The program uses the DE algorithm, a robust evolutionary optimization technique, to find the best parameter values (pm, pm1, pm2, pm3) for the swing curve simulation. The objective is to achieve a specific target angle and time during the fault clearance event. The DE algorithm evolves a population of candidate solutions over multiple generations, exploring the parameter space to converge to an optimal solution.
The main steps of the program include:
- Initializing the DE algorithm parameters and the target angle and time.
- Setting up the swing curve simulation with initial parameter values.
- Implementing the DE algorithm's main loop, including mutation, crossover, and selection operations.
- Evaluating the fitness of each candidate solution based on the swing curve's performance.
- Updating the population and best individual based on fitness evaluations.
- Displaying the optimized parameter values that best achieve the target angle and time.
- Performing the swing curve simulation using the optimized parameters and plotting the results.
引用格式
recent works (2024). Swing Curve Optimization by Differential Evolution Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/132623-swing-curve-optimization-by-differential-evolution-algorithm), MATLAB Central File Exchange. 检索来源 .
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