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A Voltage-Frequency Fuzzy Logic Controller for Large Scale Power Systems
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR...
Copyright © 1999 IFAC 14th Trienni
14th World Congress ofIFAC
0-7c-lO-2 P .\{. China
A Voltage-Frequency Fuzzy Logic Controller for Large Scale Power Systems W. Sabry
Egyptiall Armed Forces
Abstract : This paper presents a novel control operation of fuzzy logic power system stabilizer (FLPSS) for stability enhancement of large scale power systems. The FLPSS is applied for each machine in the system. In order to accomplish best damping characteristics for rotor speed and terminal voltage of each machine in the system, two signals from each machine are chosen as inputs to the FLPSS of this machine; deviation of rotor speed and deviation of term lnal voltage. These technique proved its efficiency in damping oscillations in the frequency and variations in the terminal voltage signals of each machine in the system. Hence, a better system srability is achieved. Copyright @19991FAC Keywords: Fuzzy Logic, Power System Stabilizer, Large Scale System, Stability.
contalnlllg fuzzy descriptions. Therefore, fuzzy logic is a natural choice for this purpose and may be considered acceptable for such a purpose t5,6].
1. INTRODUCTION In the last decade, efforts have been directed into the enhancement of the stability problem of power systems. For the extension in power systems, the problem of stability bas a great attention. Different approaches have been discussed in literature to provide the damping required for improving the system stahility. The main approaches have lead to the devdopment of two types of contt'ollers; the power system stabilizers (PS Ss) and the static V AR compensators (SVCs) [I]. The design of PSSs and SVCs have employed many different control techniques such as conventional controllers, adaptive controllers, optimal controllers, ... etc. Also, with the devel0p.rnent of computer science and technology and their applications, different new branches of artificial intelligence (AI) and expert systems (ESs) have been generated and applied in power systems controL Different fields have stemmed from AI such as artificial nemal network (ANN) approaches and genetic algorithms (GAs) [2-4]. ESs are built on basis oflhe knowledge gained from the field experience. In FL techniques, this knowledge is generally expressed in linguistic expressions
In recent controllers design, FL controllers have received more attention, since they are robust, 1110delindependent, and adaptable. Fuzzy logic controllers are mainly used for power system exciters, A YRs, SYCs, PSSs. and converter controllers. In many sources of the previously published work, the FLPSSs are used to improve frequency osci lIations neglecting their effect on other important signals slIcb as the terminal VOltage. This paper rresents a new addition in the continuous development of the FLPSSs. The proposed FLPSS uses two input Signals represented by deviation of rOlor speed and deviation of ler-m inal voltage. The intluence of the proposed FLPSS schem '~ on the dynamic characteristics of the controlled system is investigated. Simlllation restdts to illustrate the effectiveness of the proposed controller are presented. These results have been obtained as an outcome of a detailed simulation study on a three machine power system. In the simulation study, the power nenvork has been subjected to a severe Iype of disturbance namely sudden short circuit at the end of one of the system busbars. Th is test can demonstrate
7493
Copyright 1999 IF AC
ISBN: 0 08 043248 4
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR. ..
the enhancement of the system.
transient stability of the
14th World Congress ofIFAC
numerical input v3[·iables. For good control actions, seven variables llre chosen as [9]: Large positive Medium positive Small positive Very small Small negative Medium negative Large negative
a-
2. POWER SYSTEM MODEL
bc-
A typical power system is to be studied. It consists of three synchronous machines connected to a nine-bus network as shown in Figure (1). An IEEE type IS excitation system has been used t.x each machine in the system. The state-space equations of each synchronous machine and the associated excitation system are written as obtained in different literature sources [7,8]. Thc system data is illustrated in Appendix (A) [7,8].
ef.. g-
d-
: "LP".
: "MP". : ~'SP". "VS". : "SN". : "[\IIN". : "LN".
The membership functions are chosen to be trapezoidal if the input signal is "LP" or "LN" and triangular for the others. Table (I) shows the domain for the two input signals.
