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Research On Comprehensive Coal Blending Based On Gaussian Process

Posted on:2021-05-08Degree:MasterType:Thesis
Country:ChinaCandidate:D L ZhangFull Text:PDF
GTID:2392330605451253Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of our economy,there is a great demand for energy consumption.China's energy consumption is mainly coal,and most the coal is used for power generation.Due to the coal storage distribution and economic development uncoordinated,coal transport capacity shortage at the same time,the freight price increases,caused many power plants burning coal mixed,the gasification of coal off the boiler design value,and the regional coal quality difference is bigger,most of the coal of coal quality often cannot meet the requirements of the coal-fired power plant.According to the coal quality of the coal,the power coal blending technology can match the coal quality that meets the conditions of high thermal efficiency of the boiler,less slagging,economic power generation and so on,so as to meet the requirements of the power plant.This paper takes Wuhu Power Plant as the background.Aiming at the problem of boiler thermal efficiency and slagging in the power plant,a GPR prediction model is established,which takes the calorific value,volatile matter,moisture,ash and oxygen content of coal as input parameters and the corresponding output parameters as boiler thermal efficiency.A Gaussian process regression?GPR?prediction model was established with Fe2O3?MgO?CaO?TiO2?AL2O3?SiO2?K2O?Na2O as input parameters,and the corresponding output parameters as coal softening temperature.The corresponding mixed coal data was used to verify the established prediction model of softening temperature.Particle swarm optimization algorithm?PSO?was used to find the best parameters of Gaussian process regression.The results show that the model has high accuracy and good generalization ability.This paper puts forward a mathematical model of coal blending which takes the calorific value,volatile matter,sulfur,moisture,ash,ash melting point and boiler thermal efficiency as constraints and coal blending price as objective function.Based on the mathematical model of coal blending,the software system of coal blending for power plant boiler is developed with C + +,which improves the economic benefits of power plant.
Keywords/Search Tags:Boiler, Particle swarm optimization algorithm, Gaussian process regression, Coal blending, Coal blending software system
PDF Full Text Request
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