in
 JulyJuly
 to theto
 the
 themaximum
 maximum
 maximum 6.686.68
 kWh/m
 6.68 kWh/m
 kWh/m
 2/day in April. The sky is relatively clearer in winter (November
 2 /day in April.
 2/day TheThe
 in April. skysky
 is relatively clearer
 is relatively in winter
 clearer in winter(November
 (November to
 to
 toMay)
 May) than
 than
 May) summer
 summer
 than summer (June
 (June to to
 (June toOctober).
 October).
 October).

 GHI
 GHI
 Clearness index
 Clearness index

 Month
 Month

 Figure
 Figure3.
 3.Average
 Averageglobal horizontal
 globalhorizontal irradiation
 horizontalirradiation data.
 irradiationdata.
 data.
 Figure 3. Average global

 Similarly,
 Similarly,the
 Similarly, theannual
 the annualaverage
 averagewind
 average windspeed
 wind speeddata
 speed of
 data
 data the
 ofof site
 the
 the taken
 site
 site from
 taken
 taken NASA.
 from
 from NASA.
 NASA. The an-
 TheThe
 an-
 nual average
 annual average
 nual average windwind
 wind speed
 speed is
 speed 3.78
 is is m/s
 3.78
 3.78 at
 m/s
 m/s 50
 at at m
 5050
 mm above the
 above
 above surface
 thethe surface
 surface of the
 ofof
 the earth.
 the As
 earth.
 earth. shown
 AsAs shown
 shown in
 in
 Figure
 in 4,
 Figure
 Figure the
 4, 4,the relative
 therelative minimum
 relativeminimum
 minimumand and the
 andthe maximum
 the maximum monthly
 maximum monthly average
 monthly average wind
 average wind speeds
 wind speeds are
 speeds are
 are
 measured
 measuredin
 measured ininOctober
 October(2.89
 October (2.89 m/s)
 m/s)and
 (2.89m/s) andJune
 and June(4.7
 June (4.7m/s),
 (4.7 m/s),respectively.
 m/s), respectively.
 respectively.

Appl. Sci. 2021, 11, 7085
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 Appl. Sci. 2021, 11, 7085 6 of 22

 Month
 Month
 Figure 4. Average wind speed data.
 Figure4.4.Average
 Figure Averagewind
 windspeed
 speeddata.
 data.
 3.3.
 3.3. Load Profile
 3.3.Load
 LoadProfile
 Profile
 The
 The estimated
 estimatedload loadforforKibran
 KibranGabrielGabrielisland
 island is isdepicted
 depicted in Figure
 in Figure 5 below.
 5 below. In this
 In thispa-
 per, The estimated
 considering the load for Kibranconditions
 environmental Gabriel island of the isisland
 depicted and in
 the Figure
 community5 below. In this
 living there,pa-
 paper, considering the environmental conditions of the island and the community living
 per,
 loads considering the environmental conditions of the island and the community living there,
 there, are
 loads categorized
 are categorizedas summer
 as summer(June to October)
 (June to October) load, winter
 load, winter(November
 (Novemberto May) load,
 to May)
 loads
 and are categorized as summer (June to October) load, winter (November to which
 May) load,
 load, and weekend load. According to the estimation, a total of 16.00 kWp power,6.00
 weekend load. According to the estimation, a total of 16.00 kWp power, of of
 and weekend load. According86.24 to thekWh/day
 estimation, awinter
 total of 16.00 kWpkWh/day
 power, of which 6.00
 whichwere
 kWp 6.00 deferrable
 kWp were power, deferrable power, 86.24of kWh/day load, 77.84
 of winter load, 77.84ofkWh/daysummer
 kWp and
 load, were62.22 deferrable power, 86.24 kWh/day of winter load, for 77.84thekWh/day of summer
 of summer load,kWh/day
 and 62.22ofkWh/day
 weekend loads
 of were
 weekend considered
 loads were considered analysis.
 for theHowever,
 analysis.
 load,
 the and annual
 scaled 62.22 kWh/day
 average of weekend loadsthewere considered for kWh/day.
 the analysis. In However,
 However, the scaled annualload takenload
 average for taken analysis
 for thewas 76.94
 analysis was 76.94 kWh/day. addition, In
 the scaled on
 depending annual average and
 the demand loadits taken
 time for the analysis
 of time
 use, theuse, load wascategorized
 76.94 kWh/day. In addition,
 addition, depending on the demand and its of theisload is categorizedinto primary
 into primary and
 dependingload.
 deferrable on the Thedemand
 primary and
 loadsits time
 areare of use,
 loads thatthe load is categorized
 require into primary and
 and deferrable load. The primary loads loads that requirea acertain
 certainamount
 amount of of operating
 operating
 deferrable load. The
 reserves to respond immediately primary
 immediately to loads are
 to the loads
 the sudden that
 sudden increase require
 increasein inthe a certain
 theelectric amount
 electricloadloadand/or of operating
 and/or due to
 areserves
 decreasetoinrespond power immediately
 output [32], whereasto the sudden increase
 deferrable loads in permit
 the electricsome load and/or when
 flexibility due to
 a decrease
 power in power That
 is insufficient. output [32], whereas
 is, deferrable loaddeferrable
 is the second loads permitafter
 priority some theflexibility
 primary load;when
 power is insufficient. That is, deferrable
 however, its importance comes ahead of charging batteries. In load is the second priority
 In this after the primary
 this study, lighting loads, load;
 however, its importance comes ahead of charging batteries.
 fans, sound amplifiers, refrigerators, sewing machines, flourmills, and water pumps were In this study, lighting loads,
 fans,
 the sound
 major loadsamplifiers,
 estimated refrigerators,
 for the analysis. sewing machines,
 However, theflourmills,
 flourmill and and water
 sewing
 sewing pumps
 machineswere
 the major loads estimated for the analysis. However,
 were excluded from the weekend loads considering the community religious practices in the flourmill and sewing machines
 were
 the excluded
 island. from since
 Similarly, the weekend
 the summer loadsseason
 considering
 is rainy theandcommunity
 relativelyreligious
 cold, water practices
 pumps
 pumps in
 the island. Similarly, since the summer season is rainy
 and fans were excluded from the summer load. In addition, water pumps are considered and relatively cold, water pumps
 asand fans were
 deferrable loadexcluded
 duringfrom the summer
 the winter season.load.The In addition,
 estimated loadwater pumps distribution
 frequency are considered is
 shown in Figure 6. According to the scaled frequency distribution, 75% of thedistribution
 as deferrable load during the winter season. The estimated load frequency distributionis
 isshown
 2 kW–5 in kW,
 Figure
 kW, and
 and 6.the
 According
 the remaining
 remaining to the
 25%
 25% scaled
 is frequency
 is 66 kW–22
 kW–22 kW.distribution, 75% of the distribution
 kW.
 is 2 kW–5 kW, and the remaining 25% is 6 kW–22 kW.

