Abstract
{ "background": "Power-distribution losses in many developing nations remain persistently high, undermining grid reliability and economic development. In Tanzania, technical and non-technical losses have historically constrained the efficiency of the national grid, yet comprehensive methodological evaluations of system-wide equipment performance are scarce.", "purpose and objectives": "This case study aims to methodologically evaluate the efficiency of Tanzania's power-distribution equipment systems. Its objectives are to develop a robust analytical framework for quantifying efficiency gains and to identify the principal technical factors driving performance variability across the network.", "methodology": "A multilevel regression analysis was applied to a longitudinal, system-level dataset comprising technical performance indicators. The core statistical model is specified as $y{ij} = \\beta{0} + \\beta{1}X{ij} + u{j} + e{ij}$, where $y{ij}$ is the efficiency metric for transformer $i$ in region $j$, $X{ij}$ denotes a vector of equipment-level covariates, $u{j}$ represents regional random effects, and $e{ij}$ is the residual error. Inference was based on robust standard errors.", "findings": "The analysis indicates a statistically significant positive relationship between targeted equipment upgrades and systemic efficiency. A key concrete result is that the modernisation of ageing circuit breakers and switchgear was associated with an estimated 7.5 percentage point reduction in technical losses (95% CI: 5.2 to 9.8). Regional heterogeneity accounted for approximately 22% of the total variance in efficiency outcomes.", "conclusion": "The methodological approach confirms that multilevel modelling effectively captures the hierarchical structure of distribution network data. It provides a validated framework for isolating the impact of specific equipment interventions from broader regional operational disparities.", "recommendations": "Utilities should adopt hierarchical modelling for future investment planning and performance benchmarking. Priority should be given to programmes targeting the identified high-impact equipment categories, with monitoring systems adapted to collect data at appropriate hierarchical levels.", "key words": "power distribution,