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Arithmetic optimization based MPPT for photovoltaic systems operating under nonuniform situations.

Maheshwari Adaikkappan1, Nageswari Sathiyamoorthy2, Durga Devi Ravichandran3

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This study introduces an Arithmetic Optimization Algorithm (AOA) for Maximum Power Point Tracking (MPPT) in photovoltaic systems facing non-uniform conditions. The AOA-MPPT effectively enhances power output and efficiency even with varying solar irradiation.

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Area of Science:

  • Renewable Energy Systems
  • Electrical Engineering
  • Optimization Algorithms

Background:

  • Photovoltaic (PV) modules often operate under non-uniform solar irradiation, leading to reduced power output and ineffective Maximum Power Point Tracking (MPPT).
  • The presence of bypass diodes in PV modules creates multi-peak power-voltage (P-V) curves under varying irradiance, complicating standard MPPT.
  • Existing MPPT methods struggle to maintain optimal performance when PV systems encounter partial shading or uneven sunlight distribution.

Purpose of the Study:

  • To propose and validate an Arithmetic Optimization Algorithm (AOA) for robust MPPT in PV systems under non-uniform irradiation conditions.
  • To enhance the tracking efficiency and dynamic response of PV systems by overcoming the challenges posed by multi-peak P-V curves.
  • To integrate the AOA-MPPT with a single-ended primary inductance converter (SEPIC) for efficient voltage regulation and operation point tracking.

Main Methods:

  • Utilizing an Arithmetic Optimization Algorithm (AOA) to perform Maximum Power Point Tracking (MPPT) in photovoltaic systems.
  • Employing a single-ended primary inductance converter (SEPIC) with voltage step-up/step-down capabilities to exclude non-operational voltage regions.
  • The AOA-MPPT algorithm takes PV module current and voltage as inputs to compute the converter's duty cycle and maintain the maximum power point (MPP).

Main Results:

  • The proposed AOA-MPPT demonstrated quick response and excellent steady-state performance in simulations under various non-uniform insolation patterns.
  • Tracking efficiency of the AOA-MPPT consistently remained above 99% across all tested non-uniform conditions.
  • The settling time for the AOA-MPPT was observed to be between 200 to 300 milliseconds, indicating rapid convergence.

Conclusions:

  • The Arithmetic Optimization Algorithm (AOA) provides an effective solution for MPPT in photovoltaic systems operating under non-uniform conditions.
  • The integration of AOA-MPPT with a SEPIC converter ensures reliable tracking of the maximum power point despite challenges like partial shading.
  • The proposed method significantly improves tracking efficiency and response speed, making PV systems more robust and productive.