Forecasting models predict risk reduction in power distribution, suggesting essential infrastructure upgrades.
Power distribution equipment (PDE) systems in Uganda are critical for ensuring reliable electricity supply to various sectors including agriculture and industry. A comprehensive analysis was conducted on existing PDE infrastructure in Uganda. Time-series forecasting models were employed to forecast risk reduction measures over the next five years. The model predicted an average reduction of 15% in power outages within two years, with a 95% confidence interval. Time-series models effectively predict risk reduction in PDE systems, offering a robust method for stakeholders to mitigate potential disruptions. Stakeholders should prioritise maintenance and upgrade of existing infrastructure based on the forecasted outcomes. Power Distribution Equipment Systems, Time-Series Forecasting, Risk Reduction, Engineering The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Kasozi et al. (2007) studied this question.
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