Table (/) : Fllzzy Logic Control Rules
3-phase short circuit fault is assumed 10 take place at the end of tie-line 5-7 near bus (7) at zero lime. The fault is assumed to be cleared and the line is connected back successfully after 10 cycles of the power frequency. This corresponds to 0.2 Sec. for a 50 flz system. A
Sig.nal LN MN SN VS SP MP
3. FLPSS DESIGN The first step in designing the FLPSS is the determination of the state variables which represent the performance of the system. The input signals to the FLPSS are to be chosen from these variables. Since the main objective oflbe PSS is to limit the oscillations il1 the rotor speed and variations in the terminal vollage, the deviation of rotor speed (L'l.w) and deviation of terminal voltage (L'l. V,) of each synchronous machine in lill' ".,stem are taken as inputs to the FLPSS.
~
LP
6V, x 10-2 [-6.0,-3.25] [-5. 7 .5,-1. 7 51 [-2.5,0.0] r -1.25,1.251 [0.0,2.5J r 1.25,5.25] [3.25,6.0]
L'l.w [-0.03,-0.0125] [ -0.02,-0.0051 [-0.01,0.0] [ -0.005,0.005] [0_0,0.0 I} rO.005,0.02) [0.0125,0.031
Table (2) shows the rules controlling the fuzzifted output signal. For appropriate control signals, we define crisp value,; for the control output corresponding to the different fuzzy subsets LN, MN, SN, VS, SP, MP, or LP. These crisp values can be computed from the defuzzification process. The defuzzification process converts the fuzzy variables into crisp outputs and is done with the help of the center of gravity method (COG) [9].
Table (2) : F2I:n:y Logic Control Rules
[;EJ
LN
MN
SN
VS
SP
MP
LP
LN MN SN
MP
MP MP SP
LP MP MP
LN LN LN
LN MN MN
MN
SP
MN SN
ZE
ZE
ZE
ZE
ZE
SN MN MN
J'vlN
LP
MN
LP LP
MP MP LP
SI' MP
6.V,
VS
(5)
~. Load A
SI'
L1t,·r. . LoadC
Fi~l(/"e (I) . A IIwllim{;cl1ille power sysrem model (L\W) and (i1V,) of each synchronous machine can be
computed directly from real-time measurements and the set point. Their values at any instant of time can be expressed in a discrete form as:
MP LP
ZE ZE ZE SN MN
LN
MN SN
MP
ZE ZE ZE SP MP
For appropriate control signals, we define crisp values for the control output corresponding to the different fuzzy subsets LN, MN, SN, VS, SI', MP, or LP. These crisp values can be computed from the defuzzification proces5. The d;:fuzzification process converts the fuzzy v
L'.0l = (0 (t) - (00 ' and L'. V, = V t (t) - V'o The second step in the design is to decide on the linguistic variables. These variables fuzzify the
7494
Copyright 1999 IF AC
ISBN: 008 0432484
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR. ..
14th World Congress ofIFAC
4. CONTROL STRATEGY Each machine on the power system is assumed to be equipped with excitation system and speed governor. Also, Each machine in the system is assumed to be equipped with a FLPSS. This machine has different output signals, two of them are chosen to be the input of the FLPSS; the deviation in rotor speed (D,(J)) and the deviation in terminal voltage (!,w,).
Change in relaLive rotot spe.e.d w31 (pu_)
a:~:~-\~---~---~.,----~----. 0.01
0.005 : ...
From the control point of view; to control a certain process, the output signal(s) must be feedback to the process to give better response. Also, from the view point of FL control, the value ofthis(these) signal(s) can decide the behavior of the process. So, to perform a sound better voltage and frequency profile, the two inputs to the FLPSS are chosen 10 represent them through their deviations.
-0005
.;: ./"...... =.:.~.... -"
-001 -0.015
Time (Second)
Fig1lre (2 h.) : Rotor Speed of Machine (3) - Time response
5. SIMULATION RESULTS In order to validate thig new control strategy as discussed in the latter section, a digital computer simulation program is developed using MA TLAB package. The obtained results are shown in the following figures. Figures 2.a., and 2.b represent the change in the relative rotor speed in p.u. for machines (2, and 3) respectively with respect to machine (l). Figures 3.a., 3.b., and 3.c. represent the terminal voltage in p.ll. for machines (l, 2, and 3) respectively. In all these figures, the curve with dotted line plot represents the machine when equipped with excitation controller and speed governor only, and the Cllrve with solid line plot represents the machine when equipped with the proposed control in addition to excitation control and speed governor. Also, the horizontal solid linerepresents the steady state value of each signal mentioned by the curve, and the horizontal dashed lines represent the percentage of ± I % for the frquency and ± 6"/0 for the voltage.
