基于隨機(jī)聚焦粒子群算法的PSS參數(shù)協(xié)調(diào)優(yōu)化.pdf

1、西南交通大學(xué)碩士學(xué)位論文基于隨機(jī)聚焦粒子群算法的PSS參數(shù)協(xié)調(diào)優(yōu)化姓名：吳峰申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：電力系統(tǒng)及其自動(dòng)化指導(dǎo)教師：陳維榮20090601西南交通大學(xué)碩士研究生學(xué)位論文第1l頁(yè)AbstractWiththeexpansionofelectricpowersystemandinstallationofthefastandhighmagnificationexcitation10wfrequencyoscillationisbe

2、comingoneoftheimportantproblemwhichinfluencesthestabilityofinterconnectionpowersystemPowersystemstabilizers(vss)employedingeneratorsisaneffectivewaytosolvethisproblemPSSgeneratesuchsupplementaldampingtorquethatincreasing

3、systemdampingtoenhancethestabilityofsystemPSS，employedinpowersystem，existthesituationthatsuppressingonemainoscillationmodebutdeterioratinganotherthendeterioratingsystemfurtheroncetheparametersarenotsuitablethatcontrolres

4、ultinevitablydeviatesfromtheoptimalpointdecreasingtheeffectofPSSThereforesuchproblemneedstheoptimizationalgorithmtocoordinatetheworkingstateofPSSThisthesisdemonstratesthebackground，mathematicalmodelandoptimizationprocess

5、ofSFPSOBasedonthemodelofsingle—machinewithinfinite—bussystemand2area4machinesystem，theobjectivefunctionisconsideredastheabilityofsystemoutputtrackingreferencevalueaccordingtotheleasterror(ITAEcriteria)，thenestablishingth

6、emodelofoptimizationofPSSparametersThisthesisalsocomparesandsummariesthepopularoptimizationalgorithmsPSO60(Particleswarmoptimizerwithinertiaweight)，AGA(adaptivegeneticalgorithm)etcAnadvancedPSOStochasticfocusingparticles

7、warmoptimization(SFPSO)isusedtocoordinateandoptimizetheparametersofPSSBythesimulationtestsofthestateofoperatingsystemandcomparisonresultswithvariousoptimizationalgorithmsinmatlab，itdemonstratsthatPSScanobtainthefavorable

8、performanceunderthedifferentdisturbancesusingSFPSOandsuppressthelowfrequencyoscillationeffectivelytomaintainthestabilityofsystemSimultaneouslythevalidityandsuperiorityofSFPSOisprovedKeywords：PowerSystemStabilizers(PSS)；S