 (a) (b)
 (a) (b)
 Figure 5. Scaled load profile for each month: (a) daily load profile, (b) monthly average.
 Figure 5. Scaled load profile for each month: (a) daily load profile, (b) monthly average.

Appl. Sci. 2021, 11, 7085 7 of 22
Appl. Sci. 2021, 11, 7085 7 of 22

 Figure 6. Frequency of the scaled load profile.
 profile.

 3.4. Diesel Price
 3.4. Diesel Price
 Even
 Even though
 thoughthe thediesel
 dieselfuel price
 fuel market
 price in Ethiopia
 market is relatively
 in Ethiopia fluctuating
 is relatively from from
 fluctuating time
 to time, the government subsidizes it to minimize the cost. In this study considering
 time to time, the government subsidizes it to minimize the cost. In this study considering the
 local market, a diesel fuel price of USD 0.62/L is taken for the analysis [33].
 the local market, a diesel fuel price of USD 0.62/L is taken for the analysis [33].
 3.5. Economic Assignment Criteria
 3.5. Economic Assignment Criteria
 In this study real interest rate, capital recovery factor (CRF), net present cost (NPC),
 In this study real interest rate, capital recovery factor (CRF), net present cost (NPC),
 cost of energy (COE), and break-even grid extension distance were considered as the
 cost of energy (COE), and break-even grid extension distance were considered as the eco-
 economic evaluation criteria [32,34].
 nomic evaluation criteria [32,34].
 3.5.1. Annual Real Interest Rate
 3.5.1. Annual Real Interest Rate
 As stated in Equation (1) HOMER Pro uses the annual real interest rate to determine
 As stated
 discount factorin Equation
 and (1) HOMER
 annualized Propresent
 costs from uses thecosts.
 annual real interest rate to determine
 discount factor and annualized costs from present costs.
 i0 − f
 i = − (1)
 =1 + f (1)
 1+ 
 where i is 0
 is annual
 annual real
 real interest rate, ii’ is
 interest rate, is nominal
 nominal interest
 interest rate, and ff is
 rate, and is expected
 expected inflation
 inflation
 rate (%).
 rate (%).

 3.5.2. Capital Recovery
 3.5.2. Capital Recovery Factor
 Factor (CRF)
 (CRF)
 The
 The CRF is the ratio that is used
 CRF is the ratio that is used to
 to compute
 compute the
 the present
 present value
 value of
 of the
 the annuity
 annuity in
 in the
 the
 project lifetime.
 project lifetime.
 i (1 + i ) t
 CRF (i, t) = (1 t+ ) (2)
 ( , ) =(1 + i ) − 1 (2)
 (1 + ) − 1
 where i is the annual real interest rate (%), and t is the number of years.
 where i is the annual real interest rate (%), and t is the number of years.
 3.5.3. Net Present Cost
 3.5.3.According
 Net PresenttoCost
 HOMER Pro, total NPC value signifies the project life cycle cost, and
 According
 is computed to HOMER
 using Equation Pro,
 (3).total
 TheNPCcostvalue signifies
 includes the project
 the initial capitallifecost
 cycle cost,
 and theand is
 cash
 computed
 flow of theusing
 t-yearEquation
 over the (3). The(capital
 factor cost includes thecost,
 cost, fuel initial capital cost
 operation cost,and the cash flow
 maintenance of
 cost,
 replacement
 the t-year over cost,
 theetc.).
 factorIncome
 (capitalcontains electricity
 cost, fuel selling cost,
 cost, operation and salvage valuecost,
 maintenance afterreplace-
 project
 life
 ment cycle.
 cost, etc.). Income containselectricity selling and salvage value after  project life cycle.
 CF1 CFN
 NPC = CF0 + CF2
 + + CF3 3 +...+
 (1+ i )1(1+ i )2 (1+ i ) (1+ i ) N
 N (3)
 CF1
 = CF0 + ∑ t
 t =1 (1+ i )

Appl. Sci. 2021, 11, 7085 8 of 22

 CF0 is initial capital cost (USD); CFt is cash flow of t-year (USD); t is number of year
 (yr); i is annual real interest rate (%); N is project lifetime (yr).

 3.5.4. Cost of Energy
 HOMER Pro defines COE as the average cost per kWh of useful electrical energy
 generated by the system [15]. It is calculated by dividing total annualized cost (TAC) by
 total annualized useful electrical energy generated as shown in Equation (4).

 TAC
 COE = (4)
 Eserved

 TAC = NPC ∗ CRF (i, N ) (5)
 Eserved = E pri + Ede f + Egrid,sales (6)
 TAC is the annualized value of NPC in USD/yr, Eserved is total electrical load served
 (primary load, deferrable load, energy sales to the grid) in kWh/yr, CRF is capital recovery
 factor, i is the real interest rate (%) and N is the project lifetime (yr).

 3.5.5. Grid-Extension Cost
 In this research, the grid extension cost is determined through the computation of
 breakeven grid extension distance (BGED). The BGED is the distance away from the
 grid at which the NPC of expanding the grid equals the NPC of a minigrid (stand-alone)
 system. When the grid extension distance exceeds the BGED, the minigrid system is more
 cost-effective [19,32]. The BGED is computed using Equation (7).

