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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
مراجع
  1. R. Prakash and S. S, “Optimal distributed generation planning considering economic and operational aspects,” Electr. Power Compon. Syst., vol. 52, no. 9, pp. 1581–1596, 2024.
  2. M. Rezaee, R. Fathi, and V. A. Maleki, “Dynamic analysis and uncertainty modeling of viscoelastic beam response to fluid stimulation: Insights into nonlinear effects and velocity uncertainties,” Appl. Ocean Res., vol. 157, p. 104487, 2025.
  3. N. Sharafkhani, J. O. Orwa, S. D. Adams, J. M. Long, G. Lissorgues, L. Rousseau, and A. Z. Kouzani, “An intracortical polyimide microprobe with piezoelectric-based stiffness control,” J. Appl. Mech., vol. 89, no. 9, p. 091008, 2022.
  4. S. Pirouzi, M. Zadehbagheri, and S. Behzadpoor, “Optimal placement of distributed generation and distributed automation in the distribution grid based on operation, reliability, and economic objective of distribution system operator,” Electr. Eng., pp. 1–14, 2024.
  5. M. Abbasi, E. Abbasi, L. Li, R. P. Aguilera, D. Lu, and F. Wang, “Review on the microgrid concept, structures, components, communication systems, and control methods,” Energies, vol. 16, no. 1, p. 484, 2023.
  6. A. Younesi, H. Shayeghi, and P. Siano, “Assessing the use of reinforcement learning for integrated voltage/frequency control in ac microgrids,” Energies, vol. 13, no. 5, p. 1250, 2020.
  7. K. H. M. Azmi, N. A. M. Radzi, N. A. Azhar, F. S. Samidi, I. T. Zulkifli, and A. M. Zainal, “Active electric distribution network: applications, challenges, and opportunities,” IEEE Access, vol. 10, pp. 134655–134689, 2022.
  8. S. Kiani, A. Salmanpour, M. Hamzeh, and H. Kebriaei, “Learning robust model predictive control for voltage control of islanded microgrid,” IEEE Trans. Autom. Sci. Eng., 2024.
  9. C. Zhong, H. Zhao, Y. Liu, and C. Liu, “Model predictive secondary frequency control of island microgrid based on two-layer moving-horizon estimation observer,” Appl. Energy, vol. 372, p. 123721, 2024.
  10. Q. Ullah, E. C. Resende, L. C. G. Freitas, H. Laaksonen, and M. G. Simões, “Enhancing voltage stability of grid forming power converters based on model predictive controller,” Int. J. Electr. Power Energy Syst., vol. 163, p. 110317, 2024.
  11. H. Shayeghi, H. A. Shayanfar, and A. Jalili, “Load frequency control strategies: A state-of-the-art survey for the researcher,” Energy Convers. Manage., vol. 50, no. 2, pp. 344–353, 2009.
  12. H. Shayeghi, A. Rahnama, and H. Mojarad, “Designing a multi-objective optimized parallel process controller for frequency stabilization in an islanded microgrid,” J. Oper. Autom. Power Eng., 2025.
  13. H. Shayeghi, A. Rahnama, N. Bizon, and A. Szumny, “Interconnected microgrids load-frequency control using stage-by-stage optimized tida+1 error signal regulator,” Eng. Rep., vol. 7, no. 1, p. e13095, 2025.
  14. H. Shayeghi, A. Rahnama, and N. Bizon, “Green microgrid’s lfc using recursive step-by-step optimized multi-stage fuzzy controller with separated inference systems,” Renew. Energy Focus, vol. 51, p. 100625, 2024.
  15. R. Kumar and C. N. Bhende, “Voltage oscillations stabilization in dc microgrids: A strategy using improved model predictive control,” IEEE J. Emerg. Sel. Top. Power Electron., 2024.
  16. A. K. Tudu, N. Naguru, S. H. N. Dey, and S. Paul, “Load frequency control of an isolated microgrid using optimized model predictive control by ga,” Electr. Eng., vol. 106, no. 4, pp. 4171–4183, 2024.
  17. C. I. Muresan and R. De Keyser, “Revisiting ziegler–nichols: A fractional order approach,” ISA Trans., vol. 129, pp. 287– 296, 2022.
  18. S. Othman, N. Sunar, A. Ismail, M. Ayob, M. M. Azmi, and M. Hashim, “Position tracking performance with fine tune ziegler-nichols pid controller for electro-hydraulic actuator in aerospace vehicle model,” J. Phys. Conf. Ser., vol. 2021, p. 012021, 2021.
  19. M. Nasrabadi and L. Hussein, “Designing the optimal energy damping suspension system with the method of least displacement and genetic algorithm,” Procedia Environ. Sci. Eng. Manage., vol. 10, no. 3, pp. 469–476, 2023.
  20. P. K. Ray, H. K. Sahoo, A. Mohanty, J. K. Bhutto, A. B. Barnawi, and A. A. Alshaya, “Robust h-infinity filter and pso-svm based monitoring of power quality disturbances system,” IEEE Access, vol. 12, pp. 39041–39057, 2024.
  21. Y. Zou, J. Qian, Y. Zeng, S. Ismail, F. Dao, Z. Feng, C. Nie, and H. Mei, “Optimized robust controller design based on cpsogsa optimization algorithm and h2/h∞ weights distribution method for load frequency control of micro-grid,” IEEE Access, vol. 9, pp. 162093–162107, 2021.
  22. P. S. Prasad and A. M. Parimi, “Robust µ-synthesis controller design and analysis for load frequency control in an ac microgrid system,” IFAC-Pap. Online, vol. 55, no. 1, pp. 547–554, 2022.
