Sustainable Energy Technologies and Assessments 75 (2025) 104244
Available online 22 February 2025
2213-1388/© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Original article
Assessing the viability of solar-biogas hybrid systems for energy provision in rural Kenyan communities
Stephen K. Kimutai
*, Bernadette Dushengere , Isaiah Muchilwa
Department of Mechanical, Production and Energy Engineering, Moi University, P.O. Box 3900 -30100, Eldoret, Kenya
A R T I C L E I N F O Keywords:
HOMER
Hybrid Energy system Kenya
PV–Biogas Rural Viability
A B S T R A C T
This study evaluated the viability of a hybrid solar photovoltaic (PV)-biogas system with the goal of resolving the ongoing lack of energy access in rural communities with a focus on Kenya’s Kesses region, Uasin Gishu county.
The study aims to assess energy demand, economic and environmental impacts, evaluate resource potential, model a hybrid system and gather data from 100 households. An estimated 780 kg of firewood per day is needed, with maize residues and cattle manure having biogas potentials of 88.08 and 309.7 m3/day, respectively against minimum requirement of 141.8 m3/day. The electrical demand is 114.75 kWh/day. The best setup which makes use of HOMER, includes an 18.20 kW converter, a 25.50 kW PV module, a 143-kWh battery capacity, and a 3-kW biogas generator. The Net Present Cost (NPC) and levelized Cost of Energy (LCOE) come to USD 183,558 and 0.171$/kWh, respectively. Additionally, findings showed that switching to biogas for cooking reduce CO2 emissions by 60,193.39 kg annually. Sensitivity analysis indicates that the costs of biogas generators have no effect on NPC and LCOE, while a greater inflation rate shows a double effect. PV-Biogas hybrid systems present a viable way to electrify rural areas and household’s livelihood improvement.
Introduction
The United Nations Development Programme emphasizes the pivotal role of affordable, reliable, and sustainable energy access in driving global economic and social development [1,2], particularly in achieving the Sustainable Development Goals [3,4]. In Africa, approximately 650 million people live without electricity [5], while anticipated that by 2030 between 660 to 820 million individuals in Sub-Saharan Africa still rely on traditional biomass, such as wood, charcoal, and agricultural residues, for cooking. In Kenya, inadequate electricity generation infrastructure has left numerous households without access to elec- tricity. Additionally, over 90 % of rural households depend on fuelwood and charcoal as their key energy sources for cooking. This dependence significantly impacts public health, environmental sustainability, women’s welfare, greenhouse gas emissions, and economic develop- ment, while contributing to premature deaths from indoor air pollution [6,7]. This underscores the urgent need for decentralized energy solu- tions like solar-biogas hybrid systems to tackle these issues efficiently.
In Kenya, biomass is expected to remain the dominant energy source in the foreseeable future [8,9]with biogas holding a promising option for cooking [10]especially rural areas [11,12]. Biogas utilization offers
health benefits by reducing smoke exposure, particularly for women and children, lowering respiratory issues. It also enhances lighting, educa- tional opportunities, hygiene, cleanliness, energy security, and allevi- ates energy poverty [13,14]. Biogas emissions range from − 81 to 251 gCO2/kWh, much lower than alternative energy sources while substituting fossil oil with biogas for cooking can cut emissions by around 266 gCO2/kWh [15,16]. Additionally, Kenya’s year-round solar radiation ranges between 4–6 kWh/m2 daily with 5–7 peak sunshine hours offering great potential for PV [17]. Therefore, implementation of a PV-biogas HES brings about time and labor savings in the collection and utilization of fuelwood [18].
The utilization of a HES is advocated as a more effective solution for communities [19–22]currently relying on firewood, kerosene and other unclean fuels. These hybrid systems can function independently or connect directly to the grid when supplying electrical loads [23]. Several factors contribute to the appeal of hybrid renewable energy power systems over single-resource alternatives, including their nonpolluting nature, cost-effectiveness, production of nutrient-rich manure for plants, continuous power supply, pollution control through waste disposal, and efficient use of renewable energy [24,25]. While electrical energy can address the demand for powering appliances and cooking, it may not
* Corresponding author.
E-mail address: [email protected](S.K. Kimutai).
