Optimal Fuzzy Gain Scheduling of Pid Controller of Superconducting Magnetic Energy Storage for Power System Stabilization

It is well known that the proportional-integral-derivative (PID) can be applied to solve practical control problems effectively. However, in the face of the high system nonlinearity, the PID controller with fixed parameters may fail to provide satisfactory control performance. To enhance the PID control effect, a new design of the fuzzy gain scheduling of PID controller (FGS-PID) is presented in this paper. The proposed technique is applied to design FGS-PID controllers of superconducting magnetic energy storage (SMES) for power system stabilization. Without trial and error, the scale factors, membership functions and control rules of the FGS-PID controller are automatically tuned by a bee colony optimization. With the optimal FGS-PID controller, the PID parameters can be adjusted automatically according to various system operating conditions. As a result, the high robustness of the FGS-PID controller can be expected. Simulation study confirms that the stabilizing effect and robustness of the proposed SMES with an optimal FGS-PID controller are much superior to those of the SMES with an optimal PID controller.