A Randomised Field Trial Methodology for Cost-Effectiveness Evaluation of Power-Distribution Infrastructure in Nigeria

{ "background": "The persistent inefficiency of power-distribution infrastructure in Nigeria necessitates robust, evidence-based methods for evaluating the cost-effectiveness of new equipment and interventions. Current evaluation practices often rely on laboratory tests or non-randomised field deployments, which fail to account for real-world operational heterogeneity and confounding factors.", "purpose and objectives": "This article presents a novel methodology for conducting a randomised field trial (RFT) specifically designed to evaluate the cost-effectiveness of power-distribution equipment, such as transformers and conductors, within the Nigerian grid. The objective is to provide a rigorous framework for comparing the lifecycle costs and performance of different technological systems under actual operating conditions.", "methodology": "The proposed RFT methodology employs a cluster-randomised design, where geographically distinct distribution feeders serve as experimental units. Feeders are randomly assigned to receive either the new intervention equipment or the existing standard equipment. Cost-effectiveness is measured via a primary composite metric, the Total Owning Cost per Unit Reliability (TOCUR), calculated over the trial period. The analysis employs a linear mixed-effects model: ij = \μ + \τ \· i + \β Xij + uj + \εij, where uj is a random intercept for region j, and Xᵢⱼ are feeder-level covariates. Inference will utilise robust standard errors clustered at the regional level.", "findings": "As a methodology article, this paper presents no empirical trial results. However, the detailed protocol specifies that the primary analysis will determine the direction and magnitude of the cost-effectiveness ratio, with a minimum detectable difference in TOCUR of 15% set a priori. Power calculations indicate that a minimum of 40 feeder clusters per treatment arm is required to achieve 80% power at a 5% significance level.", "conclusion": "The structured RFT methodology provides a scientifically rigorous framework for generating high-quality evidence on the economic and operational performance of power-distribution