Contents lists available at ScienceDirect
Sustainable Energy Technologies and Assessments
journal homepage: www.elsevier.com/locate/seta
https://doi.org/10.1016/j.seta.2025.104244
Received 19 January 2024; Received in revised form 20 January 2025; Accepted 15 February 2025
always be economically viable in rural areas due to diverse technologies and energy requirements [26].
Many studies have been conducted on HRES and several tools have been created for their design and optimization such as TRNSYS and the widely used HOMER modeling tool [24,27–33]. According to Thir- unavukkarasu et al. [25], HOMER is the most widely used software application. Although HRS have been researched extensively, there is still a lack of modeling and simulation tailored to Kenya’s rural house- holds. In order to maximize performance, cost-effectiveness, and energy access for better rural livelihoods, this study investigates solar-biogas integration. This solves the dearth of thorough assessments on viability and sustainability [34]. Also, rural electrification is prioritized over urban areas to address the scarcity of clean and sustainable energy in these regions [35,36].
The scientific aim of the work is employs HOMER modeling to tackle Kenya’s unique energy challenges, aligning parameters with local geographic, meteorological, and socioeconomic conditions. The focus of the research was to obtain feasibility of implementing a PV-Biogas HRES [19]to meet the daily cooking and electrical energy needs of remote households, aiming to optimize integration and streamline the evalua- tion process for different system configurations, considering factors such as location, load demand, economics, and environmental considerations [37,38]for remote villages to enhance livelihoods. This study extends the existing research in hybrid systems.
Literature review
Access to reliable and affordable energy remains a significant chal- lenge in rural communities, particularly in sub-Saharan Africa, where about half of the population lacks access to electricity [17,39,40]. In Kenya, rural electrification levels remain low due to factors such as high grid extension costs, limited infrastructure, and the distributed nature of remote settlements [41]. Dependence on outdated household fuel sources such as firewood and kerosene, worsens environmental degra- dation, leads to high greenhouse gas emissions, adverse health effects from indoor air pollution and overall cost burdens. In addition, fire wood collection places a hefty burden on women and children consuming time and labor that could be used on education or income- generating actions. These challenges highlight the imperative need for sustainable energy such as HRES for remote parts.
Renewable energy systems for example solar and biogas, offer feasible substitutions to traditional energy sources, specifically for off- grid rural societies [42]. These technologies provide clean, justifiable, and decentralized energy solutions. In Kenya, the plentiful availability of solar energy and agricultural biomass makes renewable systems an attractive option and therefore, hybrid renewable systems such as solar- biogas arrangements are highly promising as they syndicate comple- mentary energy sources, ensuring consistent energy availability while addressing fluctuations in resource supply [43]. Solar energy provides reliable electricity for lighting and appliances, while biogas offers a cleaner cooking fuel that can replace firewood and charcoal [44]. By integrating these technologies into rural energy contexts, it is possible to enhance the food-water-energy-health nexus and the overall living standards.
Recent research extensively investigates HRES for electrifying remote areas [45,46]. A study done in Kenya investigated the limited uptake of small wind turbines in PV and wind mini-grids from techno- economic and diffusion perspectives. Using a techno-economic model, the viability of PV/wind hybrids was back-tested, and a conceptual framework based on innovation and technology diffusion theories was applied to assess the Kenyan mini-grid sector and identify barriers. Re- sults showed that PV/wind hybrids are technically and economically feasible at wind speeds above 4.5 m/s but less effective at lower speeds.
The study additionally identified significant technical, economic, and systemic barriers faced by stakeholders, which hinder the acceptance of these solutions [47]. Additionally, in Machakos, a study on wind/PV
HES revealed promising complementarity between wind and solar re- sources, with an annual average solar insolation of 2130 kWh/m2 and an average power density of 17 W/m2 for wind at a mean speed of 3.0 m/s [48]. As well, an evaluation of the commercial application of a HES at the East African School of Aviation in Kenya utilized sensitivity analysis, optimization, and simulation. The most efficient system, incorporating grid energy solar PV and wind displayed a competitive energy cost with NPC of KSh 68,927,127, a COE of KSh 7.39/kWh, and a 4.93-year simple payback period [49].
