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某600MW汽轮机配汽方式优化方法研究 Title:OptimizationMethodsforSteamExtractionModesina600MWSteamTurbineSystem 1.Introduction: Steamturbinesarewidelyusedinpowergenerationsystemsduetotheirhighefficiencyandreliability.Inatypical600MWsteamturbinesystem,steamisextractedatvariousstagesfordifferentpurposes,suchasfeedwaterheating,processsteamproduction,anddistrictheating.Optimalsteamextractionplaysacrucialroleinmaximizingthesystem'soverallperformanceandenergyutilization.Thispaperaimstoexploreoptimizationmethodsforsteamextractionmodesina600MWsteamturbinesystem. 2.Background: Inaconventionalsteamturbinesystem,steamisadmittedintothehigh-pressuresectionandexpandsinmultiplestagesbeforebeingexhaustedtothecondenser.However,inlargepowerplants,itiscommontoextractsteamatdifferentpressuresandtemperaturesforvarioussecondaryuses.Thechallengeliesindeterminingtheoptimalextractionpointsanddischargepressurestoachievethedesiredbalancebetweenpowergenerationandenergyutilization. 3.SteamExtractionModes: Therearedifferentextractionmodesemployedina600MWsteamturbinesystem.Theseincludeconstantpressureextraction,slidingpressureextraction,andsequentialextraction.Theselectionoftheextractionmodedependsonfactorssuchassteamtemperature,pressure,andquantityrequiredforeachsecondaryuse. 4.OptimizationMethods: 4.1MathematicalModeling: Tooptimizethesteamextractionmodes,amathematicalmodelcanbedevelopedtosimulatethesystem'soperationundervariousextractionconfigurations.Themodelshouldconsidervariousconstraints,suchasminimumandmaximumsteamextractionflowrates,allowablepressuredrops,andsafetymargins.Theobjectivefunctioncanbeformulatedtomaximizetheoverallefficiencyorenergyutilizationofthesystem. 4.2GeneticAlgorithm: Geneticalgorithm(GA)isapowerfuloptimizationtechniqueinspiredbytheprocessofnaturalselection.Itcaneffectivelyexplorethesolutionspaceandidentifytheoptimalextractionconfiguration.Byrepresentingdifferentextractionmodesaschromosomesandevaluatingtheirfitnessbasedontheobjectivefunction,GAcaniterativelyevolvethepopulationtoconver