ORIGINAL_ARTICLE
Mechanical System Modelling of Robot Dynamics Using a Mass/Pulley Model
The well-known electro-mechanical analogy that equates current, voltage, resistance, inductance and capacitance to force, velocity, damping, spring constant and mass has a shortcoming in that mass can only be used to simulate a capacitor which has one terminal connected to ground. A new model that was previously proposed by the authors that combines a mass with a pulley (MP) is shown to simulate a capacitor in the general case. This new MP model is used to model the off-diagonal elements of a mass matrix so that devices whose effective mass is coupled between more than one actuator can be represented by a mechanical system diagram that is topographically parallel to its equivalent electric circuit model. Specific examples of this technique are presented to demonstrate how a mechanical model can be derived for both a serial and a parallel robot with both two and three degrees of freedom. The technique, however, is extensible to any number of degrees of freedom.
http://jaiee.iau-ahar.ac.ir/article_513197_8ece5bb2a73b7ee9c5fb2763240e6853.pdf
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10
Mass matrix
inertia matrix
MP model
pulley
differential transmission
mechanical system representation
robot dynamics
Impedance
equivalent electric circuit
Brown, O., 1931. "Synthesis of a finite two-terminal network whose driving-point impedance is a prescribed function of frequency". J. Math. Physics. vol. 10, pp. 191-236.
1
Craig, J.J., 2005. “Introduction to Robotics Mechanics and Control”. 3rd ed., Pearson Prentice Hall.
2
Eppinger, S., Seering, W., 1992. “Three Dynamic Problems in Robot Force Control”. IEEE Trans. Robotics & Auto., V. 8, No. 6, pp. 751-758.
3
Fairlie-Clarke, A.C., 1999. “Force as a Flow Variable”. Proc. Instn. Mech. Engrs., V. 213, Part I, pp. 77-81. Foster, R. M., 1924. "A reactance theorem". Bell System Tech. J., vol. 3, pp. 259-267.
4
Hamill, D.C., 1993. "Lumped Equivalent Circuits of Magnetic Components: The Gyrator-Capacitor Approach". IEEE Transactions on Power Electronics, vol. 8, pp. 97.
5
Hayward, V., Choksi, J., Lanvin, G., Ramstein, C., 1994. “Design and Multi-Objective Optimization of a Linkage for a Haptic Interface”. Proc. of ARK „94, 4th Int. Workshop on Advances in Robot Kinematics (Ljubliana, Slovenia), pp. 352-359.
6
Paynter, H.M., 1961. Analysis and Design of Engineering Systems. MIT Press.
7
Sass, L., McPhee, J., Schmitke, C., Fisette, P., Grenier, D., 2004. "A Comparison of Different Methods for Modelling Electromechanical Multibody Systems". Multibody System Dynamics, vol. 12, pp. 209-250.
8
Stocco, L., Yedlin, M., Sept. 2006. “Closing the Loop on the Electro-Mechanical System Analogy”. Submitted to: IEEE J. Circuits & Systems.
9
Tilmans, H.A.C., 1996. "Equivalent circuit representation of electromechanical transducers: I. Lumpedparameter systems". J. Micromech. Microeng, vol. 6, pp. 157-176.
10
van Amerongen, J., Breedveld, P., 2003. "Modelling of physical systems for the design and control of mechatronic systems". Annual Reviews in Control, vol. 27, pp. 87-117.
11
Yamakita, M., Shibasato, H., Furuta, K., 1992. “Tele- Virtual Reality of Dynamic Mechanical Model”. Proc. IEEE/RSJ Int. Conf. Intel
12
ligent Robots & Systems, (Raleigh, NC), pp. 1103,-1110
13
ORIGINAL_ARTICLE
Design of A Self-Tuning Adaptive Power System Stabilizer
Power system stabilizers (PSSs) must be capable of providing appropriate stabilization signals over abroad range of operating conditions and disturbances. The main idea of this paper is changing aclassic PSS (CPSS) to an adaptive PSS using genetic algorithm. This new genetic algorithm based onadaptive PSS (GAPSS) improves power system damping, considerably. The controller design issue isformulated as an optimization problem that is solved by GA to identify PSS parameters in variousoperating conditions. Numerical simulation studies have been done on a modified model of IEEEsecond benchmark. The consequence of these studies shows that, the performance of the suggestedgenetic algorithm based adaptive PSS in damping of electromechanical oscillations of power system isbetter than CPSS.
http://jaiee.iau-ahar.ac.ir/article_513198_7e02586b3fe51e71df84c3599c8626f7.pdf
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21
Power System Stabilizer
Genetic Algorithm
Adaptive Controller
Electromechanical Oscillations
[1] Yao-nan Yu, “Electric Power System
1
Dynamics”, Academic Press, 1983.
