ANN-tuned PIDN controller for LFC with modified HVDC tie-line in deregulated environment

This article focuses on designing and analyzing the most intelligent frequency controller. The Load Frequency Control (LFC) mechanism is a well-known and important way of restoring system frequency and scheduled tie-line power to their nominal values. The adoption of an appropriate controller increases the LFC mechanism's performance. This paper proposes an adaptive control-based Artificial Neural Network (ANN)-tuned Proportional-Integral-Derivative with derivative N-filter (PIDN) controller for the LFC mechanism. An innovative Opposition-learning-based Volleyball Premier League (OVPL) algorithm is also analyzed to identify the optimal control parameters. For a multi-area, nonlinear, interconnected power system in a deregulated environment, the suggested ideal intelligent controller is investigated. Numerous established methods for managing step and random load disturbances have been used to evaluate the effectiveness of the suggested LFC design. The resilience of the suggested strategy has also been investigated for a variety of system parameter changes. However, the redesigned High Voltage Direct Current (HVDC) tie-line model and the effect of the Inertia Emulation Technique (IET) with converter capacitors are presented in this article. The planned LFC scheme's supporting infrastructure has undergone literary analysis, which has confirmed the scheme's efficacy. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.