Open Access

ARTICLE

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

Aadel M. Alatwi^1,2, Abualkasim Bakeer³, Sherif A. Zaid^1,*, Ibrahem E. Atawi¹, Hani Albalawi^1,4, Ahmed M. Kassem⁵

1 Electrical Engineering Department, Faculty of Engineering, University of Tabuk, Tabuk, 47913, Saudi Arabia
2 Industrial Innovation and Robotic Center (IIRC), University of Tabuk, Tabuk, 47731, Saudi Arabia
3 Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, 81542, Egypt
4 Renewable Energy and Environmental Technology Centre, University of Tabuk, Tabuk, 47913, Saudi Arabia
5 Electrical Engineering Department, Faculty of Engineering, Sohag University, Sohag, 82524, Egypt

* Corresponding Author: Sherif A. Zaid. Email:

(This article belongs to the Special Issue: Advanced Artificial Intelligence and Machine Learning Methods Applied to Energy Systems)

Computer Modeling in Engineering & Sciences 2024, 140(2), 1807-1830. https://doi.org/10.32604/cmes.2024.048521

Received 10 December 2023; Accepted 07 March 2024; Issue published 20 May 2024

Abstract

An autonomous microgrid that runs on renewable energy sources is presented in this article. It has a superconducting magnetic energy storage (SMES) device, wind energy-producing devices, and an energy storage battery. However, because such microgrids are nonlinear and the energy they create varies with time, controlling and managing the energy inside them is a difficult issue. Fractional-order proportional integral (FOPI) controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance. The suggested dedicated control for the SMES comprises two loops: the outer loop, which uses the FOPI to regulate the DC-link voltage, and the inner loop, responsible for regulating the SMES current, is constructed using the intelligent FOPI (iFOPI). The FOPI+iFOPI parameters are best developed using the dandelion optimizer (DO) approach to achieve the optimum performance. The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load. The optimal FOPI+iFOPI controller manages the voltage and frequency of the load. The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller. MATLAB simulations were used to evaluate the recommended system’s performance. The results of the simulations showed that throughout all interruptions, the recommended microgrid provided the load with AC power with a constant amplitude and frequency. In addition, the required load demand was accurately reduced. Furthermore, the microgrid functioned incredibly well despite SMES and varying wind speeds. Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller. When utilizing the optimal FOPI+iFOPI controller with SMES, it was found that the microgrid performed better than the microgrid without SMES.

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Keywords

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