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7 Νοε 2013 (πριν από 3 χρόνια και 11 μήνες)

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1.

Gene expression programming algorithm for transient security classification



Almoataz Y. Abdelaziz
,

S. F. Mekhamer
,

H. M. Khattab
,

M. L. A. Badr
,

Bijaya Ketan
Panigrahi

Department of Electrical Power &
Machines, Faculty of Engineering, Ain Shams
University, Cairo, Egypt

Abstract


In this paper, a gene expression programming (GEP) based algorithm is implemented for power
system transient security classification. The GEP algorithms as evolutionary algorithms for pattern
classification have recently received attention for classificati
on problems because they can perform
global searches. The proposed methodology applies the GEP for the first time in transient security
assessment and classification problems of power systems. The proposed algorithm is examined
using different IEEE standar
d test systems. Power system three phase short circuit contingency
has been used to test the proposed algorithm. The algorithm checks the static security status of
the power system then classifies the transient security of the power system as secure or not

secure. Performance of the algorithm is compared with other neural network based classification
algorithms to show its superiority for transient security classification
.


Publisher:

Springer
-
Verlag


References



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-
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Assessment. In: Proceedings of the IEEE PowerCon 2002, International C
onference on Power System
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17, vol. 1, pp. 220
-
224 (2002)


Santo, M. D., Vaccaro, A.: A Distributed Architecture for Online Power System Security Analysis.
IEEE Trans. on Industrial Electronics 51(6), 1238
-
1248 (2004)


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., Prabhakara, F., Al
-
Abiad, A., Koivo, A.: Security Evaluation in Power Systems Using Pattern
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Sterpu, S., Lu, W., Basenger, Y., Hadjisaid, N.: Power System Security Analysis. In: Proceedings of
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e IEEE Power Engineering Society General Meeting (2006)

Bizjak, G., Kerin, U., Kerbs, S. R., Lerch, E., Ruhle, O.: Vision 2020 Dynamic Security Assessment in
Real time Environment. Proceedings of the IEEE (2008)


Mansour, Y., Vaahedi, E., El
-
Shark
awi, M. A.: Large Scale Dynamic Security Screening and Ranking
using Neural Networks. IEEE Trans. on Power Systems 12(2), 954
-
958 (1997)

Kevin Warwick , Arthur Ekwue , Raj Aggarwal, Artificial intelligence techniques in power systems,
Institution of E
lectrical Engineers, Stevenage, UK, 1997


Bansal, R.C.: Overview and Literature Survey of Artificial Neural Networks Applications to Power
Systems (1992
-
2004). IE (I) Journal
-
EL 86, 282
-
296 (2006)


Khattab, H. M., Abdelaziz, A.Y., Mekhamer, S. F., Badr, M. A. L.: Static Security Assessment using a
Probabilistic Neural Network Based Classifier. The Online Journal on Electronics and Electrical
Engineering (OJEEE) 3(4), 454
-
461 (2011)


Kalyani, S.,

Swarp, K. S.: Transient Security Assessment and Classification using Support Vector
Machine. Journal of Electrical Systems (2009)

Abdul Wahab, N. I., Mohamed, A.: Transient Stability Assessment of Power Systems Using
Probabilistic Neural Network wit
h Enhanced Feature Selection and Extraction. International Journal on
Electrical Engineering and Informatics 1(2), 103
-
114 (2009)

Kalyani, S., Swarp, K. S.: Study of Neural Network Models for Security Assessment in Power Systems.
International Journa
l of Research and Reviews in Applied Sciences 1(2), 104
-
117 (2009)



Silveria, M.C., Lutofo, A. D., Minussi, C. R.: Transient Stability Analysis of Electrical Power Systems
Using a Neural Network Based on Fuzzy ARTMAP. In: IEEE Bologna Power Tech. Conf
erence,
Bologna, Italy, June 23
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26 (2003)




Ferreira, C.: Gene Expression Programming: A New Adaptive Algorithm for Solving Problems.
Complex Systems 13(2), 87
-
129 (2001)


Abdelaziz, A.Y., Mekhamer, S. F., Badr, M. A. L., Khattab, H. M.: Probabili
stic Neural Network
Classifier for Static Voltage Security Assessment of Power Systems. Electric Power Components and
System 40(2), 147
-
160 (2012)



2
-

Genetic algorithm based approach for optimal allocation of TCSC for power system
loadability enhancement

Almoataz Y. Abdelaziz
,

M. A. El
-
Sharkawy
,

M. A. Attia
,

Bijaya Ketan Panigrahi

Department of Electrical P
ower & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt

Abstract


This paper presents an approach to find the optimal location of thyristor controlled series
compensators (TCSC) in a power system to improve the loadability of its lines and minimize its
total loss. Also the proposed approach aims to find the optimal numbe
r of devices and their
optimal compensation levels by using genetic algorithm (GA) based approach with taking into
consideration the thermal and voltage limits. Examination of the proposed approach is carried out
on a modified IEEE 30
-
bus system
.