Furthermore, research on a hybrid wind-solar and battery system in a Naivasha school in Kenya indicates that the system, comprising two 0.9 kW wind turbines, three 1 kW solar panels, and a 57.6 kWh battery system, cannot meet the load requirements independently without grid support [50]. While a feasibility assessment for a hybrid renewable energy system at the University of Nairobi’s School of Engineering in Kenya indicated that the most viable configuration for powering insti- tutional buildings is a grid-tied system, combining grid components, photovoltaic cells, and a diesel generator, with a COE of Ksh 7.89 and a NPC of Ksh 69,512,100.00 [25]. Moreover, a study in Northern Kenya focused on modeling, simulating, and optimizing a Hybrid Wind and Solar Photovoltaic Power System. Combining 1,976 solar PV modules (494 kW), 13 wind turbine generators (3,250 kW), and a battery storage array with 94,856 advanced lead-acid batteries (7,968 kWh), the find- ings confirmed successful hybridization in environments where wind and solar patterns complement each other. The study resulted in an off- grid deployment-ready system with an attractive levelized cost of energy at 17 US cents per kWh [51]. Moreover, another study examines the techno-economic feasibility of using grid-connected PV hybrid systems to power large grid-dependent academic institutions, using Moi Uni- versity’s administration building as a case study [52]. The results from simulations using HOMER Pro software indicate that the optimal sys- tem, combining solar PV and grid power without battery storage, offers significant cost savings, reducing energy costs by 83.94 % compared to the existing grid, with a payback period of 5.08 years. This paper brings a new look to the existing literature in tackling Kenya’s unique chal- lenges using decentralized solar-organic solutions and evaluates the possible saving in CO2 emissions.
Materials and method Description of study area
Kesses is one of the remote places located in Uasin Gishu County, the mid-west of Kenya’s Rift Valley. The geographic coordinates of this location are 0.28705, 35.28627 in Latitude and Longitude respectively as shown in Fig. 1. It is a densely populated sub-count of 731.0 km2 with a population density of 204 people/km2. Fig. 1. shows the location under study. Kesses is an example of a typical isolated community where the heads of households are mostly farmers. After school, kids help their parents with farm chores and firewood collection. This community’s 90
% of households engage in a variety of agricultural pursuits, such as planting trees, raising cattle, sheep, and poultry, and cultivating crops like corn and beans according to the fertilizer subsidy programme [53].
The community relies predominantly on firewood, charcoal [54], kerosene lamps, candles, torches, and, to a lesser extent, solar lanterns for lighting and other energy-related activities. The indoor pollution resulting from the use of non-clean energy sources presents a significant barrier to quality education, human well-being, and community busi- ness endeavors [55].
Data collection
The study employed a comprehensive approach, integrating personal observations, interviews, and questionnaires to gather data on energy demands, resource availability, and related factors. Fieldworkers received thorough training in data collection, equipment use, and
biomass assessment. A household survey was conducted between January and July 2022. Focus groups provided additional context, while collaboration with community leaders ensured engagement and data validation. Random sampling was used to ensure representative, unbi- ased data across diverse locations and vegetation types [56].
Load Estimations
The modeling and simulation of the HES were conducted using HOMER software. Data on electrical loads, usage periods, cooking en- ergy needs, and household-level biodegradable resource generation (from livestock and agricultural residues) were collected through a structured questionnaire. Fuel use estimates were based on energy equivalence from prior research [57]. The cooking energy demand for 100 households was calculated as approximately 780 kg/day, based on 5.5 bundles of fuel per week per household (≈7.8 kg). Table 1provides an analysis of domestic electricity demand at the proposed site, reflecting household activities.
Three classes of households were identified: class one denoted households with a greater electrical load, class two represented families with a medium load, and class three represented households with a lower load. Ten, thirty-five, and fifty families from class one, class two, and class three were distributed, respectively. For every home class, an
estimate of the load that was temporarily utilized was also computed and added. Data from resident interviews and load duration calculations were used to scrutinize power use dynamics across various household types in the study site.
Resource estimations Solar resource potential
In order to assess the potential of a solar PV system, it is essential to investigate the solar radiation characteristics unique to the deployment site. In this study, monthly averaged values for Global Horizontal Solar Radiation, Clearness Index, and Temperature over a minimum of 20 years were obtained via HOMER’s online retrieval, which is connected to NASA’s website [32]. Apart from radiation, the chosen location ex- periences year-round temperature fluctuations ranging from 19.91 ◦C to 20.46 ◦C, with an average of 20.36 ◦C and daily radiation of approxi- mately 5.89 kWh/m2/day. It was determined that the efficiency of the PV module was not affected by the slight seasonal fluctuations in tem- perature and irradiance.
