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Genetic Algorithm Optimization of Power Transfer Limit for Enhancement of Stability of Power System

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  • Aliyu Abubakar

    (Department of Electrical and Electronics Engineering Technology Federal Polytechnic, Bali Taraba State)

  • Mohammad Buhari Mohammad

    (Department of Electrical and Electronics Engineering Technology Federal Polytechnic, Bali Taraba State)

Abstract

The work presents the Genetic Algorithm (GA) as an innovative method for optimizing power transfer limits to improve the stability of power systems. This is especially important given the increasing integration of renewable energy and the growing complexity of power networks. Traditional static threshold methods often lead to inefficiencies and instability during periods of high demand or fluctuating renewable generation. The GA tackles these challenges by representing potential solutions as chromosomes that evolve over successive generations through processes inspired by natural selection. These processes include initialization, fitness evaluation, selection, crossover, mutation, and replacement. The results of the genetic algorithm optimization indicate the optimal threshold value of 1.0564602 for the power transfer limit of the power systems. This dynamic adaptation ensures robust and efficient solutions, ultimately improving power transfer efficiency and meeting constraints to prevent overloads and voltage instability. Ultimately, the GA enhances overall power system performance by ensuring efficient and reliable operation in the face of modern challenges.

Suggested Citation

  • Aliyu Abubakar & Mohammad Buhari Mohammad, 2024. "Genetic Algorithm Optimization of Power Transfer Limit for Enhancement of Stability of Power System," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(6), pages 523-529, June.
    • Handle: RePEc:bjf:journl:v:9:y:2024:i:6:p:523-529
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