Publication

Abstract : The suggested work looks at the system settings that need to stay normal in a Single-Area Power System (SAPS) and a Two-Area Power System (TAPS), which includes thermal power plants, when there is a 1% change in load. The primary controller comprises a speed governor that controls the frequency and power flow in the tie line within limits. Due to speed changer restrictions, which can operate between 2 and 2.5 Hz/p. u.MW, the system fails to operate under the nominal conditions. Therefore, the secondary controller helps to fine-tune the system frequency and tie-line power flow, retaining the Load Frequency Control (LFC), and thus maintaining the system in nominal operation. Among the conventional secondary controllers, the PID with Derivative Filter Coefficient (PIDF) controller is considered for better system response and performance to achieve what is proposed. The controller gains help optimize the system performance and maintain nominal operation through optimization techniques. In this study, Teaching Learning-Based Optimization (TLBO), Bacterial Foraging Optimization (BFO), Real Coded Genetic Algorithm (RCGA), and Particle Swarm Optimization (PSO) optimization techniques are used. Depending on the load disturbances, the robust performance of the LFC in the SAPS and TAPS was analyzed during load variations using the proposed approaches. The performance indices, namely, the Integral Absolute Error (IAE) and Integral Squared Error (ISE), are used to validate the performance of the controller. The TLBO-based controller showed superior and robust performance compared to all other optimization techniques, subject to error minimization, retaining the system performance in nominal operation. In addition, the TLBO-based controller demonstrated enhanced adaptability to varying load conditions, ensuring stability and responsiveness in real-time applications. This effectiveness highlights the potential of integrating advanced optimization techniques into modern control systems to improve efficiency and reliability.