An Empirical Reliability Assessment and Forecast of the Auchi Power Distribution Network, Edo State, Nigeria.

This study presents an empirical reliability assessment and forecast of the Auchi power distribution network in Nigeria, addressing the scarcity of granular, data-driven analyses in the sector. Utilizing a case study research design, the study analyzed actual 2023 operational data for three 11kV feeders—Auchi Town, Jattu, and Auchi GRA—obtained from the Benin Electricity Distribution Company (BEDC). The methodology involved a quantitative, two-phase approach: first, computing standard reliability indices (SAIDI, SAIFI, CAIDI, ASAI) based on IEEE Standard 1366, and second, employing the Facebook Prophet time-series model to forecast ASAI values from 2024 to 2035. The empirical results for 2023 revealed critically low and variable reliability, with the Jattu feeder, for instance, recording an ASAI of 0.1614 in February, indicating power was available only 16.14% of the time. The forecast revealed starkly divergent feeder trajectories: stagnation for Auchi Town, seasonal variation for Jattu, and consistent improvement for Auchi GRA. These findings provide crucial evidence of significant service disparity and underscore the urgent need for feeder-specific investment and policy interventions. The study demonstrates a replicable framework combining reliability indices and predictive modeling to guide targeted maintenance and planning in similar contexts.

Reliability Indices, Predictive Modeling, Power Distribution

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