.- .-~.. ~. -.. '--,~ ':,-"- _.. {. ~.-'" ... f' :,:"
.....
1.1
DSS·
09
Time (Second)
Figure
Terminal Voltage - Time response
(3.0.) : Nfachine (1)
, .. chine (21 tCI'minal \,'olta.!l-C Cpu) I
'~-r-------r-------r-------r-------,
Ch.ange in rei alive rotor s-peect w21 Cpu)
09
OD25,-----~~---r__---r__--~,__--__,
002
08
:. 0.015
01
O.()1 " : ...
0<>
o5 0.4
-0.01
..
..... ;.. Time ,Sccond)
-0.015
Fig1lre (3 h.)
-0.02
AlaciJine (2) Terminal Vollage - Time response
Time (Second,
-----,-------------------------
Figure (2. a.) : ROlOr Speed Of Alaehi ne (2) - Time response
7495
Copyright 1999 IF AC
ISBN: 008 0432484
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR...
14th World Congress ofIFAC
Machine ( 3 1 terminal voltage (P_u .)
Power Systems, Vo!. JO, No. 3 , Au g : 1995. C. V. Negoita, "Ex pel1 Systems and Fuzzy Sy stems", The Benjamin/CulI1mings Publishing Company, Inc., 1984. 7. P. M . Anderson, and A.A. , Fouad, "Power Systems Control and Stability", Ames , Iowa: State University (1977). 8. IEEE Committee report, "Computer Representation of Excitation Systems", IEE E Trans., PAS-87 (1968) : 1460-1464. 9. Y. Y. HSlJ, and C. H . Cheng," Design of Fuzzy Powe r System Stabilizers for Multimachine Power Systems", lE E Proceedings, Vol. 137, Pt. C, No. 3, PP. 233-238, May 1990.
'2r---~---~--~---~-----'
6.
09 O.B
0 .7 0.6
050!c----::----"* 2----::3,-----~4~-----!5 Time (Second)
Appendix ( A )
Figlll"e (J.c.) : fv(achine (3) Terminal Voltage - Time
response Machine parameters: It is clear that the proposed control strategy has a sound effect for voltage and frequency in the same time for each machine in the system. The overshoot is less, the settling time is less, and the steady state error is less. So, the stability enhancement of the overall system ""ill achieved.
( reactances in p.ll. to a base of 100 M V A )
H
6. CONCLUSION
P. F. Type speed
This paper demonstrates an application of a FLPSS applied for a large scale power system. The FLPSS is designed to make the response of both voltage and frequency of the system be bette r. The results discussed in the Jast section and the curves of Figures 2, and :; illustrate the quality of this controller to be a new addition over the conventional FLPSSs which mainly concerned with frequency.
7. REFERENCES 1. F. P.
Demello and C. Concordia, "Concepts of Synchronous Machines Stability as Affected by Excitation Control", IEEE Transactiolls 0 11 Powe r Apparatus and Systems, V o !. PAS-SS, No. 4, PP. 316-329, April 1969. 2. R. L. Harvey, "Neural Network Principles", Printice-Hall, Inc., 1994. 3. J. L. Chen, "A Fuzzy Expert System tor Fault Diagnosis in Electric Distribution System", 1993 Canadian Conference on Electrical and Computer Engineering, Sep. 14-/7, /993 Vancouver, Canada. 4. P. Jervanhaura, P. Verho, a n(l J. Partanen, "Using Fuzzy Sets to Model the Uncertainty in the Fault Location Process of Distribution Networks", IEEE/PES 1993 Summer Meeting, Vancouver, B.c., Canada, July 18-22 1993, 93 SM 4 J 68 PWRD. 5. J. A. Momoh, X. W. Ma, and K. Tomsovic, "Overview and Literature Survey of Fuzzy Set Theory in Power Systems", IEEE Trans. on
I
Machine Rated MVA kV
Xd X'd
Xq X'q
r
I
1
192.0
16 .5 23 .64 1.0 bvdro 180 rpm 0.146 0.0608 0.0969 0.0969
18 .0 6.4
0.85 steam 3600 rpm 0.8958 0.1198 0.8645 0.1969 6.0 0.535
&.96
do
0.0
T'(o
I
2
247.5
3 128.0
I
13.8
3.01 0.85 steam 3600 rpm 1.3125 0.1813 1.2578 0.25 5.89 0.6978
. o'neratlDl! COIll d'•hons:
I
Mach.