2
[2] P.Hoang, K. Tomsovic, “Design and Analysis
3
of an Adaptive Fuzzy Power System
4
Stabilizer”, IEEE Transaction on Energy
5
Conversion, Vol.11, No.2, Page(s): 455-461,
6
June 1996.
7
[3] Abdelazim, Tamer, O. P. Malik, “An Adaptive
8
Power System Stabilizer Using On-Line Self-
9
Learning Fuzzy System”, IEEE Power
10
Engineering Society 2003 General Meeting,
11
Vol.3, pp:1715-1720, July 2003.
12
[4] P. Shamsollahi, O. P. Malik, “An Adaptive
13
Power System Stabilizer Using On-Line
14
Trained Neural Networks”, IEEE Transaction
15
on Energy Conversion, Vol. 12, Page(s): 382-
16
387, 1997.
17
[5] W.Hussein, O.P.Malik, “GA-Identifier and
18
Predictive Controller for Multi-Machine Power
19
System”, Power India Conference, IEEE, on
20
CD, April 2006.
21
[6] K.A. Folly, “Design of Power System
22
Stabilizer: A Comparison between Genetic
23
Algorithms and Population-Based Incremental
24
Learning”, IEEE Power Engineering Society
25
General Meeting, on CD, June 2006.
26
[7] V.Miranda, S.Srinivasan, L.Proenca,
27
“Evolutionary Computation in Power
28
Systems”, International Journal of Electric
29
Power and Energy Systems, Vol.20, Page(s):
30
89-98, January 1998.
31
[8] E.R.C.Viveros, G.N.Taranto, D.M.Falcao,
32
“Coordinated Tuning of AVRs and PSSs by
33
Multi-Objective Genetic Algorithms”, ISAP
34
2005, Page(s): 247-252, 2005.
35
[9] K. J. Astrom, B. Wittenmark, “Adaptive
36
Control”, Addison Wesley, 1989.
37
[10] Benjamin C. Kua, “Automatic control
38
systems”, Prentice Hall of India, 2003.
39
ORIGINAL_ARTICLE
Design and Simulation 4-Channel Demultiplexer Based on Photonic Crystals Ring Resonators
In this paper, a new design of demultiplexer based on two-dimensional photonic crystal ringresonator is proposed. The structure is made of a hexagonal lattice of silicon rods with therefractive index 3.46 in coefficient of air with refractive index 1. The transmission efficiencyand Quality factor for our proposed demultiplexer, respectively, are more than 65% and1600. The normalized transmission spectra of the photonic crystal ring resonator are takenusing Two-dimensional (2D) Finite Difference Time Domain (FDTD) method. The photonicband gap is calculated by Plane Wave Expansion (PWE) method.
http://jaiee.iau-ahar.ac.ir/article_513199_1a947c3c973b3c4c88964db7ec6711e4.pdf
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Demultiplexer
Photonic crystal
Quality factor
Ring resonator
[1] J D Joannapolous, R D Meade and J N Winn,
1
Photonic crystals: Molding the flow of light,
2
Princeton University Press, New Jerse, 08540,
3
[2] K Sakoda, Optical properties of photonic
4
crystals, Springer, Berlin, 2001.
5
[3] YOGITA KALRA and R K SINHA, “Photonic
6
band gap engineering in 2D photonic crystals,”
7
PRAMANA journal of physics” Vol.67, 1155-
8
1164 , 2006.
9
[4] Hadjira Badaoui1, Mohammed Feham1 and
10
Mehadji Abri,“ Photonic-Crystal Band-pass
11
Resonant Filters Design Using the Twodimensional
12
FDTD Method,” IJCSI
13
International Journal of Computer Science
14
Issues, Vol. 8, 127-132 ,2011.
