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Design and Analysis of Improved Mountain Gazelle Optimization Tuned PID and FOPID Controllers for PV MPPT System

Hemachandran Veerasamy*, Arounassalame Mouttou**, Rathidevi U.***

*-*** Department of Electrical and Electronics Engineering, Puducherry Technological University, Puducherry, India.

Periodicity:April - June'2024
DOI : https://doi.org/10.26634/jee.17.4.20985

Abstract

The solar photovoltaic (PV)-based Maximum Power Point Tracking (MPPT) systems have gained popularity in recent times. This work proposes the improvement and implementation of a newly introduced optimization technique, the Improved Mountain Gazelle Optimization (IMGO) algorithm, for tuning the Fractional Order Proportional-Integral-Derivative (FOPID) and Proportional-Integral-Derivative (PID) controllers for the MPPT control strategy. The performances of the controllers were evaluated with reference to error criteria and settling time of the response. The performance parameters mentioned above are compared with those of PID and FOPID controllers tuned using Genetic Algorithm (GA) and Grey-Wolf Optimization (GWO) algorithms. The simulation study was carried out in the MATLAB/SIMULINK environment. The analysis found that the FOPID controller tuned using the Improved Mountain Gazelle Optimization algorithm provides better results in terms of settling time and error when compared to the PID controller.

Keywords

Boost Converter, PID Controller, FOPID Controller, Improved Mountain Gazelle Optimization, Maximum Power Point Tracking.

How to Cite this Article?

Veerasamy, H., Mouttou, A., and Rathidevi, U. (2024). Design and Analysis of Improved Mountain Gazelle Optimization Tuned PID and FOPID Controllers for PV MPPT System. i-manager’s Journal on Electrical Engineering, 17(4), 1-10. https://doi.org/10.26634/jee.17.4.20985

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