What question did this study set out to answer?

The aim is to assess the performance of forecasting models for power-distribution systems in Ethiopia and identify potential yield improvements.

March 12, 2026Open Access

Time-Series Forecasting Model Evaluation for Power-Distribution Equipment Systems in Ethiopia: A Methodological Approach

Puntos clave

The aim is to assess the performance of forecasting models for power-distribution systems in Ethiopia and identify potential yield improvements.
Data collection and preprocessing of power system data.
Development of a hybrid ARIMA-GARCH time-series forecasting model.
Validation of the model using out-of-sample testing.
Conducting sensitivity analysis to evaluate forecasting performance.
The hybrid ARIMA-GARCH model achieved an average R-squared value of 0.85 across datasets.
Significant improvement in forecast accuracy was observed compared to traditional models.
Substantial yield enhancement potential was identified through optimized forecasting practices.

Resumen

This study focuses on power-distribution equipment systems in Ethiopia, assessing their performance through time-series forecasting models to identify yield improvements. A comprehensive approach was adopted to develop and validate a hybrid ARIMA-GARCH (AutoRegressive Integrated Moving Average-Generalized Autoregressive Conditional Heteroskedasticity) time-series forecasting model for Ethiopian power distribution systems. The methodology involved data collection, preprocessing, model development, validation using out-of-sample testing, and sensitivity analysis. The findings indicate a significant improvement in forecast accuracy with the hybrid ARIMA-GARCH model, achieving an R-squared value of 0. 85 on average across all datasets analysed, suggesting substantial yield enhancement potential through optimised forecasting. This study contributes to the methodological framework for power distribution system performance evaluation and management by introducing a robust time-series forecasting approach that outperforms traditional models in terms of accuracy and reliability. Based on these findings, recommendations include the implementation of the hybrid ARIMA-GARCH model as a standard practice for monitoring and optimising Ethiopian power distribution systems. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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