Analysis of Power System Stabilizer Using Fuzzy Logic Controller

Analysis of Power System Stabilizer Using Fuzzy Logic Controller

International Journal of Engineering Research & Technology (IJERT)

ISSN: 2278-0181

Vol. 1 Issue 5, July – 2012

Analysis of Power System Stabilizer Using Fuzzy Logic Controller

Mr. Polamuri Pradeep1, Mr.N.Vamsi Krishna2

1M. Tech Student, 2Assistant professor,

1, 2 Electrical and Electronics Department,

1, 2 V R Siddhartha Engineering College, Kanuru

1,2Vijayawada, India

AbstractThe performance of fuzzy-logic power systemstabilizer (FPSS), is investigatedby applying it to a single- machine power system connected to infinite bus. FPSS is developedusingspeeddeviation andthederivativeofspeed deviationasthecontrollerinputvariables.Theperformanc eofthesystemwith fuzzylogicbasedpowersystemstabilizeris compared withthesystemhavingconventionalpowersystem stabilizer

andsystemwithoutp ow er systemstabilizer.The simulationresultsshowthatthe proposedFPSSexhibitsverygood performanceindampingpowersystemlow frequencyoscillationsandgreatlyimprovespowersyste mstability.

Keywords: Power s y s t emstabilizer, s i n g l e -machine pow ersystem, fuzzylogiccontrol,lowfrequencyoscillations,system stability.

I.INTRODUCTION

Thepowersystem isadynamic system.Itis constantlybeingsubjectedto disturbances,which causethe generatorvoltageangletochange.When thesedisturbances dieout,anew acceptable steadystateoperatingconditionis reached.Itis importantthatthesedisturbances donot drive thesystemto unstable condition

In the pastfive decades thePSShave beenusedto providethedesired system performanceundercondition that requiresstabilization.Stability ofsynchronousgenerator dependson

anumberoffactorssuch asthesetting of automaticvoltage regulator(AVR).Manygenerators are designedwithhighgain,fastactingAVRs toenhancelarge scalestabilitytoholdthegeneratorin synchronismwith the

powersystemduringlargetransient faultconditions.But withthehighgainofexcitation systems,itcan decreasethe damping torque of generator.Asupplementaryexcitation controller referred to as PSS have been added to synchronousgeneratorstocounteracttheeffect ofhigh gain AVRs and other sourcesofnegative damping[7].

To provide damping,the stabilizersmust producea componentof

electricaltorqueontherotorwhichisinphase with speedvariations. The application of a PSSistogenerateasupplementarystabilizingsignal,whic h isapplied

totheexcitationsystemorcontrolloopofthegenerating unittoproduceapositivedamping.Themostwidely used conventional PSS is the lead-lag PSS, where the gain settingsare fixed atcertain values whichare

determined underparticularoperatingconditionsto resultinoptimal performanceforthatspecificcondition.However,theygi vePoorperformanceunderdifferentsynchronousgenerat or loadingconditions. ConventionalPSS(CPSS) iswidelyused in existing powersystemsandhasmadea contributionin enhancingpowersystemdynamicstability.Theparamete rs ofCPSSaredeterminedbasedon alinearizedmodel [2]of thepowersystem

aroundanominaloperatingpointwhere theycanprovidegoodperformance.Sincepowersystems arehighlynon-linearsystems,with configurations and parameters thatchangewith time,theCPSS design basedon thelinearizedmodelofthepowersystemcannotguarantee its performance ina practicaloperatingenvironment[3].

