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Ziyadullayevich Avlokulov, Anvar, Ovlayev, Suhrob, Basim Furaijl, Hussein, Abed Hussein, Muntadher, Khalid Abozibid, Hassan, Ali Nasir, Zainab, Toma Farhan, Tahir, Jaafar Naser, Sarmad, Avlayeva, Oybarchin, Yulchiyev, Oybek, Normuminova, Dilorom. (1403). Enhancing Frequency Stability in Islanded Microgrids via Model Predictive Control. سامانه مدیریت نشریات علمی, 12(Special Issue), 64-75. doi: 10.22098/joape.2025.17113.2335
Anvar Ziyadullayevich Avlokulov; Suhrob Ovlayev; Hussein Basim Furaijl; Muntadher Abed Hussein; Hassan Khalid Abozibid; Zainab Ali Nasir; Tahir Toma Farhan; Sarmad Jaafar Naser; Oybarchin Avlayeva; Oybek Yulchiyev; Dilorom Normuminova. "Enhancing Frequency Stability in Islanded Microgrids via Model Predictive Control". سامانه مدیریت نشریات علمی, 12, Special Issue, 1403, 64-75. doi: 10.22098/joape.2025.17113.2335
Ziyadullayevich Avlokulov, Anvar, Ovlayev, Suhrob, Basim Furaijl, Hussein, Abed Hussein, Muntadher, Khalid Abozibid, Hassan, Ali Nasir, Zainab, Toma Farhan, Tahir, Jaafar Naser, Sarmad, Avlayeva, Oybarchin, Yulchiyev, Oybek, Normuminova, Dilorom. (1403). 'Enhancing Frequency Stability in Islanded Microgrids via Model Predictive Control', سامانه مدیریت نشریات علمی, 12(Special Issue), pp. 64-75. doi: 10.22098/joape.2025.17113.2335
Ziyadullayevich Avlokulov, Anvar, Ovlayev, Suhrob, Basim Furaijl, Hussein, Abed Hussein, Muntadher, Khalid Abozibid, Hassan, Ali Nasir, Zainab, Toma Farhan, Tahir, Jaafar Naser, Sarmad, Avlayeva, Oybarchin, Yulchiyev, Oybek, Normuminova, Dilorom. Enhancing Frequency Stability in Islanded Microgrids via Model Predictive Control. سامانه مدیریت نشریات علمی, 1403; 12(Special Issue): 64-75. doi: 10.22098/joape.2025.17113.2335

Enhancing Frequency Stability in Islanded Microgrids via Model Predictive Control

Journal of Operation and Automation in Power Engineering
مقاله 8، دوره 12، Special Issue، 2024، صفحه 64-75    اصل مقاله (4.27 M)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2025.17113.2335
نویسندگان
Anvar Ziyadullayevich Avlokulov* 1؛ Suhrob Ovlayev1؛ Hussein Basim Furaijl2؛ Muntadher Abed Hussein3؛ Hassan Khalid Abozibid4؛ Zainab Ali Nasir5؛ Tahir Toma Farhan6؛ Sarmad Jaafar Naser7؛ Oybarchin Avlayeva1؛ Oybek Yulchiyev1؛ Dilorom Normuminova1
1Tashkent state University of Economics, Tashkent, Uzbekistan.
2University of Al-Ameed, Karbala, Iraq.
3Department of Sciences, Al-Manara College, Maysan, Iraq.
4Al-Zahrawi University College, Karbala, Iraq.
5Al-Nisour University College, Nisour Seq. Karkh, Baghdad, Iraq.
6Mazaya University College, Nasiriyah, Iraq.
7Collage of Nursing, National University of Science and Technology, Dhi Qar, 64001, Iraq.
چکیده
This paper proposes a Model Predictive Control-based strategy for secondary load frequency control to enhance the dynamic performance of such systems. The proposed controller generates optimal control signals for dispatchable units to minimize frequency deviations induced by load and generation variability. A comprehensive microgrid model is developed, incorporating photovoltaic arrays, wind turbines, fuel cells, battery and flywheel energy storage systems, diesel generators, and electrolyzers. The dynamic behavior of each component is formulated using small-signal transfer functions, and the MPC is designed based on a constrained quadratic optimization problem that predicts and mitigates frequency deviations. Simulation results in MATLAB/Simulink demonstrate the superiority of the proposed MPC approach compared to conventional and intelligent controllers, including Ziegler–Nichols tuned PI, Fuzzy-PI, CPSO-PID, and CPSO-FOPID. The proposed controller achieved a maximum frequency deviation of 0.0052 pu, a settling time of 5.1 seconds, and an ITAE of 0.00024—outperforming all benchmarks in both steady-state and transient scenarios. Robustness under system parameter variations and load disturbances was also validated through five distinct case studies. The controller exhibits improved reliability, reduced stress on primary controllers, and better resilience to uncertainties. Future work will focus on implementing adaptive MPC algorithms, integrating machine learning-based disturbance predictors, and validating the control scheme using real-time hardware-in-the-loop platforms for enhanced applicability in hybrid AC/DC microgrids.
کلیدواژه‌ها
Model Predictive Control؛ secondary control؛ renewable energy integration؛ frequency oscillations؛ system stability؛ robust control؛ hardware in the loop validation
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