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March 7, 20260 citationsOpen Access

Forecasting Adoption Rates in Nigerian Power-Distribution Equipment Systems Using Time-Series Models

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OAOsita AgbakachiwaCUChinedu Ugwuoye

Key Points

  • The aim is to forecast adoption rates of power distribution equipment systems in Nigeria using time-series analysis.
  • Utilized ARIMA model for forecasting based on historical data
  • Analyzed adoption rates across different regions of Nigeria
  • Evaluated the future trends over a five-year period
  • Predicted an average increase of 2.5% in adoption rates
  • Confidence interval ranged from 1.8% to 3.2%
  • Implications for targeted interventions to improve adoption rates in low-performance regions

Abstract

Nigeria's power distribution equipment (PDE) systems face significant challenges in terms of reliability and efficiency, with adoption rates varying across different regions. A comprehensive analysis using ARIMA (AutoRegressive Integrated Moving Average) model was conducted to forecast future adoption rates based on historical data from various regions. The ARIMA model predicted an average increase of 2. 5% in PDE system adoption over the next five years, with a confidence interval ranging from 1. 8% to 3. 2%. This finding highlights the potential for targeted interventions to boost adoption rates. ARIMA models provide valuable insights into future trends and can aid policymakers in formulating strategies to enhance PDE system performance and user satisfaction. Policymakers should consider implementing ARIMA-based forecasting as a tool for planning and resource allocation, particularly focusing on regions with lower adoption rates. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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Cite This Study

Agbakachiwa et al. (2008) studied this question.

synapsesocial.com/papers/69abc2725af8044f7a4ec0f0https://doi.org/10.5281/zenodo.18879336
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