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Implementation of FPGA Based MPPT Techniques for Grid-Connected PV System

Thamatapu Eswara Rao*, S. Elango

Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology, Coimbatore, India

* Corresponding Author: Thamatapu Eswara Rao. Email: email

Intelligent Automation & Soft Computing 2023, 35(2), 1783-1798. https://doi.org/10.32604/iasc.2023.028835

Abstract

Global energy demand is growing rapidly owing to industrial growth and urbanization. Alternative energy sources are driven by limited reserves and rapid depletion of conventional energy sources (e.g., fossil fuels).Solar photovoltaic (PV), as a source of electricity, has grown in popularity over the last few decades because of their clean, noise-free, low-maintenance, and abundant availability of solar energy. There are two types of maximum power point tracking (MPPT) techniques: classical and evolutionary algorithm-based techniques. Precise and less complex perturb and observe (P&O) and incremental conductance (INC) approaches are extensively employed among classical techniques. This study used a field-programmable gate array (FPGA)-based hardware arrangement for a grid-connected photovoltaic (PV) system. The PV panels, MPPT controllers, and battery management systems are all components of the proposed system. In the developed hardware prototype, various modes of operation of the grid-connected PV system were examined using P&O and incremental conductance MPPT approaches.

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APA Style
Rao, T.E., Elango, S. (2023). Implementation of FPGA based MPPT techniques for grid-connected PV system. Intelligent Automation & Soft Computing, 35(2), 1783-1798. https://doi.org/10.32604/iasc.2023.028835
Vancouver Style
Rao TE, Elango S. Implementation of FPGA based MPPT techniques for grid-connected PV system. Intell Automat Soft Comput . 2023;35(2):1783-1798 https://doi.org/10.32604/iasc.2023.028835
IEEE Style
T.E. Rao and S. Elango, "Implementation of FPGA Based MPPT Techniques for Grid-Connected PV System," Intell. Automat. Soft Comput. , vol. 35, no. 2, pp. 1783-1798. 2023. https://doi.org/10.32604/iasc.2023.028835



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