"background": "Ghana's power-distribution network has faced persistent reliability challenges, with frequent outages impacting economic development. Existing policy evaluations often rely on aggregate failure rates, lacking the granularity to identify specific equipment vulnerabilities and regional disparities that inform targeted infrastructure investment. ", "purpose and objectives": "This policy analysis aims to develop and apply a novel Bayesian hierarchical model to quantify the reliability of distribution system components. The objective is to provide evidence-based insights for prioritising maintenance and capital renewal within the national grid. ", "methodology": "A Bayesian hierarchical Weibull survival model is employed, treating failure times for transformers, circuit breakers, and lines as right-censored data. The model structure is \ (\, \ (\T X{ij) ), where \ are component-specific shape parameters and X₈₉ are regional covariates. Posterior distributions are estimated using Markov chain Monte Carlo sampling. ", "findings": "The analysis reveals a pronounced spatial heterogeneity in reliability, with the posterior probability that component failure rates in the northern regions exceed the national median being 0. 92 (95% credible interval: 0. 87, 0. 96). Distribution transformers were identified as the most critical component, accounting for an estimated 42% of system unreliability. ", "conclusion": "The hierarchical model successfully disentangles component-specific failure patterns from regional effects, offering a superior evidence base for policy compared to traditional reliability metrics. The findings underscore the necessity of geographically and technically differentiated investment strategies. ", "recommendations": "Policy should mandate the adoption of probabilistic reliability modelling for grid planning. Investment should be prioritised towards transformer replacement programmes in high-failure regions and the establishment of a centralised, component-level failure database to continuously update model parameters. ", "key words": "infrastructure reliability, Bayesian inference, survival analysis, power distribution, grid investment, maintenance policy", "contribution statement": "This paper introduces a
Asante et al. (Mon,) studied this question.
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