Revolutionizing Hybrid Microgrids Enhanced Stability and Efficiency with Nonlinear Control Strategies and Optimization

Rimsha Ghias, Atif Rehman, Hammad Iqbal Sherazi, Omar Alrumayh, Abdulrahman Alsafrani and Abdullah Alburidy ()
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Rimsha Ghias: School of Electrical Engineering and Computer Sciences (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
Atif Rehman: School of Interdisciplinary Engineering and Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
Hammad Iqbal Sherazi: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia
Omar Alrumayh: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia
Abdulrahman Alsafrani: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia
Abdullah Alburidy: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia

Energies, 2025, vol. 18, issue 19, 1-26

Abstract: Microgrid systems play a vital role in managing distributed energy resources like solar, wind, batteries, and supercapacitors. However, maintaining stable AC/DC bus voltages and minimizing grid reliance under dynamic conditions is challenging. Traditional control methods such as Sliding Mode Controllers (SMCs) suffer from issues like chattering and slow convergence, reducing practical effectiveness. This paper proposes a hybrid AC/DC microgrid that operates in both grid-connected and islanded modes while ensuring voltage stability and efficient energy use. A Conditional-Based Super-Twisting Sliding Mode Controller (CBSTSMC) is employed to address the limitations of conventional SMCs. The CBSTSMC enhances system performance by reducing chattering, improving convergence speed, and offering better tracking and disturbance rejection. To further refine controller performance, an Improved Grey Wolf Optimization (IGWO) algorithm is used for gain tuning, resulting in enhanced system robustness and precision. An Energy Management System (EMS) is integrated to intelligently regulate power flow based on renewable generation and storage availability. The proposed system is tested in real time using a Texas Instruments Delfino C2000 microcontroller through a Controller-in-the-Loop (CIL) setup. The simulation and hardware results confirm the system’s ability to maintain stability and reliability under diverse operating scenarios, proving its suitability for future smart grid applications.

Keywords: microgrids; power converters; batteries; inverter; nonlinear; improved grey wolf optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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