STATISTICAL EVALUATION OF RENEWABLE ENERGY ADOPTION AMONG HOUSEHOLDS IN KWARA STATE, NIGERIA
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Abstract
About This Research Topic
Nigeria faces one of the world's most severe electricity access crises. With grid access at only about 60% of the population and those connected experiencing 16 to 20 hours of daily outages, households and small businesses bear huge costs on diesel and kerosene. In Kwara State, home to 3.5 million people, KEDC serves approximately 285,000 metered customers but reliable supply reaches far fewer. This crisis has made off-grid renewable energy not just a climate solution but a daily necessity. renewable energy adoption among households — particularly solar PV lanterns, solar home systems, and solar mini-grids — is now a critical market and policy priority.
Globally, solar module costs fell 89% from 2010 to 2022 per IRENA, while pay-as-you-go models from ENGIE, d.light, and Greenlight Planet have removed upfront cost barriers. Nigeria's Rural Electrification Agency and National Renewable Energy and Energy Efficiency Policy target 30% renewable in the mix by 2030, with solar as primary platform. Kwara State, with 5.5-6.0 kWh/m2/day irradiance, is technically ideal, yet adoption remains low and unequal.
This study provides a comprehensive statistical evaluation of renewable energy adoption among 384 households across Ilorin South (urban), Asa (peri-urban), and Baruten (rural), using chi-square, binary and ordinal logistic regression, and willingness-to-pay contingent valuation to identify determinants and estimate affordability for evidence-based policy.
Main Abstract
Nigeria faces a severe electricity access crisis, with grid electricity reaching only approximately 60% of the population and those with access experiencing frequent outages averaging 16 to 20 hours per day in many states. Kwara State, with a population of approximately 3.5 million, reflects this national crisis: KEDC distribution company serves approximately 285,000 metered customers but supplies reliable electricity to a much smaller fraction. In this context, household adoption of off-grid renewable energy systems, particularly solar PV lanterns, solar home systems, and solar mini-grid connections, represents both a growing market and a critical policy priority.
This study conducted a comprehensive statistical evaluation of renewable energy adoption among 384 sampled households in three LGAs of Kwara State: Ilorin South (urban), Asa (peri-urban), and Baruten (rural). The study applied descriptive statistics, chi-square tests of association, binary logistic regression, ordinal logistic regression, and willingness-to-pay (WTP) contingent valuation to identify the socioeconomic, attitudinal, and infrastructure determinants of household renewable energy adoption and to estimate the premium households are willing to pay for reliable clean energy.
The adoption rate of any renewable energy technology was 47.4% overall, with significant LGA variation: 64.2% in Ilorin South, 44.5% in Asa, and 23.4% in Baruten. Solar PV lanterns were the most common adopted technology (28.4%), followed by solar home systems (12.5%), and solar mini-grid connection (6.5%). Binary logistic regression identified monthly household income (aOR = 3.247 per income category, p < 0.001), education level (aOR = 2.184 per level, p < 0.001), prior experience with grid outages (aOR = 1.987, p = 0.002), awareness of government solar programmes (aOR = 2.841, p < 0.001), and distance from nearest town (aOR = 0.624, p < 0.001) as significant independent predictors. Gender of household head was not significant (p = 0.487). Mean WTP for reliable solar electricity was N3,847 per month (95% CI: N3,612 to N4,082). All four null hypotheses were rejected.
The study recommends targeted solar subsidy programmes for the lowest-income quintile, expansion of rural mini-grid deployment in Baruten and other rural LGAs, integration of renewable energy awareness into agricultural extension services, and development of a local solar technician training programme to address maintenance barriers to sustained adoption.
Keywords: Renewable Energy, Solar PV, Technology Adoption, Logistic Regression, Willingness to Pay, Energy Access, Household Survey, Kwara State, Off-Grid Electrification
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Background to the Study
Access to reliable, affordable, and clean energy is recognised as a fundamental enabler of human development, economic growth, and poverty reduction. Sustainable Development Goal 7 commits the international community to ensuring universal access to affordable, reliable, sustainable, and modern energy by 2030. Despite this, the International Energy Agency's 2023 World Energy Outlook estimates approximately 685 million people worldwide still lack electricity, with sub-Saharan Africa accounting for 81% of the deficit. Nigeria, despite being Africa's largest petroleum producer, is home to 85 to 90 million people without reliable access – more than any other country.
Nigeria's electricity sector has been characterised by chronic underperformance. Installed capacity of 12,500 to 13,000 MW exists on paper, but actual generation averages only 4,000 to 5,000 MW due to gas shortfalls, transmission limitations, distribution deterioration, and payment failures. This translates into national average of 16 to 20 hours of daily cuts, costing approximately 2 to 3% of GDP annually in diesel self-generation.
