Type-2 fuzzy-based branched controller tuned using arithmetic optimizer for load frequency control

Abstract

Frequency deviations are triggered by load changes and the inclusion of renewable energy sources. Hence, a novel type-2 fuzzy proportional derivative-integral control tactic is suggested for controlling load frequency in a deregulated power system with distributed generating (DG) units and plug-in electric vehicles (PEVs). The suggested controller is tuned with arithmetic optimizer (AO) to minimize the integrated time-squared error. Practical constraints such as boiler characteristics, governor dead bands, and generation rate constraints are incorporated into the thermal system. Simulations show the superiority of the suggested scheme compared to integral, proportional-derivative, proportional-integral, proportional-integral-derivative, and type-1 fuzzy logic proportional-derivative branched with integral controllers in rejecting step load disturbances occurring in frequency deviations and tie-line power. Furthermore, the dominance of the suggested AO over other well-known evolutionary methods is established by performing comparative studies. The robustness of the suggested strategy is also studied by considering ±30% perturbation in various system parameters. Moreover, the efficiency of the suggested scheme in rejecting random load disturbance, and the effect of integrating DG units and PEVs on the system are also studied. Finally, the suggested control scheme’s dominance is also demonstrated by comparing the results with previously reported control strategies. The maximum frequency deviation in area-1 is improved by 1.35% while that of area-2 is improved by over 6.70% as compared to reported works.