Bayesian Hierarchical Model Evaluation of Power-Distribution Equipment Systems in Uganda

Power distribution equipment (PDE) systems in Uganda are critical for ensuring reliable power supply to various sectors such as industry and residential areas. Despite significant investments in infrastructure, there is a need to evaluate and optimise these systems to improve efficiency and reduce costs. A Bayesian hierarchical model was developed using data from several power distribution networks in Uganda. This model accounts for spatial heterogeneity and incorporates prior knowledge about system performance. Data were collected through field surveys and remote sensing techniques, ensuring comprehensive coverage of the study area. The BHM revealed significant yield improvement potential, with an estimated average increase in efficiency by 15% across all regions studied. This finding suggests substantial gains that can be realised through targeted system upgrades and maintenance strategies. This study demonstrates the effectiveness of using a Bayesian hierarchical model for evaluating power distribution equipment systems in Uganda. The results provide valuable information for policymakers, utility companies, and investors to make informed decisions on infrastructure improvements. Based on the findings, it is recommended that investment priorities be directed towards upgrading older PDE systems and implementing preventive maintenance programmes. Additionally, regional disparities should guide targeted interventions to maximise overall efficiency gains. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.