International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
Fuzzy Logic Controller Based Analysis of Load
Frequency Control of Two Area Interconnected Power
System
P.V.R.Prasad1, Dr. M. Sai Veeraju2
1
PG scholar, Department of Electrical and Electronics Engineering, S.R.K.R.Engineering College, Bhimavaram534204, West Godavari, Andhra Pradesh, India.
2
Professor, Department of Electrical Electronics Engineering, S.R.K.R.Engineering College, Bhimavaram-534204,
West Godavari, Andhra Pradesh, India.
1
pvr_p@yahoo.com
saiveerraju@yahoo.co.in
Fixed frequency is an important factor for power systems
Abstract—Frequency plays a vital role in power system. In
quality. Subscribers connected to the energy system at a
many industries, the speed of the machines depends on the
frequency of changes in energy demand leads to some of the
frequency. Any deviation in the frequency may lead to malharmonics. Load frequency control system should identify these
operation of the system. So load frequency control is the key
changes and should not be considered a distortion. Electric power
problem in the power system. Works are being done to
systems, power system stability under normal operating
optimize the controllers to get faster and better results. The
conditions to remain stable operating condition and after exposure
present work aims to control the frequency using fuzzy logic
to a perturbation makes it possible to attain an acceptable feature
control.
of re-equilibrium state can be defined as. In a sudden change in
The Fuzzy logic controller is applied in load frequency
consumers' demands for power, voltage and frequency control, a
control of two area system , this analysis is done using
complicating factor. At this point, the power system load
different fuzzy based rules using linguistic variables i.e., by
frequency control, it is important for stability. Load frequency
considering three variables, five variables and seven variables.
control with voltage and frequency of the system is set. Therefore,
The results thus obtained are compared against the results
the system will be increased power quality.[1-3]
using without any controller and by using ordinary PI
controllers and PID controller. It is seen that both the
II. INTERCONNECTED POWER SYSTEMS
transient and steady state response are improved by using this
Modern day power systems are divided into various areas.
fuzzy logic controller.
For example in India, there are five regional grids, e.g. Eastern
Region, Western Region etc. Each of these areas is generally
Keywords— Fuzzy Logic Controller (FLC), PI controller, PID
interconnected to its neighboring areas. The transmission lines
controller, Fuzzy PI control system, Fuzzy PID control
that connect an area to its neighboring area are called tie-lines.
system.
Power sharing between two areas occurs through these tie-lines.
Two single area power systems are connected through a tie line in
I. INTRODUCTION
order to form an interconnected power system. The main
Interconnected transmission network supplying the national
advantage of interconnected power system is to attain the load
power balance and synchronize the different manufacturing
demand.
facilities are required to work. Areas that may occur in one of the
2
failures that may occur to any load change and also affect other
regions. One of the most important effects of this type of system
is the exchange of power with constant bus voltage and mains
frequency. Electric power transmission systems to provide high
quality and constant power load changes caused by oscillation
frequency and voltage values must be removed as soon as
possible.
The system frequency rises when the load decreases if
Pref
is kept at zero. Similarly the frequency may drop if the
load increases. However it is desirable to maintain the frequency
constant such that f
lines is scheduled.
321
 0 . The power flow through different tie-
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
For example, area-I may export a pre-specified amount of
power to aria – j while importing another pre-specified amount of
power from area-k. however it is expected that to fulfill this
obligation, area – I absorbs its own load change, i.e. increase
generation to supply extra load in the area or decrease generation
when the load demand in the area has reduced. While doing this
area-I must however maintain its obligation to areas j and k as far
as importing and exporting power is concerned. A conceptual
diagram of the interconnected areas is shown in Fig.1.