15
[5] S-I. Takayama, H. Kitagawa, Y. Tanaka, T.
16
Asano and Susumu Noda, “Experimental
17
demonstration of complete photonic band gap
18
in two-dimensional photonic crystal slabs,”
19
Appl.Phys. Lett., vol. 87, Article no.
20
061107, 2005.
21
[6] Nobuhiko Susa, “Large absolute and
22
polarization-independent photonic band gaps
23
for various lattice structures and rod
24
shapes,” J. OF Appl. Phys., vol. 91, no. 6,
25
pp.3501-3510, March ,2002.
26
[7] Z.-Y. Li, “Large absolute band gap in 2D
27
anisotropic photonic crystals,” Phys. Rev.
28
Lett., vol. 81, no. 12, pp. 2574-2577, Sept.
29
[8] A. Ghaffari,et al., “Heterostructure
30
wavelength division demultiplexers using
31
photonic crystal ring resonators,” Opt.
32
Commun.vol. 281, 4028–4032, 2008.
33
[9] M. David, et al., “T-Shaped channel drop
34
filters using photonic crystal ring
35
resonators,” Physica E,vol. 40, pp. 3151–
36
3154, 2008.
37
[10] M.Y.Mahmoud,GH.Massou,A.Taalbi and
38
Z.M.Chekroun,“Optical channel drop filters
39
based on photonic crystal ring resonators,”
40
Optics Communications 285,368–372.,
41
ORIGINAL_ARTICLE
Finite Element Method Application in Analyzing Magnetic Fields of High Current Bus Duct
The goal of paper is to present the magnetic field calculations in high current bus ducts. Finiteelement method is used to do this. Bus ducts under study have figure such as circle area. Thecalculations will be using mathematical relations, meshed geometric shape and analyzing them.Geometric mean will help us to determine the value of magnetic field. COMSOL software is appliedfor simulation studies. Calculations have been analyzed in three phase state and also, simulations areimplemented into the three dimensional position. Demonstration procedure and numericalcalculations are used for presentation the front of view of bus duct. Skin effect and connectionconfiguration between bus ducts are considered in the calculations. Aforementioned method can beused in the magnetic fields analyzing in transmission lines and electrical energy link which consist ofinsulator, easily. Typical bus duct which is applied in simulation studies produced by a pars generatorcorporation, it has been installed in Ardebil substation.
http://jaiee.iau-ahar.ac.ir/article_513200_1136b50c2c8e76fe076e8aef95e7c1c7.pdf
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33
High Current Bus Duct
Magnetic field
Meshed-Finite Element
Gas Insulated Lines (GIL)
[1] Benato, R,”Gas Insulated Transmission Lines in Railway
1
Galleries”, IEEE Trans. Power Deliv.2005, 20, pp: 704–
2
[2] Piatek, Z., Kusiak, D., Szczegielniak,
3
T.,”Electromagnetic Field and Impedances of High
4
Current Busducts”, In Proceedings of the International
5
Symposium Modern Electric Power Systems (MEPS),
6
Wroclaw, Poland, 20–22, Sep 2010.
7
[3] Surutka, J. “Electromagnetics, 2nd ed.; Engineering
8
Books”, Belgrade, Yugoslavia, 1966 (in Serbian).
9
S.M.H.Hoseyni, V.Montaghemi: Finite Element Method Application in Analyzing Magnetic …
10
[4] Sarajčev, P., Goić, R.”Power loss computation in high-current generator bus ducts of rectangular cross-section”, Electric Power Compon. Syst. 2010, 38, 1469–1485. [5] K. B. Madhu Sahu and J. Amarnath,” Effect of Various Parameters on the Movement of Metallic Parameters in a Single Phase Gas Insulated Bus Duct With Image Charges and Dielectric Coated Electrodes”, ARPN Journal of Engineering and Applied Sciences, VOL. 5, NO. 6, JUNE 2010. [6] K.B. Madhu Sahu and J. Amarnath,” Movement of metallic particle contamination in a gas insulated busduct under dielectric coated enclosure with electromagnetic field effect”, Indian Journal of Science and Technology, Vol. 3 No. 7, July 2010. [7] L. Rajasekhar , D. Subbarayudu, and J. Amarnath,” Metallic Particle Motion in A Single Phase Gas Insulated Busduct Under the Influence of Power Frequency Voltages”, International Journal of Electronic and Electrical Engineering, Volume 3, Number 12010. [8] http://www.comsol.com.
