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Hybrid Genetic Algorithm-Based Optimal Sizing of a PV–Wind–Diesel–Battery Microgrid: A Case Study for the ICT Center, Ethiopia

Author

Listed:
  • Adnan Kedir Jarso

    (Department of Electrical Power and Control Engineering, Graduate School, Adama Science and Technology University, Adama P.O. Box 1888, Ethiopia)

  • Ganggyoo Jin

    (Department of Electrical Power and Control Engineering, Adama Science and Technology University, Adama P.O. Box 1888, Ethiopia)

  • Jongkap Ahn

    (Training Ship Operation Center, Gyeongsang National University, Tongyeong-si 53064, Republic of Korea)

Abstract

This study presents analysis and optimization of a standalone hybrid renewable energy system (HRES) for Adama Science and Technology University’s ICT center in Ethiopia. The proposed hybrid system combines photovoltaic panels, wind turbines, a battery bank, and a diesel generator to ensure reliable and sustainable power. The objectives are to minimize the system’s total annualized cost and loss of power supply probability, while energy reliability is maintained. To optimize the component sizing and energy management strategy of the HRES, we formulated a mathematical model that incorporates the variability of renewable energy and load demand. This optimization problem is solved using a hybrid genetic algorithm (HGA). Simulation results indicate that the HGA yielded the best solution, characterized by the levelized cost of energy of USD 0.2546/kWh, the loss of power supply probability of 0.58%, and a convergence time of 197.2889 s.

Suggested Citation

  • Adnan Kedir Jarso & Ganggyoo Jin & Jongkap Ahn, 2025. "Hybrid Genetic Algorithm-Based Optimal Sizing of a PV–Wind–Diesel–Battery Microgrid: A Case Study for the ICT Center, Ethiopia," Mathematics, MDPI, vol. 13(6), pages 1-28, March.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:6:p:985-:d:1614195
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