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Neural Network Based Load Frequency Control F

Restructuring Power Industry

Sushil Sharma Kharel

068 BEL 346

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Introduction

When load changes the system changes from normcondition

Conventional controller are set to some level forcomromise the demand

!"" controller is roosed #hose action is $ased of change of fre%uency than change in fre%uency acase of conventional controller

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-Slo# in &rocess'Li(ely to have transients and overshoot

Conventional Controller

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Conventional Controller

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!ggregator )unction

-Sigmoidal and Gaussianfunctions are used asactivation function

-Sigmoidal for accurateinterpolation

-Gaussian forextrapolation ability

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Feed Forward BackPropagation

Contains of 3 inut *df+dh+dt, + - hidden and a single outut*d&ref

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!datation of "eural "et#or( Controller

.*n, reresents the

characteristic oflant model /df*n,d&t*n, d&h*n,

C comares .*n, to.steady stateto generate thecontrol signal

Control signal u*n, isd&ref to oerate thetur$ine

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!datation of "eural "et#or( Controller

!t each time ste

1*n2, is evaluated$ased on d&e+u*n,and 1*n,

!t t50 + C ta(es 1*0, generate u*0,

!t t5" + .*",7.steady'

state+error is $ac(roagated for#eight adustment

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!earning "lgorit#m

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!"" in single area system

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!"" in t#o area system

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Conclusion

$on-linear and dynamic be#avior can be lineari%more accurately

!ess execution time due to less number of #iddelayers

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Thank You