Biomass potential
This research focused on assessing available biomass resources, including maize and three livestock categories, for calculating biogas production for cooking and a biogas generator. It involved co-digestion of maize residues, the primary crop, with manure from cattle, sheep, and chicken to enhance biogas generation. Estimations considered factors like weather conditions, land type, crop variety, and soil fertility, with sustainable agricultural residue removal ranging from 30 % to 70 % based on various factors [58]. Variability in the utilization of livestock residues among villagers influences their availability for clean energy, and this study, employing a combination of field interviews and existing literature, estimated biomass potential by considering the availability fraction of these residues, detailed in Table 4, with consistent cross- verification to enhance robustness and reliability by minimizing errors associated with any single method [59]. The available technical manure and biogas potential were determined using equations (3.1)which were based on existing literature [60–62].
BPb=Pmx DM x Et (3.1)
where: Pm represents the daily available fresh manure,
DM: Total dry matter from fresh manure and DM%: Dry matter percentage of the fresh manure.
Et is the biogas yield of animal per each kilogram of dry matter in m3 (kg DM)-1.
Using data gathered from field interviews and literature sources, Table 2 presents the estimated biomass potential, factoring in the availability fraction. This table provides comprehensive information on the quantity of livestock, along with the rate of daily fresh manure production. Additionally, the rate of availability (Ra) or collection rate for energy use was estimated at 70 % for cattle, 70 % for chicken, and 60
% for sheep [58]. Approximately 5.5 kg of firewood is considered equivalent to 1 cubic meter of biogas [57].
To estimate the theoretical and potential of crop residues used in this study, equations (3.2). and 3.3. were used.
PAR=∑n
i=1
(CixRPRi) (3.2)
TBP=PARx RFi (3.3)
where:
pAR is the potential for yearly crop residue, Ci is the annual production of crop i,
RPRi represents the residue-to-product ratio of crop i.
TBP is the technical biomass residues potential,
RFi is the removal rate (or recoverability fraction) of the residue i, Fig. 1.Selected as a case study, Kesses in Uasin Gishu County.
According to shane [63], yearly biogas potential (in m3) from agri- culture residues is estimated through equation (3.4).
By
(m3/yr)
=Cr(kg/yr)x TS x VS x Bp
(m3/kgVS)
(3.4) where:
By is the annual biogas potential of agriculture residues, The term (Cr=CixRPRi)is the annual crop residues in kg/yr.
BP: the theoretical biogas yield (m3 per kg of volatile solids).
TS: the total solids in percentage.
VS: the volatile solids in percentage.
Based on field visits done in the studied area, maize was found as the main crop. Then, from its estimated annual production, the quantity of expected maize residues and its corresponding biogas potential were estimated based on relations from the literature and Residue to Product Ratio(RPR) [9]. The considered rate of availability for maize cob, husk and stalks were 80, 100, and 70 per cent respectively. The estimated
annual production, the quantity of expected maize residues and its corresponding biogas potential were estimated based (Table 3) on re- lations from the literature [60].
Hybrid system components
After the technology type is determined, HOMER requires users to choose appropriate hardware that is in line with the system architecture.
These parts are essential for producing, transforming, and storing ther- mal or electrical energy [64,65]. The components chosen for this inquiry consist of a power inverter for conversion, a PV array, biogas digester, a biogas generator, and an electrical storage battery.
Economic and Constraints input
The expenses associated with the PV array, inverter, and batteries were computed based on prevailing prices in the Kenyan market.
Conversely, the cost of the biogas generator is approximated by aver- aging the expenses derived from a literature survey. The cost includes;
system’s capital, operation and maintenance costs, project lifetime, discount rate, interest rate, efficiency, and lifespan of the components [64,66]. Capital expenses, installation costs, replacement costs, O&M costs, fuel costs, pollution penalties, and grid power costs were all included in the costs. HOMER categorizes and ranks all system config- urations in the optimization findings based on the total NPC value, which serves as the basis for calculating the total annualized and Lev- elized cost of energy that presents the average cost of production for both electricity [67,68]. HOMER use equation (3.5)to calculate project NPC and COE respectively [27].
