Swing Curve Optimization using Harmony Search Algorithm

Optimize swing curve parameters for power systems using a Harmony Search Algorithm.

• The provided MATLAB code implements a Harmony Search Algorithm to optimize parameters for swing curve simulations in power systems. The optimization aims to achieve a target rotor angle and time, crucial for maintaining system stability during faults.
• The process begins with defining algorithm parameters such as population size, maximum iterations, and pitch adjustment rates. The objective function evaluates the fitness of parameter sets by comparing simulated rotor angles to the target angle.
• During optimization iterations, the Harmony Search Algorithm adjusts parameter values, maintains a harmony memory, and explores the search space efficiently.
• To evaluate the optimized parameters, a swing curve simulation is performed using the updated parameters. The simulation calculates rotor angles over time, considering the dynamic response of the system.
• Finally, the optimized results are displayed, showcasing the parameters that yield the desired swing curve characteristics. This iterative optimization process enhances the understanding of power system dynamics and contributes to improved stability and reliability.