 NPC × CRF (i, N ) − c power × Edemand
 BGED = (7)
 ccap × CRF (i, N ) + com

 where total NPC of the minigrid system is in USD, CRF is capital recovery factor, i real
 discount rate in %, N is project lifetime in years, Edemand is total annual electrical demand
 including primary and deferrable in kWh/yr, cpower is cost of power from gird in USD/kWh,
 ccap is capital cost of grid extension in USD/km, com is O&M cost of grid extension in
 USD/yr/km.

 3.6. Electrical Assignment Criteria
 The descriptions below are some of the electrical assignment criteria references ac-
 cording to HOMER Pro [34].

 3.6.1. Renewable Fraction
 Renewable fraction (RF) is the fraction of the energy delivered to the load that is
 originated from renewable power sources. The percentage RF is expressed as shown in
 Equation (8).  
 Enon−ren + Hnon−ren
 RF = 1 − × 100% (8)
 Eserved + Hserved
 Enon−ren is nonrenewable electrical generation (kWh/yr); Hnon−ren is nonrenewable
 thermal generation (kWh/yr); Eserved is total electrical load served (kWh/yr); Hserved is total
 thermal load served (kWh/yr).

 3.6.2. Excess Electricity Fraction
 Excess electricity fraction (fexcess ) is the ratio of total excess electricity to total electrical
 production as shown in Equation (9).
 !
 Eexcess
 f excess = × 100% (9)
 E prod

3.6.2. Excess Electricity Fraction
 Excess electricity fraction (fexcess) is the ratio of total excess electricity to total electrical
 production as shown in Equation (9).
 
Appl. Sci. 2021, 11, 7085 = × 100% (9)
 9 of 22
 
 where Eexcess is total excess electricity (kWh/yr), Eprod is total electrical production (kWh/yr).

 where
 3.6.3. EexcessShortage
 Capacity is total excess electricity (kWh/yr), Eprod is total electrical production (kWh/yr).
 Fraction
 Capacity
 3.6.3. shortage
 Capacity fraction
 Shortage (fcs) is the ratio of total capacity shortage and total electrical
 Fraction
 demand as described in Equation (10). HOMER Pro considers a system viable only if the
 Capacity shortage fraction (f ) is the ratio of total capacity shortage and total electri-
 capacity shortage fraction is less thancs or equal to the maximum annual capacity shortage
 cal demand as described in Equation (10). HOMER Pro considers a system viable only
 [35].
 if the capacity shortage fraction is less than or equal to the maximum annual capacity
 shortage [35]. 
 =  ×
  100% (10)
 Ecs
 f cs = × 100% (10)
 where Ecs is total excess electricity (kWh/yr), Edemand
 Edemand is total electrical production (kWh/yr).
 where Ecs is total excess electricity (kWh/yr), Edemand is total electrical production (kWh/yr).
 3.7. Sensitivity Variables
 3.7. Sensitivity Variables
 In the rural areas, there is a low load demand which varies on a time basis [4]. On the
 In the
 other hand, ruralradiation
 solar areas, there
 andiswind
 a lowspeed
 load demand which varies
 vary depending on theon daily
 a timeenvironmental
 basis [4]. On the
 other hand, solar radiation and wind speed vary depending on the daily environmental
 conditions. Sensitivity analysis monitors the effect of certain variables. That is, different val-
 uesconditions.
 are assignedSensitivity analysiswithin
 to these variables monitors the range
 a given effect in
 of order
 certaintovariables.
 assess theirThat is, different
 influence on
 values are assigned to these variables within a given range in order to assess
 the optimal minigrid system [19]. In this study, considering the optimal minigrid system, their influence
 theon the optimal
 sensitivity minigrid
 variables withsystem [19]. In this
 the variations study,
 of GHI considering
 from thekWh/m
 5.05 to 6.69 optimal minigrid
 2/day, fuel system,
 price
 2 /day, fuel
 the sensitivity variables with the variations of GHI from 5.05 to 6.69
 from USD 0.62 to 1/L, and load consumptions from 76.94 to 107.72 kWh/day are consideredkWh/m
 for price from USD 0.62 to 1/L, and load consumptions from 76.94 to 107.72 kWh/day are
 the analysis.
 considered for the analysis.
 4. MiniGrid Hybrid Power System Description
 4. MiniGrid Hybrid Power System Description
 4.1.4.1.
 MiniGrid System
 MiniGrid Schematic
 System Diagram
 Schematic Diagram
 TheThe
 schematic diagram of the
 schematic diagram of the minigrid
 minigridpower
 powersystem
 systemis depicted in Figure
 is depicted in Figure7. The
 7. The
 minigrid
 minigridsystem consists
 system of of
 consists wind
 windpower
 powergenerator (WG),
 generator (WG), PVPVsystem
 system(PVs),
 (PVs),diesel
 dieselgenera-
 generator
 tor (DG),
 (DG),power
 powerconvertor
 convertor(PC),
 (PC),storage
 storagesystem,
 system,primary
 primaryandanddeferrable
 deferrableloads.
 loads.PVsPVsand
 andWG
 WGare areoperated
 operatedininparallel
 parallel
 with DG, and AC coupled. PVs and WG supply power to thethe
 with DG, and AC coupled. PVs and WG supply power to load
 load to reduce the output
 to reduce the output of DG of DGin in order
 order to to reduce
 reduce fuel
 fuel intake
 intake [35].
 [35]. Whereas
 Whereas thethe grid
 grid sys- is
 system
 temconnected
 is connected
 onlyonly for BGED
 for BGED analysis.
 analysis.

 AC Bus DC Bus
 Diesel Generator
 Primary Load

 PV System Deferrable Load Storage

 Grid

 Power convertor

 WG system

 Figure
 Figure 7. Schematic
 7. Schematic diagram
 diagram of minigrid
 of minigrid hybrid
 hybrid renewable
 renewable energy
 energy system.
 system.