1. OVERVIEWOFPOWERSYSTEMAND MODELLING

   Asimplifiedschematicdiagram [3]ofasingle- machineinfinite-bussystem isshowninFig.1.The system consistsof agenerating unit connectedtoaconstantvoltage bus throughtwoparalleltransmissionlines.An excitation systemandautomaticvoltageregulator (AVR)areemployed tocontroltheterminalvoltage,andan associatedgovernor monitors theshaftfrequencyandcontrolsmechanical power. Neglectingthetransientsinthestatorcircuitandtheeffect ofrotoramortisseur,thesynchronousgeneratorcan be representedin theform of Park'stwo- axismachinemodel by aset of simplifiedlinearequations [2]. Thetransmission networkwithanimpedance of re+jx,is connectedtoan infinite bus of voltage Vb and the AVR and excitation systemarerepresentedby afirstorderdifferentialequation. Undernormal operating conditions,alinear,time-invariant systemcan be derivedby applying smallperturbation relationsaroundacertainequilibriumpoint.A linearized model [6] isshowninBlockdiagramformatFig.2

   Fig.1Aschematic diagram of the powerstem.

   Fig.2Linearzedpower systemmodelwithFPSS

   Fig.3Linearizedpower systemmodelwithPSS TABLE.1

   PARAMETERS FORTHELINEARIZED POWERSYSTEMMODEL

   Parameter	Value
   K1	1.5495
   K2	1.2255
   K3	0.3231
   K4	0.8910
   K5	-0.0138
   K6	0.4942
   H	3.5
   D	0
   T3	2.3567
   Ga(s)	210
   TR	0.02
   0	314

   The blockdiagramfor power systemstabilizer [6] is shown below.

   TABLE.2

   PARAMETERS FOR THE ANALOG PSS

   Fig.4Thermistor excitationsystemswithAVRandPSS

2. FUZZYLOGICBASEDPSS

   The fuzzycontrolsystemsarerule-basedsystemsin whichasetoffuzzy rulesrepresentacontrol decision mechanismtoadjusttheeffectsofcertain system stimuli. Withaneffectiverulebase,thefuzzy controlsystemscan replaceaskilledhuman operator.Thefuzzy logiccontroller providesanalgorithmwhichcan convertthelinguistic control strategy based on expert knowledge into an automatic control strategy. The Fig.5 illustrates the schematicdesignofafuzzylogiccontrollerwhichconsist s ofafuzzification interface,a knowledge base,decision makinglogic, anda DefuzzificationInterface.

   Fig.5Theprincipledesign of fuzzy logic controller

3. CONTROLLERDESIGNPROCEDURE

   Thefuzzylogiccontroller(FLC)designconsistsofth e followingsteps.

   1)

   Identificationofinputandoutputvariabl es.

   2)

   Constructionofcontrolr ules.

   1. Establishingthe approachfor describingsystemstate in termsoffuzzy sets,i.e.establishingfuzzificationmethod andfuzzymembershipfunctions.

   2. Selectionofthe compositionalrule ofinference.

   3. Defuzzification m e t h o d , i . e ., t r a n s f o r m a t i o n of t h e fuzzycontrol statementintospecific controlactions.

      MEMBERSHIPFUNCTION:

      Thevariableschosenforthiscontrollerarespeed deviation, accelerationandvoltage. In this, the speedDeviationandaccelerationaretheinputvar iablesandvoltageisthe outputvariable.

      NB	NegativeBig
      NM	NegativeMedium
      NS	NegativeSmall
      ZE	Zero
      PS	Positive Small
      PM	Positive Medium
      PB	Positive Big

      Table3. Membership functions for fuzzyvariables.

      Fig.6Membership functionsfor Acceleration

      Fig.7Membership functionsfor speeddeviation

      Fig.8Membership functionsfor voltage

      Eachoftheinput andoutputfuzzyvariablesisassigned seven linguisticfuzzy subsets varyingfromnegativebig(NB)topositivebig(PB).Ea chsubsetisassociatedwithaTriangularmembershipfu nction toform asetofseven membershipfunctionsfor eachfuzzyvariable.Thevariables arenormalizedby multiplyingwith respective gainsKin1,Kin2,Koutsothat thirvalueliesbetween- 1and1. Themembershipfunctions ofthe inputoutputvariableshave 50% overlap between adjacent fuzzy subsets.Themembershipfunctionfor acceleration,speedandvoltageare Shown below.

