Open Access

ARTICLE

An Efficient MPPT Tracking in Solar PV System with Smart Grid Enhancement Using CMCMAC Protocol

by B. Jegajothi^1,*, Sundaram Arumugam², Neeraj Kumar Shukla³, I. Kathir⁴, Monia Digra⁶

1 Saveetha School of Engineering, SIMATS, Chennai, 602105, India
2 Department of Electrical and Computer Engineering, Navajo Technical University, Crown Point, NM, USA
3 Department of Electrical Engineering, King Khalid University, Abha, Saudi Arabia
4 Department of EEE, V.S.B. Engineering College, Tamilnadu, India
5 Department of Electrical Engineering, Peri Institute of Technology, Tamilnadu, India
6 Department of CSE, Model Institute of Engineering and Technology, Jammu, India

* Corresponding Author: B. Jegajothi. Email:

Computer Systems Science and Engineering 2023, 47(2), 2417-2437. https://doi.org/10.32604/csse.2023.038074

Received 26 November 2022; Accepted 10 April 2023; Issue published 28 July 2023

Abstract

Renewable energy sources like solar, wind, and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment. Because, Since the production of renewable energy sources is still in the process of being created, photovoltaic (PV) systems are commonly utilized for installation situations that are acceptable, clean, and simple. This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking (MPPT) in solar systems with the help of an embedded controller. The adaptive method incorporates both the Whale Optimization Algorithm (WOA) and the Artificial Neural Network (ANN). The WOA was implemented to enhance the process of the ANN model's training, and the ANN model was developed using the WOA. In addition to this, the inverter circuit is connected to the smart grid system, and the strengthening of the smart grid is achieved through the implementation of the CMCMAC protocol. This protocol prevents interference between customers and the organizations that provide their utilities. Using a protocol known as Cross-Layer Multi-Channel MAC (CMCMAC), the effect of interference is removed using the way that was suggested. Also, with the utilization of the ZIGBEE communication technology, bidirectional communication is made possible. The strategy that was suggested has been put into practice, and the results have shown that the PV system produces an output power of 73.32 KW and an efficiency of 98.72%. In addition to this, a built-in regulator is utilized to validate the proposed model. In this paper, the results of various experiments are analyzed, and a comparison is made between the suggested WOA with the ANN controller approach and others, such as the Particle Swarm Optimization (PSO) based MPPT and the Cuckoo Search (CS) based MPPT. By examining the comparison findings, it was determined that the adaptive AI-based embedded controller was superior to the other alternatives.

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Keywords

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