Multi-Objective Genetic Algorithm Optimization of Thermal Limit Parameters for Low-Frequency Oscillation Control in Power Systems

Aliyu Abubakar and Mohammad Buhari Mohammad
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Aliyu Abubakar: Department of Electrical and Electronics Engineering Federal Polytechnic, Bali Taraba State
Mohammad Buhari Mohammad: Department of Electrical and Electronics Engineering Federal Polytechnic, Bali Taraba State

International Journal of Research and Innovation in Applied Science, 2024, vol. 9, issue 5, 536-540

Abstract: This work presents the optimization of thermal limit parameters constraint using a multi-objective genetic algorithm. By optimizing the constraint parameters of the formulated objective function, the power transfer capabilities of the system can be maximized, thereby reducing the chances of oscillations in the power system. The study involves formulating an objective function and constraints, implemented in MATLAB Simulink. Initialization of generation fitness and optimal mean value precedes computation of fitness function and mean value. Fitness values are compared against predefined benchmarks to gauge optimization levels, with verification ensuring mean fitness meets a predetermined threshold. Achieving the threshold to 1.05706 resulted to better power transfer efficiency by decreasing oscillations that previously impacted power stability. Optimized thermal limit parameters enhance power transfer capabilities, minimizing oscillations, ensuring stable operation, and reducing the risk of system instability.

Date: 2024
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