10.57647/j.mjee.2025.1901.02

Fuzzy controller optimized by the grasshopper algorithm to realize maximum power in photovoltaic systems

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  • Kamran Safaei1,
  • Aida Esmaeilian-Marnani*2,
  • Hossein Emami3,
  • Amir Hossein Zaeri4,
  1. Department of Electrical Engineering, Majlesi Branch, Islamic Azad University, Isfahan, Iran
  2. Department of Electrical Engineering, Mobarakeh Branch, Islamic Azad University, Isfahan, Iran
  3. Department of Skill Development and Entrepreneurship, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
  4. Department of Electrical Engineering, Shahinshahr Branch, Islamic Azad University, Isfahan, Iran

Received: 2024-09-04

Revised: 2024-11-16

Accepted: 2024-11-23

Published in Issue 2025-03-01

Copyright (c) 2025 ©The Author(s)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Safaei, K., Esmaeilian-Marnani, A., Emami, H., & Zaeri, A. H. (2025). Fuzzy controller optimized by the grasshopper algorithm to realize maximum power in photovoltaic systems. Majlesi Journal of Electrical Engineering, 19(1), 1-8. https://doi.org/10.57647/j.mjee.2025.1901.02
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Abstract

In this paper, a fuzzy controller is presented in order to achieve the maximum power in a solar cell. For improvement of the controller performance and achievement of the maximum power, the fuzzy controller variables are improved by the Grasshopper Optimization Algorithm (GOA). This algorithm has flexibility and fast convergence. In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. The results show that under the supposed conditions, the power value of the solar
cell utilizing the suggested algorithm has increased compared to other algorithms. In the simulation, the power value using the  proposed algorithm is 182.3 watts and the cell efficiency in this case is 99.97%. Therefore, the achieved results show at least 0.03% and 1.2% improvement, respectively in power and efficiency, compared to some examined methods.

Keywords

  • Fuzzy Controller,
  • Grasshopper optimization algorithm,
  • Maximum Power Point Tracking,
  • Coati optimization algorithm
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