COE=Canntot
EServed (3.5)
where Eserved represents the total amount of energy provided by the system
Hybrid energy system modelling and simulation
The design, modeling, and simulation of off-grid were done using HOMER as shown in Fig. 2. It also makes techno-economic and envi- ronmental assessments of electricity generation easier [69].
Table 1
Electrical Load estimation categorized by various tiers within the study area.
Load Category Appliances Quantity Power (W) Time of use (hour/day) Usage (hr/d) AC loads (KWh/d)
Class one Bulbs 50 10 18:00–21:00 3 1.5
Bulbs 20 10 18:00–06:00 12 2.4
Radio 10 15 06:00–18:00 12 1.8
Mobile Phones 40 5 18:00–20:00 2 0.4
Television 10 80 19:00–22:00 3 2.4
Computer 10 100 18:00–21:00 3 3
DVD player 10 30 11:00–13:00 2 0.3
Refrigerator 10 200 00:00–23:00 24 48
Class two Bulbs 105 10 18:00–21:00 3 3.15
Bulbs 70 10 18:00–06:00 12 8.4
Radio 35 15 06:00–18:00 12 6.3
Mobile Phones 105 5 18:00–20:00 2 1.05
Television 35 80 19:00–22:00 3 8.4
Computer 0 100 18:00–21:00 0 0
Refrigerator 0 200 05:00–17:00 0 0
Class three Bulbs 165 10 18:00–21:00 3 4.95
Bulbs 55 10 18:00–06:00 12 6.6
Radio 55 15 06:00–18:00 12 9.9
Mobile Phones 110 5 18:00–20:00 2 1.1
Television 0 80 19:00–22:00 0 0
Computer 0 100 18:00–21:00 0 0
Refrigerator 0 200 05:00–17:00 0 0
Other 5.1
Total load 114.75
Table 2
Estimated Fresh manure produced.
Animal
livestock No. of
livestock Expected fresh manure (t/day)
Total collectable fresh manure, kg/
day
Total collectable DM (kg/
day)
Total biogas (m3/day)
Cattle 279 5580 3906 781.2 273.42
Sheep 190 342 239.4 71.82 30.8826
Poultry 540 54.8 32.88 10.85 5.3166
Total 5976.8 4178.28 863.87 309.619.7
Table 3
Biogas potential from maize residue.
Biomass
residues Total collectable fresh residues, kg/day
Total collectable TS, kg/day
Total collectable VS, kg/day
Total biogas, m3/day
Maize cob 57.439 17.2317 14.13 8.478
Maize
husk 157.8 22.092 11.2669 7.8868
Maize
stalk 368.2 272.468 256.1199 71.7136
Total 583.4392 311.79176 281.51688 88.078
Carbon emissions and potential savings
The potential savings in emissions by using biogas instead of the predominant cooking fuel, firewood was assessed. In this case, it was considered that the homes under investigation had switched entirely from using firewood for fuel to biogas. To compute the carbon emissions from burning fuel wood [70–72], HOMER calculated emissions based on the specific fuel consumption and emission factors of the generators included in the model. Further, validation of carbon emissions and savings were calculated using equations explained in Appendix.
Ethical approach
The ethical approach in biomass estimation and data collection involved obtaining informed consent, comprehensive training, cultural sensitivity, privacy, fair partnerships, accuracy, transparency, and random sampling, ensuring the rights and well-being of both researchers and local communities, fostering responsible data collection with reli- ability and validity.
Results and discussions
Energy requirement of the households Lighting and appliances
The estimated electrical demand was 114.75 kWh/day, with a scaled peak load of 21.59 kW. This peak load, determined by HOMER, in- corporates random daily load variability the system must accommodate.
The demand exhibited a peak during the evening hours from 18:00 h to 21:00 h when people return home from their duties, and numerous appliances operate during this period. Fig. 3shows the daily load profile.
Cooking requirements
The cooking requirements in the surveyed area were fulfilled using firewood. Field visit findings indicated that the total daily firewood consumption to meet the cooking needs of 100 households was esti- mated at 780 kg. Employing the relationship, the corresponding biogas equivalent was calculated to be 141.8 m3 per day. It was presumed that the cooking demand would be satisfied through biogas combustion instead of the currently used fuelwood.
