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1. Improve Generation Control Quality in
Restructure Power System
Master Project 1 and 2
GUIDED BY: PREPARED BY:
Dr. Jamal Rizk Japan atel
Assistant professor 19212757
1
5. INTRODUCTION
What is automatic generation control (AGC)?
Automatic generation controller(AGC) is a system for adjusting the
power output of multiple generators at different power plants, in
response to changes in the load.
Load-frequency control (LFC).
Load-frequency control is employed to allow an area to first meet
its own load demands, then to assist in returning the steady state
frequency of the system (Δf) to zero.
5
6. LFC has the following two objectives(Primary ALFC loop ):-
I. Hold the frequency constant ( Δf = 0) against any load change.
II. Each area must maintain the tie-line power flow to its pre-specified value.
Secondary ALFC loop :-
The primary ALFC loop yields a frequency droop between zero and full load of the
generator.
I. Following a load change, the frequency error should return to zero.
II. The magnitude of the transient frequency deviation should be minimized.
III. Integrated frequency error should be minimum.
6
Continue …..
7. Modeling of Generator :-
Generators receive mechanical power from the turbines and then convert it to electrical
power.
The mechanical power given out by the turbine does not counterpart the electrical power
generated by the generator which results in an error which is being integrated into the rotor
speed deviation( ).
Where, = Output from the generator
= Input to the generator
Tg =Time constant of the generator
( ) 1
( ) 1
V
gg
P s
P s sT
( )VP s
( )gP s
7
MODELING OF SYSTEM
8. Modeling of Load :-
The system block diagram including the effect of the load damping is show in Figure :
Where, M s= 2H
D = 2.H/f.
= Power system time constant.
= 1/D
pT
pT
81
p
P
K
sT
pK
1
sM D
Continue …..
9. Superconducting Magnetic Energy Storage(SMES).
Superconducting Magnetic Energy Storage Devices (SMES) can store the excessive electronic
energy as electromagnetic energy in high temperature superconducting inductors and
releases the stored energy if required SMES is a large superconducting coil capable of storing
electric energy in the magnetic field generated by the current crossing through it.
The advantage of MES devices compared to the other energy storage devices are high energy
storage density, high energy storage efficiency, long application lifetime and few
environmental pollution.
Application of Superconducting Magnetic Energy Storage (SMES) system is in Power system
load leveling, Power system stabilizers, Fault Current Limiter and voltage support for critical
loads because of SMES high efficiency and speedy reaction to power demand. 9
Continue …..
10. SMES systems store energy in the magnetic field created by the flow of direct
current in a superconducting coil .
The DC current is covert to three-phase AC output using a inverter.
Where ,
= Energy stored in
magnetic
field of an inductor
L = Inductance
I = Current flow in the
winding
21
2
lE LI
lE
SMES circuit diagram
10
Continue …..
11. Pros:
High power
Quick recharge
No moving part(low maintains)
Quickly response
High efficiency (>95%)
Cons:
low energy density
Expensive
Status:
Currently viable for short-term power (seconds).
Capable of providing 40 MW of power for 30 minutes or 10 MW of power for 2 hours.
Main application are in PQ and transmission support. 11
Continue …..
12. Optimization of the integral gain setting
The optimum integral gain settings of the integral controllers are obtained using
integral squared error (ISE) technique. A characteristic of the ISE criterion is that, it
weighs large errors heavily and small errors lightly. A quadratic performance index
by,
is minimized for1% step load perturbation in either of the area to obtain the area to
obtain the optimum values of Ki1 and Ki2.
2 2 2
1 2 12
0
( )dt
t
tieJ f f P
120 2 4 6 8 10 12 14 16 18 20
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
Deviation in frequency of area-1
Time(s)
variation
f1
f2
Ptie
Continue …..
