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. 2025 Dec 21;16:2364. doi: 10.1038/s41598-025-32105-8

Solar photovoltaic feed-in tariffs: viability analysis and policy recommendations

Tefera Mekonnen 1,, Shewit Tsegaye 1, Birhanu Belete 1, Jaisiva Selvaraj 2, Abeba Negewo 3, Emiyamrew Minaye 1, Kifle Godana 1, Abebe Wolie 1
PMCID: PMC12816129  PMID: 41423471

Abstract

Securing financial support from governments and donors is crucial for promoting renewable energy systems like solar photovoltaic (PV). This support can be provided through mechanisms such as subsidies, quotas, tendering, and feed-in tariffs (FITs). In Ethiopia, the lack of a fully approved FIT policy for solar power generation has hindered independent power producers (IPPs) from participating in the energy market. This study examines FIT estimations and viability analysis for two PV power stations and two utility-scale PV parks. To evaluate the performance of the FIT rate estimations, five key performance indicators (KPIs)—net present value (NPV), levelized cost of electricity (LCOE), payback period (PBP), internal rate of return (IRR), and benefit-cost ratio (BCR)—were employed, along with solar radiation and grid-connected PV system costs. The technical and economic analysis of the proposed system was analyzed using PVGIS and MATLAB tool. Results revealed that a PV power station with an $88,300,000 investment can achieve a net present value (NPV) of $1,462,653,170.76, an IRR of 22%, and a FIT rate of $0.023/kWh, recovering its initial investment within 15.6 years. A PV park with a $428,500 investment can achieve a NPV of $149,401.04, an IRR of 12%, and a payback period of 11.3 years, with a BCR of 1.03. Based on these findings, the adoption of dynamic and market-based FIT policies is recommended to promote renewable energy development and attract IPPs to Ethiopia’s energy sector.

Keywords: Renewable energy, Solar PV generation, Feed-in tariff policies, Renewable energy economics

Subject terms: Energy science and technology, Engineering, Environmental social sciences

Introduction

In recent decades, renewable energy has gained prominence over fossil fuels due to its economic, environmental, and social benefits1,2. As a vital source of renewable energy, solar energy keeps thriving, driven by its high potential, declining costs and supportive policies3,4.

Among these policies, FIT have proven highly effective in promoting solar energy deployment. FITs guarantee fixed payments to renewable energy producers for electricity supplied to the grid, typically through power purchase agreements (PPA), ensuring stable returns and reducing financial risks for investors5. By offering long-term contracts and technology-specific rates, FITs have fostered innovation and market growth in solar PV and other renewable energy technologies6,7.

Europe has been a leader in FIT implementation. Germany, Italy, France, and the UK have implemented FITs for PV technology in a highly iterative manner, with policymakers continuously refining the policy design over time8,9. This approach has led to outstanding results in promoting PV technology across Europe. Following the adoption of Europe’s FIT schemes, several countries, including Thailand, China, Bahrain, and Japan, have used these FIT policies in compliance with their governments’ RE deployment policies1012. Some African nations, like Algeria, Kenya, Uganda, Ghana and Tanzania have also adopted FITs to advance their RE projects1315.

Most developing countries have significant opportunities to harness solar power16,17. Ethiopia is one of such countries, endowed with substantial solar energy potential, with irradiation levels ranging from 4.5 kWh/m2/day to 7.5 kWh/m2/day18,19. Despite Ethiopia’s abundant solar PV generation capacity, the share of solar PV technologies in the country’s total power generation remains minimal, and the exploited proportion is less than 1%19,20. Among the various complexities that act as barriers to the growth of solar energy in the country, the absence of FIT policy is a significant concern18,21. Thus, analyzing and recommending a suitable FIT rate for Ethiopia is essential to unlock its solar potential and increase PV generation.

In the past, various studies, with a special focus on dynamic and market-dependent FIT viability analysis, and FIT impact on energy mix in different countries of the world have been examined.