Potential of biomass resources
Cattle were found to generate a lot of manure compared to sheep and chickens. Based on maize production, the total collectable maize husk, maize cob, and maize stalks were estimated to be 583.43 kg/day. For agricultural residues, maize stalks were found to have higher residues of 368.2 kg while maize cob was found to be lower residues of 57.43 kg.
The total collectable biomass residues of 4762 kg (583.44 +4178.28) per day were estimated against the minimum required 3131 kg per day taking the biogas density of 1.15 kg/m3 [60].
Proposed PV- biogas hybrid system
The optimal hybrid system configuration is as follows: A 3-kW biogas-fueled generator, 25.50 kW PV modules for solar energy gener- ation, A 143-kWh battery with usable capacity for energy storage and an 18.20 kW system converter to facilitate the integration and distribution of power within the community.
PV module
Table 4provides a detailed overview of the yearly performance of the PV module within the optimal system configuration. The total annual production is recorded at 55,622 kWh, accounting for 77.5 % of the overall production, with the PV-rated capacity set at 25.5 kW, Fig. 2.Flow chart illustrating optimization procedure.
Fig. 3. Depicts the daily load profile, including hourly demand.
generating an average output of 152 kWh/day. The operational hours per month amount to 4,385 h annually, and the corresponding levelized cost of energy is determined to be 0.171 $/kWh. This data illustrates the intermittent nature of solar resources, with power production occurring between 7:00 and 18:00 hrs.
Power converter
In the optimized system, a converter plays a crucial role in facili- tating the conversion between DC and AC power based on both pro- duction and demand. The optimal configuration for this conversion system includes an 18.2 kW inverter and an 18.2 kW rectifier. The annual input and output for the inverter are 27,587 kWh and 26,207 kWh, respectively, while for the rectifier, the input is 463 kWh, and the output is 416 kWh. The converter incurs annual losses of 1,379 kWh for the inverter and 46.3 kWh for the rectifier. The inverter operates for 7,699 h annually, while the rectifier operates for 1,056 h.
Battery storage
In the optimal system configuration, a battery with a storage capacity of 220 Ah was carefully selected. The arrangement includes 34 strings in parallel, each comprising 2 batteries. Over the course of the year, the battery’s annual input is measured at 15,998 kWh, while the output is recorded at 13,644 kWh. This disparity is attributed to losses incurred during charging and discharging (2,404 kWh) and storage depletion (49.5 kWh). The anticipated annual throughput, representing the overall energy processed by the battery,was calculated to be 14,799 kWh. In addition, the operational condition of the in-use battery reveals that between 00:00 and 09:00, its State of Charge (SoC) consistently stays within the 55 % to 80 % range. Subsequently, from 10:00 to 18:00, it increases to the 80 % to 100 % range, signifying a higher charge level.
Finally, from 18:00 to 24:00, the SoC was observed to be within the 60 % to 80 % range.
Biogas generator
In the optimal configuration, the biogas generator was rated at 3 kW with a mean electrical output was 2.99 kW, producing 16,123 kWh/
year. It operates for 5,388 h/year and 446 starts. In this system, the PV modules serve as the primary energy source, and the generator’s oper- ation schedule is designed to provide power when there is insufficient insolation. The biogas generator’s annual fuel consumption is 564 tons, translating to a fuel energy input of 51,734 kWh/yr, with a specific fuel consumption of 2.1 kg/kWh.
Need for storage
Because agricultural leftovers are produced in seasonal quantities, storage is essential. This approach stabilizes prices and markets, pro- motes opportunities for research and development, increases resilience to climate variability, minimizes environmental impact by avoiding burning, optimizes energy and resources, and assures a continuous supply for processing industries.
Environmental evaluation
In comparison to biogas, solar photovoltaic technology emits pol- lutants to a lesser extent, with the optimal system in simulation exhib- iting emissions of CO2, CO, and minimal NOX. In this configuration, the emitted pollutants are measured at 162 kg/yr, 1.1 kg/yr, and 0.6 kg/yr for carbon dioxide, carbon monoxide, and nitrogen oxide, respectively.
