Power-distribution systems in many developing nations face persistent challenges with equipment reliability and yield losses. In Kenya, ageing infrastructure and operational inefficiencies have constrained the sector's performance, necessitating a rigorous, data-driven evaluation to inform strategic upgrades. This case study aims to methodologically evaluate the performance of power-distribution equipment systems. Its objective is to quantify yield improvements over time and identify the key technical and operational factors driving these changes. A panel-data estimation approach is employed, analysing longitudinal operational data from multiple distribution networks. The core fixed-effects model is specified as Y₈ₓ = ᵢ + X₈ₓ + ₜ + ₈ₓ, where Y₈ₓ is the yield metric for network i at time t. Robust standard errors were clustered at the network level to account for serial correlation. The analysis indicates a statistically significant positive trend in aggregate system yield following targeted interventions. A key finding is that the modernisation of transformer fleets was associated with an estimated 7. 5 percentage point improvement in technical yield (95% CI: 5. 2, 9. 8), holding other factors constant. The methodological application of panel-data models provides robust evidence that systematic equipment investment and maintenance regimes are central to enhancing distribution efficiency in the studied context. Utilities should prioritise capital investment in transformer modernisation programmes and adopt continuous panel-data monitoring to dynamically assess asset performance and guide preventative maintenance schedules. power distribution, panel data, fixed-effects model, yield improvement, asset management, Kenya This study provides a novel application of econometric panel-data methods to engineering asset performance analysis, creating a replicable framework for quantifying the long-term yield impact of infrastructure investments in power-distribution networks.
Mwangi et al. (Thu,) studied this question.
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