A hybrid intelligent control strategy to improve the stability of wind-PV-thermal-bundled system

This paper investigates the intelligent optimal control problem for the stability of wind-PV-thermal-bundled (W-PTB) system. Based on the weak damping characteristics of the WPTB system, the damping ratio, bus voltage, and generator active power are constructed as objective functions, and an improved greater cane rat algorithm (IGCRA) is proposed for the parameter optimization problems of power system stabilizers (PSS), power oscillatory damping (POD) controller, and unified power flow controllers (UPFC). Compared with the existing methods, the algorithm proposed in this paper improves the optimization and global search capability and prevents local optimization by introducing the Sin chaos model, nonlinear control, and the Cauchy mutation operator. Finally, different states of the WPTB system are simulated separately, and the results show that the method proposed in this paper can give full play to the advantages of each controller, significantly enhance the system damping ratio, and shorten the amplitude of the oscillations and suppression of low-frequency oscillations (LFO) occurring in the system.