Optimization and Setting of the PSS Parameters Based on the Differential Evolutionary Particle Swarm Optimization Algorithm
WANG Jianbo
LIU Yili
LIANG Jiguo
DING Huanhuan
Abstract：In order to better solve the problems of power system stabilizer(PSS)parameter optimization,differential evolution particle swarm optimization(DEPSO)is applied to PSS parameter optimization. DEPSO algorithm can seek global optimal location through information exchange mechanism between PSO population and DE population,so that the algorithm has dynamic adaptabili?ty to skip local optimum easily. First,the paper expatiates on the optimization method of PSS lead-lagging link and gain parameters by DEPSO algorithm in the low frequency range(0.1～2.5Hz). Then constructing a single machine infinite system model using Mat?lab and is studied by simulation,the results show that the PSS stability designed by DEPSO algorithm has been improved greatly, and the effect of DEPSO is better than PSO algorithm's. Using the proposed method,adjusting PSS parameters of some units,Anhui power grid,based on the unit measured uncompensated phase characteristics,the algorithm's validity is tested.
Keywords：PSSdifferential evolutionary particle swarm optimizationsingle machine infinite busParameter optimiza?tionsetting parameter
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 53-58 )