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Application of Fuzzy FoPID Controller for Energy Reshaping in Grid Connected PV Inverters for Electric Vehicles

M. Manjusha1,*, T. S. Sivarani2, Carol J. Jerusalin1

1Department of EEE, Mar Ephraem College of Engineering and Technology, Elavuvilai, Marthandam, 629171, India
2Department of EEE, Arunachala College of Engineering for Women, Manavilai, Vellichanthai, 629203, India

* Corresponding Author: M. Manjusha. Email:

Intelligent Automation & Soft Computing 2022, 32(1), 621-641.


By utilizing Fuzzy based FOPID-controller, this work is designed via the energy reshaping concept for Grid connected Photovoltaic (PV) systems for electric vehicles and this PV module has its own inverter which is synchorised with the utility grid. In grid connected PV system, the mitigation plays an important role where the capacity of PV arrays increases it maintains power quality and it is necessary to comply with some requirements such as harmonic mitigation. Unless a maximum power point tracking (MPPT) algorithm is used, PV systems do not continuously produce their theoretical optimal power. Under various atmospheric conditions, MPPT is obtained by using Perturb and Observe (P&O) techniques. A storage function in terms of DC-link voltage and current, and q-axis current is created, by means of which physical characteristics are studied. Further the energy reshaping is done with the aid of the proposed Fuzzy Fractional Order PID (Fuzzy-FoPID) framework. The FOPID control parameters λ and μ are optimally tuned by Grey Wolf Optimization technique (GWO). The results obtained verify the advantages of using Fuzzy-FoPID control as compared to conventional PID (Proportional Integral Derivative) control and FoPID control. The injected reactive power into the grid and the efficiency of the proposed systems is studied by extensive simulations.


Cite This Article

M. Manjusha, T. S. Sivarani and C. J. Jerusalin, "Application of fuzzy fopid controller for energy reshaping in grid connected pv inverters for electric vehicles," Intelligent Automation & Soft Computing, vol. 32, no.1, pp. 621–641, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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