Fuzzy based stochastic algorithms for multi objective reactive power optimization

dc.contributor.guideSomasundaram Pen_US
dc.coverage.spatialMulti objective reactive power optimizationen_US
dc.creator.researcherSilas stephen Den_US
dc.date.accessioned2014-02-28T09:49:58Z
dc.date.available2014-02-28T09:49:58Z
dc.date.awarded30/10/2013en_US
dc.date.completed01/10/2013en_US
dc.date.issued2014-02-28
dc.date.registereden_US
dc.description.abstractThe main objective of this research work is to develop enhanced newlinestochastic search algorithms for solving Multi-Objective Reactive Power newlineOptimization (MORPO) problem. The enhanced stochastic search algorithms newlineare developed from the conventional Evolutionary Programming (EP), Tabu newlineSearch (TS) and Particle Swarm Optimization (PSO) algorithms. The newlineenhancements in these stochastic search algorithms are based on certain newlineaffirmative modifications using fuzzy logic and hence these algorithms are newlineappropriately termed as Fuzzy Mutated Evolutionary Programming (FMEP), newlineFuzzy Guided Tabu Search (FGTS) and Fuzzified Particle Swarm newlineOptimization (FPSO). The modifications made into the conventional EP, TS newlineand PSO algorithms ensure more reliable and faster convergence in obtaining newlinea global optimal solution. The integrity of the proposed algorithms lies in the newlinesignificance of dealing the optimization problems without placing any newlinerestrictions on the structure or type of the function to be optimized. The newlinevarious RPO problems that are solved using the proposed algorithms are newlineMulti-Objective Reactive Power Optimization (MORPO) problem and newlineMORPO with FACTS controllers. newlineThe RPO problem gives the optimal reactive power dispatch for newlinestatic power system loading condition. The objective function of RPO newlineproblem is to minimize the total real power loss in the system with power newlinebalance equality constraints, limits on the control variables namely newlinecontrollable voltage magnitudes, switchable VAR compensators and transformer tap ratios, limits on the dependent variables namely reactive newlinepower generations and load bus voltage magnitudes and limits on MVA line newlineflows. Certain additional objectives like voltage deviation, cost of VAR newlinesources and voltage stability index are considered in the RPO problem leading newlineto the formulation of Multi-Objective Reactive Power Optimization newline(MORPO) problem. newlineen_US
dc.description.noteAppendix p.137-154, References p.155-159.en_US
dc.format.accompanyingmaterialNoneen_US
dc.format.dimensions21 cm.en_US
dc.format.extentxxvii, 162p.en_US
dc.identifier.urihttp://hdl.handle.net/10603/16543
dc.languageEnglishen_US
dc.publisher.institutionFaculty of Electrical and Electronics Engineeringen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.relationp.155-159.en_US
dc.rightsuniversityen_US
dc.source.universityUniversityen_US
dc.subject.keywordElectrical engineeringen_US
dc.subject.keywordEvolutionary Programming (EP)en_US
dc.subject.keywordMulti-Objective Reactive Power Optimization (MORPO)en_US
dc.subject.keywordParticle Swarm Optimization (PSO)en_US
dc.titleFuzzy based stochastic algorithms for multi objective reactive power optimizationen_US
dc.title.alternativeen_US
dc.type.degreePh.D.en_US

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