Quasi-Oppositional African Vultures Optimization-Based PI^λDn Plus PI^λ Controller for Frequency Control of an Interlinked Hybrid Power System

One of the challenging tasks in a hybrid power system is to provide an effective control strategy to attenuate frequency and power deviations that occur due to the intermittency of renewable energy resources (RERs) and load demand. To address this issue, we present a novel proportional fractional-order integral derivative filter plus proportional fractional-order integral (PIλDn plus PIλ) controller, which is applied for the load frequency control (LFC) operation of an interlinked hybrid thermal power system. Using quasi-oppositional learning, we also propose the maiden quasi-oppositional African vultures optimization algorithm (QOAVOA), which is used to tune the proposed controller by minimizing the objective function. First, the capability of the proposed QOAVOA tuned PIλDn plus PIλ controller is examined with a two-area thermal power system under load uncertainty and the performance is compared with the results of various optimization-based classical/fuzzy controllers. The sensitivity study is also performed to validate the robustness of the proposed control approach for handling systems’ parametric uncertainties. The suggested LFC mechanism is further validated on a two-area-hybrid thermal power system (2A-hTPS) comprising RERs and distributed generation sources to authenticate the tuning ability of the proposed optimization approach. The dynamic performance of considered 2A-hTPS with the suggested control approach is examined considering various scenarios such as changing load demand, uncertain wind perturbation, and random multi-step load perturbations of the wind turbine generator. The comparative dynamic performance of the suggested controller reveals its superiority over other controllers in terms of transient and steady-state responses. Finally, a few non-linearities are introduced to the test system, and the simulation study with non-linearities validates the potency of the proposed controller.