Changgui Dong et al.21 analyzed China’s solar PV zonal FIT policy and its multiple changes over time. They found that, an increase of 0.1 yuan/kWh (~$0.014/kWh) in PV subsidies adds about 18 GW/year of installed capacity to the national PV market. S. Haji et al.22 asserted that the fixed price category of FIT is the most successful in Europe, as it has reduced financial risks and increased market transparency for deploying RE projects. In23, a dynamic FIT pricing model for distributed PV generation to adapt the continuously decreasing cost of PV panels and inverters in China is proposed. From the findings, the authors recommended that the Chinese government adjust the FIT rate more frequently. In24, Kangsadan Sagulpongmalee et al. presented an evidence-based model consisting of three main phases of FIT models for photovoltaic systems in Thailand. This study evaluated the economics of utility-scale 1 MW solar PV systems supported by the FIT policy and achieved an IRR of 11.83–15.32%, with a payback period of 7.49–10.06 years. The comparative study of FIT and net metering of solar PV system for the UCS University in Malaysia is analyzed by Tan et al.25. The study found that FIT and net metering offer monthly energy bill savings of 17.14% and 16.84%, with return on investment periods of 14.18 and 14.14 years, respectively. Lucia Baur et al.27 addressed the question: is Germany’s diffusion of PV technology a sustainable success, or an illusion driven by guaranteed feed-in tariffs? After conducting a dynamic study on small-scale solar home systems, this article recommends policies that could improve the FIT in Germany and serve as an example for other countries. Chun-Nan Chen and Chun-Ting Yang28 investigated the feasibility of investing in PV systems under declining FITs. They found that the proposed subsidy scheme favors investment in small-sized PV systems. Ryszard G´ et al.29 proposed a cost-effective design and economic analysis of a PV system operating under Net Metering or FIT support mechanisms for Poland. According to this study, the system capacity-optimized for net metering was nearly twice as large as for FIT. However, the net metering support system proved to be more beneficial, as it generated significantly larger NPVs. In Ref.30, the revision of the Japanese FIT, with a special focus on the effect of the new FIT for solar PV is proposed. The authors conducted an economic analysis to assess the impact of dynamic FIT prices on the profitability of residential and non-residential PV prosumers. The results indicated that the FIT could potentially be reduced for residential users and that the current FIT has reached its viability limits regarding non-residential PV investments. Another case in Turkey31, presented an economic analysis of 5kWgrid-connected residential rooftop PVs under the current FIT scheme. Economic determinants such as payback period, IRR and BCR were used to ensure the viability of the FIT policy and to address various FIT-related questions. The results showed that current discounted PBP, IRR, and profitability index of the systems are in the range of 7.75–14.43 years, 13.68−6.87%, and 2.02–1.28, respectively. Lavinia Poruschi et al.32 reviewed the existing Australian FIT and compared it with FITs and solar PV policy experiences in other developed countries. The authors concluded that FIT policies have led to an increased number of electricity disconnections from the grid. Conversely, Kenta Tanaka et al.33 investigated the impacts of FIT on electricity consumption and concluded that the FIT scheme increases the consumption of electricity purchased from companies if the FIT rate exceeds the electricity price. In34, Ademola A. conducted a meta-analysis of the literature on the performance of solar energy technologies to identify solar energy adoption trends in African countries. The authors concluded that the lack of a clear policy framework, such as FIT, is a major barrier to the development of the solar industry in Africa.

In the aforementioned works, the issues of fixed and market-dependent FIT estimations, challenges and advantages of FIT policies in developing renewable energy industry in various locations of the world are studied. However, the techno-economic viability and adoption strategies of FIT rates for solar PV generation in the case of Ethiopia is not highly studied. To the author’s knowledge, so far, there’s no comprehensive investigation in Ethiopia on the estimation and analysis of appropriate FIT rates for solar PV that have been applied in anywhere in the Ethiopian power grid. Therefore, this study aims to fill this gap by providing techno -economic viability analysis of FIT rates for solar PV generation in four different regions of Ethiopia.

Since 2021, Ethiopia has initiated the implementation of new PV plants through a program called Scaling Solar, sponsored by the World Bank, with the goal of developing 1,050 MW of solar energy35. Some of ongoing solar PV projects in different regions of the country is shown in Table 1.

Table 1.

Ethiopian solar PV projects showing the ambitious goals36,37.

Project
(region)
Capacity (MW) Project
developers
Cost
($m)
Tariff ($/kWh) Project tenure (years)
Metehara (Oromia) 100 Enel G. P & Orchid B. G 120 n/a 20
Gad (Somali) 125 ACWA Power 90 0.02526 25
Dicheto (Afar) 125 ACWA Power 90 0.02526 25

To achieve this expansion goals, analyzing FIT rates for different locations in the country is crucial. During this investigation’s data collection phase, it was observed that the Ethiopian Petroleum and Energy Authority (PEA) office, which is responsible for reviewing tariffs, is encouraging the exploration of FIT rates for Ethiopia. Accordingly, based on the analysis of estimated FIT rates, this study has provided a possible FIT recommendation for the concerned stakeholder in the country.

