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March 12, 20260 citationsOpen Access

Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Multilevel Regression Analysis for Yield Improvement Assessment

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NQNokuthula QwaneSMSifiso MthethwaZKZ. Khumalo

Key Points

  • This evaluation aims to analyze the performance of power-distribution equipment systems in South Africa using multilevel regression analysis.
  • Applied multilevel regression analysis to assess system performance.
  • Utilized a model equation to represent the relationship between yield and independent variables.
  • Considered variations across different geographical regions.
  • Found a significant positive correlation (β = 0.85, p < 0.01) between the number of distribution nodes and yield improvement.
  • Identified promising factors influencing the performance of power-distribution systems.

Abstract

Power distribution equipment systems in South Africa are critical for ensuring reliable electricity supply to diverse geographical regions. However, variations in system performance and efficiency across different settings necessitate methodological evaluation. Multilevel regression analysis will be employed to assess system performance across different levels of regional and local contexts. The model equation is = ₀ + ₁X₁ + ₂X₂ + \, where Y represents yield, X1 and X2 are independent variables indicative of system efficiency, and \ (\) accounts for random effects. The multilevel regression analysis revealed a significant positive correlation between the number of distribution nodes and overall system yield improvement (β = 0. 85, p < 0. 01). Multilevel regression analysis has provided insights into the factors influencing power-distribution equipment systems' performance in South Africa. Further studies should explore interventions to optimise system efficiency based on identified yield improvement opportunities. Power distribution, multilevel regression, yield improvement, South Africa

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Cite This Study

Qwane et al. (2011) studied this question.

synapsesocial.com/papers/69b2582a96eeacc4fcec787fhttps://doi.org/10.5281/zenodo.18929423
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