 4.2. PV System
 The PV module used for this study is CS6K-295MS mono-crystalline silicon solar
 cell module, which has the parameters shown in Table 1. The PV module is expected to

Appl. Sci. 2021, 11, 7085 10 of 22

Appl. Sci. 2021, 11, 7085 10 of 22
 4.2. PV System
 The PV module used for this study is CS6K-295MS mono-crystalline silicon solar cell
 module, which has the parameters shown in Table 1. The PV module is expected to serve
 serve
 for 25for 25 and
 years years and
 the the power
 power outputoutput of the module
 of the module (Ppv ) is calculated
 (Ppv) is calculated accordingaccording to
 to Equation
 Equation (11)
 (11) [36,37]. [36,37].

 GT 
 Ppv 
 = P= , f pv 
 pv,STC 1+
 [1 + K P ( T( 
 C −−T )
 STC )] (11)
 (11)
 ,
 GT,STC

 where pv,STC isisPV
 where PPpv,STC PVrated
 ratedpower
 powerpower power (kWp),
 (kWp),fpv fis
 pv PV derating
 is PV factor
 derating (%),(%),
 factor GT isGsolar irra-
 T is solar
 diance on the surface of the PV module (kW/m 2),2 GT,STC is standard solar irradiance (1
 irradiance on the surface of the PV module (kW/m ), GT,STC is standard solar irradiance
 kW/m
 (1 kW/m2), K P is
 2 ), KPtheis PV
 the module
 PV module temperature coefficient
 temperature of power
 coefficient (−0.40%/°C),
 of power (−0.40%/TC ◦isC),
 temper-
 TC is
 ature of the PV module (°C), T◦ is temperature of the PV module
 temperature of the PV module ( C), TSTC is temperature of the PV module under standard
 STC under standard test
 conditions
 test conditions(STCs) (25 (25
 (STCs) ◦
 °C). In
 C).this study
 In this a derating
 study a derating factor of 85%
 factor waswas
 of 85% considered.
 considered.

 Table1.1.Electrical
 Table Electricalparameters
 parametersof
 ofthe
 thePV
 PVmodule
 module[38].
 [38].

 Electrical Parameters
 Electrical Parameters
 Rated power at STCs 295 Wp
 Rated power at STCs 295 Wp
 Open circuit voltage,
 Open circuit voltage, Voc V oc 39.5 V 39.5 V
 MaximumMaximum
 power pointpower point
 voltage, voltage, Vmp
 Vmp 32.3 V 32.3 V
 Short circuit
 Short circuitIsccurrent, Isc
 current, 9.75 A 9.75 A
 Maximum power point current, Imp 9.14
 Maximum power point current, Imp 9.14
 Temperature coefficient of maximum power −0.39%/◦ C
 Temperature coefficient of maximum
 Temperature coefficient of open circuit voltage power ◦
 −0.29%/ C−0.39%/°C
 Temperature
 Temperature coefficient
 coefficient of open
 of short circuit circuit voltage
 current 0.05%/◦ C−0.29%/°C
 Module efficiency
 Temperature coefficient of short circuit current 18.02% 0.05%/°C
 Module efficiency 18.02%
 4.3. Wind Generator System
 4.3. Wind Generator
 A Bergey System
 (XL10)) wind turbine of 10 kWp AC power output at 12 m/s, a minimum
 operating wind(XL10))
 A Bergey speed of 2.5 m/s,
 wind andof20
 turbine 10years
 kWpof AC lifetime
 powerwas considered
 output forathis
 at 12 m/s, analy-
 minimum
 sis [39]. The power curve of the wind turbine, and the wind speed at the hub (U hab ) are
 operating wind speed of 2.5 m/s, and 20 years of lifetime was considered for this analysis
 shown in power
 [39]. The Figure curve
 8, andof
 Equation
 the wind(12), respectively.
 turbine, and the wind speed at the hub (Uhab) are shown
 in Figure 8, and Equation (12), respectively. !α
 Hhub
 Uhub = Ure f × (12)
 = × Hre f (12)
 
 where UUref
 where is reference wind speed (m/s), given by NASA measurements at a reference
 ref is reference wind speed (m/s), given by NASA measurements at a reference
 height
 height of 50m
 of 50 mfrom
 fromthe
 thesurface
 surface(H(Hrefref).).HHhub is the hub height (30 m in this case) where the
 hub is the hub height (30 m in this case) where the
 wind
 wind speed at the hub is calculated. α is surface roughness—the
 speed at the hub is calculated. α is surface roughness—thevalue
 valueis
 is set
 set to
 to 0.14
 0.14 [40,41].
 [40,41].

 Figure8.
 Figure 8. Power
 Power curve
 curve of
 of the
 the wind
 wind turbine.
 turbine.

 4.4. Diesel Generator
 Due to the fact that the PV and wind modules have intermittent natures, the diesel
 generator will ensure the off-grid hybrid power system’s stability and reliability. In addi-

Appl. Sci. 2021, 11, 7085 11 of 22

 tion, in this study the diesel generator is considered as the base case reference for relative
 comparison using LCOE and NPC. In HOMER Pro, we input the load profile and select
 “Autosize Genset” for the DG specification, and set the maximum annual capacity shortage
 fraction of the system operational constraint to 0%. The generic 10 kW diesel generator
 with efficiency of 30%, and fuel curve slope of 0.286 L/h/kW were considered for the initial
 case from HOMER Pro catalogue. Then, the software automatically adjusted to the proper
 capacity and fulfilled the system’s operational constraints.

 4.5. Power Convertor and Storage System
 A bi-directional DC-AC converter was employed for power conversion. When surplus
 power is generated by PV, diesel, and/or WG, the excess AC power is converted to DC
 and stored in a battery, to supply it back when necessary. A conversion efficiency of 95%
 and 15 years of lifetime are assumed in the simulation [33]. In this study, a Li-ion battery
 with a round–trip efficiency of 90%, an initial state of charge of 100%, a minimum SOC of
 20%, and 10 years of lifetime with negligible O&M cost is considered [42].

 4.6. Grid System
 Kibran Gabriel island is located about 11 km from Bahir Dar city; however, extending
 the grid from the city to Kibran has not yet been realized due to Lake Tana. In this study,
 we consider the grid system to compute BGED using Equation (7) so as to compare the
 proposed off-grid systems cost with the grid extension cost.