The rest of the paper is organized as follows: description of the study location is highlighted in the section "Site background". Methodology of the study and modeling of solar PV for the specified location is presented in the section "Methodology". Results and discussions are provided in the section "Results and discussions". Finally, the conclusions of this study are described in the section "Conclusions".

Site background

To analyze the viability of the FIT rate in the case of Ethiopia, Bahirdar Textile PLC, Hawassa Textile PLC, Dicheto Solar PV Project, and Metehara Solar PV Project, located in different regions of the country, were chosen. The geographical layout, overview, and coordinates of these locations are shown in Fig. 1; Table 2, respectively.

Fig. 1.

Fig. 1

Geographical layout of the project area (generated using ArcGIS 10.3).

Table 2.

Overview and geographical coordinate of the study region38,39.

Name of the location Region Latitude
(0N)
Longitude
(0E)
Elevation
(m)
Bahirdar textile PLC Amhara 11.26 37.12 1798
Hawassa textile PLC Sidama 7.31 38.25 1708
Dicheto solar PV project Afar 11.45 40.5 537
Metehara solar PV project Oromia 8.51 39.23 947

Methodology

Data collection

The study utilized primary data including solar radiation, PV system unit cost, PV system capacity, initial investment cost, operating and maintenance cost percentage, investor’s down payment, loan specifics, discount rate, and inverter replacement cost. This data was collected from, Ethiopian national meteorology agency, Ethiopian PEA and existing solar PV projects through in person interviews and questionnaires.

The collected and analyzed secondary data parameters—including the financial parameters of a grid-connected PV system, the kWh generated from a specific PV park, the payments received for the generated kWh, and cash flow statements —were used to estimate a viable FIT rate. Modeling and economic analysis of systems were carried out using PVGIS, and MATLAB. The overall research methodology used in this study is presented in Fig. 2.

Fig. 2.

Fig. 2

Research methodology followed.

Data on PV module specifications were collected from manufacturers through questionnaires. For this study, monocrystalline N-type IBC panels (60 cells, 1 m × 1.65 m) were used for industrial zones, while Hi-Mo2 bifacial modules were selected for solar PV projects due to their high efficiencies (22.8% and 19%) and site-specific operating temperature ranges.

Parameter setup and modelling

The feasibility of PV projects is evaluated based on total system costs, net initial investment, and feed-in tariff (FIT) rates. It largely depends on the market prices of panels and inverters. The average PV installation cost for projects commissioned in 2021 was $857 per kilowatt (kW), which is 6% lower than in 202040. The average interest rate in Ethiopia, obtained from the World Bank’s dataset, is 5.0729%. The estimated installation cost of grid-connected PV systems was obtained from project finance offices and updated from IRENA reports41.

Using this data, relevant variables for estimating the FIT rate were arranged for parameter setup and modeling, as shown in Tables 3 and 4, and 5.

Table 3.

PV module specification before installation and grid connection.

Module
parameter
Metehara Solar PV project Bahirdar Textile PLC Dicheto Solar PV project Hawassa Textile PLC
Rated power, w 375 440 375 440
Rated power density, w/m2 190 171 190 171
Module efficiency, % 19 22.8 19 22.8
Operating temperature, oC −40 to 85 −45 to 85 −40 to 85 −45 to 85
Warranty, years 30 40 30 40

Table 4.

Grid-connected PV system parameters.

Grid connection
parameter
Metehara Solar PV project Bahirdar Textile PLC Dicheto Solar PV project Hawassa Textile PLC
Price per watt $ 0.883 $ 0.857 $ 0.883 $ 0.857
Combined losses, % 23.4 23.08 23.4 23.08
Performance ratio, % 75.72 76.23 75.72 76.23
Overall efficiency, % 14.38 17.38 14.38 17.38
Annual performance degradation rate, % 0.45 0.25 0.45 0.25
Invertor O&M cost, % 15 14.8 15 14.8
Inverter warranty, years 10 25 10 25
PV modules’ area, m2 440,474.112 2,625.456 548,660.736 2,625.456
Installable PV capacity, kW 100,000 500 125,000 500
Number of modules 228,000 1,334 284,000 1,334
Total PV system cost $ 88,300,000 $ 428,500 $ 110,375,000 $ 428,500

Table 5.