Additionally, substituting biogas for firewood in cooking is estimated to avoid the emission of 60,193.39 kgCO2eq per year. The findings align with Girma’s study on powering an Ethiopian rural school, showing that a PV/battery/diesel hybrid system reduced emissions by 36,833.22 kgCO2eq annually, confirming its technical and financial viability [73].
They also support research by Vanessa et al. [74]and Habib et al. [75], which reported 20.45 tCO2eq net mitigation from a hybrid PV/biogas system.
Economic evaluation
Levelized Cost of Energy (LCOE) stands at $0.171/kWh. Breaking down the costs, the capital cost is $62,954.99, replacement costs are
$72,156.92, and O&M costs are $65,360.79. For fuel and salvage, the costs are $ 0 and $16,914.41, respectively. In terms of conversion technologies, the solar system components (PV arrays, battery, system converter) account for $123,625, while the biogas generation system incurs costs of $59,941. Notably, since HOMER doesn’t model a bio- digester separately, all associated costs are integrated into the fixed costs of the biogas-fueled generator. A detailed breakdown of costs based on components and cost types is visually presented in Fig. 4.
Sensitivity analysis
An optimized biogas generation system was subjected to a sensitivity analysis in order to determine how vulnerable it was to various un- certainties, including changes in the market, a shortage of biomass, and national inflation rates. Cost multipliers were applied to key variables such as solar radiation, capital costs, replacement costs, operation and maintenance costs, biomass costs, and inflation rates to simulate how these factors could influence the system’s performance. The NPC and COE increased as a result of rising generator-related expenses, according to the results, preserving economic feasibility but at a higher cost. The study also looked at how changes in inflation rates affected NPC, and it found an increasing trend up until a point where it became less economically feasible. A sensitivity study on the cost of biomass revealed a proportionate link between growing NPC and COE and rising biomass costs.
Model validation
To validate the study’s findings, a comparative analysis was con- ducted by referencing related studies on HRES. The cost of energy, calculated at $0.171/kWh in this study, aligns closely with similar studies, as indicated in Table 5. This comparison affirms the feasibility of a hybrid PV-biogas system as a viable solution for meeting household energy requirements in rural communities in Kenya, despite potential fluctuations due to changes in economic parameters.
The validated results indicate that the CO2 reductions from the PV system, battery system, and biogas system are approximately 6,115, 34,291, and 66,342.4 kg CO2/year, respectively, totaling around 106,748.4 kg CO2/year for the HES. The biogas system’s value closely aligns with the HOMER estimate of 60,193.39 kg/year, further con- firming the accuracy of the results.
Conclusion and policy directions
This study demonstrates the viability of a solar PV-biogas HES to address energy access challenges in rural communities, with a focus on Table 4
PV operation.
Quantity Value Units Quantity Value
Units Units
Rated capacity 25.5 kW Minimum Output 0 kW
Mean output 6.35 kW Maximum
Output 27.0 kW
Mean output 152 kWh/d PV penetration 133 %
Capacity factor 24.9 % Hours of
Operation 4.385 Hrs/yr
Total
Production 55,622 kWh/
yr Levelized Cost 0.171 $/kWh
Kenya’s Kesses region. The findings highlight the adequacy of local biomass resources, such as maize residues and cattle manure, to meet biogas production requirements, alongside the feasibility of a hybrid system. The hybrid system not only provides a reliable, clean energy solution but also reduces dependence on firewood, mitigating environ- mental degradation and improving household livelihoods. These results stress the potential for scaling PV-biogas systems to electrify rural areas sustainably, offering an economically and environmentally sound pathway to enhance energy access and rural development.
We propose policies to incentivize the adoption of solar-biogas hybrid systems through subsidies and tax benefits, reducing upfront costs for rural communities. Additionally, promoting biogas as a cleaner alternative to firewood should be integrated into national energy stra- tegies and establishing financial support mechanisms like grants and public–private partnerships that can address venture barriers. Further, capacity-building initiatives, pilot projects, and community engagement through education and skill-building are vital for demonstrating viability, fostering acceptance, and encouraging widespread adoption.
Areas for future research
Impending study on Solar-Biogas Hybrid Systems for rural energy provision should stress on their economic, social, and environmental impacts in line with the SDG’s Agenda 2030. Additionally, efforts must focus on improving cost-effectiveness and scalability through innova- tion hubs and collaboration advancements. Moreover, there is a need to explore how solar-biogas energy solutions can enhance the food-water- energy-health nexus.
