Maiden Application of a Modified HBA-Optimized Cascaded (2DOF + FOPIDN)-PD Controller for Load Frequency Control of Diverse Source Power System

Abstract

Electricity has become one of the most essential components of establishing a quality standard of living in any country. Consequently, considerable work has been focused on designing a sophisticated load frequency control (LFC) system. However, in light of limited resources and real-world challenges, computationally based control algorithms that are more effective and less expensive remain critically needed. Thus, this paper employs a modified honey badger algorithm (HBA) in conjunction with the concepts of Lévy flight and inertia weight to optimize the parameters of a new cascaded two-degree-of-freedom fractional-PID structure coupled with a proportional derivative (2DOF + FOPIDN)-PD controller to solve LFC problems in an interconnected power system (IPS) comprising conventional and renewable energy sources (RES). The proposed control technique is applied to a two-area IPS under diverse load conditions and in the presence of nonlinear elements and electronic devices. The proposed method is evaluated with respect to a range of performance metrics, such as settling time, undershoots, and error criteria values. The collective performance of the established control scheme indicated that the suggested control approach provides excellent reliability under various load condition scenarios, sensitivity tests, and perturbations, proving the system’s efficacy and dependability.

A modified differential evolution algorithm for frequency management of interconnected hybrid renewable system

“…The PIDN controller comprises of P, I, D controller with a derivative filter coefficient N and the PIDFN controllers is of the form of PI λ D µ and a derivative filter coefficient N. λ and µ are the order of integrators and differentiators respectively. With the inclusion of a fractional order PIDN controller, the integer order PIDN controller may be extended from point to plane, making the PIDN control method more adaptable and robust [20], [21].The scaling parameters provided by the advanced control optimization, the gain parameters of a cascaded PIDFN controller becomes more flexible [22], [23] and by implementing a fuzzy PID filter [24].…”