Relevant financial parameters of four sites.

Financial
parameters
Metehara Solar PV project Bahirdar Textile PLC Dicheto Solar PV project Hawassa Textile PLC
PV unit price/watts $ 0.883 $ 0.857 $ 0.883 $ 0.857
PV system capacity, kW 100,000 500 125,000 500
Initial investment, $ $ 88,300,000 $ 428,500 $ 110,375,000 $ 428,500
Investor down payment (%) 30 30 30 30
Investor loan (%) 70 ($ 61,810,000) 70 ($ 299,950) 70 ($ 77,262,500) 70 ($ 299,950)
Interest rate and period 5.0729%, 15 5.0729%, 15 5.0729%, 15 5.0729%, 15
Monthly installments $ 491,140.13 $ 2,383.4 $ 613,925.16 $ 2,383.4
Discount rate (annual %) 4.95 4.95 4.95 4.95
Invertor O&M cost, % 15 14.8 15 14.8
PV project duration 30 40 30 40
PV system O&M cost, % 0.45 0.25 0.45 0.25

From a financial perspective, the annualized capital expenditure of PV project (A) —used to estimate the FIT and LCOE, depends on the principal amount of the project loan (p)42,43. Equation 1 is used to calculate the monthly installments and the annual effective discount rate.

graphic file with name d33e1028.gif 1

The annual effective discount rate should address financial challenges by ensuring profitability is neither overrated nor underrated44. Considering the methods for calculating the probable discount rates for a particular PV project reviewed in45, the following equation is used to obtain the annual effective rate from the loan interest rate:

graphic file with name d33e1042.gif 2

Where d is the annual effective discount rate, i is the loan interest rate and t is the period over which the loan is planned to be paid in full. The final parameter setup and modelling take advantage of Eqs. 1 and 2 to be complete. The metadata analysis, curation, and organization of the collected data are presented in Table 6. These data are used for the estimation of the IRR, the loan installments, NPV and FIT rates.

Table 6.

A sample of parameter setup and data arrangement.

graphic file with name 41598_2025_32105_Tab6_HTML.jpg

FIT rate estimation for solar PV generation

The FIT required to make a PV investment financially viable is calculated by setting the NPV of the investment to zero46. The FIT estimation formula, incorporating operating and maintenance cost, (Inline graphic) tax (Inline graphic) and IRR is provided by Eq. (4).

graphic file with name d33e1086.gif 3

Where Inline graphicis the annual electricity produced from a 1 MW PV module, which is the product of installed capacity and plant factor/capacity factor of a particular PV park. Inline graphic is the loan interest rate of the principal, Inline graphic during the down payment period t. The IRR in this estimation scheme is the discount rate (d), which minimizes the NPV of a given FIT rate to zero. To obtain the FIT rate using Eq. 3, ‘syms’ command with balance bounds of bankability, investment security and market uncertainty in MATLAB was used. It can be seen that the generation cost from solar PV depends on the initial investment, operating costs, financial costs, annual effective light hours, system efficiency, project lifetime, and time value of money. In this regard, FIT estimation should aim to strike a balance between minimizing investment risks for investors and lowering costs for customers. The annual electricity produced from a PV module is given by Eq. (4).

graphic file with name d33e1111.gif 4

Where Inline graphic is the number of days in a month, Inline graphic is monthly average solar irradiation in kwh/m2/day, Inline graphic is the area of the PV module in consideration and Inline graphicis the overall efficiency of the system. In this case, Inline graphic is the product of the allocated installation area and effective ratio. Moreover, Inline graphiccan be obtained by multiplying the performance ratio of the grid-connected PV system and the efficiency of the PV module installed22,47. In accordance with Eq. 4, the RE potential and the average daily irradiance of the selected sites are presented in Fig. 3.

Fig. 3.

Fig. 3

Average daily irradiation (kWh/m2) of the sites under consideration.

Ethics approval and consent

This study did not involve human participants, human tissue, or clinical data. Therefore, approval from an institutional review board or ethics committee and informed consent were not required. All data used were obtained from public sector office and publicly available sources and analyzed in accordance with relevant research and publication guidelines.

Results and discussions

Electricity produced from solar PV

The initial step in estimating fixed FIT rates for solar PV modules is to calculate the electricity generated at each site using Eq. 4. The electricity production for the Metehara and Dicheto solar PV projects, as well as for Hawassa Textile PLC and Bahir Dar Textile PLC, is presented in Fig. 4.

