Multiverse optimized fuzzy-PID controller with a derivative filter for load frequency control of multisource hydrothermal power system

In this paper, a multiverse optimized (MVO) fuzzy PID controller with a derivative filter (fuzzy-PIDF) is proposed for the load frequency control (LFC) of a two-area multisource hydrothermal power system. The superiority of the MVO algorithm is demonstrated by comparing the system LFC performance with integral and fuzzy-PIDF controllers, both optimized using MVO, as well as some of the recent heuristic optimization techniques such as the ant lion optimizer, gray wolf optimizer, differential evolution, bacterial foraging optimization algorithm, and particle swarm optimization. To the best of the knowledge of the authors, the use of the MVO technique has not yet been reported for LFC studies. Among many of the controllers implemented here for comparison, the proposed MVO fuzzy-PIDF controller exhibits the best performance under different operating conditions in terms of settling times, maximum overshoot, and values of cost function, i.e. integral time absolute error. Furthermore, the robustness of the proposed control scheme is also investigated against variation of system parameters within +/- 10%, along with random step load disturbances. The proposed control scheme is not very sensitive to parametric variations and therefore keeps providing effective performance even under +/- 10% variations in system parameters. System modeling and simulations are carried out using MATLAB/Simulink.