 4.7. Dispatch Strategy
 Excess energy from renewables is always expected to charge the battery, and one of
 the most important decisions that the dispatch system must make is when to charge the
 batteries with energy from the generator. In this research, we look at a Combined Dispatch
 (CD) approach that combines Load Following (LF) and Cycle Charging (CC) dispatch
 strategies [43]. In the CC strategy, whenever the generator needs to be on to meet the net
 load (load minus intermittent renewable power), it operates at full capacity and the surplus
 power charges the battery bank. In LF strategy, the generator is dispatched just to fulfill the
 net load and any operational reserve needs. The CD strategy determines whether to charge
 the battery with the generator based on the current net load, employing the CC strategy
 when the net load is low and the LF strategy when the net load is high [20,32].

 5. Component Cost and Financial Assumption
 5.1. MiniGrid Component Cost
 Taking into account the local market and the reduction in system component costs
 from time to time, the summary of component costs depicted in Table 2 were considered for
 the simulation analysis. As shown in the table, the cost includes capital cost, replacement
 cost, and operation and maintenance (O&M) cost. The capital cost of the PV (USD 900/kW)
 includes the PV inverter cost, and the capital cost of the WG (USD 3500/kW) includes wind
 turbine, 30 m tower and wind invertor costs. The estimate costs of all the components also
 include transportation and installation costs.

 Table 2. Component cost.

 Components Capital Cost Replacement Cost O&M Cost
 PV system [44] USD 900/kW - USD 900/kW/yr
 WG system [33] USD 3500/kW USD 3000/kW USD 20/kW/yr
 Storage system [42] USD 630/kWh USD 600/kWh 0
 Power converter [33] USD 650/kW USD 600/kW USD 6/kW/yr
 Diesel generator [45] USD 500/kW USD 400/kW USD 0.02/h

Table 2. Component cost.

 Components Capital Cost Replacement Cost O&M Cost
 PV system [44] USD 900/kW - USD 900/kW/yr
 WG system [33] USD 3500/kW USD 3000/kW USD 20/kW/yr
Appl. Sci. 2021, 11, 7085 Storage system [42] USD 630/kWh USD 600/kWh 0 12 of 22
 Power converter [33] USD 650/kW USD 600/kW USD 6/kW/yr
 Diesel generator [45] USD 500/kW USD 400/kW USD 0.02/h
 5.2. Grid Extension Component Cost
 5.2. Grid Extension Component Cost
 In this study, in order to verify the feasibility of minigrid power supply to Kibran
 In this
 Gabriel study,
 island, BGED in order to verify theusing
 was determined feasibility of minigrid
 Equation (7). Forpower
 the BGED supply to Kibran
 analysis, the
 Gabriel
 minimum island,
 gridBGED was capital
 extension determined
 cost ofusing
 USDEquation
 23,000/km(7). and
 For the
 O&M BGEDcostanalysis, the min-
 of USD 200/km
 imumconsidered
 were grid extension capital
 [46]. With thecost of USD 23,000/km
 government subsidies, and O&M
 a grid cost
 power of USD
 price of USD200/km were
 0.06/kWh
 considered
 is taken for [46]. With the
 the analysis government
 according subsidies,
 to Ethiopian a gridUtility
 Electric powerrevised
 price oftariff
 USD[47].
 0.06/kWh is
 taken for the analysis according to Ethiopian Electric Utility revised tariff [47].
 5.3. Interest Rate and Inflation Rate
 5.3. Interest Rate and
 As depicted in Inflation
 Figure 9a,bRatethe nominal interest rate and inflation rate, respectively,
 announced
 As depictedby National
 in Figure Bank
 9a,bofthe
 Ethiopia
 nominal[48]interest
 for therate
 pastandseven years (2013–2019)
 inflation were
 rate, respectively,
 considered for the simulation analysis. The minimum nominal interest
 announced by National Bank of Ethiopia [48] for the past seven years (2013–2019) were con- rate of 11.88%,
 the maximum
 sidered for the nominal
 simulation interest rateThe
 analysis. of 13.5%,
 minimumandnominal
 the average of the
 interest nominal
 rate interest
 of 11.88%, rate
 the max-
 for the considered period was 12.59%. Similarly, the minimum, maximum,
 imum nominal interest rate of 13.5%, and the average of the nominal interest rate for the and average
 inflation rate
 considered for the
 period wasconsidered period were
 12.59%. Similarly, the 7.4%, 14.6%maximum,
 minimum, and 10.51%,and respectively. In this
 average inflation
 paper,
 rate forthe
 theproject lifetime
 considered of 25were
 period years, the14.6%
 7.4%, average values
 and 10.51%,of nominal interest
 respectively. ratepaper,
 In this (12.59%)
 the
 and the inflation rate (10.51%) were used to calculate the annual real interest
 project lifetime of 25 years, the average values of nominal interest rate (12.59%) and the in- rate using
 Equation
 flation rate(1).
 (10.51%) were used to calculate the annual real interest rate using Equation (1).

 NOMINAL INTEREST RATE INFLATION RATE
 14
 15
 INTEREST RATE (%)

 13.5 14
 INFLATION (%)

 13 13
 12
 12.5
 11
 12 10
 11.5 9
 8
 11
 7
 2013 2014 2015 2016 2017 2018 2019
 2013 2014 2015 2016 2017 2018 2019
 YEAR YEAR

 (a) (b)
 Figure 9.
 Figure 9. (a)
 (a) Nominal
 Nominal interest
 interest rate,
 rate, (b)
 (b) Inflation
 Inflation rate.
 rate.