I P (p.lI.)
Ea
0.716 1.63 0.85
Transmission lines' Node No. 4-5
I
4-6 5-7
6-8 7-8
8-9
Q (p.u.)
V (p.u.)
0 .2 7 0.067 -0.109
1.04 1.025 1.025
11
ImEedance( E.u. ) 0.0 I + i 0.085 0.017 + i 0.092 0.032 + j 0.161 0.039 + j O. I 7 0.0085 + j 0.072 0.0119 + j 0.1008
Excitation system oarameters: 2 1 45.0 35.0 0.1 0.2 T .\ 0.015 K,.. 0001 0.7 0.8 TI
~
(rad.) 0.0625 1.0665 0.9458
(5
I
~
..)
40.0 0.15 0.002 0.75
7496
Copyright 1999 IF AC
ISBN: 0 08 043248 4
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR...
.S
ee dG.overnor parameters:
achine
14th World Congress ofIFAC
Loads ' 2
3
Kc Tc
1 0.9 0.07
LI 0.09
1.0
R~
0.G3
0 .05
I
I~
0.08 0.04
Load
11
I
( (l.u. )
I
1./6 - j 0.5044 0.8777 - j 0.2926 0 .969 -10.3391
7497
Copyright 1999 IF AC
ISBN: 0 08 043248 4
Copyright © 1999 IFAC 14th Trienni
14th World Congress ofIFAC
0-7c-lO-2 P .\{. China
A Voltage-Frequency Fuzzy Logic Controller for Large Scale Power Systems W. Sabry
Egyptiall Armed Forces
Abstract : This paper presents a novel control operation of fuzzy logic power system stabilizer (FLPSS) for stability enhancement of large scale power systems. The FLPSS is applied for each machine in the system. In order to accomplish best damping characteristics for rotor speed and terminal voltage of each machine in the system, two signals from each machine are chosen as inputs to the FLPSS of this machine; deviation of rotor speed and deviation of term lnal voltage. These technique proved its efficiency in damping oscillations in the frequency and variations in the terminal voltage signals of each machine in the system. Hence, a better system srability is achieved. Copyright @19991FAC Keywords: Fuzzy Logic, Power System Stabilizer, Large Scale System, Stability.
contalnlllg fuzzy descriptions. Therefore, fuzzy logic is a natural choice for this purpose and may be considered acceptable for such a purpose t5,6].
1. INTRODUCTION In the last decade, efforts have been directed into the enhancement of the stability problem of power systems. For the extension in power systems, the problem of stability bas a great attention. Different approaches have been discussed in literature to provide the damping required for improving the system stahility. The main approaches have lead to the devdopment of two types of contt'ollers; the power system stabilizers (PS Ss) and the static V AR compensators (SVCs) [I]. The design of PSSs and SVCs have employed many different control techniques such as conventional controllers, adaptive controllers, optimal controllers, ... etc. Also, with the devel0p.rnent of computer science and technology and their applications, different new branches of artificial intelligence (AI) and expert systems (ESs) have been generated and applied in power systems controL Different fields have stemmed from AI such as artificial nemal network (ANN) approaches and genetic algorithms (GAs) [2-4]. ESs are built on basis oflhe knowledge gained from the field experience. In FL techniques, this knowledge is generally expressed in linguistic expressions
In recent controllers design, FL controllers have received more attention, since they are robust, 1110delindependent, and adaptable. Fuzzy logic controllers are mainly used for power system exciters, A YRs, SYCs, PSSs. and converter controllers. In many sources of the previously published work, the FLPSSs are used to improve frequency osci lIations neglecting their effect on other important signals slIcb as the terminal VOltage. This paper rresents a new addition in the continuous development of the FLPSSs. The proposed FLPSS uses two input Signals represented by deviation of rOlor speed and deviation of ler-m inal voltage. The intluence of the proposed FLPSS schem '~ on the dynamic characteristics of the controlled system is investigated. Simlllation restdts to illustrate the effectiveness of the proposed controller are presented. These results have been obtained as an outcome of a detailed simulation study on a three machine power system. In the simulation study, the power nenvork has been subjected to a severe Iype of disturbance namely sudden short circuit at the end of one of the system busbars. Th is test can demonstrate
7493
Copyright 1999 IF AC
ISBN: 0 08 043248 4
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR. ..