13. P1
P1
K
1+sT
11-K
s
11apf
12apf
13apf
1B
SM ES
TH
1
R HY
1
R G
1
R
0
122πT
1
1
s
P1
P1
K
1+sT
11-K
s
21apf
22apf
23apf
TH
1
R HY
1
R G
1
R
2B
12a12a
+
-
-
-
+
+
-
-
+
-
+
+
+
+
+
+
+
-
-
∆Pg6
∆Pg3
∆Pg1
∆Pg5
∆Pg2
∆Pg4
-
-
∆Pd1+∆Pd2+
∆Pd3
∆Pd4+∆Pd5+
∆Pd6
Reheat-turbine Thermal power plant
Hydro power plant Mech. Hydraulic governor
Gas Turbine Power plant
Hydro power plant Mech. Hydraulic governor
Reheat-turbine Thermal power plant
Gas Turbine Power plant
Scheduld_Pti12 +
+
-
AREA 1
AREA 2
-
GH
1
1+sT
RS
RH
1+sT
1+sT
W
W
1-sT
1+0.5sT
G
1
1+sT
R R
G
1+sK T
1+sT T
1
1+sT
G
1
1+sT
R R
G
1+sK T
1+sT T
1
1+sT
GH
1
1+sT
RS
RH
1+sT
1+sT
W
W
1-sT
1+0.5sT
g g
1
C + sb
G
G
1 + sX
1 + sY
C R
F
1 -sT
1 + sT C D
1
1 + sT
g g
1
C +sb
G
G
1+sX
1+sY
CR
F
1-sT
1+sT CD
1
1+sT
+
+
+
+
+
Simulation Software :MATLAB R2017B)
Test system 1: Two area multi-source power system with SMES (In area-1)
14. Optimization of the integral gain setting
The optimal gain values are obtained for with and without SMES are tabulated in
Table 1.
Table 1
Condition Ki1 Ki2
SMES in area -1 0.86 0.256
SMES in area -2 0.265 0.86
SMES in both area 0.94 0.94
Without SMES 0.18 0.18
14
Continue …..
18. 18
Load
perturbation in
area
Variation in Condition
Settling
time(sec)
Max over
shoot
Under
Shoot
1
Without SMES 23 0.0062 -0.0399
SMES in Area-1 13 0.0055 -0.0308
Without SMES 25 0.01 -0.036
SMES in Area-1 12 0.004 -0.025
Without SMES 22 -0.0026 -0.0112
SMES in Area-1 11 -0.00159 -0.0079
2
Without SMES 25 0.009 -0.0356
SMES in Area-1 14 0.0119 -0.033
Without SMES 24 0.0067 -0.0391
SMES in Area-1 15 0.0043 -0.0395
Without SMES 23 0.0111 0.0025
SMES in Area-1 13 0.0105 0.0017
1
f
1
f
2
f
2
f
12
P
tie
12
P
tie
.
Simulation results
Table 2:- Effect of SMES on variation in area frequency and tie-line power
19. The schematic block diagram of two- area system in restructured Environment
show in fig below :
GENCO 1 DISCO 1
GENCO 2 DISCO 2
GENCO 3 DISCO 3
DISCO 4 GENCO 4
DISCO 5 GENCO 5
DISCO 6 GENCO 6
Tie line 12
AREA 1 AREA 2
19
Load-A1 Load-A2
Restructure system:-
20. AGC in Two area inter connected restructured power system with SMES
Case A: Poolco based transactions
Poolco based contracts between DISCOs and available GENCOs is simulated based
on the following contract participation factor matrix (cpfm1).
The load is demanded only by all the DISCOs on own area GENCOs . Let the value
of this load demand be 0.1 pu MW for each of them.
0.4 0.4 0.2 0 0 0
0.4 0.2 0.4 0 0 0
0.2 0.4 0.4 0 0 0
1
0 0 0 0.4 0.3 0.3
0 0 0 0.3 0.4 0.3
0 0 0 0.3 0.3 0.4
cpf
20
Continue …..
21. Case B: Combination of Poolco and bilateral based transactions
In this case, any DISCO has the freedom to have a contract with any GENCO in its
own and other areas. Consider that all the DISCOs contract with the available
GENCOs for power as per the following:
The scheduled power on the tie line in the direction from area I to area II is
= -0.2700 pu MW
3 6 6 3
1 2,
1 4 4 1
tie scheduled Lj Li
i j i j
P cpfij P cpfij P
21
0.25 0.2 0.25 0.1 0.1 0.1
0.2 0.3 0.2 0.1 0.1 0.1
0.25 0.2 0.25 0.1 0.1 0.1
2
0.1 0.1 0.1 0.2 0.3 0.2
0.1 0.1 0.1 0.3 0.1 0.3
0.1 0.1 0.1 0.2 0.3 0.2
cpf
Continue …..