Publisher:

Springer
-
Verlag




References


Xiao
-
Ping Zhang , Christian Rehtanz , Bikash Pal, Flexible AC Transmission Systems:
Modelling and C
ontrol, Springer Publishing Company, Incorporated, 2012

Meikandasivam, S., Nema, R. K., Jain, S. K.: Behavioral Study of TCSC Device
-

A
Matlab/Simulink Implementation. World Academy of Science, Engineering and
Technology 45 (2008)

Gerbex, S., Ch
erkaoui, R., Germond, A. J.: Optimal Location of Multi
-
Type FACTS
Devices in a Power System by Means of Genetic Algorithms. IEEE Trans. Power Syst.
16(3), 537
-
544 (2001)

Banu, R. N., Devaraj, D.: Genetic Algorithm Approach for Optimal Power Flow with
FACTS Devices. In: 4th International IEEE Conference Intelligent Systems (September
2008)

Saravanan, M., Slochanal, S., Venkatesh, P., Abraham, J.: Application of Particle Swarm
Optimization Technique for Optimal Location of FACTS Devices Considering
Cost of
Installation and System Loadability. Electric Power Syst. Res. 77(3/4), 276
-
283 (2007)

Cai, L., Erlich, I., Stamtsis, G.: Optimal Choice and Allocation of FACTS Devices in
Deregulated Electricity Market Using Genetic Algorithms. In: Proceeding of the IEEE
PES General Meeting, pp. 201
-
207 (2004)




Feng, W., Shrestha, G.: Allocation of TCSC

Devices to Optimize Total Transmission
Capacity in a Competitive Power Market. In: Proceedings of the IEEE Power Engineering
Society Transmission and Distribution Conference (Winter Meeting), Columbus, OH, pp.
587
-
593 (January 2001)

Kazemi, A., Shahn
azari, M., Naghshbandi, A.: A Genetic Algorithm Based Approach to
Allocation of SVC Considering System Loadability. In: Proceedings of the 41st
International Universities Power Engineering Conference, UPEC (September 2006)


Mahdad, B., Bouktir, T., Sra
iri, K.: Strategy of Location and Control of FACTS Devices
for Enhancing Power Quality. In: IEEE MELECON, Benalmádena, Málaga, Spain (May
2006)

Rashed, G., Shaheen, H., Cheng, S.: Optimal Location and Parameter Setting of TCSC by
Both Genetic Algorit
hm and Particle Swarm Optimization. In: Second IEEE Conference
on Industrial Electronics and Applications, Art. No. 4318586, pp. 1141
-
1147 (2007)

Sadiq M. Sait , Habib Youssef, Iterative Computer Algorithms with Applications in
Engineering: Solving C
ombinatorial Optimization Problems, IEEE Computer Society
Press, Los Alamitos, CA, 1999

David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning,
Addison
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Wesley Longman Publishing Co., Inc., Boston, MA, 1989

Zimmerman,

R. D., Murillo
-
Sanchez, E.C.: Matpower A Matlab™ Power System
Simulation Package Version 3.2, User's Manual (September 21, 2007)

Yang, G.Y., Hovland, G., Majumder, R., Dong, Z.Y.: TCSC Allocation based on Line Flow
Based Equations Via Mixed
-
Integer
Programming. IEEE Trans. Power Syst. 22(4), 2262
-
2269 (2007)


Abdelaziz, A.Y., El
-
Sharkawy, M. A., Attia, M. A.: Optimal Location of Thyristor
-
Controlled Series Compensators in Power Systems for Increasing Loadability by Genetic
Algorithm. Electric Po
wer Components and Systems 39(13), 1373
-
1387 (2011)







3
-

An adaptive protection scheme for optimal coordination
of overcurrent relays

Almoataz Youssef Abdelaziz, HEA Talaat, AI Nosseir, Ammar A Hajjar



Professor of Electrical Power Engineering, Faculty of Engineering, Ain Shams University,Cairo, Egypt



almoataz_abdelaziz@eng.asu.edu.eg





Abstract

This paper presents an adaptive protection scheme for optimal coordination of overcurrent
relays (OCR) in interconnected power networks with an improved formulation. The scheme
adapts to system changes;
new relays settings are implemented as load, generation
-
level or
system
-
topology changes. The software developed for this application is described. The
developed scheme is applied to the IEEE 30
-
bus test system. Results showed the
importance and necessi
ty of this scheme in maintaining the optimal performance of the ...