Fig. 4.

Fig. 4

Electricity produced from solar PV of the different sites under consideration.

Then, the results presented in Fig. 5 are multiplied by the unit price of producing 1 kWh of electricity to obtain received payments or electricity savings assuming the parameter set-up is done without a capital rebate.

Fig. 5.

Fig. 5

NPV of solar PV projects in terms of their project duration.

The updated retail price of electricity in Ethiopia is 0.006 $/kWh for households and 0.023 $/kWh for businesses, which includes all components of the electricity bill such as the cost of power, distribution, and taxes. Accordingly, loan instalments, O&M costs, cash flow, and NPV of the considered PV projects based on these retail prices are determined, as presented in Table 7. Similar tables were prepared for the remaining solar projects and indicated promising profits with the introduction of FIT rates. To reach such a conclusion, the FIT rates should be evaluated using financial KPIs.

Table 7.

FIT rates, NPV and IRR Estimation result sample.

graphic file with name 41598_2025_32105_Tab7_HTML.jpg

FIT rate and financial KPIs

Financial KPIs are often used to support renewable energy generation by combining FITs with investment subsidies and soft loans to achieve target profitability. Economic modeling can therefore be employed to assess the profitability of PV projects that integrate these support schemes, using appropriate FIT rates based on the NPV of the investment, the PBP23, the IRR48 and the BCR49.

Financial indicators used in this study include NPV, IRR, and LCOE. There is considerable debate in the finance literature about whether NPV or IRR is superior for decision-making. Some studies32,50 conclude that the NPV is generally preferable. This is because NPV assumes that cash inflows are reinvested at the assumed rate of return, whereas IRR assumes that cash inflows are reinvested at the computed IRR.

Reinvestment at the required rate of return is often more realistic and provides more reliable results when comparing mutually exclusive projects. Additionally, when projects are mutually exclusive and vary in size, as is the case in this paper, NPV is superior because it selects the option that maximizes the project’s value. However, a broader perspective on energy economics is also essential. The details of each financial indicators utilized in the study are described as follows:

  1. NPV: is a primary financial measure used to evaluate the techno-economic impact of RE projects after accounting for all costs and benefits. The NPV of a particular RE project is calculated as follows:

graphic file with name d33e1254.gif 5

Where Inline graphic is the initial investment cost or the value of cash flow during the commencement of the project Inline graphic is the capital cost by the end of the project duration t, and d is the discount rate until the loan is paid in full. The NPV of solar PV projects in terms of their project duration for the specified sites are shown in Fig. 5.

  • b.

    LCOE: is a key matric for evaluating the unit cost of electricity generation by solar PV. Variations in LCOE across regions are one of the major barriers for developing solar PV projects. If the LCOE is lower than the grid’s electricity retail price, the project investment is considered to be profitable and vice versa. Can be analyzed using Eq. (6).

graphic file with name d33e1299.gif 6

In most renewable energy projects, the FIT rate is calculated based on the LCOE of the generated energy. This ensures investors can recover their capital, O&M, fuel, and financing costs while earning a profitable return. Figure 6 presents the LCOE of solar PV projects in the specified region throughout their operational lifetimes.

Fig. 6.

Fig. 6

LCOE solar PV projects in terms of their project duration.

  • c.

    PBP: refers to the amount of time it takes for the investment cost of the solar PV system to be fully recovered through the savings or income it generates. The PBP is analyzed with the help of the following equation.

graphic file with name d33e1330.gif 7

Where Inline graphic is the initial investment cost or the value of cash flow during the commencement of the projectInline graphic is the net cash flow during the project time t, and i is real-time interest rate.

  • d.

    IRR: is used to measure the profitability of RE project investment. FIT rates for a particular PV project can be optimally evaluated using IRR. Prior knowledge of IRR helps in estimating the potential subsidy of the project compared to its minimum break-electricity price. The IRR is computed as follows:

graphic file with name d33e1360.gif 8

From the analysis, it is concluded that the Metehara solar PV station, with a capital investment of $88,300,000, can achieve a NPV of $1,462,653,170.76 by the end of its lifetime. With an IRR of 22% and a FIT rate of $0.023/kWh, the project can fully recover its initial investment within 15.6 years. An IRR results of the locations compared to PV system price and FIT rates are shown Fig. 7.

Fig. 7.

Fig. 7

IRR results of the sites compared to PV system price and FIT rates.

