Enhanced multi-area automatic generation control in renewable energy-based microgrids using an IPFC-SMES system and COA-optimized FOPID controller

Integrating renewable energy sources (RESs) into multi-area microgrids introduces significant challenges to maintaining system stability and frequency regulation due to the inherent intermittency and variability of RESs. This study proposes an innovative approach to enhance the multi-area automatic generation control (AGC) of renewable energy-based microgrids by employing a robust Fractional Order Proportional-Integral-Derivative (FOPID) controller optimized using the Cheetah Optimizer Algorithm (COA). To further improve system performance, the Interline Power Flow Controller (IPFC) and Superconducting Magnetic Energy Storage (SMES) systems are incorporated as advanced control devices to mitigate power imbalances and improve dynamic response. The proposed methodology is validated through extensive simulation studies under various operating scenarios, including load disturbances and renewable energy fluctuations. Comparative analysis with conventional PID and other optimization techniques demonstrates the superior performance of the COA-optimized FOPID controller in terms of reduced frequency deviations, faster settling times, and improved system robustness. Robustness tests and sensitivity analysis were conducted to assess the stability of the power network under varying system parameters and randomly selected loading conditions. The COA-optimized FOPID controller demonstrated superior performance compared to the COA-tuned PID controller by achieving a 62 % reduction in settling time for frequency variations, eliminating overshoot, and decreasing undershoots for frequency and tie-line power deviations by 73 % and 55 %, respectively. Additionally, it maintains frequency deviation within ± 0.012 Hz and tie-line power deviation within ± 0.015 p.u, with an average settling time of 4.584 s. Comprehensive robustness tests and sensitivity analyses were conducted by varying system parameters such as the governor time constant T_g, turbine time constant T_t, frequency bias, B, speed regulation parameter R, and interconnection coefficient T₁₂. The results demonstrate the proposed controller's stability and adaptability to diverse loading conditions and parameter uncertainties. The ITAE values, ranging from 0.000225 to 0.000682, highlight the effectiveness of the proposed controller in maintaining frequency stability. The settling times, spanning from 1.318 s to 4.584 s, reflect the system's ability to achieve a rapid response. Overshoots and undershoots are minimal, with overshoot values ranging from 1.6×10⁻³ p.u. (9.6×10⁻²Hz) to 1.96×10⁻³p.u. (0.1176 Hz) and undershoot values varying between −3×10⁻³−p.u. (−0.18Hz) and −2.5×10⁻³ p.u. (−0.15 Hz). These results demonstrate the controller's capability to maintain system stability and effectively minimize transient deviations. Ultimately, the study confirms that the proposed IPFC-SMES integrated AGC scheme, combined with a COA-optimized FOPID controller, offers a highly reliable and effective solution for next-generation multi-area microgrids with high RES penetration.