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March 2, 20260 citationsOpen Access

Time-Series Forecasting Model for Evaluating Off-Grid Community Systems in Kenya,

NNNaikai NanyakiKMKipruto MuriukiOOOkoth Opiyo

Key Points

  • The aim is to evaluate the cost-effectiveness of off-grid community systems in Kenya using a time-series forecasting model.
  • Developed a forecasting model using historical electricity usage data.
  • Employed robust statistical techniques to manage data uncertainties.
  • Estimated model parameters using a specific optimization method.
  • Evaluated model performance through out-of-sample error.
  • Forecast indicates a 10% annual reduction in per capita system costs over five years.
  • Improvements reflect enhanced efficiency and economies of scale.
  • Identified limitations like data variability and potential technological obsolescence.

Abstract

Off-grid community systems in Kenya have evolved significantly over recent years, yet their cost-effectiveness remains a subject of debate and evaluation. A time-series forecasting model was developed using historical data on electricity usage, cost structures, and technological advancements within off-grid community systems. Robust statistical techniques were employed to account for uncertainties in the data. The forecast indicated a steady decline in per capita system costs over five years, with an average reduction of approximately 10% annually, reflecting improved efficiency and economies of scale. The time-series model provided valuable insights into cost-effectiveness trends but acknowledged limitations such as data variability and potential technological obsolescence. Further research should focus on incorporating real-time data inputs to enhance the predictive accuracy of future forecasting models. Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.

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Cite This Study

Nanyaki et al. (2005) studied this question.

synapsesocial.com/papers/69a52de5f1e85e5c73bf1066https://doi.org/10.5281/zenodo.18817914
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