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Study On Integration Of Gas Turbine And Furnace

Posted on:2015-10-29Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y YaoFull Text:PDF
GTID:2272330422982281Subject:Chemical Engineering
Abstract/Summary:PDF Full Text Request
Gas turbine has many advantages: relatively low capital cost, compact structure, highflexibility and reliability, quick starting and loading, lower operating manpower needs andenvironmental friendliness etc. But due to the waste of high temperature and oxygen contentof gas turbine exhaust, its power generation efficiency is limited. So, more and more peopleconcerned about the integration of gas turbine and furnace, which focus on the efficient use ofgas turbine exhaust.Based on the accurate mechanism model and multivariate global optimization algorithm,this paper presents a systematic method of gas turbine and furnace integration research. Itmainly includes the following steps:1) Do the degree of freedom (DOF) analysis for theintegrated system, and get the number of optimal variables;2) Establish the detailedmechanistic model of gas turbine subsystem, furnace sub system and integrated system. Thusprepared the corresponding computer program, which is not only suited to the requirements ofthe system optimization in this paper, but also for the design and accounting of furnacesubsystem and gas turbine subsystem;3) Select optimization variables, objective function andconstraints, calculate the optimal result of integrated system with global random searchalgorithm;4) Uses two indicators to evaluate and analyze the results of the optimal integratedsystem.The proposed method is applied to the case study, which consist of a gas turbine and anatmospheric furnace of a12Mt/a crude oil distillation unit. Its DOF is5. In order to make theselection of gas turbine and the operation scheme of furnace easier to identify, gas turbinecombustion chamber outlet temperature, compressor pressure ratio, flow rate of furnace air,excess air ratio and flow rate of furnace fuel were chosen as the optimization variables.Genetic algorithm (GA) was adopted to optimize the system. And the objective function is tomaximize extra-fuel power generation efficiency, the optimal result is56.4%. Characteristicsanalysis showed that: there is7.37%reduction in heat transfer exergy loss per unit load.
Keywords/Search Tags:gas turbine, integration, multivariable optimization, exergy analysis
PDF Full Text Request
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