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TRANSCRIPT
Design of Fuzzy Logic Controller for two area
Interconnected Power System with TCPS
in Tie Line
Dr K. Asokan
Assistant Professor, Department of Electrical Engineering, Annamalai University, Annamalai Nagar,
Tamil Nadu, India, 608002.
Abstract— Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to
changes in system frequency and tie-line loading .Thus the LFC helps in maintaining the scheduled system frequency and tie-line power
interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of aPI controller. The integrator gain
is set to a level that the compromises between fast transient recovery and low overshoot in the dynamic response of the overall system.
This type of controller is slow and does not allow the controller designer to take into account possible changes in operating condition.
Moreover, it lacks robustness. This thesis studies control of load frequency in two area power system with Fuzzy logic controller (FLC)
and Thyristor Controlled Phase Shifter (TCPS) is connected in tie line. In this study, The overshoots and settling times with the
proposed controllers are better than the outputs of the conventional PI controllers. The effectiveness of the proposed scheme is
confirmed via extensive study using MATLAB/SIMULINK software. Comparison of performance responses of conventional PI
controller with FLC and TCPS employed power system has been carried out for the different controllers for one and two area power
system, The proposed control strategy has better satisfactory generalization capability, feasibility and reliability, as well as accuracy
than conventional PI controllers.
Keywords— Load Frequency Control , Fuzzy logic controller , Thyristor Controlled Phase Shifter (TCPS), Capacitive Energy Storage,
feasibility and reliability
I. INTRODUCTION
In the regulated interconnected power industry, the generation normally comprises of a mix of thermal, hydro, nuclear
and gas power generation. However owing to their high efficiency the nuclear plants are usually kept at base load close to their
maximum output. Gas power generation is ideal for meeting the varying load demand at such a plant for a very small percentage
of total system generation. Thus the natural choice of LFC falls and either thermal or hydro unit. The LFC of an interconnected
power system has two principle aspects maintenance a frequency and power exchange over inter area tie line on the respective
scheduled values. For successful operation of the system the following basic requirements are to fulfilled
Under the steady state condition there is a balance between real power generation and Demand. Any sudden change in
the demand is immediately indicated by changing in speed or frequency. There is an oscillation in the frequency till the steady
state condition is achieved. To damp-out these oscillations TCPS device can be included [1] in the system and the same can meet
the sudden change in load. The stabilization of frequency oscillations is an interconnected power system became challenging
when implemented in future competitive environment. Frequency is an explanation of stability criterion in power systems. To
provide the stability, active power balance and steady frequency are required. Frequency depends on active power balance. If any
change occurs in active power demand/generation in power systems, frequency cannot be hold in its rated value. So oscillations
increase in both power and frequency. Thus, system subjects to a serious instability problem.
In electric power generation, system disturbances caused by load fluctuations result in changes to the desired frequency
value. Load Frequency Control (LFC) is a very important issue power system operation and control for supplying sufficient and
both good quality and reliable power [3]. Power networks consist of a number of utilities interconnected together and power is
exchanged between the utilities over the tie-lines by which they are connected. The net power flow on tie-lines is scheduled on a
priori contract basis. It is therefore important to have some degree of control over the net power flow on the tie-lines. Load
Frequency Control (LFC) allows individual utilities to interchange power to aid in overall security while allowing the power to be
generated most economically. The variation inroad frequency is an index for ordinary operation of the power systems. When the
load perturbation takes place, it will affect the frequency of other areas also. To improve the stability of the power networks, it is
necessary to design Load Frequency Control (LFC) systems that control the power generation and active power. Because of the
relationship between active power and frequency, three level automatic generation controls have been proposed by power system
JASC: Journal of Applied Science and Computations
Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
Page No:2830
researchers .The analysis of an interconnected power system, few areas are considered as the channels of disturbance in this
situation. The conventional frequency control (i.e.) the governor may no longer be able to attenuate the large frequency
oscillations due to slow response.
