10.57647/j.spre.2025.0902.08

A Fuzzy-based Reset Control Technique for Enhanced Multi-Agent Microgrid Performance

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  • Shahram Fallah Faal ,
  • Alireza Sahab*1,
  • Behnam Alizadeh2,
  1. Department of Electrical Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran
  2. Niroo Research Institute (NRI), Iran

Received: 2025-01-10

Revised: 2025-01-22

Accepted: 2025-05-08

Published in Issue 2025-06-01

Copyright (c) 2025 Shahram Fallah Faal , Alireza Sahab, Behnam Alizadeh (Author)

Creative Commons License

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

How to Cite

Fallah Faal , S. ., Sahab, A., & Alizadeh, B. (2025). A Fuzzy-based Reset Control Technique for Enhanced Multi-Agent Microgrid Performance. Signal Processing and Renewable Energy (SPRE), 9(2 (June 2025). https://doi.org/10.57647/j.spre.2025.0902.08
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Abstract

Microgrid systems play a critical role in energy management and the development of diverse communities. However, these systems' islanded setup and operation within a multi-agent structure present significant challenges for secondary frequency and voltage control. This paper proposes a robust and intelligent hybrid approach for frequency control in multi-agent islanded microgrid systems to address these challenges. The proposed control technique combines robust reset control with a fuzzy intelligent approach. The reset control technique effectively eliminates frequency tracking errors and, due to its integral structure, overcomes the limitations of traditional linear controllers. The fuzzy intelligent technique is employed to dynamically adjust and tune the coefficients of the reset controller. The integration of these two approaches ensures effective frequency control in multi-agent islanded microgrids, even under the presence of disturbances and uncertainties caused by renewable energy sources and variable loads. The performance of the proposed controller is evaluated through simulations in the MATLAB environment under various scenarios. Comparative analyses with PI and PID controllers demonstrate that the proposed controller achieves faster frequency regulation and superior performance in overcoming adversities compared to conventional methods.

Keywords

  • Renewable sources,
  • Microgrid,
  • Multi-agent systems,
  • Uncertainty,
  • Disturbance,
  • Reset control,
  • Fuzzy approach,
  • Microgrid frequency control
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