"background": "The reliability of power-distribution networks in developing economies is often constrained by ageing infrastructure and limited maintenance regimes. Systematic, quantitative evaluations of equipment performance and intervention efficacy are scarce, hindering evidence-based asset management and investment planning. ", "purpose and objectives": "This case study aims to develop and apply a robust methodological framework for evaluating the impact of a nationwide equipment refurbishment programme on network reliability. It seeks to quantify the causal effect of the intervention while controlling for external confounding factors. ", "methodology": "A quasi-experimental difference-in-differences (DiD) model is employed, leveraging panel data from treated and control groups of substations. The core statistical model is Y{it = \0 + \1 + \2 + \ (\) +, where Yit is the System Average Interruption Duration Index (SAIDI). Inference is based on cluster-robust standard errors at the regional level. ", "findings": "The refurbishment programme yielded a statistically significant reduction in SAIDI. Estimates indicate a 22% decrease in average outage duration for treated substations relative to the control group, with a 95% confidence interval of 18%, 26%. The parallel trends assumption, critical to the DiD design, was validated using pre-intervention data. ", "conclusion": "The applied DiD model provides a rigorous, transferable methodology for isolating the causal impact of infrastructure interventions on reliability metrics. The results demonstrate the substantial effectiveness of targeted equipment refurbishment. ", "recommendations": "Utilities should adopt quasi-experimental evaluation frameworks for major capital projects. Future planning should prioritise proactive refurbishment cycles informed by similar reliability-centred analyses to optimise resource allocation. ", "key words": "power distribution, reliability engineering, difference-in-differences, causal inference, asset management, infrastructure
Ssebaggala et al. (Sat,) studied this question.