  23. M. R. Ghodsi, A. Tavakoli, and A. Samanfar, “A robust controller design for load frequency control in islanded microgrid clusters,” Int. Trans. Electr. Energy Syst., vol. 2022, no. 1, p. 4218067, 2022.
  24. M. Ramesh, A. K. Yadav, P. K. Pathak, and C. H. Basha, “A novel fuzzy assisted sliding mode control approach for frequency regulation of wind-supported autonomous microgrid,” Sci. Rep., vol. 14, no. 1, p. 31526, 2024.
  25. T. M. Shami, A. A. El-Saleh, M. Alswaitti, Q. AlTashi, M. A. Summakieh, and S. Mirjalili, “Particle swarm optimization: A comprehensive survey,” IEEE Access, vol. 10, pp. 10031–10061, 2022.
  26. J. Wang, “Optimizing support vector machine (svm) by social spider optimization (sso) for edge detection in colored images,” Sci. Rep., vol. 14, no. 1, p. 9136, 2024.
  27. X. Li, J. Chen, D. Zhou, and Q. Gu, “A modified biogeography-based optimization algorithm based on cloud theory for optimizing a fuzzy pid controller,” Optim. Control Appl. Methods, vol. 43, no. 3, pp. 722–739, 2022.
  28. F. Qin, A. M. Zain, and K.-Q. Zhou, “Harmony search algorithm and related variants: A systematic review,” Swarm Evol. Comput., vol. 74, p. 101126, 2022.
  29. M. H. Khooban, T. Niknam, F. Blaabjerg, and T. Dragiceviˇ c,´ “A new load frequency control strategy for micro-grids with considering electrical vehicles,” Electr. Power Syst. Res., vol. 143, pp. 585–598, 2017.
  30. S. Ahmad, M. Shafiullah, C. B. Ahmed, and M. Alowaifeer, “A review of microgrid energy management and control strategies,” IEEE Access, vol. 11, pp. 21729–21757, 2023.
  31. A. Younesi, Z. Wang, H. T. Nguyen, and P. Mandal, “A pathway to enhance the modern distribution systems resilience: Flexible behavior investigations on electric vehicles,” in Proc. IEEE Power Energy Soc. Gen. Meet., pp. 1–5, 2022.
  32. M. Schwenzer, M. Ay, T. Bergs, and D. Abel, “Review on model predictive control: An engineering perspective,” Int. J. Adv. Manuf. Technol., vol. 117, no. 5, pp. 1327–1349, 2021.
  33. K. S. Joshal and N. Gupta, “Microgrids with model predictive control: a critical review,” Energies, vol. 16, no. 13, p. 4851, 2023.
  34. B. Khokhar and K. S. Parmar, “A novel adaptive intelligent mpc scheme for frequency stabilization of a microgrid considering soc control of evs,” Appl. Energy, vol. 309, p. 118423, 2022.
  35. B. Khokhar, S. Dahiya, and K. P. S. Parmar, “Load frequency control of a multi-microgrid system incorporating electric vehicles,” Electr. Power Compon. Syst., vol. 49, no. 9-10, pp. 867–883, 2021.
  36. A. Tabesh and R. Iravani, “Small-signal dynamic model and analysis of a fixed-speed wind farm—a frequency response approach,” IEEE Trans. Power Del., vol. 21, no. 2, pp. 778–787, 2006.
  37. M. Carrasco, F. Mancilla-David, and R. Ortega, “An estimator of solar irradiance in photovoltaic arrays with guaranteed stability properties,” IEEE Trans. Ind. Electron., vol. 61, no. 7, pp. 3359–3366, 2013.
  38. J. V. Knudsen, “Modeling, control, and optimization for diesel-driven generator sets,” 2017.
  39. M. S. Genc, M. Celik, and I. Karasu, “A review on wind energy and wind–hydrogen production in turkey: A case study of hydrogen production via electrolysis system supplied by wind energy conversion system in central anatolian turkey,” Renew. Sustain. Energy Rev., vol. 16, no. 9, pp. 6631–6646, 2012.
  40. M. Shen and Q. Gao, “A review on battery management system from the modeling efforts to its multiapplication and integration,” Int. J. Energy Res., vol. 43, no. 10, pp. 5042–5075, 2019.
  41. T. John and S. P. Lam, “Voltage and frequency control during microgrid islanding in a multi-area multi-microgrid system,” IET Gener. Transm. Distrib., vol. 11, no. 6, pp. 1502–1512, 2017.
  42. H. Bevrani, Robust Power System Frequency Control, vol. 4. Springer, 2014.
  43. A. H. Glattfelder and W. Schaufelberger, Control Systems with Input and Output Constraints, vol. 1. Springer, 2003.
  44. J. Hu, Y. Shan, J. M. Guerrero, A. Ioinovici, K. W. Chan, and J. Rodriguez, “Model predictive control of microgrids – an overview,” Renew. Sustain. Energy Rev., vol. 136, p. 110422, 2021.
  45. S. M. S. Hussain, A. Latif, M. A. Aftab, C. Konstantinou, A. Al-Durra, and M. A. Abido, “Standardized communicationbased diverse structure model predictive controller with demand response for frequency regulation in microgrids,” IEEE Trans. Ind. Appl., vol. 60, no. 2, pp. 3554–3567, 2023.
  46. I. Pan and S. Das, “Fractional order agc for distributed energy resources using robust optimization,” IEEE Trans. Smart Grid, vol. 7, no. 5, pp. 2175–2186, 2015.
  47. H. Bevrani, F. Habibi, P. Babahajyani, M. Watanabe, and Y. Mitani, “Intelligent frequency control in an ac microgrid: Online pso-based fuzzy tuning approach,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1935–1944, 2012.
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