Effect of Electric Vehicles and Renewable Sources on Frequency Regulation in Hybrid Power System Using QOAOA Optimized Type-2 Fuzzy Fractional Controller

In the modern era, the demand for an interconnected power system, which can integrate electric vehicles and renewable energy sources is increasing day by day. The primary goal of this demand is to make a sustainable and green power source, which can be fulfilled by utilizing Electric vehicles and renewable energy sources. However, there are some demerits of this technology, its lesser system inertia and hence it is not sufficient to respond to the required load capabilities. Further, the approach of electric vehicles with moving batteries can enable higher performance and resolve the issue. In this current analysis, the vehicles to grid idea (V2G) technique has been discussed, which can react as automatic generation control (AGC) in a three-area deregulated environment including hydro, thermal, and gas turbine units. In this type of power grid, all the sources such as Solar, wind, geothermal, and DEG power is also incorporated. To grip various ambiguities, the current study proposed a cascade combination of Interval type-2 fuzzy and Fractional Order Proportional-integral-derivative (FOPIDN) controllers. Further, the current work proposed a modified quasi-opposition Arithmetic Optimization Algorithm (QOAOA) to tune the scaling factor and membership function of an interval type-2 fuzzy FOPIDN controller. To discuss the significance of the anticipated controller, the estimated outputs have been compared with previously reported controllers and optimization techniques. The effect of constant and variations in DG, the penetration level of (PEVs) in various operating modes, subjected to step and random load disturbances have been focused on. Finally, to validate the outcomes of the proposed controller, a real-time (RT) hardware-in-the-loop (HIL) simulation has been adopted by using OPAL-RT.