A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions

  • Abstract
  • Keywords
  • References
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  • Abstract

    In this study, a hybrid Ant Colony Optimization-Particle Swarm Optimization (ACO-PSO) algorithm was proposed to optimally determine the maximum power point tracking (MPPT) parameters. The main goal of current study is to improve the overall performance of the MPPT system.The efforts of oscillation filtering and noise suppression were taken in this design, as well as the time response and the settling time. The proposed method is employed to track the global MPP under different shadow conditions, based on three different irradiation levels to test the ability and accuracy of the proposed method. The results of tracking MPP by the proposed MPPT technique showed that the improved method tracked the MPP for all the tested cases with a reasonable accuracy and in a very short convergence time as compared to the P&O method.



  • Keywords

    Ant Colony Optimization; Maximum Power Point Tracking; MPPT accuracy; MPPT convergence time; MPPT performance; MPPT settling time; P&O; Particle Swarm Optimization.

  • References

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Article ID: 23613
DOI: 10.14419/ijet.v7i4.37.23613

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