11
ORIGINAL_ARTICLE
Minimizing Loss of Information at Competitive PLIP Algorithms for Image Segmentation with Noisy Back Ground
In this paper, two training systems for selecting PLIP parameters have been demonstrated. The first compares the MSE of a high precision result to that of a lower precision approximation in order to minimize loss of information. The second uses EMEE scores to maximize visual appeal and further reduce information loss. It was shown that, in the general case of basic addition, subtraction, or multiplication of any two images, γ, k, and λ = 1026 and β = 2 are effective parameter values. It was also found that, for more specialized cases, it can be effective to use the training systems outlined here for a more application-specific PLIP. Further, the case where different parameter values are used was shown, demonstrating the potential practical application of data hiding.
http://jaiee.iau-ahar.ac.ir/article_513201_9d0dd30a19cd8522d81bd1dd5cc0abb7.pdf
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38
[1] Sos Agaian, Blair Silver, and Karen Panetta, ―Transform Coefficient Histogram Based Image Enhancement Algorithms Using Contrast Entropy,‖ IEEE Trans. Image Processing, Vol. 16, No. 3, pp. 751—758, March, 2007.
1
[2] M. Heat, S. Sarkar, T. Sanocki, and K. Bowyer, ―Comparison of Edge Detectors: A Methodology and Initial Study,‖ Computer Vision and Image Understanding, Vol. 69, No. 1, pp. 38—54, 1998.
2
[3] S. Agaian, K. Panetta, and A. M. Grigoryan. ―A New Measure of Image Enhancement,‖ inProc. IASTED 2000 Int. Conf. Signal Processing & Communication, Marbella, Spain, 2000.
3
[4] M. K. Kundu and S. K. Pal, ―Thresholding for Edge Detection Using Human Psychovisual Phenomena,‖ Pattern Recognition Letters, Vol. 4, No. 6, December 1986, pp. 433—441.
4
[5] Sos S. Agaian, Karen Panetta, and Artyom Grigoryan, ―Transform based imageenhancement with performance measure,‖ IEEE Transactions On Image Processing, Vol. 10, No. 3, pp.367—381, March, 2001.
5
[6] H. S. Kim, et al., ―An Anisotropic Diffusion Based on Diagonal Edges,‖ in Proc. 9th Int. Conf. Advanced Communication Technology, pp. 384—388, February, 2007.
6
[7] Y. Bao and H. Krim, ―Smart Nonlinear Diffusion: A Probabilistic Approach,‖ IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 1, pp. 63—72, January, 2004.
7
ORIGINAL_ARTICLE
Vehicle Logo Recognition Using Image Matching and Textural Features
In recent years, automatic recognition of vehicle logos has become one of the important issues in modern cities. This is due to the unlimited increase of cars and transportation systems that make it impossible to be fully managed and monitored by human. In this research, an automatic real-time logo recognition system for moving cars is introduced based on histogram manipulation. In the proposed system, after locating the area that contains the logo, image matching technique and textural features are utilized separately for vehicle logo recognition. Experimental results show that these two methods are able to recognize four types of logo (Peugeot, Renault, Samand and Mazda) with an acceptable performance, 96% and 90% on average for image matching and textural features extraction methods, respectively.
http://jaiee.iau-ahar.ac.ir/article_513202_03f0cf05c5adcc3490f6997968d9ec5b.pdf
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45
Vehicle logo recognition
textural features
image matching
vehicle positioning
ORIGINAL_ARTICLE
Optimal Design of UPFC Output Feed Back Controller for Power System Stability Enhancement by Hybrid PSO and GSA
In this paper, the optimal design of supplementary controller parameters of a unified powerflow controller(UPFC) for damping low-frequency oscillations in a weakly connected systemis investigated. The individual design of the UPFC controller, using hybrid particle swarmoptimization and gravitational search algorithm (PSOGSA)technique under 3 loadingoperating conditions, is discussed. The effectiveness of proposed controller on enhancingdynamic stability is tested through eigenvalue analysis and time domain simulation. Alsononlinear and electrical simulation results show the validity and effectiveness of theproposed control schemes over a wide range of loading conditions. It is also observed that theproposed UPFC-based damping stabilizers greatly enhance the power system transientstability. Also, simulation results of coordinated design of stabilizer based on δE and mB ispresented and discussed,the system performance analysis under different operating conditionsshow that the δE-based controller is superior to the mB-based controller.