CRediT authorship contribution statement
Stephen K. Kimutai: Writing – review & editing, Writing – original draft, Visualization, Methodology, Conceptualization. Bernadette Dushengere: Writing – original draft, Resources, Methodology, Inves- tigation, Formal analysis, Data curation. Isaiah Muchilwa: Supervision.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This paper’s research was financially supported by the European Union through the Mobility for Innovative Renewable Energy Tech- nologies (MIRET) initiative at Moi University.
Appendix. Carbon emissions and potential savings validation
The emissions reduction estimates were validated also using the following equations;
CO2 from PV system [82]
SPV=Cfx QPV (3.6)
where Cf is fossil fuel carbon emission factor (0.73 kg CO2/kWh (diesel fuel)) and QPV is energy generated.
Carbon Savings from Battery use
SB=ηx Cfx QDelivered (3.7)
where: QB =143kWh, Battery capacity, η =0.9 (90 %): Battery efficiency [83].
Fig. 4. An in-depth breakdown of costs categorized by components.
Table 5
Energy Cost of different hybrid systems.
System Location COE $/kWh Reference
PV/Biogas gen/Battery Kenya 0.254 [76]
PV/Diesel gen/Wind T/Battery Kenya 0.066 [25]
PV/Biogas gen/Battery Rwanda 0.154 [69]
PV/Biogas gen/Battery Ghana 0.256 [64]
PV/Biogas/Wind T/Battery India 0.181 [77,78]
PV/Biogas/Diesel gen/Battery India 0.145 [79]
PV/Biogas gen/Diesel gen/Grid Iran 0.193 [80]
PV/Biogas gen/Battery Bangladesh 0.341 [81]
The total carbon savings from the biogas system (considering firewood replacement and methane capture) are:
SBM=Sbiogas+Smethane (3.8)
where,Sbiogas=Efirewood=Cf×Qbiogas (3.9)
Smethane=GWPCH4×MCH4 (3.10)
where also; Qbiogas =3KW ×24 h a day =72kWh/day and Carbon emission factor for firewood: Cf =1.83 kg CO2/kWh, MCH4 =2 kg CH4/day and GWPCH4 is the Global Warming Potential (GWP) of methane =25 (CO2 equivalent) [84].
Calculations
1) Carbon emission reduction (SPV) from 25.50 kW PV module assuming an average daily solar irradiance of 6 h/day SPV=Cf⋅QPV
where Cf is fossil fuel carbon emission factor (0.73 kg CO2/kWh (diesel fuel)) and QPV is energy generated by the PV system Substitute values:
SPV=0.73x22.95=16.7535kg CO2/day
=0.73⋅22.95 =16.7535 kg CO2/day (same as 6115 kg CO2/year) 2) Carbon emission Savings from Battery:
Sbattery =Cf⋅Qbattery, delivered =0.73 ×128.7 =93.951 kg CO2/day =0.73 ×128.7 =93.951 kg CO2/day (same as 34,291 kg CO2/year).
3) Carbon Emissions and Savings: Biogas System vs. Firewood
The total carbon savings from the biogas system (considering firewood replacement and methane capture) are:
Sbiogas=Efirewood=Cf⋅Qbiogas
where: Qbiogas =3KW ×24 h a day =72kWh/day and Carbon emission factor for firewood: Cf =1.83 kg CO2/kWh Substitute the values:
Efirewood=1.83×72=1.83⋅72=131.76kg CO2/day
If the biogas system prevents the release of methane (MCH4M) during the decomposition of organic waste, the avoided emissions are:
Smethane=GWPCH4×MCH4
where: MCH4 =2 kg CH4/day and GWPCH4 is the Global Warming Potential (GWP) of methane =25 (CO2 equivalent).
Substitute the values:
Smethane =25 ×2 =50 kg CO2/day Stotal=Sbiogas+Smethane
Substitute the values:
Stotal=131.76+50=181.76kg CO2/day(sameas66,342.4kg CO2/year)
The estimated CO2 reduction from the PV, batter and biogas system are 6115 kg CO2/year, 34,291 kg CO2/year and 66,342.4 kg CO2/year respectively) totaling to about 106,748. 4 CO2/year.
Data availability
Data will be made available on request.
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