Shahid Beheshti University International Journal of Research and Technology in Electrical Industry 2821-0190 4 2 2025 07 01 Using Quadratic Inspired Optimization in Fuzzy Fractional Order PID Load Frequency Control of Microgrids with Motor Drive-based Load 106741 10.48308/ijrtei.2026.241506.1101 EN Reza Nobari Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran Mohsen Hasan Babayi Nozadian Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran Mohamad Amin Ghasemi Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran Journal Article 2025 09 17 Microgrids operating in isolated mode often suffer from frequency instability due to unpredictable load variations and intermittent renewable energy generation. This paper proposes an enhanced load frequency control strategy that combines fuzzy logic with fractional-order PID dynamics to address these challenges. The fuzzy inference mechanism generates a nonlinear control action based on frequency deviation and its rate of change, enabling real-time, intelligent adaptation to disturbances. Fractional-order operators enhance damping and robustness across a wide operating range.<br />Controller parameters are tuned using a Quadratic Inspired Optimization (QIO) algorithm to minimize performance indices like Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE). A key innovation is incorporating motor drive-based loads as controllable frequency-responsive elements, rather than mere disturbances. Despite their nonlinear nature, these loads are harnessed to boost dynamic performance and accelerate stabilization.<br />MATLAB/Simulink simulations across scenarios—consumer loads only, renewables only, and combined—confirm the strategy reduces frequency deviations and improves transient performance over PID, FOPID, and fuzzy-based benchmarks, with superior error metrics and recovery times. This highlights the method's robustness for real-world microgrids.