the enhancement of the system.
transient stability of the
14th World Congress ofIFAC
numerical input v3[·iables. For good control actions, seven variables llre chosen as [9]: Large positive Medium positive Small positive Very small Small negative Medium negative Large negative
a-
2. POWER SYSTEM MODEL
bc-
A typical power system is to be studied. It consists of three synchronous machines connected to a nine-bus network as shown in Figure (1). An IEEE type IS excitation system has been used t.x each machine in the system. The state-space equations of each synchronous machine and the associated excitation system are written as obtained in different literature sources [7,8]. Thc system data is illustrated in Appendix (A) [7,8].
ef.. g-
d-
: "LP".
: "MP". : ~'SP". "VS". : "SN". : "[\IIN". : "LN".
The membership functions are chosen to be trapezoidal if the input signal is "LP" or "LN" and triangular for the others. Table (I) shows the domain for the two input signals.
Table (/) : Fllzzy Logic Control Rules
3-phase short circuit fault is assumed 10 take place at the end of tie-line 5-7 near bus (7) at zero lime. The fault is assumed to be cleared and the line is connected back successfully after 10 cycles of the power frequency. This corresponds to 0.2 Sec. for a 50 flz system. A
Sig.nal LN MN SN VS SP MP
3. FLPSS DESIGN The first step in designing the FLPSS is the determination of the state variables which represent the performance of the system. The input signals to the FLPSS are to be chosen from these variables. Since the main objective oflbe PSS is to limit the oscillations il1 the rotor speed and variations in the terminal vollage, the deviation of rotor speed (L'l.w) and deviation of terminal voltage (L'l. V,) of each synchronous machine in lill' ".,stem are taken as inputs to the FLPSS.
~
LP
6V, x 10-2 [-6.0,-3.25] [-5. 7 .5,-1. 7 51 [-2.5,0.0] r -1.25,1.251 [0.0,2.5J r 1.25,5.25] [3.25,6.0]
L'l.w [-0.03,-0.0125] [ -0.02,-0.0051 [-0.01,0.0] [ -0.005,0.005] [0_0,0.0 I} rO.005,0.02) [0.0125,0.031
Table (2) shows the rules controlling the fuzzifted output signal. For appropriate control signals, we define crisp value,; for the control output corresponding to the different fuzzy subsets LN, MN, SN, VS, SP, MP, or LP. These crisp values can be computed from the defuzzification process. The defuzzification process converts the fuzzy variables into crisp outputs and is done with the help of the center of gravity method (COG) [9].
Table (2) : F2I:n:y Logic Control Rules
[;EJ
LN
MN
SN
VS
SP
MP
LP
LN MN SN
MP
MP MP SP
LP MP MP
LN LN LN
LN MN MN
MN
SP
MN SN
ZE
ZE
ZE
ZE
ZE
SN MN MN
J'vlN
LP
MN
LP LP
MP MP LP
SI' MP
6.V,
VS
(5)
~. Load A
SI'
L1t,·r. . LoadC
Fi~l(/"e (I) . A IIwllim{;cl1ille power sysrem model (L\W) and (i1V,) of each synchronous machine can be
computed directly from real-time measurements and the set point. Their values at any instant of time can be expressed in a discrete form as:
MP LP
ZE ZE ZE SN MN
LN
MN SN
MP
ZE ZE ZE SP MP
For appropriate control signals, we define crisp values for the control output corresponding to the different fuzzy subsets LN, MN, SN, VS, SI', MP, or LP. These crisp values can be computed from the defuzzification proces5. The d;:fuzzification process converts the fuzzy v
L'.0l = (0 (t) - (00 ' and L'. V, = V t (t) - V'o The second step in the design is to decide on the linguistic variables. These variables fuzzify the
7494
Copyright 1999 IF AC
ISBN: 008 0432484
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR. ..
