{ "background": "Diagnostic systems for power-distribution equipment are promoted to enhance grid reliability, yet robust field evidence of their cost-effectiveness in sub-Saharan African contexts is scarce. Previous studies, often based on modelled data or controlled environments, lack validation through randomised field trials. ", "purpose and objectives": "This study replicates and extends a prior methodological evaluation by implementing a randomised field trial to empirically measure the cost-effectiveness of a transformer health diagnostics system within an operational utility in Kenya. The primary objective is to determine whether the diagnostic intervention reduces the total cost of ownership per distribution transformer. ", "methodology": "A randomised controlled trial was conducted where 400 distribution transformers were randomly assigned to treatment (diagnostics installed) and control groups. Cost-effectiveness was evaluated over an operational period using a generalised linear model: \ (Ci) = \0 + \1 Ti + \\ + \, where Ci is total cost, Ti is the treatment indicator, and ᵢ is a vector of covariates. Inference was based on robust standard errors. ", "findings": "The diagnostic intervention reduced the mean total cost of ownership by approximately 18% (95% CI: 12% to 24%). This reduction was primarily driven by a 35% decrease in unplanned repair costs and a significant reduction in catastrophic failure rates. ", "conclusion": "The replication confirms that implementing transformer diagnostics in this context is a cost-effective strategy for improving asset management. The results are robust to the randomised field trial methodology, providing stronger causal evidence than prior observational studies. ", "recommendations": "Utilities in similar regional contexts should consider integrating targeted diagnostic systems into their maintenance programmes. Further research should investigate the scalability and long-term sustainability of such interventions across different network architectures. ", "key words": "power distribution, asset management, randomised controlled trial, cost-benefit analysis, sub-Saharan Africa, reliability engineering", "contribution statement
Mwangi et al. (Thu,) studied this question.
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