Effect of TCPS, SMES, and DFIG on load frequency control of a multi-area multi-source power system using multi-verse optimized fuzzy-PID controller with derivative filter

In this paper, a novel multi-verse optimized fuzzy-PID (proportional–integral–derivative) controller with derivative filter (fuzzy-PIDF) is proposed for load frequency control of a two-area multi-source power system, with each area consisting of a reheat thermal and a hydro unit. The superiority of the Multi-Verse Optimizer algorithm is demonstrated against some recently published modern heuristic optimization techniques. For comparative analysis of the proposed control scheme, the conventional integral, proportional–integral, and PIDF controllers are also implemented. The effect of the thyristor-controlled phase shifter, superconducting magnetic energy storage, and doubly fed induction generators, considered individually and in various combinations, is investigated. Further, with an integral controller optimized using Multi-Verse Optimizer, the value of the integral of time multiplied absolute error, one of the performance indicators, is reduced by 85.61%, 83.91%, 70.42%, 67.69%, and 73.15% compared with optimization of the integral controller using Ant Lion Optimizer, Grey Wolf Optimizer, Differential Evolution, Bacterial Foraging, and Particle Swarm Optimization, respectively. Also, to quote a representative case, with Multi-Verse Optimizer, the settling times in respect of frequency deviations of area-1, area-2, and tie-line power are improved by 94.36%, 98.28%, and 95.44%, respectively, as compared with the results obtained using Ant Lion Optimizer. Further, robustness of the proposed control scheme is also investigated against variation of system parameters within ±10% besides random step load disturbances. Of all the controllers implemented here, the proposed optimized fuzzy-PIDF controller exhibits the best performance. Modeling and simulations were carried out using MATLAB/Simulink.