http://jaiee.iau-ahar.ac.ir/article_513203_0bc340bc6860314cbd5776e8fe932c13.pdf
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62
Power system dynamic stability
UPFC
PSOGSA
(1)A.T. Al-Awami, Y. L. Abdel-Magid, M. A.
1
Abido, “A particle-swarm-based approach of
2
power system stability enhancement with
3
unified power flow controller”, International
4
Journal of Electric Power and Energy Systems,
5
vol. 29, no. 3, pp. 251 – 259, 2007
6
[2] P. M. Anderson, A. A. Fouad, “Power System
7
Control and Stability”, Ames, IA: Iowa State
8
University .Press ,1977.
9
[3] H. Shayeghi, H. A. Shayanfar, S. Jalilzadeh, A.
10
Safari,“A PSO based unified power flow
11
controller for damping of power system
12
oscillations”, Energy Conversion and
13
Management,vol. 50, no.10, pp. 2583-2592,
14
[4] H. Shayeghi, H. A. Shayanfar, S. Jalilzadeh, A.
15
Safari,“Design of output feedback UPFC
16
controller for damping of electromechanical
17
oscillations using PSO”, Energy Conversion
18
and Management,vol. 50, no.10, pp. 2554-
19
2561, 2009.
20
[5] Ali Ajami and Mehdi Armaghan,“Application
21
of multi-Objective PSO algorithm for power
22
system stability enhancement by means of
23
SSSC”, International Journal of Computer and
24
Electrical Engineering, vol. 2, no. 5, pp.
25
1793-8163, 2010
26
[6] M. A. Abido, “Robust design of multimachine
27
power system stabilizers using simulated
28
annealing”, IEEE Trans. Energy Conversion,
29
vol. 15, no. 3, pp. 297-304, 2000.
30
[7] Chun liu, Ryuichi Yokoyama, Kaoru Koyanagi,
31
Kwang Y. Lee, “PSS design for damping of
32
inter-area power oscillations by coherencybased
33
equivalent model”, International
34
Journal of Electrical Power and Energy
35
Systems, vol. 26, no. 7, pp. 535-544, 2004.
36
[8] P. Kundur, M. Klein, G.J. Rogers, M.S.
37
Zywno, “Application of power system
38
stabilizers for enhancement of overall system
39
stability”, IEEE Trans. on Power System, vol.
40
4, no. 2, pp. 614-626, 1989.
41
[9] A. J. F. Keri, X. Lombard, A. A. Edris,
42
“Unified power flow controller: modeling and
43
analysis”, IEEE Trans. on Power Systems, vol.
44
14, no. 2, pp. 648-654, 1999.
45
[10] M. R. Banaei, A. Kami, “Interline power flow
46
controller (IPFC) based damping recurrent
47
neural network controllers for enhancing
48
stability”, Energy Conversion and
49
Management, vol. 52, no.7, pp. 2629-2636,
50
[11] L. Gyugyi, C.D. Schauder, S. L. Williams, T.
51
R. Rietman, D. R. Torgerson, A. Edris, “The
52
unified power flow controller: a new approach
53
to power transmission control”, IEEE Trans.
54
on Power Delivery, vol. 10, no. 2, pp.1085-
55
1097, 1995.
56
[12] L. Gyugyi, “A unified power flow control
57
concept for flexible AC transmission systems”,
58
IEE Proceedings -Generation Transmission
59
Distribution, vol. 139, no. 4, pp. 323-333,
60
[13] A. Nabavi-Niaki, M.R. Iravani, “Steady-state
61
and dynamic models of unified power flow
62
controller (UPFC) for power system studies”,
63
IEEE Trans. on Power Systems, vol. 11, no. 4,
64
pp. 1937-1943, 1996
65
[14] P. C. Stefanov, A. M. Stankovic, “Modeling of
66
UPFC operation under unbalanced conditions
67
with dynamic phasors”, IEEE Trans. on Power
68
Systems, vol. 17, no. 2, pp. 395-403, 2002.
