Nigerian Journal of Engineering Science and Technology Research

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The stability and efficient operation of power systems are of paramount importance to ensure reliable electricity supply and system security to consumers. One of the critical aspects of power system stability is the proper tuning of Power System Stabilizers (PSSs), damping out oscillations and maintaining the system's equilibrium plays a critical role in the stability of the system. Traditional tuning methods for PSSs often rely on trial-and-error approaches, making them time-consuming and suboptimal. To address these challenges, this research proposes the application of the Optimal Foraging Algorithm (OFA) to optimize the tuning of PSS parameters in a multi-machine power system. The Optimal Foraging Algorithm is inspired by the foraging behavior of animals seeking to maximize their energy intake while minimizing effort. The objective is to find the optimal set of PSS parameters that enhance the overall stability and performance of the power system. The research involves the development of a multi-machine power system model which is the Nigeria 10-bus 330kV power system network operating on 50Hz, with six (6) generators and four (4) transmission stations. The OFA was applied to tune the PSS parameters Kstab, T1, T2, T3 and T4, after the system was subjected to a 1 second disturbance. Simulation results demonstrated the effectiveness of the OFA-based tuning approach in minimizing overshoot and reduced settling time. The graphical mean deviation obtained gave the OFA a minimal value of 0.14pu, 0.092pu, 0.011pu & 0.212pu for the Power, Voltage, Angle and PSS Voltage stabilities respectively as compared to the other methods. The utilization of the Optimal Foraging Algorithm for PSS tuning represents a promising step towards enhancing the stability and reliability of multi-machine power systems in the modern electrical grid. It is recommended that further development of the model by adding more parts of the grid and different types of disturbances, and testing it in a real power system.

Authors : Ibrahim, M.B., Jiya, J.D., Gana, M.A., Mustapha, I. and Jafaru, U.

Category : Open Access     Volume (Issue) : 10(1)     Date Uploaded : 16th April 2024

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