Optimal Sizing and Techno-Economic Analysis of Minigrid Hybrid Renewable Energy System for Tourist Destination Islands of Lake Tana, Ethiopia - MDPI
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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; email@example.com (T.M.B.); firstname.lastname@example.org (C.-H.W.) * Correspondence: email@example.com; 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 . 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 . 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 . Similar studies showed that a number of people without access to electricity reside in rural areas of sub-Saharan Africa and South Asia . 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 . 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 . 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 . 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 . 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 . 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 . 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.  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.  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.  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 . Bahramara et al.  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.  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 . However, the study mainly considers batteries and diesel generators to increase system reliability. Oladigbolu et al.  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.  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 . The study optimized the total annualized cost at the maximum fuel saving. Gebrehiwot et al.  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 . 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 . 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 . 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 . 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. Appl. Sci.2021, 2021,11, 11,7085 7085 44 of 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 .analysis Figure 1. 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  with latitude 11.6516◦ and longitude 37.3644◦ . Lake Tana is one of the city, Ethiopia  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 . It is UNESCO world biosphere reserve sites in Ethiopia, registered on 19 June 2015 . 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 Appl. 66 of of 22 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 , 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 , 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 . the local market, a diesel fuel price of USD 0.62/L is taken for the analysis . 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 . 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 . 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 . if the capacity shortage fraction is less than or equal to the maximum annual capacity shortage . = × 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 . 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 . 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 . In this study, considering the optimal minigrid system, their influence theon the optimal sensitivity minigrid variables withsystem . 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 18.104.22.168. 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 . . 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. . 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 . 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 . 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 . 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 . 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 . 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  USD 900/kW - USD 900/kW/yr WG system  USD 3500/kW USD 3000/kW USD 20/kW/yr Storage system  USD 630/kWh USD 600/kWh 0 Power converter  USD 650/kW USD 600/kW USD 6/kW/yr Diesel generator  USD 500/kW USD 400/kW USD 0.02/h
Table 2. Component cost. Components Capital Cost Replacement Cost O&M Cost PV system  USD 900/kW - USD 900/kW/yr WG system  USD 3500/kW USD 3000/kW USD 20/kW/yr Appl. Sci. 2021, 11, 7085 Storage system  USD 630/kWh USD 600/kWh 0 12 of 22 Power converter  USD 650/kW USD 600/kW USD 6/kW/yr Diesel generator  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 . 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 . With the the analysis government according subsidies, to Ethiopian a gridUtility Electric powerrevised price oftariff USD. 0.06/kWh is taken for the analysis according to Ethiopian Electric Utility revised tariff . 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 nominalinterest 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  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
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