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<p>This study presents a direct model reference adaptive control (MRAC) system integrated with a tilt-integral-derivative (TID) controller to improve power grid stability during high-renewable energy sources (RESs) penetration and daily load variations. The MRAC incorporates a self-tuning regulator (STR) that dynamically estimates process parameters, enabling real-time adaptation to system changes. Furthermore, the manta ray foraging optimization (MRFO) algorithm is used to adjust the parameters of the TID-MRAC controller. In addition, system nonlinearities, including generation rate constraints (GRC), governor dead bands (GDB), and communication delay time (CDT), are considered within the optimization framework. The effectiveness of the TID-MRAC controller is demonstrated by comparing its performance against other controllers, such as conventional proportional–integral–derivative (PID), PID-MRAC, and fractional-order PID MRAC-MRFO (FO-PID-MRAC-MRFO) controllers. Furthermore, to counteract the challenges posed by high-RESs penetration, plug-in electric vehicles (PEVs) are integrated to assist in load balancing and dynamic power management. The results demonstrate that the synergy between the TID-MRAC controller and PEVs integration provides a robust and adaptive solution for maintaining frequency stability, even under abnormal grid conditions. This innovative approach ensures improved resilience and reliability in modern power grids with high renewable energy integration.</p>

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Enhancing power grid frequency stability with an optimized TID-MRAC controller and electric vehicle integration under renewable energy penetration

  • 期刊论文

  • 发表日期：

    2025年6月28日

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  • Mustafa M. Ali,
  • Ahmed H. A. Elkasem,
  • Salah Kamel,
  • Ahmed S. Ali,
  • Gamal T. Abdel- Jaber,
  • Abdel-Nasser Sharkawy,
  • Mohamed Khamies

摘要

This study presents a direct model reference adaptive control (MRAC) system integrated with a tilt-integral-derivative (TID) controller to improve power grid stability during high-renewable energy sources (RESs) penetration and daily load variations. The MRAC incorporates a self-tuning regulator (STR) that dynamically estimates process parameters, enabling real-time adaptation to system changes. Furthermore, the manta ray foraging optimization (MRFO) algorithm is used to adjust the parameters of the TID-MRAC controller. In addition, system nonlinearities, including generation rate constraints (GRC), governor dead bands (GDB), and communication delay time (CDT), are considered within the optimization framework. The effectiveness of the TID-MRAC controller is demonstrated by comparing its performance against other controllers, such as conventional proportional–integral–derivative (PID), PID-MRAC, and fractional-order PID MRAC-MRFO (FO-PID-MRAC-MRFO) controllers. Furthermore, to counteract the challenges posed by high-RESs penetration, plug-in electric vehicles (PEVs) are integrated to assist in load balancing and dynamic power management. The results demonstrate that the synergy between the TID-MRAC controller and PEVs integration provides a robust and adaptive solution for maintaining frequency stability, even under abnormal grid conditions. This innovative approach ensures improved resilience and reliability in modern power grids with high renewable energy integration.