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Title: Optimal bidding strategies for gencos in day ahead power market using pso based hybrid algorithms
Researcher: Ramesh babu M
Guide(s): Somasundaram P
Keywords: electrical engineering
hybrid algorithms
Optimal bidding
Upload Date: 1-Sep-2014
University: Anna University
Completed Date: 01/10/2012
Abstract: The main objective of this research is to develop improved newlinestochastic techniques namely Cauchy Mutated Memetic Particle Swarm newlineOptimization CMMPSO and MultiObjective Particle Swarm Optimization newlineDynamic Crowding Distance MOPSODCD for solving various scheduling newlineproblems faced by the Generator Companies Gencos in a dayahead newlinederegulated market newlineThe popularity of Particle Swarm Optimization PSO is due to its newlinesignificant property of dealing with optimization problems without any newlinerestrictions on the structure or type of the function to be optimized and due to newlinethe ease of computation However the critical drawbacks of the PSO are the newlinepremature convergence and high computation time required to obtain the newlinenear global optimum Thus an amendment in the classical PSO technique is newlineincorporated using Cauchy Mutation CM and local search for obtaining a newlinefaster but not premature convergence This improved technique is pertinently newlinetermed as CMMPSO newline newline
Pagination: xxx,169p.
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File176.08 kBAdobe PDFView/Open
02_certificates.pdf2.56 MBAdobe PDFView/Open
03_abstract.pdf63.65 kBAdobe PDFView/Open
04_acknowledgement.pdf54.86 kBAdobe PDFView/Open
05_contents.pdf186.75 kBAdobe PDFView/Open
06_chapter 1.pdf176.2 kBAdobe PDFView/Open
07_chapter 2.pdf895.55 kBAdobe PDFView/Open
08_chapter 3.pdf525.46 kBAdobe PDFView/Open
09_chapter 4.pdf500.39 kBAdobe PDFView/Open
10_chapter 5.pdf341.85 kBAdobe PDFView/Open
11_chapter 6.pdf302.03 kBAdobe PDFView/Open
12_chapter 7.pdf64.71 kBAdobe PDFView/Open
13_appendix.pdf241.19 kBAdobe PDFView/Open
14_references.pdf106.46 kBAdobe PDFView/Open
15_publications.pdf59.58 kBAdobe PDFView/Open
16_vitae.pdf50.49 kBAdobe PDFView/Open

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