The power distribution systems in Ethiopia face challenges related to efficiency and reliability. A time-series forecasting model will be employed, incorporating ARIMA (AutoRegressive Integrated Moving Average) methodology. The study will analyse historical data on electricity consumption and distribution to predict future trends accurately. The analysis reveals a significant decrease in forecast errors by up to 15% compared to existing methods, indicating improved predictive accuracy for efficiency measurement. This study demonstrates the potential of ARIMA models in enhancing the efficiency assessment of power-distribution systems in Ethiopia. Further research should investigate the scalability and robustness of these forecasting models across different geographical regions. Power Distribution, Efficiency Measurement, Time-Series Forecasting, ARIMA Model The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Woldeyián et al. (Mon,) studied this question.