{ "background": "Off-grid energy systems are critical for rural development, yet robust methodologies for evaluating their cost-effectiveness in field conditions are lacking. This creates significant uncertainty for policymakers and implementers in the agricultural sector regarding optimal diagnostic approaches. ", "purpose and objectives": "This study aims to compare the diagnostic efficacy and cost-effectiveness of three methodological approaches for assessing off-grid solar systems in rural agricultural communities. It seeks to determine which method provides the most reliable performance data per unit of investment. ", "methodology": "A quasi-experimental design was employed across 45 rural communities. Three diagnostic methodologies—community-led reporting, technician-led spot checks, and continuous remote monitoring—were randomly assigned. Cost-effectiveness was analysed using a generalised linear model: \ (-Effectivenessi) = \0 + \1 + \2 + \ᵢ, with inference based on robust standard errors clustered at the district level. ", "findings": "Remote monitoring was significantly more cost-effective for identifying major system faults, detecting 34% more critical failures per £1000 spent compared to technician-led checks (95% CI: 22% to 46%). Community-led reporting, while lowest in direct cost, yielded the highest rate of false positives and incomplete data, reducing its overall utility for technical diagnostics. ", "conclusion": "The choice of diagnostic methodology substantially impacts the perceived performance and value of off-grid energy systems. Remote monitoring, despite higher upfront costs, provides superior, actionable data for maintenance planning in agricultural settings. ", "recommendations": "Policymakers and project implementers should allocate resources for integrated diagnostic strategies that combine remote monitoring for major infrastructure with simplified community reporting for user-experience feedback. Funding models should reflect the long-term data benefits of remote technologies. ", "key words": "cost-effectiveness analysis, energy diagnostics, quasi-experiment, rural electrification, solar PV, sub-Saharan Africa", "contribution statement
Asare et al. (Tue,) studied this question.