In this context, off-grid solar PV has emerged as transformative alternative. Global cost reduction (89% fall 2010-2022 per IRENA) has made solar competitive with diesel and grid even unsubsidised. Pay-as-you-go financing pioneered by ENGIE Energy Access, d.light, and Greenlight Planet enables installment acquisition.
Nigeria's Federal Government recognises off-grid as critical. The Rural Electrification Agency has deployed mini-grids and SHS via Energizing Economies Initiative and Nigeria Mini-Grid Acceleration Scheme. The National Renewable Energy and Energy Efficiency Policy targets 30% renewable by 2030 with solar as primary platform. Yet household adoption remains low and unequal across income, education, geography, and awareness.
Kwara State, located in north-central Nigeria with economy spanning agriculture, education, and small industry, exemplifies these challenges and opportunities. Ilorin is served by KEDC but receives severely rationed supply. Rural LGAs including Baruten, Kaiama, and Edu have extremely limited connectivity, many communities never having had grid infrastructure. State's high irradiance of 5.5 to 6.0 kWh/m2/day makes it technically ideal for solar deployment.
Renewable energy project topics on ScholarnestHub | Environmental and energy economics topics | External: IEA - World Energy Outlook 2023, IRENA - Solar Cost Data, World Bank ESMAP - Multi-Tier Framework
Statement of the Problem
Despite significant reduction in solar PV costs and growing availability of PAYG financing, renewable energy adoption among Kwara State households remains substantially below its potential. Anecdotal evidence and preliminary surveys suggest high awareness but low uptake, with cost, lack of information, distrust of product quality, and limited after-sales support as commonly cited barriers. However, no rigorous statistical study has quantified determinants of adoption specifically for Kwara State households using multivariate regression controlling for confounding sociodemographic variables.
Without this evidence, the Kwara State Rural Electrification Agency and Federal REA cannot rationally target subsidies, awareness campaigns, and technical support to household segments most likely to benefit and least likely to adopt without intervention. Additionally, the premium that households are willing to pay for reliable solar electricity, compared with current expenditure on kerosene, candles, and diesel, has not been estimated using rigorous WTP methodology, preventing evidence-based pricing and subsidy design. This study addresses these gaps through binary logistic regression, ordinal logistic regression, and double-bounded contingent valuation among 384 households across three LGAs.
Aim and Objectives of the Study
The main aim of this study is to conduct a statistical evaluation of renewable energy adoption among households in Kwara State, Nigeria.
· Describe the sociodemographic and energy access profile of sampled households in three Kwara State LGAs.
· Assess the current adoption rates of various renewable energy technologies and identify the most common barriers to adoption.
· Examine bivariate associations between socioeconomic variables and renewable energy adoption using chi-square tests.
· Identify independent determinants of household renewable energy adoption using binary logistic regression.
· Examine determinants of adoption level (technology tier) using ordinal logistic regression.
· Estimate households' willingness to pay for reliable solar electricity using the double-bounded contingent valuation method.
· Make evidence-based recommendations for improving renewable energy adoption in Kwara State.
Research Questions
· What proportion of Kwara State households have adopted renewable energy technologies, and which technologies are most commonly adopted?
· Which socioeconomic and infrastructure factors are most strongly associated with renewable energy adoption?
· What is the mean willingness to pay for reliable solar electricity among non-adopter households in the study area?
· Does income, education, or programme awareness most strongly predict adoption after multivariate adjustment?
Research Hypotheses
H01: Household monthly income does not significantly predict renewable energy adoption status.
H02: Education level of the household head does not significantly influence renewable energy adoption.
H03: Awareness of government solar energy programmes does not significantly predict renewable energy adoption.
H04: Grid electricity outage experience does not significantly influence renewable energy adoption.
(All four null hypotheses were rejected in this study).
Significance of the Study
Programme Significance: Binary logistic regression findings identify which household segments are most and least likely to adopt renewable energy, enabling REA and KWREA to target subsidies and awareness cost-effectively. WTP estimates (N3,847/month, 95% CI: N3,612-N4,082) provide evidence-based pricing guidance balancing viability with affordability.
Academic Significance: Contributes to limited literature on renewable energy adoption in north-central Nigerian states using multivariate methods – chi-square, binary logistic (income aOR=3.247, education aOR=2.184, outage experience aOR=1.987, awareness aOR=2.841, distance aOR=0.624, gender p=0.487 NS), ordinal logistic for technology ladder.
Policy Significance: Ordinal logistic identifies factors predicting moving from lantern (28.4%) to SHS (12.5%) to mini-grid (6.5%) adoption, informing ESMAP technology ladder strategy for progressive electrification. LGA disparity – Ilorin South 64.2%, Asa 44.5%, Baruten 23.4% – highlights rural electrification gap requiring targeted mini-grid deployment.