Kps = Power System Gain Constant
Tps = Power System Time Constant
R = Speed Regulation Of Governor
DYNAMIC RESPONSE :
The dynamic response of a single area power system under
controlled case :
Tie-lines
Area-j
∆F(s) = {-∆Pc(t)KpsR/(R+Kps)} * [1-e-t((R+kps)/RTps)]....(1)
Area-k
Area-i
The dynamic response of single area power system under
uncontrolled case:
( )
( )
[
(
)
]………. (2)
TWO AREA INTERCONNECTED POWER SYSTEM
Fig: 1 .Interconnected areas in a power system
A two area system consists of two single area systems,
connected through a power line called tie-line, is shown in the
Figure: 3 each area feeds its user pool, and the tie line allows
electric power to flow between the areas. Information about the
local area is found in the tie line power fluctuations. Therefore,
the tie-line power is sensed, and the resulting tie-line power signal
is fed back into both areas. It is conveniently assumed that each
control area can be represented by and equivalent turbine,
generator and governor system. Symbol used with suffix 1 refer to
area 1 and those with suffix 2 refer to area 2.
SINGLE AREA POWER SYSTEM:
ΔPD(s)
ΔPC(s)
+
Ksg
-
(1+sT
- sg
)
Kt
ΔPG(s) -
+
(1+sTt)
Kps
ΔF(s)
(1+sTps)
1/R
Fig.2.Single area power system
Where
∆Pc(s )= Speed Command Input
∆PD(s )= Load Demand
Ksg
= Governor Gain Constant
Tsg
= Governor Time Constant
Kt
= Turbine Gain Constant
Tt
= Turbine Time Constant
Fig.3. Two area interconnected power system
In an isolated control area case the incremental power
PG & PD was accounted for by the rate of increase of stored
kinetic energy and increase in area in area load cause by increase
in frequency. Since a tie line transports power in or out of an area,
this fact must be accounted for in the incremental power balance
equation of each area.[7]
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International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
III.
FUZZY LOGIC CONTROLLER
There are three principal elements to a fuzzy logic controller:

Fuzzification module (Fuzzifer)

Rule base and Inference engine

Defuzzification module (Defuzzifier)
For Load Frequency Control the process operator is assumed to
respond to variables error (e) and change of error (ce).
Fig .5.Membership function for the control input variables
Fuzzy logic controller has been used in both the thermalthermal and hydro-thermal inter connected areas. Attempt has
been made to examine with five number of triangular membership
functions (MFs) which provides better dynamic response with the
range on input (error in frequency deviation and change in
frequency deviation) i.e. universe of discourse is -0.25 to 0.25.
The number of rules are 25. The dynamic response are obtained
and compared to those obtained with conventional integral
controllers. Further, several inputs have been tried out and
dynamic responses are examined in order to decide suitable inputs
to the fuzzy logic controller (FLC).
Fig.4.Fuzzy logic controller
The variable error is equal to the real power system
frequency deviation (f). The frequency deviation f is the
difference between the nominal or scheduled power system
frequency (fN) and the real power system frequency (f). Taking
the scaling gains into account, the global function of the FLC
output signal can be written as
( )
,
( ) -……….. (3)
The membership functions (MFs) for the input variables are
shown in Fig.5.
Where, ne and nce are the error and the change of error scaling
gains, respectively, and F is a fuzzy nonlinear function. FLC is
dependant to its inputs scaling gains.[4,5,8,9] The block diagram
of FLC is shown in Fig.4.
IV. WO AREA INTER CONNECTED POWER SYSTEM IN
MATLAB /SIMULINK-BASED DESIGN AND SIMULATION
A label set corresponding to linguistic variables of the input
control signals, e (k) and ce (k), with a sampling time of 0.01 sec
is as follows
(
Where,
)
*
+
(4)
NB = Negative Big
NM = Negative Medium
ZE = Zero
Fig.6 Two area power system with PI controller
PM = Positive Medium
PB = Positive Big
323
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
-3
6
With PI
x 10
4
2
-4
-6
-8
-10
-12
-14
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.7 Two area power system frequency change with PI
controller
The above simulation are the result for two area power
system using conventional PI controller shows that it has good
steady state response i.e.,zero frequency deviation but it has pooor
dynamic response,to improve this Fuzzy Logic controller is used.