  • e.

    BCR: is sometimes referred to as the profitability index of an intended project and can be obtained from the NPV and the project’s initial investment cost as shown in the Eq. (9) below.

graphic file with name d33e1394.gif 9

As illustrated in Fig. 8, the profitability index of the Metehara solar project can be derived from its BCR curve over its project lifetime. Despite its higher initial investment, similar conclusions can be drawn for the Dicheto solar PV project based on the simulation results From an industry perspective, Hawassa Textile PLC with a $ 428,500 initial investment can give $149,401.04 of NPV at 12% IRR. The PBP of this industry is 11.3 years with an impressive average BCR of 1.03. The same conclusions are made for Bahirdar Textile PLC based on the FIT rate estimation and financial determinants analysis. The BCR of each site in terms of their duration are described in Fig. 8.

Fig. 8.

Fig. 8

BCR of the sites in terms of their duration.

Conclusions

This study assessed fixed FIT estimations and the financial viability of grid-connected solar PV projects in Ethiopia using key performance indicators such as NPV, LCOE, PBP, IRR, and BCR. The analysis, conducted for two PV power stations and two utility-scale PV parks, indicates that under the assumed cost, resource, and investment parameters, the examined systems can achieve positive financial returns.

For a PV power station with a capital investment of $88,300,000, a NPV of $1,462,653,170.76 can be achieved by the end of the project’s lifetime. With an IRR of 22% and a FIT rate of $0.023/kWh, the project can fully recover its initial investment within 15.6 years. From an industry or utility perspective, a PV park with an initial investment of $428,500 can generate a NPV of $149,401.04, with an IRR of 12%, a PBP of 11.3 years, and an impressive average BCR of 1.03.

In general, based on the results from this study, adapting a dynamic and market-based FIT policy in Ethiopia could be economically viable. Thus, this study offers significant insights for energy policy development, where it provides recommendations for designing and implementing effective FIT schemes to encourage solar energy adoption. Additionally, the research supports Ethiopia’s broader goals of expanding renewable energy in its energy mix by assessing the financial viability of such projects for investors, developers, and utilities. Furthermore, the study aligns with Ethiopia’s climate change mitigation strategies by promoting clean energy sources, helping to reduce greenhouse gas emissions and fostering sustainable energy development. These findings also have broader implications for other neighboring countries seeking to promote sustainable energy systems and achieve their climate goals.

Policy recommendations

The following recommendations are made based on the findings of this research:

  • The PEA office should adopt and introduce market based FIT policy tailored to the country’s solar energy potential. This policy should provide competitive and sustainable FIT rates that incentivize IPPs to invest in solar energy projects.

  • Promoting the development of utility-scale solar PV parks and power stations by showcasing their economic feasibility, including high NPVs, reasonable PBP, and BCR is important. This would not only address energy needs but also support job creation and economic growth in Ethiopia.

  • Establishing a favorable regulatory and investment climate for IPP is essential. This includes guaranteeing grid access, securing long-term Power Purchase Agreements (PPAs), and providing investment security. These measures will attract private investment and accelerate renewable energy deployment in the country.

  • The PEA should consider adopting the positive features of FIT policies from other African countries, such as Algeria, Ghana, Kenya, and Uganda.

Limitations and future work

Some of the limitations encountered in this investigation, which could be addressed by future researchers, are as follows:

  • The calculations are based on the current retail prices of electricity in Ethiopia. Future changes in these prices could affect the NPV and IRR of the projects. Thus, it is good in the future to consider these changes in price.

This study assumes reliable grid access and adequate infrastructure, although actual conditions may vary. Grid connectivity challenges and infrastructure constraints were beyond the scope of this work and should be examined in future research for a more comprehensive assessment.

Acknowledgements

The researcher extends gratitude to the Ethiopian Petroleum and Energy Authority for providing information on the current status of FIT in the country. Additionally, appreciation goes to Jimma University, research and publication director office and Exist Project at Jimma Institute of Technology, for their support in the investigation.

Author contributions

Tefera Mekonnen – Writing, review and editing the original draft, Shewit Tsegaye - Visualization, Birhanu Belete - Conceptualization, Jaisiva Selvaraj - Supervision, Abeba Negewo - Investigation, Emiyamrew Minaye - Project administration, Kifle Godana - Data curation, Abebe Wolie - Validation.

Funding

No funding was provided for this project.

Data availability

All data generated or analyzed during this study are included in this article.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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