      FUZZYRUL E BASE:

      Asetof ruleswhich definetherelation between the inputandoutputoffuzzycontrollercan befoundusingthe availableknowledgeintheareaofdesigningPSS.Thes e rulesare definedusing thelinguisticvariables.Thetwo

      inputs,speedandacceleration, resultin49rulesforeach machine. The typical rules are having the following structure: Rule1:Ifspeeddeviation isNM (negativemedium)AND acceleration is PS (positivesmall)thenvoltage(output of fuzzyPSS) isNS(negative small).

      Rule2:IfspeeddeviationisNB (negative big)AND accelerationis NB(negativebig) thenvoltage (outputof fuzzyPSS) isNB(negative big).

      Rule 3: If speeddeviationisPS(positive small) AN D

      Acceleration isPS(positivesmall)thenvoltage(outputof fuzzyPSS) isPS(positive small). Andso on.

      Allthe49rulesgoverningthemechanism areexplainedin Table3.2whereallthesymbolsaredefinedinthebasic fuzzylogic terminology:

      T A B L E

      . 4

      RULE BASEOF FUZZYLOGICCONTROLLER

      Speed Deviation	Acceleration
      	NB	NM	NS	ZE	PS	PM	PB
      NB	NB	NB	NB	NB	NM	NM	NS
      NM	NB	NM	NM	NM	NS	NS	ZE
      NS	NM	NM	NS	NS	ZE	ZE	PS
      ZE	NM	NS	NS	ZE	PS	PS	PM
      PS	NS	ZE	ZE	PS	PS	PM	PM
      PM	ZE	PS	PS	PM	PM	PM	PB
      PB	PS	PM	PM	PB	PB	PB	PB

4. RESULTSANDDISCUSSION SIMULINKMODEL:

Fig.9Simulinkmodel forsinglemachine connectedtoinfinitebuswithPSS

Fig.10Simulink model for singlemachineconnected toinfinitebuswith

Fuzzylogic basedPSS

CaseI:

Simulation resultswithoutPSS when voltage(0.1p.u)Disturbanceisapplied

Fig.11Loadanglewhen0.1 pp.voltagedisturbanceapplied

Fig.12Speeddeviation when5% torque disturbanceapplied

Fig.13Loadanglewhen5%torquedisturbanceapplied

CaseII:

Simulation resultswithPSS when voltagedisturbance (0.1p.u)andtorquedisturbanceof5%isapplied.

Fig.14Controlsignalwhen0.1 pp. voltagedisturbanceapplied

Fig.15Controlsignalwhen5% torquedisturbanceapplied

Fig.16 Load angle when 0.1 p.u voltage disturbance applied

Fig.17Loadanglewhen5%torquedisturbanceapplied

Fig.18Speeddeviation when0.1 pp.voltagedisturbanceapplied.

CaseIII:

Simulation resultswithFPSS when voltagedisturbance(0.1p.u)andtorquedisturbance of5%isapplied

Fig.19Controlsignalwhen0.1 pp. voltagedisturbanceapplied

Fig.20Controlsignalwhen5% torquedisturbanceapplied

Fig.23Speeddeviations when0.1 pp.voltage disturbanceapplied

Fig.24 Speeddeviationswhen5% torque disturbanceapplied VII.CONCLUSION

FromtheaboveresultswecansaythatFPSS shows thebettercontrolperformancethanpowersystemstabili zer interms ofsettling timeanddamping effect.Itisthus possibleto

realizethecontrollerefficiently.Therefore,it can beconcludedthat the performanceofthe proposedFPSSis much better andtheoscillations are dampedoutmuchquicker

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Fig .21Loadanglewhen0.1 pp.voltagedisturbanceapplied

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