69
[15] H.F. Wang, “Damping function of unified
70
power flow controller”, IEE Proceedings-
71
Generation Transmission Distribution, vol.
72
146, no. 1, pp. 81-87, 1999.
73
[16] H. F. Wang, “Application of modeling UPFC
74
into multi-machine power systems”, IEE
75
Proceedings– Generation Transmission
76
Distribution, vol. 146, no. 3, pp. 306-312,
77
[17] K.R. Padiyar, A.M. Kulkarni, “Control design
78
and simulation of unified power flow
79
controller”, IEEE Trans. on Power Delivery,
80
vol. 13, no. 4, pp. 1348 1354, 1997.
81
[18] E. Uzunovic, C.A. Canizares, J. Reeve,
82
“EMTP studies of UPFC power oscillation
83
damping”, Proc. of the North American Power
84
Symposium, pp. 405-410, 1999.
85
[19] N. Mithulananthan, C. Canizares, J. Reeve, G.
86
Rogers, “Comparison of PSS, SVC, and
87
STATCOM for damping power system
88
oscillations”, IEEE Trans. on Power Systems,
89
vol. 18, no. 3, pp. 786-792, 2003.
90
[20] R.K. Pandey, N.K. Singh, “Minimum singular
91
value based identification of UPFC control
92
parameters”, Proc. of IEEE Region 10
93
Conference, pp. 1-4, 2006.
94
[21] A.K. Baliarsingh, S. Panda, A.K. Mohanty, C.
95
Ardil, “UPFC supplementary controller design
96
using real-coded genetic algorithm for
97
damping low frequency oscillations in power
98
systems”, International Journal of Electrical
99
Power and Energy Systems Engineering, vol.
100
3, no.4, pp. 165-175, 2010.
101
[22] M. Tripathy, S. Mishra, G.K.
102
Venayagamoorthy, “Bacteria foraging: a new
103
tool for simultaneous robust design of UPFC
104
controllers”,Proc. of theInternational Joint
105
Conference on Neural Networks, pp. 2274-
106
2280, 2006.
107
[23] Y. Lee, S. Yung, “STATCOM controller design
108
for power system stabilization with suboptimal
109
control strip pole assignment”,
110
International Journal of Electrical Power and
111
Energy Systems, vol. 24, no. 9, pp. 771-779,
112
[24] A. Ajami,R. Gholizadeh, “Optimal design of
113
UPFC-based damping controller using
114
imperialist competitive algorithm”, Turkish
115
Journal of Electrical Engineering and Computer
116
1122,2011.
117
[25] A. Ajami, H. Asadzadeh, “Damping of Power
118
System Oscillations Using UPFC Based
119
Multipoint Tuning AIPSO-SA Algorithm”, Gazi
120
University Journal of Science, vol. 24, no. 4,pp.
121
791-804, 2011.
122
[26] J. Kennedy, R.C. Eberhart, “Particle swarm
123
optimization”, Proc. of IEEE International
124
Conference on Neural Networks, pp. 1942–
125
1948, 1995.
126
[27] E. Rashedi, S. Nezamabadi, S. Saryazdi,
127
“GSA: a gravitational search algorithm”,
128
Information Sciences, vol. 179, no. 13, pp.
129
2232–2248, 2009.
130
[28] A.A. Atapour, A. Ghanizadeh, S.M.
131
Shamsuddin,“Advances of Soft Computing
132
Methods in Edge Detection”, International
133
Center for Scientific Research and Studies,
134
vol. 1. no. 2, pp162–202, 2009.
135
[29] E. Rashedi, H. Nezamabadi-pour, S. Saryazdi,
136
“BGSA: binary gravitational search
137
algorithm”, Natural Computingvol. 9, no. 3,pp.
138
727–745, 2009.