Statistics project topics on ScholarnestHub | Economics of energy adoption
Scope of the Study
The study covers three Kwara State LGAs: Ilorin South (urban), Asa (peri-urban), and Baruten (rural). Survey data were collected from 384 sampled households between January and February 2025. Environmental data from KWREA and REA supplement primary survey data. Technologies covered include solar PV lanterns (Tier 0-1), solar home systems (Tier 2-3), and solar mini-grid connections (Tier 4-5). Analysis includes descriptive statistics, chi-square tests, binary logistic regression, ordinal logistic regression, and double-bounded contingent valuation for WTP.
Operational Definition of Terms
Renewable Energy Adoption: Acquisition and current use of any off-grid renewable technology, including solar PV lanterns, solar home systems, biomass gasifier, or mini-grid connection.
Solar PV Lantern: Portable solar-powered lantern with 1-5 Wp panel, providing basic lighting, entry-level tier Tier 0-1 in Multi-Tier Framework.
Solar Home System (SHS): Solar PV system at household level, typically 10-100 Wp, providing multi-room lighting plus phone charging and small appliance – Tier 2-3.
Mini-Grid: Small-scale power system 10-500 kW using solar PV with battery or hybrid solar-diesel serving multiple households via distribution network – Tier 4-5.
Willingness to Pay (WTP): Maximum monthly payment household willing to make for reliable solar electricity, elicited via double-bounded dichotomous choice contingent valuation – mean N3,847 in this study.
Grid Outage Experience: Hours per day grid electricity unavailable as reported for past three months, proxy for energy insecurity motivating adoption.
Conclusion
This study shows renewable energy adoption is 47.4% overall but highly unequal geographically: Ilorin South 64.2%, Asa 44.5%, Baruten 23.4%. Solar PV lanterns dominate (28.4%), followed by SHS (12.5%) and mini-grid (6.5%).
Multivariate analysis identified income (aOR 3.247, p<0.001), education (aOR 2.184, p<0.001), programme awareness (aOR 2.841, p<0.001), outage experience (aOR 1.987, p=0.002), and distance from town (aOR 0.624, p<0.001) as significant predictors; gender was not significant (p=0.487). Mean WTP of N3,847 (95% CI N3,612-N4,082) indicates affordability for reliable clean energy above current kerosene/diesel spend.
Recommendations: targeted solar subsidy for lowest-income quintile, expansion of rural mini-grid deployment in Baruten and other rural LGAs, integration of awareness into agricultural extension services, and local solar technician training to address maintenance barriers. Without these, low-income rural households will remain trapped in energy poverty despite high solar potential.
Frequently Asked Questions (FAQs)
What is renewable energy adoption rate in Kwara State?
47.4% overall in sampled 384 households: 64.2% Ilorin South urban, 44.5% Asa peri-urban, 23.4% Baruten rural, showing significant LGA variation.
Which renewable technology is most common?
Solar PV lanterns 28.4% most common, followed by solar home systems 12.5% and solar mini-grid connection 6.5%.
What factors most strongly predict adoption?
Monthly income aOR 3.247, awareness of government programmes aOR 2.841, education aOR 2.184, outage experience aOR 1.987, and distance from town aOR 0.624 – all significant at p<0.01; gender not significant p=0.487.
What is willingness to pay for solar electricity?
Mean WTP N3,847 per month with 95% CI N3,612 to N4,082, estimated via double-bounded contingent valuation, useful for pricing and subsidy design.
Why is adoption lower in Baruten LGA?
Baruten is rural with limited grid, greater distance from towns (negative predictor aOR 0.624), lower income and awareness, indicating need for targeted mini-grid deployment.
What is binary logistic regression in this study?
Binary logistic models adoption status (adopter vs non-adopter) as function of socioeconomic variables, providing adjusted odds ratios controlling for confounders.
What is ordinal logistic regression used for?
Examines determinants of technology tier – moving from lantern (Tier 0-1) to SHS (Tier 2-3) to mini-grid (Tier 4-5), informing progressive electrification strategy per ESMAP ladder.
How does grid outage experience affect adoption?
Households reporting more hours of outage have 1.987 times higher odds of adopting renewable energy, showing energy insecurity motivates off-grid investment.
What is pay-as-you-go solar model?
PAYG enables households to acquire solar systems via installment payments rather than large upfront cost, pioneered by ENGIE, d.light, Greenlight Planet in Nigeria.
What policy recommendations does study make?
Targeted subsidy for lowest-income quintile, rural mini-grid expansion in Baruten, integrate awareness into agricultural extension, and develop local technician training programme for maintenance.
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