Particle Swarm Optimization Experiment Study And Expand

Particle Swarm Optimization (PSO) is a new intelligent optimization algorithm, programming to be widespread concern due to its simple, adaptable, better global optimization features etc. Particle Swarm Optimization also has a large number of applications to power system optimization. How to further improve the PSO algorithm design and performance of specific system efficient algorithm is currently the focus of the study. The main propuse of this paper is to explore the PSO algorithm optimization mechanism through a large of experimentation. Based on this, new optimization algorithm is design, in order to design new, more effective algorithm. In this paper, the specific arrangements are as follows:The paper reviewed the hydro-thermal power system short-term optimal operation of the status quo, focus on reviewing the modern Heuristic Optimization Algorithm in the system application. Then the PSO algorithm for the birth, development, and the results achieved, and the shortcomings of the Comprehensive are reviewed. Based on this established a research paper, and gives arrangements of the paper.introduceing PSO algorithm for the birth, principle, on the basis of this, the PSO algorithm technology and the realization of concrete steps are given. Also focuses on the PSO algorithm four typical forms. In order to further improve the performance of the algorithm proposed a modified PSO algorithm -- random perturbation PSO Algorithm. Through some of the typical function optimization, the algorithm's effectiveness is proved.The working mechanism for the PSO algorithm is probed through experimentation study. At first, according to the different performance of the speed of updating the formula in different optimize phase, the typical definition of the concept of circumstances and four typical cases of specific forms are given. On this basis, under typical circumstances of dynamic and static of a pilot study to explore PSO algorithm works. Moreover, different combinations of parameters to optimize the performance of a pilot study to be some useful conclusions. Finally a few exploratory test of the new algorithm is provided.The three new optimization algorithms derived from the basic PSO algorithm are proposed. 1. the simulation PSO algorithm is given through simulate each particle distribution after each iteratives ; 2.The optimal worst PSO algorithm is proposed through removing the formula for the speed of inertia, adding the worst particle; 3. by simulating the entire population distribution, the overall distribution optimization algorithm is given. The overall distribution optimization algorithm is simple, robust and strong performance optimization features among above algorithms through comparing.The overall distribution optimization algorithm is used to solve short-term scheduling for hydro-thermal power systems. The result is compared with the results of genetic algorithm and evolutionary programming for the same system, the validity of the overall distribution optimization algorithm is verificated. This example notes the overall distribution optimization algorithms are more suitable for short-term hydropower electricity generation schemes such complex systems optimization.Finally, the paper summarized the results and made pending further study.