DSpace at VNU: Optimal Reactive Power Dispatch Using Improved Pseudo-gradient Search Particle Swarm Optimization

G73
PG74
PG76
PG77
PG80
PG85
PG87
PG89
PG90
PG91
PG92
PG99
PG100
PG103
PG104
PG105
PG107

Case 1: Ploss

Case 2: VD

Case 3: Lmax

0
0
0
0
450
85
0

0
0
0
220
314
0
7
0
0
0
0
0
19
204
48
0
0
155
160
0
391
392
497.6133
0
0
0
0
0
0
477

0
4
607
0
0
0
0
252
40
0
0
0

0
0
0
0
450
85
0
0
0
0
220
314
0
7
0
0
0

0
0
19
204
48
0
0
155
160
0
391
392
546.0628
0
0
0
0
0
0
477
0
4
607
0
0
0
0
252
40
0

0
0

0
0
0
0
450
85
0
0
0
0
220
314
0
7
0
0
0
0
0
19
204
48
0
0
155
160
0

391
392
595.7806
0
0
0
0
0
0
477
0
4
607
0
0
0
0
252
40
0
0
0

TABLE A2. Best control variables of ORPD by IPG-PSO method
on the IEEE 118-bus system

Input/control
variables
PG110
PG111

PG113
PG116
VG1 (p.u.)
VG4
VG6
VG8
VG10
VG12
VG15
VG18
VG19
VG24
VG25
VG26
VG27
VG31
VG32
VG34
VG36
VG40
VG42
VG46
VG49
VG54
VG55
VG56
VG59
VG61
VG62
VG65

VG66
VG69
VG70
VG72
VG73
VG74
VG76
VG77
VG80
VG85
VG87
VG89
VG90
VG91
VG92
VG99
VG100

Case 1: Ploss

Case 2: VD

Case 3: Lmax

0
36
0
0
1.0276
1.0383

1.0267
1.0331
1.0318
1.0307
1.0271
1.0303
1.0270
1.0510
1.0737
1.0772
1.0317
1.0264
1.0250
1.0360
1.0278
1.0216
1.0269
1.0312
1.0562
1.0408
1.0380
1.0405
1.0524
1.0406
1.0354
1.0497
1.0586
1.0851
1.0445
1.0600

1.0459
1.0378
1.0380
1.0495
1.0492
1.0518
1.0479
1.0633
1.0283
1.0316
1.0512
1.0471
1.0544

0
36
0
0
1.0048
1.0217
0.9996
0.9752
1.0078
1.0058
1.0035
1.0427
1.0308
1.0305
0.9696
1.0114

1.0157
1.0014
0.9950
1.0101
0.9987
1.0030
1.0180
1.0451
1.0036
1.0236
1.0029
1.0150
1.0326
1.0002
0.9956
1.0200
1.0159
0.9500
0.9763
1.0313
1.0212
1.0350
1.0128
1.0089
1.0146
1.0177
0.9948
1.0038
1.0553
1.0562

1.0014
1.0400
1.0353

0
36
0
0
1.0830
1.1000
1.0608
1.1000
1.0654
1.0755
1.0812
1.1000
1.0772
1.0299
1.1000
1.1000
1.0431
1.0419
1.0417
1.1000
1.1000
1.0408
1.1000
1.1000
1.1000
1.0303

1.0640
1.0570
0.9500
0.9500
1.0366
1.1000
0.9664
0.9882
1.0517
0.9500
0.9500
1.0318
1.0411
1.0669
1.0851
1.0546
1.0880
1.0353
1.1000
1.1000
1.0043
0.9500
1.0061

TABLE A2. Best control variables of ORPD by IPG-PSO method
on the IEEE 118-bus system (continued)


Polprasert et al.: Optimal Reactive Power Dispatch Using Improved Pseudo-gradient Search Particle Swarm Optimization

Downloaded by [New York University] at 00:10 06 March 2016

Input/control
variables

Case 1: Ploss

Case 2: VD

Case 3: Lmax

1.0436
1.0435
1.0393
1.0304
1.0234
1.0296
1.0007
1.0319
1.0329
−3.9655
8.8322
−5.7183
0.2743
4.9950
3.1075
3.7288
2.4739
12.0609
15.9061