22. Case C: Contract Violation
DISCO violates a contract by demanding more power than that specified in the
contract. This unconstructed power must be supplied by the GENCOs in the
same area as the DISCO.
It must be reflected as a local load of the area but not as the contract demand.
Consider case b again with a modification that DISCOs of area one demands 0.2
puMW and area two 0.05 puMW of excess power.
22
Continue …..
23. 23
P1
P1
K
1+sT
1i-K
s
11apf
12apf
13apf
1B
SMES
TH
1
R HY
1
R G
1
R
0
122πT
1
1
s
P1
P1
K
1+sT
2i-K
s
21apf
22apf
23apf
TH
1
R HY
1
R G
1
R
2B
12a12a
+
-
-
-
-
+ -
+
+
+
+
+
+
+
-
-
∆f2
∆f1
∆Pg6
∆Pg3
∆Pg1
∆Pg5
∆Pg2
∆Pg4
+
+
+
+ -
-
∆Pd1+∆Pd2
+∆Pd3
∆Pd4+∆Pd5
+∆Pd6
Reheat-turbine Thermal power plant
Hydro power plant Mech. Hydraulic governor
Gas Turbine Power plant
Scheduld_Pti12 +
+
-
AREA 1
AREA 2
-
+
+
+
1
2
3
4
5
6
-
+
+
+
+
+
cpf11
∆Pd1
cpf12
cpf13
cpf14
cpf15
cpf16
cpf21
∆Pd2
cpf22
cpf23
cpf24
cpf25
cpf26
cpf31
∆Pd3
cpf32
cpf33
cpf34
cpf35
cpf36
cpf51
∆Pd5
cpf52
cpf53
cpf54
cpf55
cpf56
cpf61
∆Pd6
cpf62
cpf63
cpf64
cpf65
cpf66
cpf41
∆Pd4
cpf42
cpf43
cpf44
cpf45
cpf46
1
3
5
2
4
6
1
3
5
2
4
6
1
3
2
4
6
5
1
3
2
4
6
5
1
3
2
4
6
5
1
3
2
4
6
5 +
+
+
+
+
+
1
1 GsT
1
1
R R
G
sK T
sT
1
1 TsT
1
1 GsT
1
1
R R
G
sK T
sT
1
1 TsT
1
1 GHsT
1
1
RS
RH
sT
sT
1
1 0.5
W
W
sT
sT
1
1 GHsT
1
1
RS
RH
sT
sT
1
1 0.5
W
W
sT
sT
1
g gc sb
1
1
G
G
sX
sY
1
1
CR
F
sT
sT
1
1 CDsT
1
g gc sb
1
1
G
G
sX
sY
1
1
CR
F
sT
sT
1
1 CDsT
Two area AGC simulator block diagram in restructured power system with SMES.
24. 24
0 5 10 15 20 25 30
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
Deviation in frequency of area-1
Time(s)
f1(Hz)
case a
case b
case c
Continue …..
25. “Process to find the “best” solution which is minimize/maximize a specific
objective function or cost value under satisfying various constraints or limit.”
Methods:
Classic Methods: Linear programming ,non liner programming, Quadratic
programming, Newton’s method ,etc.
Artificial intelligence: ANN,FL,PSO,ACO,GA,DE,TLBO etc
Some applications of optimization methods
1. Medical science: CT scan
2. Mobile phone: Dynamic programming
3. Stock market: Linear programming
4. Aviation system: Nonlinear programming
5. Power system, protection , power electronics…….
6. Water distribution system, transport engineering
25
Optimization …..
26. Answer
Gbest Pbest
Velocity update equation :
Position update equation :
1
* 1* 1( ) 2* 2( )k k k k
i i besti i best iV w V C R P X C R G X
1 1
*k k k
i i iX X V
Particle Swarm Optimization (1995 by James Kennedy and Russell Eberhart) …..
27. Advantages :
It is very fast.
It does not require derivation of objective function.