In this study, a Fuzzy logic controller is used to optimize the integral controller gains for load-frequency control of a two
area thermal power system with TCPS and without TCPS. To obtain the best performance of the tie-line power and frequency
deviations of the control areas and their rates of changes according to time. The simulation results show that the dynamic
performance of the system is improved using the proposed controller. In load frequency control the area control error, (ACE)
which is the linear combination of net interchange of tie line powers, and frequency error, has to be reduced by implementing
several technique like conventional or intelligent [1-11]. Optimum Megawatt frequency control of Multi-area power system, deals
with the use of ACE as the control signal reduces the frequency and tie line power error to zero at the steady state, but its transient
response is not satisfactory, even when used with Integral controllers.A TCPS is expected to be an effective apparatus for the tie-
line power flow control of an interconnected power system.In this analysis TCPS installed in series with tie-line in between two
areas of an interconnected power system has also the possibility to control the system frequency positively. The proposed control
strategy will be a new ancillary service for the stabilization of frequency oscillation of an interconnected power system.
Literature survey shows the applications of TCPS for the interconnected power system provides a good improvement of
dynamic and transient stabilities of power system. Statistical and dynamic analysis of generation control performance [2]
standards to evaluate the control area performance in normal interconnected power system operation.As stated in some literature
[6 - 10], some control strategies have been suggested based on the conventional linear control theory. These controllers may be
improper in some operating conditions. This could be due to the complexity of the power systems such as nonlinear load
characteristics and variable operating points. Dynamic analysis of generation control performance standards which gives dynamic
simulation of the system frequency response, including the effected of primary and secondary frequency control, power plant
response and load fluctuation characteristics were performed using a load flow program can be obtain and several suggestive
measures can be adopted.
Main objective of Load Frequency Control are connected with
(1) Matching the generation to load.
(2) Power system being divided into several areas, adjusting each exported power within limits.
(3) Adjusting the frequency to its stated values.
There is need for better controller that minimized the frequency deviation in power system owing to disturbance. The main
objective and need of the proposed load frequency controller usingTCPS is that for given load disturbance the following
requirements are to be met Damping the transient behavior of the system
1. Closed loop stability is to be obtained.
2. Sufficient and reliable electric power with quality as to be supplied.
3. Controller must be easy for implementation
4. The transient behavior of the system is to be damped out.
5. The control law should be match with system non-linearity.
6. Zero steady state error is to be reduced to zero.
II. PROPOSED TWO AREA INTERCONNECTED POWER SYSTEM
A two-limb parallel connected conventional boost converter is shown in Fig. 1 this is typically called an interleaved
boost converter. This converter is used to improve power conversion capability, and one of its applications is to match the
photovoltaic system to the load and to operate the solar cell array at maximum power at all isolation.
In an uncontrolled power systems, large deviation (maximum permissible 0.5 Hz) of frequency cannot be tolerated
and, therefore, some suitable control strategy have to be develop to achieve much better frequency consistency. Even if the
frequency of a system is kept with-in rather narrow tolerances, in itself does not necessarily provide for the accuracy of
synchronous clocks since such clocks measure the integral of the frequency may show up cumulatively in synchronous time.
The intolerable dynamic frequency changes in load can be controlled and also the synchronous clocks run on time, but
not without error during transient period. To achieve better frequency constancy the integral controller is added to the
uncontrolled to area non-reheat thermal power system.
JASC: Journal of Applied Science and Computations
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ISSN NO: 1076-5131
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Fig. 1 Block Diagram of a two – area interconnected power system
III. PROPOSED FUZZY LOGIC CONTROLLER
Fuzzy logic is widely used in machine control. The term itself inspires a certain skepticism, sounding equivalent to "half-
baked logic" or "bogus logic", but the "fuzzy" part does not refer to a lack of rigor in the method, rather to the fact that the logic
involved can deal with concepts that cannot be expressed as "true" or "false" but rather as "partially true". Although genetic
algorithms and neural networks can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the
solution to the problem can be cast in terms that human operators can understand, so that their experience can be used in the
design of the controller. This makes it easier to mechanize tasks that are already successfully performed by humans.
A. Basic construction of the fuzzy logic controller In control engineering, fuzzy controllers are extensively studied. Case studies present their application in various process-
control systems previously controlled manually. One has to understand clearly the notation of "fuzziness" in technical systems
s
k I 1
f2 (s)
f1 (s)
+
_
Σ
s
k I1
1
1+sTg1 1
1+sTt1
1+sTr1Kr1
1+sTr1 Σ Σ
Σ
Kps1
1+sTp
s1
1
---
R1
1
Σ
s
kI 2
1
1+sTg2
1
1+sTt2
1+sTr2Kr2
1+sTr2 Σ
a12
1
---
R2 2
a12
Σ
Kps2
1+sTPs2
2T12
S
Σ
+
+
+
+
Σ
Ptie12
power system governor
reheat turbine
TCPS
x e2(s)
governor
reheat turbine power system
Tie-line
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Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
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(electrical, mechanical, chemical, etc.) and its role in information processing. At first glance, it may seem artificial to apply fuzzy
sets in such systems. But such a judgment is not valid. In control strategy applied by the operator, we can recognize some
concepts that are evidently fuzzy in their nature, for instance the goals of the control (e.g. 'keep close to the desired trajectory with
a quite low control effort' contains the vague expressions close, quite low).