139
[30] S. Sinaie, “Solving shortest path problem using
140
Gravitational Search Algorithm and Neural
141
Networks”, Universiti Teknologi Malaysia
142
(UTM), Joho r Bahru, Malaysia, M.Sc. Thesis
143
[31] S. Mirjalili and S.Z. Mohd Hashim, “A New
144
Hybrid PSOGSA Algorithm for Function
145
Optimization”, Proc. of theInternational
146
Conference on Computer and Information
147
Application(ICCIA), pp. 374-377, 2010.
148
[32] M.A. Abido, A.T. Al-Awami, Y.L. Abdel-
149
Magid, “Power system stability enhancement
150
using simultaneous design of damping
151
controllers and internal controllers of a unified
152
power flow controller”, IEEE PES General
153
Meeting, 2006.
154
ORIGINAL_ARTICLE
Multi Objective Optimization Placement of DG Problem for Different Load Levels on Distribution Systems with Purpose Reduction Loss, Cost and Improving Voltage Profile Based on DAPSO Algorithm
Along with economic growth of countries which leads to their increased energy requirements,the problem of power quality and reliability of the networks have been more considered andin recent decades, we witnessed a noticeable growing trend of distributed generation sources(DG) in distribution networks. Occurrence of DG in distribution systems, in addition tochanging the utilization of these systems, has provided the opportunity for these companies tobe able to design systems with lower costs. In this paper, the problem of placement andcapacity determination of DG were carried out using multiple methods. The main objectivesof issue were improving the voltage profile, losses reduction and reduce the cost of operationthat were carried out based on an economic function. Using the multiple methods to improvesome purposes and utilization of weighting coefficients provided an appropriate plan.DAPSO algorithm was used for optimization and various experiments carried out on realnetwork.
http://jaiee.iau-ahar.ac.ir/article_513204_a76ce7de93adef91b05555cfc95ca6e0.pdf
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72
DAPSO Algorithm
Distribution network
Distributed Generation
[1] Y.G. Hegazy, M.M.A. Salama, and A.Y.
1
Chikhani, “Adequacy assessment distributed
2
generation system using Mont carlo simulation,”
3
IEEE Transactions on Power system, vol.18, no.1,
4
2003, pp.48-52
5
[2] C. Wang and M. H. Nehrir:” Analytical
6
Approaches for Optimal Placement of Distributed
7
Generation Sources in Power Systems”, IEEE
8
trans. on Power Sys., Vol. 19, No. 4, november
9
[3] H. Hedayati, S. A. Nabaviniaki, and A.
10
Akbarimajd,: “A Method for Placement of DG
11
Units in Distribution Networks”, IEEE trans. on
12
Power Delivery, Vol. 23, No. 3, July 2008.
13
[4] W. El-Khattam, Y. G. Hegazy and M. M. A.
14
Salama, “An Integrated DistributedGeneration
15
Optimization Model for Distribution System
16
Planning”, IEEE trans. On Power Sys., Vol. 20, No.
17
2, may 2005.
18
[5]. Prakomchai Phonrattanasak Department of
19
Electrical Engineering North Eastern University
20
Khonkaen, Thailand 40000" Optimal Placement of
21
DG Using Multiobjective particle Swarm
22
Optimization ".IEEE , Mechanical and Electrical
23
Technology (ICMET) , 2nd international
24
conference , 2010 , pp.342 - 346 .
25
[6]. T. Sutthibun and P. Bhasaputra Department of
26
Electrical and Computer Engineering Faculty of
27
Engineering Thammasat University, Patumthani
28
12120, Thailand " Multi-Objective Optimal
29
Distributed Generation Placement Using Simulated
30
Annealing". Electrical Engineering / Electronics
31
Computer Telecommunications and Information
32
Technology (ECTI – CON) , international
33
conference , 2010 , 810 – 813 .
34
[7] M.H. Moradi , M. Abedini, “A combination of
35
genetic algorithm and particle swarm optimization
36
for optimal DG location and sizing in distribution
37
systems” Electrical Power and Energy Systems 34
38
(2012) 66–74
39
[8] Fahad S. Abu-Mouti, M. E. El-Hawary
40
“Optimal Distributed GeneratioAllocation and
41
Sizing in Distribution Systems via Artificial Bee
42
Colony Algorithm” IEEE Trans. Power, VOL. 26,
43
NO. 4 OCTOBER 2011 , pp. 2090-2101
44