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

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2831

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

JASC: Journal of Applied Science and Computations

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2832

(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

JASC: Journal of Applied Science and Computations

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2833

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

JASC: Journal of Applied Science and Computations

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2838

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

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2839

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

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2840

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.

JASC: Journal of Applied Science and Computations

Volume VI, Issue V, May/2019

ISSN NO: 1076-5131

Page No:2841