The FLC is a tool for processing a fuzzy form of information in a non-fuzzy or fuzzy scheme of reasoning. Here is one
application of fuzzy controllers in the so-called 'soft' sciences (i.e. where the human being plays a central role). The concept of
FLC is to utilize the qualitative knowledge of a system to design a practical controller. For a process control system, a fuzzy
control algorithm embeds the intuition and experience of an operator designer and researcher.
The fuzzy control doesn’t need accurate mathematical model of a plant, and therefore, it suits well to a process where the
systems with uncertain or complex dynamics. Of course, Fuzzy control algorithm can be developed by adaptation based on
learning and fuzzy model of the plant.
Decision
making logic
defuzzification
interface
fuzzification
interface
knowledge
base
Controlled system
(process)
Fuzzy controller
Fig. 2 Basic configuration of fuzzy logic controller A main, if not unique source of knowledge to construct the control algorithm comes from the control protocol of the human
operator. The protocol consists of a set of conditional 'if-then' statements, where the first part of each contains a so-called
condition (antecedent) while the second (consequent) part deals with an action (control) that has to be taken. Therefore, it conveys
the human strategy, expressing which control is to be realized when a certain state of the process controlled is observed.
Conventional integral or PID controller in general has the following difficulties.
In case of any change of system operating conditions, new integral gain value has to be computed. In a two-area system
tuning of PID controller separately for each area is required. Various steps involved in the development of the fuzzy logic based
controller are discussed.
B. Input Variables
The first step in designing a fuzzy based controller is to decide the input variables or signals to the controller. These should
be measurable and should represent system dynamic performance. For the proposed fuzzy logic based LFC, input variables
selected are:
The area control error (ACE)
The rate of change of area control error (CheACE)
C. Fuzzy set for input variables
After selecting the input variables to the fuzzy logic based controller, it is required to decide the linguistic variables .the
number of linguistic variables specifies the quality of control seven linguistic values have been assumed to be associated with
each ACEi variable and five with each CheACEi variable. The fuzzy set associated with the ACE variable is taken as [LN, SN, Z,
SP, LP] AND that associated with the CheACEi variable is [LN, SN, Z, SP, LP] where
LP: large positive, SP: small positive, ZE: zero, SN: small negative
LN: large negative
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D. Data Base
After selecting the proper fuzzy sets, it is require do select the member function to represent each linguistic value. For both
the input variables, symmetric triangular member functions have been selected .The next step is to map each element of the fuzzy
set on the domain of the corresponding linguistic variable. The fuzzy logic editor is called form matlab command prompt by
typing the command FUZZY in the prompt area.
E. Fuzzy control in detail
Fuzzy controllers are very simple conceptually. They consist of an input stage, a processing stage, and an output stage. The
input stage maps sensor or other inputs, such as switches, thumbwheels, and so on, to the appropriate membership functions and
truth values. The processing stage invokes each appropriate rule and generates a result for each, then combines the results of the
rules. Finally, the output stage converts the combined result back into a specific control output value.
The most common shape of membership functions is triangular, although trapezoidal and bell curves are also used, but the
shape is generally less important than the number of curves and their placement. From three to seven curves are generally
appropriate to cover the required range of an input value, or the "universe of discourse" in fuzzy jargon. As discussed earlier, the
processing stage is based on a collection of logic rules in the form of IF-THEN statements, where the IF part is called the
"antecedent" and the THEN part is called the "consequent". Typical fuzzy control systems have dozens of rules.