Published In:

Electric Power Systems Research



References

An adaptive protection scheme for optimal coordination of overcurrent relays

AY Abdelaziz, HEA Talaat, AI Nosseir, AA Hajjar
-

Electric Power Systems Research, 2002





4
-


A neural network
-
based scheme for fault diagnosis of
power transformers

EA Mohamed, AY Abdelaziz, AS Mostafa




Professor of Electrical Power Engineering, Faculty

of Engineering, Ain Shams University, Egypt



almoataz_abdelaziz@eng.asu.edu.eg






Abstract



The proposed fault diagnosis scheme (FDS) consists of three hierarchical levels. In the first level, a pre
-
processing of input data is performed. In the second level, there is an ANN which is designed to detect
the fault and determine the faulted side if any. In the third level, there are two sides diagnosis systems.
Each system is dedicated to one side and con
sists of one ANN in series with four paralleled ANNs (for
fault type classification). ... The proposed FDS is trained and tested using local measurements of three
-
phase primary voltage and primary and ...



Published In:

Electric Power Systems Research



References

A neural network
-
based scheme for fault diagnosis of power transformers

EA Mohamed, AY Abdelaziz, AS Mostafa
-

Electric Power Systems Research, 2005





















5

-

Distribution system reconfiguration using a modified
Tabu Search algorithm

AY Abdelaziz,
FM Mohamed, SF Mekhamer, MAL Badr



Professor of Electrical Power Engineering, Faculty of Engineering, Ain Shams University, Egypt



almoataz_abdelaziz@eng.asu.edu.eg





Abstract

This article presents an efficient meta
-
heuristic method for reconfiguration of distribution
systems. A modified Tabu Search (MTS) algorithm is used to reconfigure distribution
systems so that active power losses are globally minimized with turning on/off
sectionalizing switches. TS algorithm

is introduced with some modifications such as using a
tabu list with variable size according to the system size. Also, a random multiplicative move
is used in the search process to diversify the search toward unexplored regions. The ...



Published In:


Advances in Automotive Control



References

Towards Real
-
Time Networked Embedded Generalized Predictive Control for Automotive Active
Suspension Systems

Y Shoukry, W Elkharashi, M Elshafie, S Hammad
-

Advan
ces in Automotive Control, 2010






















6
-
Distribution systems reconfiguration using a modified

particle swarm optimization algorithm

AY Abdelaziz, FM Mohammed, SF Mekhamer, MAL Badr



Professor of Electrical Power Engineering, Faculty of Engineering, Ain Shams University, Egypt



almoataz_abdelaziz@eng.asu.edu.eg




Abstract

This paper presents the particle swarm optimization (PSO) algorithm for solving the optimal
distribution system reconfiguration problem for power loss minimization. The PSO is a
relatively new and powerful i
ntelligence evolution algorithm for solving optimization
problems. It is a population
-
based approach. The PSO is originally inspired from the social
behavior of bird flocks and fish schools. The proposed PSO algorithm in this paper is
introduced with so
me modifications such as using an inertia weight that decreases linearly ...



Published In:

Electric Power Systems Research




References

Distribution systems reconfiguration using a modified particle swarm optimization algorithm

AY Abdelaziz, FM Mohammed, SF Mekhamer…
-

Electric Power Systems Research, 2009














7
-

A hybrid HNN
-
QP approach for dynamic economic
dispatch problem

AY Abdelaziz, MZ Kamh, SF Mekhamer, MAL Badr



Professor of Electrical Power Engineering, Faculty of Engineeri
ng, Ain Shams University, Egypt



almoataz_abdelaziz@eng.asu.edu.eg









Abstract

This paper introduces a solution of the dynamic economic dispatch (DED) problem using a
hybrid approach of Hopfield neural network (HNN)
and quadratic programming (QP). The
hybrid algorithm is based on using enhanced HNN; to solve the static part of the problem;
the QP algorithm for solving the dynamic part of the DED. This technique guarantees the
global optimality of the solution due t
o its look
-
ahead capability. The new algorithm is
applied and tested to an example from the literature and the solution is then compared ...




Published In:

Electric Power Systems Research




References

A hybrid HNN
-
QP approach for dynamic economic dispatch problem

AY Abdelaziz, MZ Kamh, SF Mekhamer, MAL Badr
-

Electric Power Systems Research, 2008