Frequency and voltage stability improvement in a two-area thermal power system using a novel controller and RIME optimizer

Abstract

This work presents a novel method for integrating the Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) processes to enhance frequency and voltage stability in two-area non-reheat thermal power systems. In this study, we present a novel Proportional Derivative-(1+Double Integral) (PD-(1+II)) controller, which is optimized through the utilization of the recently created Rime Optimization Algorithm (RIME). This represents the first time that the RIME algorithm and the PD-(1+II) controller are used in the context of coupled LFC-AVR systems. Our comprehensive research encompasses six distinct scenarios, including AVR system tuning, LFC system tuning, combined LFC-AVR system tuning, disturbance analysis, nonlinearity analysis, and parameter sensitivity analysis. A comparative analysis is conducted between the proposed RIME-tuned PD-(1+II) controller and established techniques such as the Nonlinear Threshold Accepting (NLTA) algorithm and its multi-objective version (MONLTA) tuned PID controllers, i.e. MONLTA-PID and NLTA-PID controllers. The simulation results demonstrate that the RIME-tuned PD-(1+II) controller consistently outperforms existing techniques. It exhibits superior performance in terms of overshoot reduction (100 % decrease in frequency deviation and 30 % decrease in terminal voltage) and faster settling times (50 % decrease in frequency control and 30 % decrease in voltage control) when compared to current methods. Furthermore, the controller demonstrates resilience in the presence of a diverse range of disturbances, nonlinearities, and parameter variations, highlighting its adaptability and reliability in a multitude of operational scenarios. The efficacy and reliability of the proposed methodology are further substantiated by statistical analysis, which demonstrates that it outperforms existing optimization algorithms, including the Gorilla Troops Optimizer (GTO) and the Whale Optimization Algorithm (WOA), with the RIME algorithm achieving an average ITSE value of 0.0881 compared to 0.1023 for GTO and 0.1057 for WOA.