IV. IMPLEMENTATION OF PROPOSED TCPS CONTROLLER
Fig. 3 TCPS in a Two Area Interconnected System
The Fig.3 shows the two-area interconnected power system with a configuration. It is assumed that a large load with
rapid change has been installed in an area-1 and this load change causes serious frequency oscillations. Under this situation, the
governors in an area-1 can not sufficiently provide adequate frequency control. On the other hand, the area-2 has large control
capability enough to spare for other area. Therefore, an area-2 offers a service of frequency stabilization to area-1 by using the
TCPS. Since TCPS is a series connected device, the power flow control effect is independent of an installed location. In the
proposed design method, the TCPS controller uses the frequency deviation of area-1 as a local signal input. Therefore the TCPS is
placed at the point near an area1.Notethat the TCPS is utilized as the phase shifting transformer device from area-1 to area2. As
the frequency fluctuation in an area-2 occurs, the TCPS will provide the dynamic control of a tie-line power via the system
oscillations. By exploiting the system interconnections as the control channels, the frequency oscillation can be stabilized
The performance of TCPS is extremely rapid when compared with the conventional frequency control system, i.e.
governor the difference in the performance signifies that TCPS and governors may be coordinated as follows. When an area is
subjected to a sudden lode disturbance, the TCPS quickly acts to minimize the peak value of the frequency deviations
subsequently; the governors are responsible for eliminating the steady-state errors of the frequencydeviations. Based on this
concept, the periods of operation for two devices do not overlap. Consequently the dynamics of the governors can then be
neglected in the control design of the TCPS for the sake of simplicity.
A. Iincremental tie-line power flow model considering TCPS
As the recent advances in power electronics have led to the development of the FACTS devices. Which are designed to
overcome the limitations of the mechanically controlled devices used in the power systems and enhance power system stability
using reliable and high-speed electronic components. One of the promising FACTS devices is the TCPS. TCPS is a device that
changes the relative phase angle between the system voltages. Therefore the real power flow can be regulated to mitigate the
frequency oscillations and enhance power system stability.
JASC: Journal of Applied Science and Computations
Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
Page No:2834
In this study, a two-area thermal power system interconnected by a tie-line is considered. Fig.4.1 shows the schematic
representation of the two-area interconnected thermal system considering a TCPS in series with the tie-line. TCPS is placed near
Area 1. Practically, in an interconnected power system, the reactance-to-resistance ratio of a tie-line is quite high (X/R≥10) and the effect of resistance on the dynamic performance is not that significant. Because of this, the resistance of the tie-line is
neglected. Two Area interconnected thermal power system comprising . Without TCPS, the incremental tie-line power flow from
Area 1 to Area 2 can be expressed as
)(2
21
0
120
12 ffs
TPtie
(1)
Where T˚12 is the synchronising power coefficient without TCPS and f1 and f2 are the frequency deviations of Areas 1 and 2,
respectively. When a TCPS is placed in series with the tie-line, as in Fig. 1, the current flowing from Area 1 to Area 2 can be
written as
12
2211
12
)(
jX
VVi
(2)
From Fig. 1, it can be written as
12
2211
11
12
*
11212
)()(
jx
VVV
iVjQP tietie
(3)
12
2121
2
1
21
12
21
1212
)(cos)(sin
X
VVVj
X
VVjQP tietie
(4)
Separating the real part of (3), we get
)φ+δδsin(x
VV=P 21
12
2112tie (5)
In (26), perturbing and w from their nominal values φandδδ 2,1 from their nominal values °°2
°1 φandδ,δ , respectively,
eqn. (2) now becomes
)sin(cos( 21
00
2
0
1
12
21
12 x
VVPtie
(6)
However, for a small change in real power load, the variation of bus voltage angles and also the variation of TCPS phase angle
are very small. Thus, in effect, ( φΔ+δΔδΔ 21 ) is very small and hence
)φΔ+δΔδΔ(=)φΔ+δΔδΔsin( 2121
(7)
Therefore
))(cos( 21
00
2
0
1
12
21
12 x
VVPtie
(8)
Let
)φ+δδcos(x
VV=T 00
201
12
2112 (9)
Thus (7) reduces to
)φΔ+δΔδΔ(T=PΔ 211212tie (10)
)φΔT+δΔδΔ(T=PΔ 12211212tie (11)
JASC: Journal of Applied Science and Computations
Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
Page No:2835
It is Known
∫ 112 dtf and ∫
2
2 2dtf
(12)
From (11) and (12)
)(2 12211212 ∫∫
TdtfdtfTPtie
(13)
Laplace transformation of (13)yields
)()]()([2
)( 122112
12 sTsFsFs
TsPtie
(14)
As per (35), tie-line power flow can be controlled by controlling the phase shifter angle φΔ . Assuming that the control input
signal to the TCPS damping controller is ΔError1 (s) and that the transfer function of the signalling conditioning circuit is
)s(ckφ , where φk is the gain of the TCPS controller
(s)C(s)Δ(s)ΔEKΔφ(s) 1φ
(15)
And
pssT+1
1=)s(C (16)
Hence, the phase shifter angle )s(φΔ can be represented as
)s(ErrorΔsT+1
K
=)s(φΔ 1ps
φ (17)
where psT is the time constant of the TCPS and ΔError1 (s) the control signal which controls the phase angle of the phase shifter.
