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September 18, 2025LAUTECH Journal of engineering and TechnologyOpen Access

Techno-economic optimization of a standalone hybrid pv-diesel-battery system for rural electrification using genetic algorithm

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Authors

EOE. O. OniGAGafari Abiola AdepojuGAGaniyu Adedayo Ajenikoko

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Overview

Analysis reveals genetic algorithm optimization improves cost efficiency and reliability in rural energy solutions.

Key Points

  • The genetic algorithm optimization achieved a cost of energy of $0.10/kWh with 0% loss of power supply probability.
  • Utilizing a hybrid renewable energy system, emissions were reduced to 84.2 kg of CO₂ daily, demonstrating environmental benefits.
  • Field surveys provided local weather and load data for a robust mathematical model supporting the optimization process.
  • This approach highlights the role of AI-driven methods in enhancing rural electrification aligned with sustainable development goals.

Cite This Study

Oni et al. (2025) studied this question.

synapsesocial.com/papers/68d462d231b076d99fa62541https://doi.org/10.36108/laujet/5202.91.0440
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