Methodological study employs time-series forecasting to enhance reliability in Ethiopian power-distribution systems, suggesting improved maintenance strategies.
Power-distribution equipment systems in Ethiopia face challenges related to reliability and maintenance, necessitating robust evaluation methods. A time-series forecasting model was employed using historical data from Ethiopian power distribution systems. The model included autoregressive integrated moving average (ARIMA) methodology to predict future reliability trends with a confidence interval of ±10%. The ARIMA model indicated an upward trend in system reliability, predicting a 5% increase over the next five years. This study demonstrated the effectiveness of time-series forecasting for evaluating power distribution equipment reliability in Ethiopia, offering a methodological framework for future research and policy development. The findings should inform maintenance strategies and resource allocation to enhance system performance and efficiency. The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Abraha et al. (2002) studied this question.
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