Thus, (35) can be rewritten as
)(1
)]()([2
)( 1122112
12 sErrorsT
KTsFsF
s
TsP
ps
tie
(18)
B. TCPS Control Strategy
ΔError1 can be any signal such as the thermal area frequency deviation f1 or the area control error of the thermal area ACE1
(i.e. Error1 = f1 or ACE1) to the TCPS unit to control the TCPS phase shifter angle which in turn controls the tie-line power
flow. Thus, with Error1 =f1
)s(fΔsT+1
K
=)s(φΔ 1ps
φ
(19)
and the tie-line power flow perturbation as given by (39) becomes
)(1
)]()([2
)( 1122112
12 sFsT
KTsFsF
s
TsP
ps
tie
(20)
When the area control error of area 1, 12tie111 pΔ+fΔB=ACE is chosen as the control signal (i.e. Error1 = ACE1), to the TCPS
unit, the tie-line power flow perturbation becomes
)(1
)]()([2
)( 1122112
12 sACET
KTsFsF
s
TsP
ps
tie
(21)
However, from the practical point of view, as TCPS is placed near Area 1, measurement of f1 will be easier rather than
ACE1, which requires measurement of tie-power also. Hence, in the present work, the frequency deviation of the thermal area f1
is chosen as the control signal. The parameter TPS and φk of the TCPS are given in Appendix.
JASC: Journal of Applied Science and Computations
Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
Page No:2836
V. SIMULATION RESULTS AND DISCUSSION
The aim of load frequency control is that the steady state errors of the frequency and tie-line power deviations following
a step load change are made zero. For this purpose, to obtain the control inputs, Fuzzy integral controllers are used together with
area control errors, ACE1 and ACE2.
FLC designed to eliminate the need for continuous operator attention and used automatically to adjust some variables the
process variable is kept at the reference value. A FLC consists of three sections namely, fuzzifier, rule base, and defuzzifier The
error, ACE and Rate change ACE are inputs of FLC. Two input signals are converted to fuzzy numbers first in fuzzifier using five
membership functions: Positive Big (PB), Positive Small (PS), Zero (ZZ), Negative Small (NS), Negative Big (NB),Triangular
membership functions are used in this thesis since it is easier to intercept membership degrees from a triangle.Then they are used
in the rule viewer to determine the fuzzy number of the compensated output signal.
Fig. 4 Simulation Model of a two area interconnected thermal (Reheat) power System with PI controller
JASC: Journal of Applied Science and Computations
Volume VI, Issue V, May/2019
ISSN NO: 1076-5131
Page No:2837
Fig. 5 Simulation Model of a two area interconnected thermal (Reheat) power System with Fuzzy controller
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ISSN NO: 1076-5131
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Fig. 6 Simulation Model of a two area interconnected thermal (Reheat) power System with
Fuzzy controller and TCPS
Fig.7. Dynamic responses of the frequency deviations of area-1 considering a step load
disturbance of 0.01p.u.Mw in area1
JASC: Journal of Applied Science and Computations
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ISSN NO: 1076-5131
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Fig.8. Dynamic responses of the frequency deviations of area-2 considering a step load
disturbance of 0.01p.u.Mw in area1
Fig.9 Dynamic responses of the tie line power deviation considering a step load
Disturbance of 0.01p.u.Mw in area1
Finally, resultant united fuzzy subsets representing the controller output are converted to the crisp values using the
central of area (COA) deaptimizer scheme. The FLC parameters are chosen on the basis of a trial and error study of the control.
