Frequency Control and Power Efficiency in Virtual Power Plants Using Novel Self-Adaptive Siberian Tiger Optimization for Fractional Order PID Controllers

Abstract

The increasing integration of renewable energy sources has significantly reduced greenhouse gas emissions and mitigated global warming. However, maintaining stability and efficient power management in Virtual Power Plants (VPPs) under dynamic operating conditions remains a major challenge. This study proposes a Self-Adaptive Siberian Tiger Optimization (SA-STO) based hybrid Proportional Integral–Fractional Order PID (PI-FOPID) controller for enhancing frequency regulation and power efficiency in VPP systems integrating solar photovoltaic systems, wind turbines, energy storage systems, diesel generators, and electric vehicles. The proposed hybrid controller combines the fast response of PI control with the robustness and flexibility of FOPID control, while the SA-STO algorithm optimally tunes controller parameters to improve system performance. MATLAB/Simulink simulations are conducted to evaluate the proposed approach against conventional PI, PID, and FOPID controllers using performance metrics such as frequency stability, overshoot response, power loss, and Total Harmonic Distortion (THD). The simulation results demonstrate that the proposed SA-STO-based hybrid PI-FOPID controller achieves enhanced dynamic response, improved stability, and reduced harmonic distortion, with a THD of 3.74%, compared with conventional controllers.