It has less parameters to adjust.
It does not require a good initial solution.
Less sensitive to the nature of objective fun.
It can be easily integrated with other methods.
Disadvantages :
Lack of solid mathematical background.
Difficulty in finding optimal design parameters.
28. State space modeling :
A= model (state input) N X N
B=model Input (step time) P X N
C= model output (Df1) N X M
D= zero matrix of appropriate dimensions. P X M
A=
B= load input
C= [1/s] (out –in)
D= 0
x Ax Bu
y Cx Du
1 2 1 2 1 2, 1 2,
3 4 1 2 1 1 2 1
2 3, 4 1 2 1 2
[ T , T , T , T , y , y T , T
T , T , b , b , P ,K , , , ,
, , , , , ]
cd cd f f g g G G
G G tie i R R T
T T T RH RH P P
T T T
T T T T T P P
Continue …..
29. Controller Gain Without SMES SMES in area 1
I
Area 1 Area 2 Area 1 Area 2
Ki 0.1763 0.1763 0.6226 0.4199
PID
Kp 1.1808 1.1808 0.2422 1.2738
Ki 0.4311 0.4311 0.7010 0.1415
Kd 1.2017 1.2017 0.9952 1.2761
Table 3:- Optimize gain value by using PSO :-
Continue …..
35. 35
Case Variation
in
Controller Condition Settling time
(sec)
Max over
shoot
Under shoot
C
I
Without SMES 16 0.26 -0.0798
SMES in Area-1 13 0.1340 -0.1255
PID
Without SMES 7 0.0776 -
SMES in Area-1 7 0.0985 -0.004
I
Without SMES 14 0.2174 -0.1330
SMES in Area-1 10 0.2728 -0.0971
PID
Without SMES 7 0.0685 -
SMES in Area-1 5 0.0745 -
I
Without SMES 6 0.0105 -0.0154
SMES in Area-1 5 0.0173 -0.0348
PID
Without SMES 4 - -0.0137
SMES in Area-1 4 - -0.0135
1f
2f
12tieP
Simulation results
Table 6:- Effect of controller on variation in area frequency and tie-line power
restructured PS case C
39. • It is clear that inclusion of SMES in the existing system improves the dynamic performance of AGC.
• When SMES placed in both areas, there is not much improvement in the system performance in
comparison with SMES in either of the areas it clearly visible in figures. Due to economic reasons, it is
advisable to consider SMES in any of the areas.
• From the result Table 4-6 it is clear that, SMES is effectively stabilize the system and notable improves the
transient response of area frequency and tie line power exchange as well as also reduce settling time
,maximum over shoot and undershoot under different contract variation in restructured electric market.
39
Conclusion …..
40. • From the table 5 and 6 it is also clear that PID gain combination with SMES give much better
performance over I controller with SMES.
• PSO take much less time for gain optimization compare to manual gain optimization.
• PSO gain over manual gain value which is less, it is improve output which conclude form Figures.
• Ring distribution update system power quality compare to Radial feeder system.
40
Conclusion …..
41. • There is possibility to stabilize frequency oscillation and power deviation of
tie line under load perturbation by FACTS device like SSSC and TCPS
installed in series with the tie-line in coordination with SMES in restructure
power system.
• We can optimize generation by using these type of APM.
41
Future work …..
42. REFERENCES…..
BOOKS….
1. P. Kundur, Power System Stability and Control, McGraw-Hill Inc., New
York, 1994.
2. Olle. L.Elegerd, Electric Energy systems Theory-An introduction Second
Edition Tata McGraw-Hill Education Private Ltd. New Delhi, 1983.
3. A.Chakrabarti, M.L.soni, P.V.Gupta, U. S.Bhatnagar,Power system
Engineering Second Edition,Dhanpat rai ,&co,2012.
Papers….
1. Deepak. M, “Improving the dynamic performance in load frequency
control of an interconnected power system with multi source power
generation using Superconducting Magnetic Energy Storage (SMES)”
Advances in Green Energy , International Conference IEEE,2014.
2. K.P Singh Parmar, S. Majhi, D.P.Kothari. “Load frequency control of a
realistic power system with multi-source power generation", Electrical
Power and Energy Systems, vol.42, pp-426-433, 2012.