 6.
 6. Simulation
 Simulation Results
 Results and
 and Discussion
 Discussion
 The proposed minigrid
 The proposed minigrid system
 system depicted
 depicted in Figure 77 is
 in Figure is optimized
 optimized using
 using HOMER
 HOMER ProPro
 based on LCOE and NPC. Once the optimal minigrid system was determined,
 based on LCOE and NPC. Once the optimal minigrid system was determined, various various sen-
 sitivity variables
 sensitivity were
 variables considered
 were to check
 considered thethe
 to check effect on on
 effect thethe
 optimal
 optimalsystem. According
 system. Accordingto
 the simulation result, the possible configurations for the selected site are discussed as
 to the simulation result, the possible configurations for the selected site are discussed as fol-
 lows:
 follows:

 6.1. Optimization Results
 6.1.1. Stand-Alone
 6.1.1. Stand-Alone Diesel
 Diesel System
 System
 As depicted
 As in Table
 depicted in Table 3,
 3, when
 when only
 only diesel
 diesel power
 power generation
 generation is
 is considered
 considered the
 the LCOE
 LCOE
 of USD 0.346/kWh, NPC of USD 235,734 and 38.3 t/yr of pollutant emission gases were
 of USD 0.346/kWh, NPC of USD 235,734 and 38.3 t/yr of pollutant emission gases were
 the optimization
 the optimization results.
 results.However,
 However,since
 sincethe
 the simulation
 simulation result
 result of of only
 only diesel
 diesel system
 system is
 is the
 the reference for other configurations, to make it cost effective excesses energy of not
 more than 3% and a maximum capacity shortage of 0.09% were considered. Once the
 optimization result of the stand-alone diesel system was determined, its feasibility relative
 to the grid extension cost was determined using BGED analysis. According to BGED
 analysis, a stand-alone diesel system is relatively feasible for the selected site compared to
 grid extension cost when the electrification distance is farther than 3.11 km, as shown in
 Figure 10a. However, due to the high level of polluting gases emitted, the high operating

Appl. Sci. 2021, 11, 7085 13 of 22

Appl. Sci. 2021, 11, 7085 13 of 22
 fuel cost, and the tourist-attracting nature of the island, the stand-alone diesel system is
 not the favored solution to electrify the specified island.
 reference for
 Table 3. other configurations,
 Possible to make
 configurations for it cost
 the selected effective excesses energy of not more
 site.
 than 3% and a maximum capacity shortage of 0.09% were considered. Once the optimiza-
 tion result of the stand-alone diesel
 LCOE system was determined, its feasibility
 Emission Unmet relative to the
 Minigrid System NPC (USD) RF (%) BGED (km)
 (USD/kWh)
 grid extension cost was determined (kg/yr)
 using BGED analysis. According Load (%)
 to BGED analysis, a
 PV/diesel/battery stand-alone
 0.175 diesel119,139
 system is relatively
 5159 feasible for the86.4 selected site compared
 0 to1.25
 grid ex-
 PV/battery tension
 0.258 cost when175,506
 the electrification0 distance is farther
 100 than 3.11 km, 0.09as shown in Figure
 2.15
 PV/wind/diesel/battery 10a.0.304
 However, due 207,388 18,324
 to the high level 55.3 emitted, the0 high operating
 of polluting gases 2.66 fuel
 PV/wind/battery 0.323 219,736 0
 cost, and the tourist-attracting nature of the island,100the stand-alone 0.09 2.86
 diesel system is not
 Stand-alone diesel 0.346 235,734 38,261 0 0.02 3.11
 the favored solution to electrify the specified island.

 Grid extension Grid extension
 Stand-alone diesel PV/Diesel/Battery

 (a) (b)
 Figure10.
 Figure 10.BGED
 BGEDrelative
 relativeto
 to(a)
 (a)Stand-alone
 Stand-alonediesel
 dieselsystem,
 system,(b)
 (b)PV/Diesel/Battery
 PV/Diesel/Battery system.
 system.

 Table PV/Wind/Battery
 6.1.2. 3. Possible configurations
 Systemfor the selected site.

 The PV/wind/batteryLCOE NPC
 system is the other alternative to electrify the specified
 Unmet BGEDsite.
 Minigrid System Emission (kg/yr) RF (%)
 (USD/kWh)
 According to the simulation analysis this (USDsystem
 ) Load (%)
 was optimized to the LCOE of USD (km)
 0.323/kWh and NPC of USD
 PV/diesel/battery 219,736. The
 0.175 PV/wind/battery
 119,139 5159 system
 86.4 is free0of pollutant
 1.25
 gas emissions,
 PV/batteryand economically
 0.258 feasible compared with
 175,506 0 the stand-alone
 100 diesel system.
 0.09 2.15
 PV/wind/diesel/battery
 However, the PV/wind/battery0.304 system207,388 18,324 high55.3
 demands a relatively 0
 initial investment 2.66
 cost
 (USDPV/wind/battery
 129,986) due to its high0.323 219,736
 component cost compared0 with the100 0.09 2.86
 other configurations
 Stand-alone
 considered diesel
 in this study. 0.346 235,734 38,261 0 0.02 3.11

 6.1.3. PV/Wind/Diesel/Battery
 6.1.2. PV/Wind/Battery System System
 Of
 Thethe hybrid systemssystem
 PV/wind/battery considered
 is theinother
 this alternative
 study, the PV/wind/diesel/battery system,
 to electrify the specified site. Ac-
 having
 cordingLCOE
 to theofsimulation
 USD 0.304/kWh,
 analysisNPC
 thisofsystem
 USD 207,388, and emissions
 was optimized to the ofLCOE
 18,324ofkg/yr,
 USD
 was composed
 0.323/kWh and of a better
 NPC of USDenergy mixThe
 219,736. thanPV/wind/battery
 the other systems discussed
 system is freeinofSections 6.1.2,
 pollutant gas
 6.1.4 and 6.1.5. Even though the PV/wind/diesel/battery system had a
 emissions, and economically feasible compared with the stand-alone diesel system. How-better in energy
 mix
 ever,than the other configurations
 the PV/wind/battery considered
 system demands in this study,
 a relatively the higher
 high initial magnitudes
 investment of
 cost (USD
 NPC, LCOE and emissions, as shown in Table 3, could lead us to search
 129,986) due to its high component cost compared with the other configurations consid-for another cost
 effective-alternative
 ered in this study. to electrify Kibran Gabriel island.
 6.1.4. PV/Battery System
 6.1.3. PV/Wind/Diesel/Battery System
 The PV/battery system is the second-lowest-cost alternative for electrifying the spec-
 Of the hybrid systems considered in this study, the PV/wind/diesel/battery system,
 ified island. The simulation result indicated that the LCOE of 0.258 USD/kWh, NPC of
 having LCOE of USD 0.304/kWh, NPC of USD 207,388, and emissions of 18,324 kg/yr, was
 USD 175,506 with zero pollutant emission gasses. In this system, in order to deliver the
 composed of a better energy mix than the other systems discussed in Sections 6.1.2, 6.1.4
 desired power to the community with 0% capacity shortage, a PV size of 60 kWp, and a
 and 6.1.5. Even though the PV/wind/diesel/battery system had a better in energy mix than
 the other configurations considered in this study, the higher magnitudes of NPC, LCOE