14th World Congress ofIFAC
4. CONTROL STRATEGY Each machine on the power system is assumed to be equipped with excitation system and speed governor. Also, Each machine in the system is assumed to be equipped with a FLPSS. This machine has different output signals, two of them are chosen to be the input of the FLPSS; the deviation in rotor speed (D,(J)) and the deviation in terminal voltage (!,w,).
Change in relaLive rotot spe.e.d w31 (pu_)
a:~:~-\~---~---~.,----~----. 0.01
0.005 : ...
From the control point of view; to control a certain process, the output signal(s) must be feedback to the process to give better response. Also, from the view point of FL control, the value ofthis(these) signal(s) can decide the behavior of the process. So, to perform a sound better voltage and frequency profile, the two inputs to the FLPSS are chosen 10 represent them through their deviations.
-0005
.;: ./"...... =.:.~.... -"
-001 -0.015
Time (Second)
Fig1lre (2 h.) : Rotor Speed of Machine (3) - Time response
5. SIMULATION RESULTS In order to validate thig new control strategy as discussed in the latter section, a digital computer simulation program is developed using MA TLAB package. The obtained results are shown in the following figures. Figures 2.a., and 2.b represent the change in the relative rotor speed in p.u. for machines (2, and 3) respectively with respect to machine (l). Figures 3.a., 3.b., and 3.c. represent the terminal voltage in p.ll. for machines (l, 2, and 3) respectively. In all these figures, the curve with dotted line plot represents the machine when equipped with excitation controller and speed governor only, and the Cllrve with solid line plot represents the machine when equipped with the proposed control in addition to excitation control and speed governor. Also, the horizontal solid linerepresents the steady state value of each signal mentioned by the curve, and the horizontal dashed lines represent the percentage of ± I % for the frquency and ± 6"/0 for the voltage.
.- .-~.. ~. -.. '--,~ ':,-"- _.. {. ~.-'" ... f' :,:"
.....
1.1
DSS·
09
Time (Second)
Figure
Terminal Voltage - Time response
(3.0.) : Nfachine (1)
, .. chine (21 tCI'minal \,'olta.!l-C Cpu) I
'~-r-------r-------r-------r-------,
Ch.ange in rei alive rotor s-peect w21 Cpu)
09
OD25,-----~~---r__---r__--~,__--__,
002
08
:. 0.015
01
O.()1 " : ...
0<>
o5 0.4
-0.01
..
..... ;.. Time ,Sccond)
-0.015
Fig1lre (3 h.)
-0.02
AlaciJine (2) Terminal Vollage - Time response
Time (Second,
-----,-------------------------
Figure (2. a.) : ROlOr Speed Of Alaehi ne (2) - Time response
7495
Copyright 1999 IF AC
ISBN: 008 0432484
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR...
14th World Congress ofIFAC
Machine ( 3 1 terminal voltage (P_u .)
Power Systems, Vo!. JO, No. 3 , Au g : 1995. C. V. Negoita, "Ex pel1 Systems and Fuzzy Sy stems", The Benjamin/CulI1mings Publishing Company, Inc., 1984. 7. P. M . Anderson, and A.A. , Fouad, "Power Systems Control and Stability", Ames , Iowa: State University (1977). 8. IEEE Committee report, "Computer Representation of Excitation Systems", IEE E Trans., PAS-87 (1968) : 1460-1464. 9. Y. Y. HSlJ, and C. H . Cheng," Design of Fuzzy Powe r System Stabilizers for Multimachine Power Systems", lE E Proceedings, Vol. 137, Pt. C, No. 3, PP. 233-238, May 1990.
