Application of Multiple-model Adaptive Control in Interconnected Power System

The interconnected power systems are strong coupling parameter uncertain nonlinear large systems, it is difficult to achieve stability tracking control for the systems. Conventional proportional-integral-derivative (PID) controller is designed to ensure desired performance under a particular operating condition. The controllers obtained from these approaches are simple but tend to lack robustness. Due to severe nonlinear and time-varying behavior of the interconnected power system, this paper tries to use a multiple-model adaptive control (MMAC) strategy to model and control an interconnected power system. Schematic of MMAC strategy is introduced. A recursive Bayesian approach is used for computing the current probability of each model being closed to the post-disturbance behavior of the system. This strategy has been used to design controllers for 2-area 4-machine power system. Simulation results illustrate that the MMAC scheme is able to identify the predominant post-disturbance dynamics and switch in the appropriate controller without any prior knowledge about the specific operating condition.