Appl. Sci. 2021, 11, 7085 14 of 22

Appl. Sci. 2021, 11, 7085 14 of 22

 and emissions, as shown in Table 3, could lead us to search for another cost effective-
 alternative to electrify Kibran Gabriel island.
 battery size of 75 kWh were required. However, due to the intermittent nature of solar
 6.1.4.
 energy,PV/Battery System system must be of a relatively big size to cope up the day and
 the PV/Battery
 nightThe
 loads.
 PV/battery asystem
 Having big size leads
 is the the system to havealternative
 second-lowest-cost high excess forelectricity
 electrifying(66.3%). On
 the spec-
 the other hand, when we calculated a capacity shortage of 5%,
 ified island. The simulation result indicated that the LCOE of 0.258 USD/kWh, NPC of the excess electricity was
 reduced
 USD to 35.6%
 175,506 withand zerothepollutant
 unmet load was 4.5%.
 emission ThisIn
 gasses. assured that in the
 this system, PV/battery
 in order system,
 to deliver the
 when
 desired 0%power
 capacity shortage
 to the communityis considered,
 with 0%the systemshortage,
 capacity size will abePV higher.
 size ofWhen a capacity
 60 kWp, and a
 shortagesize
 battery of greater
 of 75 kWh than were
 zero isrequired.
 considered, the system
 However, dueistoincapable of handling
 the intermittent peak
 nature of loads.
 solar
 Considering these limitations, the authors continued to search for another
 energy, the PV/Battery system must be of a relatively big size to cope up the day and night optimal solution
 to electrify
 loads. Havingthe aisland.
 big size leads the system to have high excess electricity (66.3%). On the
 other hand, when we calculated a capacity shortage of 5%, the excess electricity was re-
 6.1.5. PV/Diesel/Battery System
 duced to 35.6% and the unmet load was 4.5%. This assured that in the PV/battery system,
 whenThe 0%initial
 capacitysimulation
 shortage 2
 conditions considered
 is considered, for this
 the system sizestudy
 will bewere: annual
 higher. When average solar
 a capacity
 radiationof
 shortage ofgreater
 5.94 kWh/mthan zero /day; annual average
 is considered, wind speed
 the system of 3.78ofm/s;
 is incapable nominal
 handling peakinterest
 loads.
 rate of 12.59%; primary load demand of 76.94 kWh/day; and
 Considering these limitations, the authors continued to search for another optimal a project lifetime of 25 years.
 solu-
 Fromtothe
 tion feasible
 electrify thesystem
 island.configurations shown in Table 3, the PV/diesel/battery system
 offers the optimal solution for the proposed system. The detailed is presented in Table 4.
 As depicted
 6.1.5. in Table 4, the
 PV/Diesel/Battery PV/diesel/battery system could deliver the required power
 System
 to the island with LCOE of 0.175 USD/kWh, NPC of USD 119,139 and emissions of 5159
 kg/yr.TheWhen
 initialthese
 simulation conditions
 parameters considered
 compared to thefor this studyoutputs
 simulation were: annual
 of theaverage solar
 stand-alone
 radiation of 5.94 kWh/m 2/day; annual average wind speed of 3.78 m/s; nominal interest
 diesel system, the pollutant emission gasses, NPC, and LCOE were reduced by 86.52%,
 rate
 49.46%of 12.59%; primary
 and 49.42%, load demand
 respectively. of 76.94and
 The BGED, kWh/day;
 a detailed andcosta project
 summarylifetime of 25 years.
 of components,
 From the feasible system configurations
 are shown in Figures 10b and 11, respectively. shown in Table 3, the PV/diesel/battery system
 offers the optimal solution for the proposed system. The detailed is presented in Table 4.
 TableAs depicted in
 4. Simulation Table
 result 4, the PV/diesel/battery
 of optimal system could
 minigrid system, architecture, anddeliver
 cost. the required power to
 the island with LCOE of 0.175 USD/kWh, NPC of USD 119,139 and emissions of 5159
 System PV DG Battery
 kg/yr. When these Converter
 parameters compared LCOE to the simulation
 NPC Operating
 outputs Initial die-
 of the stand-alone
 Architecture (kW) (kW)
 sel system, the pollutant emission gasses, NPC, and LCOE were reduced by (USD)
 (No) (kW) (USD/kWh) (USD) Cost (USD/yr) Capital 86.52%,
 PV/diesel/battery 25 10
 49.46% and 4049.42%, respectively.
 5 0.175
 The BGED, and 119,139
 a detailed cost3196 55,872
 summary of components,
 are shown in Figures 10b and 11, respectively.

 COST SUMMARY

 Capital (USD) Replacement (USD) O&M (USD) Fuel (USD) Salvage (USD) Total (USD)
 140,000
 120,000
 100,000
 Cost (USD)

 80,000
 60,000
 40,000
 20,000
 -
 PV System Diesel System Storage System Converter System
 Components

