Open Access

ARTICLE

Maximizing Solar Potential Using the Differential Grey Wolf Algorithm for PV System Optimization

by Ezhilmathi Nagarathinam¹, Buvana Devaraju², Karthiyayini Jayamoorthy³, Padmavathi Radhakrishnan⁴, Santhana Lakshmi ChandraMohan⁵, Vijayakumar Perumal⁶, Karthikeyan Balakrishnan^7,*

1 Department of Electrical and Electronics Engineering, Pandian Saraswathiyadav Engineering College, Sivagangai, Tamil Nadu, 630561, India
2 Department of Electrical and Electronics Engineering, Sri Balaji Chockalingam Engineering College, Arni, Tamil Nadu, 632317, India
3 Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore, 560103, India
4 Department of Electrical and Electronics Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, 602105, India
5 Department of Electrical and Electronics Engineering, Sona College of Technology, Salem, Tamil Nadu, 636005, India
6 School of Electronics Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, 600127, India
7 Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, 641008, India

* Corresponding Author: Karthikeyan Balakrishnan. Email:

Energy Engineering 2024, 121(8), 2129-2142. https://doi.org/10.32604/ee.2024.052280

Received 28 March 2024; Accepted 31 May 2024; Issue published 19 July 2024

Abstract

Maximum Power Point Tracking (MPPT) is crucial for maximizing the energy output of photovoltaic (PV) systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental conditions. This work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer (DGWO). It dynamically adjusts the parameters of the MPPT controller, specifically the duty cycle of the SEPIC converter, to efficiently track the Maximum Power Point (MPP). The proposed system aims to enhance the energy harvesting capability of solar PV systems by optimizing their performance under varying solar irradiance, temperature and shading conditions. Simulation results demonstrate the effectiveness of the DGWO-based MPPT system in maximizing the power output of solar PV installations compared to conventional MPPT methods. This research contributes to the development of advanced MPPT techniques for improving the efficiency and reliability of solar energy systems.

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