'2r---~---~--~---~-----'
6.
09 O.B
0 .7 0.6
050!c----::----"* 2----::3,-----~4~-----!5 Time (Second)
Appendix ( A )
Figlll"e (J.c.) : fv(achine (3) Terminal Voltage - Time
response Machine parameters: It is clear that the proposed control strategy has a sound effect for voltage and frequency in the same time for each machine in the system. The overshoot is less, the settling time is less, and the steady state error is less. So, the stability enhancement of the overall system ""ill achieved.
( reactances in p.ll. to a base of 100 M V A )
H
6. CONCLUSION
P. F. Type speed
This paper demonstrates an application of a FLPSS applied for a large scale power system. The FLPSS is designed to make the response of both voltage and frequency of the system be bette r. The results discussed in the Jast section and the curves of Figures 2, and :; illustrate the quality of this controller to be a new addition over the conventional FLPSSs which mainly concerned with frequency.
7. REFERENCES 1. F. P.
Demello and C. Concordia, "Concepts of Synchronous Machines Stability as Affected by Excitation Control", IEEE Transactiolls 0 11 Powe r Apparatus and Systems, V o !. PAS-SS, No. 4, PP. 316-329, April 1969. 2. R. L. Harvey, "Neural Network Principles", Printice-Hall, Inc., 1994. 3. J. L. Chen, "A Fuzzy Expert System tor Fault Diagnosis in Electric Distribution System", 1993 Canadian Conference on Electrical and Computer Engineering, Sep. 14-/7, /993 Vancouver, Canada. 4. P. Jervanhaura, P. Verho, a n(l J. Partanen, "Using Fuzzy Sets to Model the Uncertainty in the Fault Location Process of Distribution Networks", IEEE/PES 1993 Summer Meeting, Vancouver, B.c., Canada, July 18-22 1993, 93 SM 4 J 68 PWRD. 5. J. A. Momoh, X. W. Ma, and K. Tomsovic, "Overview and Literature Survey of Fuzzy Set Theory in Power Systems", IEEE Trans. on
I
Machine Rated MVA kV
Xd X'd
Xq X'q
r
I
1
192.0
16 .5 23 .64 1.0 bvdro 180 rpm 0.146 0.0608 0.0969 0.0969
18 .0 6.4
0.85 steam 3600 rpm 0.8958 0.1198 0.8645 0.1969 6.0 0.535
&.96
do
0.0
T'(o
I
2
247.5
3 128.0
I
13.8
3.01 0.85 steam 3600 rpm 1.3125 0.1813 1.2578 0.25 5.89 0.6978
. o'neratlDl! COIll d'•hons:
I
Mach.
I P (p.lI.)
Ea
0.716 1.63 0.85
Transmission lines' Node No. 4-5
I
4-6 5-7
6-8 7-8
8-9
Q (p.u.)
V (p.u.)
0 .2 7 0.067 -0.109
1.04 1.025 1.025
11
ImEedance( E.u. ) 0.0 I + i 0.085 0.017 + i 0.092 0.032 + j 0.161 0.039 + j O. I 7 0.0085 + j 0.072 0.0119 + j 0.1008
Excitation system oarameters: 2 1 45.0 35.0 0.1 0.2 T .\ 0.015 K,.. 0001 0.7 0.8 TI
~
(rad.) 0.0625 1.0665 0.9458
(5
I
~
..)
40.0 0.15 0.002 0.75
7496
Copyright 1999 IF AC
ISBN: 0 08 043248 4
A VOLTAGE-FREQUENCY FUZZY LOGIC CONTROLLER FOR LAR...
.S
ee dG.overnor parameters:
achine
14th World Congress ofIFAC
Loads ' 2
3
Kc Tc
1 0.9 0.07
LI 0.09
1.0
R~
0.G3
0 .05
I
I~
0.08 0.04
Load
11
I
( (l.u. )
I
1./6 - j 0.5044 0.8777 - j 0.2926 0 .969 -10.3391
7497
Copyright 1999 IF AC
ISBN: 0 08 043248 4