4.0061
7.9725
3.5559
4.1279
0.9723
1.0733
0.9917
1.0006
0.9664
1.0156
0.9801
0.9387
0.9825
115.0605
2.112
0.0641
91.07

0.9613
1.1000
1.0065
0.9960
0.9989
1.0316
1.0362
0.9564
0.9962
−40.0000
11.6809
0.0000

9.9933
3.9027
4.5512
1.0775
4.1669
9.3147
20.0000
7.3286
17.1194
1.7582
4.4127
1.0568
1.0037
0.9964
0.9732
0.9723
0.9783
1.0837
1.0052
0.9719
171.7155
0.1620
0.0671
47.86

1.0488
1.0466
1.0524
0.9500
1.0215

0.9500
1.0498
1.0893
1.0619
−26.2979
1.8492
−25.0000
10.0000
10.0000
1.5463
10.9166
12.0000
5.0176
20.0000
0.0000
18.6604
3.0687
1.2987
0.9918
0.9000
0.9766
0.9760
1.1000
1.1000
1.0856
1.0303
0.9269
215.9290
3.2414
0.0568

55.62

VG103
VG104
VG105
VG107
VG110
VG111
VG112
VG113
VG116
Qc5 (MVAR)
Qc34
Qc37
Qc44
Qc45
Qc46
Qc48
Qc74
Qc79
Qc82
Qc83
Qc105
Qc107
Qc110
T 8 (p.u.)
T 32
T 36
T 51
T 93

T 95
T 102
T 107
T 127
Ploss (MW)
VD
Lmax
Average CPU
time (sec)

TABLE A2. Best control variables of ORPD by IPG-PSO method
on the IEEE 118-bus system (continued)

BIOGRAPHIES
Jirawadee Polprasert obtained her B.Eng. (electrical engineering) in 2004 from Suranaree University of Technology,
Thailand, and her M.Eng. (electric power system management) from Asian Institute of Technology (AIT) in 2007. She
is currently a doctoral candidate in energy with electric power

15

system management specialization; she is also an electrical
engineer and project coordinator at Italthai Engineering Company Limited. She has been serving as a research associate
at Energy Field of Study, AIT, and a program coordinator
of Greater Mekong Subregion Academic and Research Network (GMSARN) since 2007. Her research interests are in
power system operation, planning and analysis, and artificial
intelligence-based optimization applications in power systems.
Weerakorn Ongsakul obtained his B.Eng. (electrical engineering) in 1988 from Chulalongkorn University, Thailand,
and his M.S. and Ph.D. (electrical engineering) from Texas
A&M University, USA, in 1991 and 1994, respectively. He is
currently an associate professor of energy and the former dean

of the School of Environment, Resources and Development,
AIT. He has conducted projects sponsored by Sida, European
Commission and the Association of South East Asian Nations
(EC-ASEAN) Energy Facility/ACE, EU–Thailand Economic
Co-operation Small Project Facility, Energy Conservation
and Promotion Fund and Electricity Generating Authority of
Thailand (EGAT), and Provincial Electricity Authority (PEA)
with a combined funding of US$3.0 million. Based on his
research work, he has published more than 200 international
refereed journal articles and conference proceedings papers.
He served as an energy specialist on the Energy Standing
Committee, Senate of Thailand, during 2008–2011 and as a
consultant of the Asian Development Bank Institute (ADBI)
in 2011–2012. He has been serving as a secretary general of
the GMSARN since 2006. He co-authored one book (Artificial Intelligence in Power System Optimization). His research
interests are in power system operation, artificial intelligence
applications in power system optimization, smart grids, and
microgrids.
Vo Ngoc Dieu received his B.Eng. and M.Eng. in electrical engineering from Ho Chi Minh City University of Technology,
Ho Chi Minh City, Vietnam, in 1995 and 2000, respectively,
and his D.Eng. in energy from AIT, Pathumthani, Thailand,
in 2007. He is a research associate at Energy Field of Study,
AIT, and head of the Department of Power Systems, Faculty
of Electrical and Electronic Engineering, Ho Chi Minh City
University of Technology, Ho Chi Minh City, Vietnam. His
research interests are applications of AI in power system optimization, power system operation and control, power system
analysis, and power systems under deregulation and restructuring.