Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/16900
Title: Computational intelligent techniques for loadability enhancement of deregulated power system using facts devices
Researcher: Nagalakshmi S
Guide(s): Kamaraj N
Keywords: Computational intelligent techniques
Deregulated power system
Differential Evolution
Electrical Engineering
Facts devices
Flexible AC Transmission System
Static VAR Compensator
Thyristor Controlled Phase Shifting Transformer
Thyristor Controlled Series Compensator
Upload Date: 6-Mar-2014
University: Anna University
Completed Date: 01/12/2011
Abstract: In recent years, the electrical power demand has grown rapidly due to rising population. Hence, the electric utilities are called to serve more power through their networks and also to maintain system security. Environmental right-of-way and cost problems are the major hurdles for the power transmission network expansion. Hence, there is a need for better utilization of the existing power system capabilities. Flexible AC Transmission System (FACTS) devices have gained a great interest in transmission system due to recent advances in power electronics. Loadability enhancement with FACTS devices using conventional methods and computational algorithms have been carried out. However, when the size of the optimization problem increases, those techniques lag in the perspective of convergence iterations and computation time. Hence, there is a need for better algorithm with which the result converges faster and in less computation time. This approach proposes implementation of Differential Evolution (DE) algorithm for loadability enhancement of deregulated power system with optimal location and setting of FACTS devices. Three types of FACTS devices namely, Thyristor Controlled Series Compensator (TCSC), Static VAR Compensator (SVC) and Thyristor Controlled Phase Shifting Transformer (TCPST) are employed in this study. This approach uses AC load flow equations with the constraints on real and reactive power generations, transmission line flows, magnitude of bus voltages and FACTS device settings. The bilateral transactions are modeled using secured bilateral transaction matrix utilizing AC Distribution Factor (ACDF) with slack bus contribution. Maximum loadability, number of FACTS devices, location and settings, convergence iterations and computational time are determined. The results are compared with the performance of Particle Swarm Optimization (PSO) algorithm. Simulations are performed on IEEE 6 bus system, 39 bus New England system and IEEE 118 bus system.
Pagination: xxi,157p.
URI: http://hdl.handle.net/10603/16900
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File28.84 kBAdobe PDFView/Open
02_certificate.pdf46.71 kBAdobe PDFView/Open
03_abstract.pdf22.88 kBAdobe PDFView/Open
04_acknowledgements.pdf18.07 kBAdobe PDFView/Open
05_contents.pdf48.54 kBAdobe PDFView/Open
06_chapter1.pdf121.54 kBAdobe PDFView/Open
07_chapter2.pdf220.11 kBAdobe PDFView/Open
08_chapter3.pdf303.88 kBAdobe PDFView/Open
09_chapter4.pdf427.11 kBAdobe PDFView/Open
10_chapter5.pdf774.48 kBAdobe PDFView/Open
11_chapter6.pdf115.54 kBAdobe PDFView/Open
12_chapter7.pdf32.52 kBAdobe PDFView/Open
13_appendix.pdf229.08 kBAdobe PDFView/Open
14_references.pdf97.01 kBAdobe PDFView/Open
15_publications.pdf25.58 kBAdobe PDFView/Open
16_vitae.pdf18.57 kBAdobe PDFView/Open


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