3. Rajesh Joseph Abraham, D. Das, A Patra, “Automatic generation control
of an interconnected hydro thermal power system considering
superconducting magnetic storage", Electrical Power and Energy
Systems vol. 29, pp. 571-579, 2007.
42
43. 6. J nanda and B.L kaul”Automatic generation control of an interconnected power
system”,PROC IEE ,vol.125 ,No 5, MAY 1978.
7. D Vaibhav, Pai MA, Hiskens Iran A. “Simulation and optimization in an AGC system
after deregulation”. IEEE Trans Power Syst 2001, 16(3):481–8.
8. P.Bhatt, S.P.Ghoshal, R.Roy “Automatic generation control of two-area
interconnected hydro-Hydro Restructured power system with TSPS and
SMES”ACEEE international journal on electrical and power eng,vol 1,No 2, july
2010.
9. P.Bhatt, S.P.Ghoshal, R.Roy “optimized multi area AGC simulation in restructured
power systems ”Electrical power energy systems,vol 32(2010) 311-322.
9. Kennedy J and Eberhart R (1995), Particle Swarm Optimization, In Proceedings of
IEEE International Conference on Neural Networks, pp. 1942–1948.
10. Kennedy J (1999), Small Worlds and Mega-Minds: Effects of Neighborhood
Topology on Particle Swarm Performance, In Proceedings of the 1999 Congress of 43
REFERENCES…..
44. 11. J. Nanda, S. Mishra, P. G. Mishra, and K.V. Sajith.“A Novel Classical Controller for
Automatic Generation Control in Thermal and Hydrothermal Systems” IEEE Trans.
on war Electronics, Drives and Energy Systems ,2010.
12. Youssef L Abdel- Magid, M A. Abido.“AGC TUNING OF INTERCONNECTED REHEAT
THERMAL SYSTEMS WITH PARTICLE SWARM 0PTIMIZATION” IEEE Trans. on
Electronics, Circuits and Systems, vol 3,2003 Conference.
13. K Bhattaacharya,M.H Bolley J.e Dalder, “operation of restucured power
system’,Kluwe Academic Publishers,Bosten,2001.
14. Lorrin Philipson,H.lee willis, “understanding electric utilities and
deregulation,’Marcel Dekker inc.New York,1998
15 . http://www.superpower-inc.com/content/superconducting-magnetic-energy-
storage-smes
16. http://appliedsc.epfl.ch/course/smes/faq.htm 44
REFERENCES…..
46. 46
Case Variation
in
Controller Condition Settling time
(sec)
Max over
shoot
Under shoot
A
I
Without SMES 14 0.1526 -0.0451
SMES in Area-1 6 0.0922 -0.0401
PID
Without SMES 5 0.0575 -
SMES in Area-1 4 0.0544 -
I
Without SMES 16 0.1165 -0.0840
SMES in Area-1 9 0.1149 -0.0435
PID
Without SMES 4 0.0398 -
SMES in Area-1 4 0.0321 -0.0019
I
Without SMES 6 .00115 -0.0104
SMES in Area-1 5 0.0062 -0.0086
PID
Without SMES 4 0.0011 -0.0049
SMES in Area-1 4 0.0002 -0.0072
1f
2f
12tieP
Table 4:- Effect of controller on variation in area frequency and tie-line power restructured PS case A
47. 47
Case Variation
in
Controller Condition Settling time
(sec)
Max over
shoot
Under shoot
B
I
Without SMES 14 0.2060 -0.0574
SMES in Area-1 10 0.1064 -0.0934
PID
Without SMES 6 0.0825 -
SMES in Area-1 5 0.0670 -
I
Without SMES 14 0.1570 -0.1075
SMES in Area-1 10 0.2034 -0.0760
PID
Without SMES 6 0.0570 -
SMES in Area-1 5 0.0526 -
I
Without SMES 6 0.0110 -0.0145
SMES in Area-1 5 0.0118 -0.0263
PID
Without SMES 4 - -0.0137
SMES in Area-1 4 - -0.0134
1f
2f
12tieP
Table 5:-Effect of controller on variation in area frequency and tie-line power restructured PS case B
