Optimal Design

7/25/2019 Optimal Design

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Optimal Design Of a SVC

Controller Using a Small

Population Based PSO

Submitted By

Nithya C.

1690910024

M.Tech (Power ytem!


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Abstract

SVC is a shunt connected Flexible AC Transmission System

(FACTS) device.

The primary purpose of a SVC is voltae control.

!S" alorithm #ith a small population is used for the desin

of an SVC Controller that can provide better voltae control.

SVC Controller parameters are determined for a t#o$area

po#er system sub%ected to small and lare disturbances.


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&ntroduction

FACTS devices are used for control and s#itchin operations.

These controllers are fast and increase the stability operatin

limits of the transmission systems #hen their controller are

properly tuned.

SVC is employed primarily for voltae stability by providin

appropriate reactive compensation.

The conventional control of the SVC is the proportional plus

interal type (!& ).

&n conventional method best performance of SVC is obtained

tunin the parameters of the !& control.


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Since the po#er systems are hihly nonlinear systems '#ith

confiuration and parameters that chane #ith time' the

conventional SVC desin based on a linearied model of thepo#er system cannot uarantee its performance in a practical

operatin environment.

Therefore it is important to determine the parameters of the

SVC and similar controllers usin po#er system simulation

models and tools.


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hy S!!S"*

The S!!S" is suitable for online implementation.

S!!S" based alorithm re+uire less computations to determine

optimal parameters as compared to !S".


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,ulti ,achine !o#er System


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-loc /iaram of SVC Controller


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The !& controller consists of ain constant' 0p' and interal

constant Ti.

These are the parameters that need to be optimally selected for

the SVC to ensure optimal system performance under a #ide

rane of operatin conditions and disturbances.


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S!!S" Alorithm

!S" is a form of evolutionary computation techni+ue.

The system initially has a population of solutions. 1ach

solution is called as particle and is iven a random velocity and

is flo#n throuh the problem space.

The particles have memory and each particle eeps trac of

previous best position and correspondin fitness.


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The S!!S" alorithm consists of

mainly t#o features.

The use of a small population of particles .

2eeneration concept #here ne# particles are randomly

created every 3 iterations to replace all but the best particle in

the s#arm.


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"ptimal /esin "f a SVC Controller

The SVC aims at maintainin the voltae manitude set point

at the point of common couplin by providin appropriate

reactive po#er compensation.

,oreover the ob%ective of the optimiation is for the voltae

control #hich means minimiin voltae deviations under

small and lare disturbances

S!!S" is applied to determine !& parameters that results in the

least fitness value sub%ect to the constraints in (4) for various

faults and disturbances.


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S&,56AT&"3 21S56TS

The entire po#er system and S!!S" simulation is carried out

in the !SCA/71,T/C7F"2T2A3 environment.

The multiple run feature in !SCA/ is used to carry out a set

of S!!S" iterations.


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Test 8

Step chanes in the SVC !& controller voltae reference (Vref)

are applied to test the performances of the S!!S" optimied

and unoptimied !& controllers.


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Vpcc response for a step chane in

reference level of the !& controller of

SVC.


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2eactive po#er response at SVC bus


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Correspondin susceptance (-)

response of SVC


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Test 9

A transmission line outae is carried out at 8: seconds bet#een

buses ; and < in and this outae is not restored immediately.

&t can be seen that the S!!S" optimied the Vpcc response for

line outae.


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Vpcc response for a step chane in

reference level of the !& controller of

SVC.


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2eactive po#er response at SVC bus


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Correspondin susceptance (-)

response of SVC


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C"3C65S&"3

The optimal desin of a SVC controller is presented usin a

small population based particle s#arm optimiation alorithm

(S!!S").

The S!!S" alorithm is used to optimie the SVC !&

controller parameters. These parameters provide better voltae

stability than those parameters obtained by trial and error iven

the same cost function as that of S!!S"


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Thank You

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