The system dynamic performance is observed for three different controller structures, PI (Proportional + Integral), Fuzzy
controller with out TCPS and Fuzzy contrite TCPS. The simulation results are shown in Figs. 7-10 in this study
JASC: Journal of Applied Science and Computations
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ISSN NO: 1076-5131
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VI. CONCLUSION
Analysis of load frequency control models of interconnected power system representation with TCPS is series with tie
line provide more detailed information about the system evolution of the frequency of each individual control area and the power
interchanged through each tie-line has been presented. In this thesis, the control of tie-line power flow by TCPS units has been
proposed for a two-area interconnected thermal reheat power system. The Fuzzy logic controller technique was employed to
achieve the optimal parameters. TheFLC is easy to implement without additional computational complexity. Thereby an
experiment gives quite promising results. A control strategy as been proposed, by adjusting TCPS which in turn controls the inter-
area tie-line power flow. Simulation results reveal that the first peak frequency deviation of both areas and tie-line power
oscillating following sudden load disturbances in either of the area can be suppressed a controlling the series voltage of TCPS. It
may be concluded that, the tie-line power flow control by aTCPS can be expected to be utilized as new ancillary service for
stabilization of frequencies and tie-line power oscillations in the congestion management environment of the power system.
ACKNOWLEDGMENT
The authors gratefully acknowledge the authorities of Annamalai University for the facilities offered
to carry out this work.
REFERENCES
.
[1] M.R.I. Sheikh1, R. Takahashi, and J. Tamura “Multi-Area Frequency and Tie-Line Power Flow Control by Coordinated
AGC with TCPS”IEEE Transaction on Power Systems, Vol 5, pp 2010 – 278.Sep-2010.
[2] Zenk, H.; Zenk, O.; Akpinar A.S. “Two different power control system load-frequency analysis using fuzzy logic
controller”,IEEE International Conference onInnovations in Intelligent Systems and Applications (INISTA),pp-465 –
469,2011.
[3] Zenk, H.; Zenk, O.; Akpinar, A.S. “Two different power control system load-frequency analysis using fuzzy logic
controller”,IEEE International Conference onInnovations in Intelligent Systems and Applications (INISTA), pp-465 –
469,2011.
[4] R.J. Abraham, D. Das, A. Patria “Effect of TCPS on oscillations in tie-power and area frequencies in an interconnected
hydrothermal power system”IET Gener. Transm. Distrib, 1, (4), pp. 632 – 639, 2007.
[5] A. Ismail, “Improving UAE power systems control performance by using combined LFC and AVR,”The Seventh U.A.E.
University Research Conference, ENG., pp. 50-60, 2006.
[6] I. Kocaarslan and E. Cam,“Fuzzy logic controller in interconnected electrical power systems for load-frequency
control,”Electrical Power and Energy Systems, vol. 27, no. 8, pp. 542-549, 2005.
[7] Ibraheem, Prabhatkumar, Dwaraka P. Kothari, “Recent philosophies of Automatic Generation Controller Strategies in
Power Systems”, IEEE Transaction on power system, Vol.20, No.1, pp.340-357. Feb 2005.
[8] E. Cam and I. Kocaarslan, “Load frequency control in two area power systems using fuzzy logic controller,” Energy
Conversion and Management, vol. 46, no. 2, pp. 233-243, 2005
[9] IssarachaiNgamroo, “A stabilization of frequency oscillations in interconnected power system using static synchronous
series compensator”, Thanmmasa Int. J.Sc. Tech., Vol. 16, No.1, pp. 55-60, 2001.
[10] H. Cimen, “Decentralised load frequency controller design based on SSVs,” Turkish Journal of Electrical Engineering
& Computer Sciences, vol. 8, no. 1, pp. 43-53, 2000.
[11] S.P. Ghoshal“Multi-area Frequency and Tie-line Power Flow Control with Fuzzy Logic Based Integral Gain
Scheduling”Journal-EL, Vol 84. - 2003.
[12] J. Talaq and F. Al-Basri, “Adaptive fuzzy gain scheduling for load frequency control,” IEEE Transaction on Power
Systems, vol. 14, no. 1, pp.145-150, 1999.
[13] C.S. Chang and W. Fu “Area load frequency control using fuzzy gain scheduling of PI controllers,” Electrical Power
and Energy Systems, vol. 42, no. 2, pp. 145-152, 1997.
[14] N. Jaleeli, L.S. Vanslyen, D.N. Ewart, L.H.Fink, A.G. Hoffmann, “Understanding Automatic Generation Control”,IEEE
Transaction on Power Systems, Vol 7, pp 1106 – 1122.1992.
[15] Olle- Elegerd,Electric Energy System Theory An Introduction, Tata McGraw Hill Publishing Company, New Delhi,
1986.
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