Power Angle Swing Curve Optimization using PSO Algorithm

Power Angle Swing Curve Optimization using PSO Algorithm
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Updated 21 Jul 2023

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The optimization of swing curve parameters is crucial in power system stability analysis. Efficiently tuning parameters helps ensure that the system remains stable after a fault occurs and prevents potential catastrophic consequences. PSO offers an effective optimization technique, allowing engineers and researchers to determine the optimal parameter values that result in the desired rotor angle at a specific time, promoting a stable power grid.
This MATLAB script optimizes the parameters of a swing curve simulation using the Particle Swarm Optimization (PSO) algorithm. The PSO algorithm seeks to find the best set of parameters to achieve a desired rotor angle at a specified time. The script simulates the swing curve based on a predefined model and updates the particle positions and velocities iteratively to converge towards the optimal solution. The resulting optimized parameters are then used to generate the swing curve, showcasing the rotor angle variation over time.

Cite As

recent works (2024). Power Angle Swing Curve Optimization using PSO Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/132583-power-angle-swing-curve-optimization-using-pso-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.0