Improved fruit fly optimization algorithm tuned fuzzy intelligent controller for multi area power system stability

During the peak load hours, the demand for electrical power increases, and the power supply cannot exceed its limitations. This leads to an imbalance between the demanded and the supplied powers, causing the system frequency to fluctuate. The extreme fluctuations in frequency may result in the power system blackout. An automated load frequency control (LFC) with a dependable controller built in it is necessary to keep the power system frequency constant. In this work, a fuzzy intelligent integral-double derivative including filter (IDDF) (FIDDF) controller is introduced for the dynamical stability of a multi-area multi-fuel power system (MAMFPS). The suggested FIDDF is designed optimally using the heuristic technique of the improved fruit fly optimization algorithm (IFFOA). Initially, the suggested controller is tested on the most accepted model of two-area simple hydrothermal power system (TASHTPS) and the dominance of the presented controller is recognised with other techniques in the literature recently. The assessment of TASHTPS and MAMFPS dynamic behaviour’s is initiated by laying area 1 with a 10% step load disturbance (SLD). The MAMFPS of the investigative model is deliberated with all possible types of non-linearity with the intention of deliberating the work in a real-time environment. Moreover, the significant impact of one of the nonlinear constraints, such as communication time delays (CTDs), on MAMFPS’s dynamic performance is revealed. Further, the MAMFPS operation is carried out with the territorial strategy of a Thyristor-controlled series compensator (TCSC) and super capacitors (SCs) for better improvement in the system performance. Finally, the resilience of the presented control mechanism is confirmed by the conduct of sensitivity analysis under loading uncertainty.