Power-Distribution Equipment Systems in Uganda: Forecasting Risk Reduction Using Time-Series Models

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 $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.