Abstract
Optimization techniques are getting importance in control and power system of sustainable energy technologies. Particle Swarm Optimization is aversatileoptimizing technique. Due to its diversity, it attracts many researchers to modify the algorithm itself and scrutinize different parameters to get precisely optimized results. PSO plays a vital role for finding solutions for continuous optimization problems and also acts as an alternative for global optimization. The designing of standard PSO is defined in this project which has been taken into account by the latest research and developments, and is used as a guideline for performance testing by different functions. The benchmarks we used are Sphere, Ackley, Rosenbrock, Schewfel's 2.26 and Rastrigin. We implemented the original algorithm, and obtained optimized results for every function and plot the graphs against Global best value and Function evaluation.