Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/16451
Title: Application of gaussian and cauchy inspired pso algorithms for power system optimization problems
Researcher: Muthu selvan N B
Guide(s): Somasundaram P
Keywords: Cauchy
Electrical engineering
Gaussian
Power system optimization
Upload Date: 27-Feb-2014
University: Anna University
Completed Date: 01/06/2012
Abstract: The main objective of this research work is to develop an enhanced newlineParticle Swarm Optimization (PSO) algorithm for solving various power newlinesystem generation scheduling problems. The enhanced PSO algorithm is newlinedeveloped from the conventional PSO algorithm by the combined application newlineof Gaussian and Cauchy distribution and hence it is appropriately termed as newlineGaussian Cauchy inspired Particle Swarm Optimization (GCPSO). The newlinemodifications made into the conventional PSO algorithm ensure more reliable newlineand faster convergence in obtaining a global optimal solution. The integrity of newlinethe proposed algorithm lies in the significance of dealing the optimization newlineproblems without placing any restrictions on the structure or type of the newlinefunction to be optimized. The various power system problems that are solved newlineusing GCPSO algorithm include: Economic Dispatch (ED), Economic newlineEmission Load Dispatch (EELD), Multi Constrained Economic Dispatch newline(MCED) with non-smooth fuel cost function, DC Optimal Power Flow newline(DCOPF), AC Optimal Power Flow (ACOPF), Security Constrained Optimal newlinePower Flow (SCOPF), Transient Stability Constrained OPF (TSCOPF), newlineOptimal Power Flow with Flexible AC Transmission System (FACTS) newlinecontrollers and wind farm integrated ED and OPF problems. Initially the ED problem is solved with the PSO algorithm and the newlinemajor shortcomings of the PSO algorithm are analyzed. The analysis reveals newlinecertain major limitations such as relatively large computational time, tendency newlinetowards premature convergence and search inconsistency. Hence there is a newlinenecessity to enhance the PSO algorithm. The feasible modifications using newlinevarious probability distributions that can be introduced into the PSO newlinealgorithm are investigated. From this investigation it is found that the newlineapplication of Gaussian and Cauchy distributions into the velocity update newlineequation are appropriate for enhancing the PSO algorithm.
Pagination: xxv, 172p.
URI: http://hdl.handle.net/10603/16451
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File69.8 kBAdobe PDFView/Open
02_certificates.pdf279.38 kBAdobe PDFView/Open
03_abstract.pdf378.11 kBAdobe PDFView/Open
04_acknowledgement.pdf92.04 kBAdobe PDFView/Open
05_contents.pdf1.18 MBAdobe PDFView/Open
06_chapter 1.pdf2.02 MBAdobe PDFView/Open
07_chapter 2.pdf3.5 MBAdobe PDFView/Open
08_chapter 3.pdf2.74 MBAdobe PDFView/Open
09_chapter 4.pdf1.91 MBAdobe PDFView/Open
10_chapter 5.pdf2.84 MBAdobe PDFView/Open
11_chapter 6.pdf236.93 kBAdobe PDFView/Open
12_appendix.pdf1.39 MBAdobe PDFView/Open
13_references.pdf942.63 kBAdobe PDFView/Open
14_publications.pdf182.19 kBAdobe PDFView/Open
15_vitae.pdf47.2 kBAdobe PDFView/Open


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