In this work, Perturb and Observe MPPT is innovatively proposed to be merged with PSO for enhanced fault detection capabilities and overall performance of a solar PV system. This establishes that the proposed system ensures real-time optimal performance and reliability of the photovoltaic solar system by merging the fault detection algorithms with the process of MPPT. Particle Swarm Optimization tunes the P&O algorithm parameters for efficient power extraction from the PV panel even under Partial Shading Conditions (PSC). The same fault detection scheme will trigger an alert to the system for regular maintenance and repair. The system is implemented and tested in diverse operating conditions to validate the proposed approach. The results of this work therefore show that the system yields higher efficiency and more reliable results as compared to conventional methods under identical Partial Shading Conditions, and especially under faulty conditions.

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Enhanced Fault Detection in Solar Photovoltaic Systems Using PSO

  • M. S. Sivagama Sundari,
  • D. L. Ahila

摘要

In this work, Perturb and Observe MPPT is innovatively proposed to be merged with PSO for enhanced fault detection capabilities and overall performance of a solar PV system. This establishes that the proposed system ensures real-time optimal performance and reliability of the photovoltaic solar system by merging the fault detection algorithms with the process of MPPT. Particle Swarm Optimization tunes the P&O algorithm parameters for efficient power extraction from the PV panel even under Partial Shading Conditions (PSC). The same fault detection scheme will trigger an alert to the system for regular maintenance and repair. The system is implemented and tested in diverse operating conditions to validate the proposed approach. The results of this work therefore show that the system yields higher efficiency and more reliable results as compared to conventional methods under identical Partial Shading Conditions, and especially under faulty conditions.