AGC of a Multi-Area Hydrothermal Interconnected Diverse Deregulated Power System Using a Proposed Novel SBOA-Multi-Level Fuzzy Logic-Tilt Controller Incorporated With IPFC

The increasing size and complexity of power systems, along with fluctuating power demands, modeling inaccuracies, changes in system structures, and variations in system parameters over time, have made the Automatic Generation Control (AGC) task more challenging. A significant drop in frequency can negatively affect electric clock synchronization, magnetizing currents in transformers and induction motors, the consistent speed of AC motors, the ongoing operation of processes, and the coordinated functioning of various components within the power system. Traditional control methods are inadequate for handling the unpredictable changes in AGC systems. To effectively address the AGC challenges in power systems, innovative control solutions are being developed that integrate insights, techniques, and strategies from multiple fields. This study introduces a new Multi-Level-Fuzzy-Tilt-derivative-Tilt-integral (MLF-TD-TI) controller to address the Automatic Generation Control (AGC) challenge in a multi-area hydrothermal interconnected deregulated power system. The proposed expert control method is applied to manage both scheduled and unscheduled power in various agreements. The performance of the MLF-TD-TI controller is compared to that of other controllers, including the Two-Level-Fuzzy-TD-TI, Fuzzy-TD-TI, TD-TI, TID, and PID controllers. Dynamic response analysis shows that the MLF-TD-TI controller outperforms the secondary controllers in terms of overshoot, undershoot, settling time, and damping oscillations. Additionally, when an Interline Power Flow Controller (IPFC) is incorporated, the system achieves an average reduction in oscillation amplitude of 75% for frequency deviation and 79.5% for tie-line power deviation, significantly outperforming the conventional PID controller. To optimize the controller gains, the study employs the Secretary Bird Optimization Algorithm (SBOA), a recently developed optimization technique. Nonlinearities have been included in the system for a more realistic approach. The integration of the IPFC improves system performance, and the effectiveness and reliability of the SBOA-MLF-TD-TI method are validated through sensitivity analysis, considering simultaneous variations in the DISCO Participation Matrix (DPM) values.