ADVANCED HEFFRON-PHILLIPS MODEL FOR DAMPING OSCILLATIONS BASED ON WALRUS AND ENHANCED SNAKE OPTIMIZATION ALGORITHMS
DOI:
https://doi.org/10.55766/sujst-2024-06-e06027Keywords:
Algorithms, Controller, Damping, Eigenvalues, Oscillations, Parameters, Power System, Robust, StabilityAbstract
A reliable, safe, and secure operation of power systems is essential for all-round development. Low-Frequency Oscillations (LFO) hamper the smooth operation of the system. This manuscript develops an Advanced Heffron-Phillips Model (AHPM) for damping oscillations based on a higher-order Synchronous Machine (SM) Model 1.1. The effectiveness of AHPM is compared for the system without any controller and with Power System Stabilizer (PSS) based on Walrus and Enhanced Snake Optimization Algorithms (ESOA) for three loading conditions. The best damping results are obtained with AHPM, including PSS based on ESOA. The damping ratios (98.60%, 94.50%, and 78.90%) for the three loading conditions obtained with ESOA are higher than with the Walrus algorithm. The settling time, undershoot, and overshoot are also less with ESOA. The simulation is performed with MATLAB R2020. The challenges associated with integrating renewable energy sources into the grid can be met by this AHPM due to better mathematical modelling. By using AHPM with PSS based on ESOA, a robust, secure, and reliable power system is created. Based on four novel strategies, the ESOA tuned the parameters of PSS and produced excellent damping results due to improved performance in terms of speed, accuracy, convergence, and optimization. The simulation can be carried out on multimachine power systems to demonstrate the effectiveness of optimization algorithms. The multi-objective function can be designed for improving stability.
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