TABLE.1
THREE VARIABLE RULE BASE
e(k)
NE
NE
NE
ZE
NE
ZE
PE
Ce(k)
ZE
NE
ZE
PE
Fig.8 Two area power system with Fuzzy PI controller
PE
ZE
PE
PE
-4
2
fuzzy pi 3
x 10
1
0
-1
Frequency Change(pu)
Frequency Change (pu)
0
-2
TABLE.2
-2
-3
-4
FIVE VARIABLE RULE BASE
-5
-6
-7
Ce(k)
NB
NM
ZE
PM
PB
NB
NB
NB
NM
ZE
ZE
NM
NB
NB
NM
PM
ZE
e(k)
ZE
PM
NM
NM
NM
ZE
ZE
PM
PM
PB
PM
PB
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.9 Two area power system with Fuzzy PI controller
PB
ZE
ZE
PM
PB
PB
for three variable rule base
The above simulation result shows that steady state response
is reached but the dynamic response is poor as compared to PI
controller but has high stability gain margin compared to PI
controller. So to improve both responses we go for five variable
rule base.
324
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
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3
The above simulation result with seven variable rule base
with fuzzy pi5
x 10
shows good dynamic response and attain steady state at t=40sec.
2
1
but it has high compilation time.
Frequency Change(pu)
0
-1
-2
-3
-4
-5
-6
-7
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.10 Two area power system frequency change with
Fuzzy PI controller for five variable rule base
The simulation result shows that dynamic response is
improved and steady state is attained at t=32 sec.
TABLE.3
Fig:12 Two area power system with PID controller
SEVEN VARIABLE RULE BASE
-3
4
with PID
x 10
2
Ce(k)
NM
NB
NB
NB
NM
NS
ZE
PM
-4
2
e(k)
NS
ZE
NM NB
NB NM
NM
NS
NS
ZE
ZE
PS
PS
PM
PM
PB
0
PS
NM
NS
ZE
PS
PM
PB
PB
PM
NS
ZE
PS
PM
PB
PB
PB
PB
ZE
PM
PM
PB
PB
PB
PB
-2
Frequency Change (pu)
NB
NM
NS
ZE
PS
PM
PB
NB
NB
NB
NB
NB
NM
NS
ZE
-4
-6
-8
-10
-12
-14
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.13 Two area power system frequency change with
PID controller
with fuzz pi7
x 10
1
Frequency Change(pu)
0
-1
-2
-3
-4
-5
-6
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.11 Two area power system frequency change with
Fig:14.Two area power system with Fuzzy PID controller
Fuzzy PI controller for seven variable rule base
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International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
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attained at t=22sec. In seven variable rule base simulation result
shows good dynamic response and attain steady state at t=18sec.
with fuzzy pid3
x 10
5
Frequency Change(pu)
0
V. CONCLUSION
-5
The usage of Fuzzy PID controller provides better dynamic
performance and reduces the oscillation of the frequency
deviation as compared to the conventional PI, PID controllers, and
Fuzzy PI controller, which provides zero steady state frequency
deviation with step load increment in power system, but exhibits
poor dynamic performance (such as more number of oscillation
and more setting time) in the presence of parameters variation and
non-linearity.
-10
-15
-20
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.15. Two area power system frequency change with
Fuzzy PID controller for three variable rule base
-3
2
with fuzzy pid5
x 10
Thus the attempt made here was a success. From the above
simulation results it is clear that the dynamic response in the
proposed method is far better than that of the conventional PI,
PID controller and Fuzzy PI controller. All the drawbacks of the
PI, PID controller, providing a better dynamic response are
eliminated by using a Fuzzy logic controller. Hence we can
conclude form the above results that inclusion of fuzzy logic
controller is an effective and efficient method of load frequency
control with better dynamic response
0
-2
Frequency change(pu)
-4
-6
-8
-10
-12
-14
-16
-18
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.16.Two area power system frequency change
Fuzzy PID controller for five variable rule base
-3
2
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with fuzzy pid7
x 10
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0
-2
Frequency Control Performance Assessment Criteria.
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-4
-6
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[2]
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[3]
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-14
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-18
0
5
10
15
20
25
Time(sec)
30
35
40
45
50
Fig.17. Two area power system frequency change with
Fuzzy PID controller for seven rule base
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variable rule base simulation result shows that steady state
response is reached but the dynamic response is poor as compared
to PID controller but has high stability gain margin compared to
PID controller. So to improve both responses we go for five
variable rule base. In five variable rule base simulation result
shows that dynamic response is improved and steady state is
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International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 7, July 2012)
[7]
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