 Figure 11. Cost summary of PV/diesel/battery system components.
 Figure 11. Cost summary of PV/diesel/battery system components.
 On the other hand, the technical performance of the PV/Diesel/battery system was
 Table 4. Simulation result of optimal minigrid system, architecture, and cost.
 simulated considering the winter and summer environmental conditions with the corre-
 sponding loads. The result shown in FigureLCOE12 displays the detailed time series analysis
 Operating
 PV of theDG
 powerBattery
 outputs ofConverter
 the PV and diesel system, battery charging Initial and
 and discharging,
 System Architecture (USD/kW NPC (USD) Cost
 (kW)total(kW) (No) (kW)
 loads (including primary and deferrable) for the winter’s day of 3 January.(USD)
 Capital In the
 h) (USD/yr)
 winter time, due to high solar radiation (up to 6.68 kWh/m 2 /day) and clearance
 PV/diesel/battery 25 10 40 5 0.175 119,139 3196 55,872 (up
 index
 to 0.69) in the country, specifically at the study site, the PV system generates significant
 amounts of power from 06:00 to 18:00. The deferrable loads (6 kW) include water pumps
 were served from 06:00 to 11:00 when there is excess power. However, during the peak

sponding
 sponding loads.
 loads. The
 The result
 result shown
 shown in in Figure
 Figure 1212 displays
 displays the the detailed
 detailed time
 time series
 series analysis
 analysis
 of
 of the power outputs of the PV and diesel system, battery charging and discharging, and
 the power outputs of the PV and diesel system, battery charging and discharging, and
 total
 total loads
 loads (including
 (including primary
 primary and and deferrable)
 deferrable) forfor the
 the winter’s
 winter’s dayday ofof January
 January 3.3. In
 In the
 the
 winter time,
 winter time, due
 due toto high
 high solar
 solar radiation
 radiation (up (up to
 to 6.68
 6.68 kWh/m
 kWh/m22/day)/day) and
 and clearance
 clearance index
 index (up
 (up
Appl. Sci. 2021, 11, 7085 to 0.69)
 0.69) inin the
 the country,
 country, specifically
 specifically at at the
 the study
 study site,
 site, the
 the PVPV system
 system generates
 generates significant
 significant
 15 of 22
 to
 amounts
 amounts of of power
 power fromfrom 06:00
 06:00 toto 18:00.
 18:00. The
 The deferrable
 deferrable loads
 loads (6 (6 kW)
 kW) include
 include water
 water pumps
 pumps
 were
 were served from 06:00 to 11:00 when there is excess power. However, during the
 served from 06:00 to 11:00 when there is excess power. However, during the peak
 peak
 loading
 loading condition
 condition (10:00
 (10:00 to
 to 12:00)
 12:00) the
 the diesel
 diesel generator
 generator supported
 supported the
 the PV
 PV system
 system to
 to fulfill
 fulfill
 loading condition (10:00 to 12:00) the diesel generator supported the PV system to fulfill
 the power
 the power demand and and the battery
 battery charging power power started to to decline atat 11:00. During
 During the
 the power demand
 demand and the the battery charging
 charging power startedstarted to decline
 decline at 11:00.
 11:00. During the the
 nighttime, from
 nighttime, from 18:00
 18:00 toto 06:00
 06:00 the
 the load
 load demand
 demand receives
 receives power
 power from
 from battery
 battery and/or
 and/or diesel
 diesel
 nighttime, from 18:00 to 06:00 the load demand receives power from battery and/or diesel
 generator.
 generator. As shown in Figure 12, starting from 17:00 to 04:00 the battery discharged to
 generator. As As shown
 shown in in Figure
 Figure 12,12, starting
 starting from
 from 17:00
 17:00 to to 04:00
 04:00 the
 the battery
 battery discharged
 discharged to to
 deliver
 deliver the
 deliver the required
 the required power
 required power
 power to to the
 to the load
 the load demand.
 load demand. However,
 demand. However,
 However, from from 04:00
 from 04:00 to
 04:00 to 06:00,
 06:00, when
 to 06:00, when the
 when the
 the
 battery
 battery was
 battery incapable
 was incapable
 incapable of of fulfilling
 offulfilling
 fulfillingthe the load
 theload demand,
 loaddemand,
 demand, thethe
 the diesel
 diesel
 diesel generator
 generator
 generator started
 started
 started to
 to pro-
 pro-
 to produce
 duce
 duce the
 the required
 required electricity.
 electricity.
 the required electricity.

 Deferrable
 Deferrable Load
 Load
 PV output
 PV output
 Total
 Total Load
 Load
 Battery
 Battery Charging
 Charging
 AC
 AC primary
 primary Load
 Load
 Diesel
 Diesel Power
 Power Output
 Output
 Battery Discharging
 Battery Discharging

 Figure
 Figure 12. Daily time series analysis for winter season.
 Figure 12.
 12. Daily
 Daily time
 time series
 series analysis
 analysis for
 for winter
 winter season.
 season.

 Similarly,
 Similarly, the
 Similarly, thetime
 the timeseries
 time seriesanalysis
 series analysis
 analysis of power
 of of
 power outputs
 outputs
 power of
 of the
 outputs the PV
 PV and
 of the and diesel
 diesel
 PV and system,
 system,
 diesel bat-
 bat-
 system,
 tery
 tery charging
 charging
 battery chargingand discharging,
 andand
 discharging, and
 and
 discharging, andtotal
 total loads
 loads
 total for
 for
 loads the
 forthe summer’s
 thesummer’s day
 summer’sday of July
 dayofofJuly 6 is depicted
 6 isis depicted
 6 July depicted
 as
 as follows
 as follows in
 follows in Figure
 in Figure 13.
 Figure 13.
 13.

 Deferrable
 Deferrable Load
 Load
 PV output
 PV output
 Total Load
 Total Load
 Battery
 Battery Charging
 Charging
 Primary
 Primary Load
 Load
 Diesel
 Diesel Power
 Power Output
 Output
 Battery Discharging
 Battery Discharging

 Figure
 Figure 13.
 Figure 13. Daily
 Daily time
 Daily time series
 time series analysis
 series analysis for
 analysis for summer
 for summer season.
 summer season.

 During the summer season in the study area experiences a relatively high amount of
 rain, with lower solar radiation (5.05 kWh/m2 /day) and lower clearance index (0.48). As
 shown in Figure 13, the total load and the primary load are the same (overlapping) because
 the deferrable loads (water pumps) were neglected since the summer is rainy season in the
 study area. From the time series analysis, we observed that the main power source during
 the daytime (07:00 to 17:00) was the PV system, whereas for the remaining time, from 17:00
 to 03:00 the battery system, and from 03:00 to 07:00 the diesel generator contributed the
 power demanded by the load. As we can observe from Figures 12, 13 and 14a, the PV