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dc.coverage.spatialInterconnected power systems using fuzzified particle swarm optimizationen_US
dc.description.abstractThe main objective of this research is to develop an improved stochastic technique namely Fuzzified Particle Swarm Optimization (FPSO) for solving various power system optimization problems. The popularity of Particle Swarm Optimization (PSO) is due to its significant property of dealing with the optimization problems without any restrictions on the structure or type of the function to be optimized and due to the ease of computation. The various problems investigated with the proposed FPSO algorithm include multi-constrained dynamic Economic Dispatch (ED), Emission Constrained Economic Dispatch (ECED), Multi-Area Economic Dispatch (MAED), Optimal Power Flow (OPF) and Security Constrained Optimal Power Flow (SCOPF) with the incorporation of Flexible AC Transmission System (FACTS) controllers. The purpose of Emission Constrained Economic Dispatch (ECED) is to obtain the optimal generation schedule by minimizing the fuel cost and emission level simultaneously, while satisfying load demand and operational constraints. The primary objective of Optimal Power Flow (OPF) is to provide the electric utility with optimal set points of operation with respect to various objectives, such as minimization of the total generation cost, minimization of the total active power losses and maximization of the degree of security. The optimal solutions of multi-constrained dynamic ED, ECED, multi-area OPF and multi-area SCOPF with multiple FACTS controller problems obtained using Evolutionary Programming (EP), Tabu Search (TS) and PSO based algorithms are compared with FPSO. The analysis reveals that the FPSO algorithm has superior (faster) convergence than EP, TS and PSO techniques for multi-constrained dynamic ED, ECED, multi-area OPF and multi-area SCOPF with multiple FACTS controller problems. Therefore the proposed algorithm is relatively simple, efficient, reliable and applicable to other power engineering optimization problems. newlineen_US
dc.format.extentxvii, 142en_US
dc.titleGeneration scheduling of interconnected power systems using fuzzified particle swarm optimizationen_US
dc.creator.researcherJothi Swaroopan N Men_US
dc.subject.keywordPower systems, Fuzzified particle swarm optimization, economic dispatch, emission constrained economic dispatch, multi area economic dispatch, optimal power flow, tabu searchen_US
dc.description.noteAppendices 1 to 5; pp.116-134en_US
dc.contributor.guideSomasundaram, P.en_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Electrical and Electronics Engineeringen_US, June 2011en_US
dc.format.dimensions23.5 cm x 15 cmen_US
Appears in Departments:Faculty of Electrical and Electronics Engineering

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02_certificates.pdf424.92 kBAdobe PDFView/Open
03_abstract.pdf14.92 kBAdobe PDFView/Open
04_acknowledgement.pdf13.62 kBAdobe PDFView/Open
05_contents.pdf41.62 kBAdobe PDFView/Open
06_chapter 1.pdf58.12 kBAdobe PDFView/Open
07_chapter 2.pdf164.54 kBAdobe PDFView/Open
08_chapter 3.pdf98.96 kBAdobe PDFView/Open
09_chapter 4.pdf113.8 kBAdobe PDFView/Open
10_chapter 5.pdf139.31 kBAdobe PDFView/Open
11_chapter 6.pdf17.22 kBAdobe PDFView/Open
12_appendices 1 to 5.pdf137.86 kBAdobe PDFView/Open
13_references.pdf27.25 kBAdobe PDFView/Open
14_publications.pdf15.54 kBAdobe PDFView/Open
15_vitae.pdf11.63 kBAdobe PDFView/Open

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