盘南电厂石灰石—石膏湿法烟气脱硫系统性能分析与运行优化
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摘要
我国是以煤炭为主要能源的国家,煤炭一直占我国能源的生产和消耗的70%以上。随着经济的快速发展,煤炭消费不断增长。由于煤炭的燃烧而造成的SO_2对大气的污染非常严重。大气中SO_2浓度过高及酸雨的形成已严重影响了人体健康,破坏了生态系统,对工农业生产造成极大损失。据估计,仅两广、川、贵地区因酸雨造成的年经济损失就达160亿元以上。SO_2污染排放问题己成为制约我国国民经济发展的一个重要因素,对SO_2排放的控制与治理已刻不容缓。
     电力和煤炭是造成酸雨和SO_2污染的主要行业。火电厂和各种各样的工业锅炉是排放SO_2造成酸雨的主要污染源。目前火电厂SO_2排放量约占全国排放量的2/3。因此,火电厂脱硫,减少SO_2的排放是今后的重点任务。湿法烟气脱硫作为一种相对较成熟、脱硫效率较高的脱硫技术,得到了广泛的应用。由于石灰石-石膏湿法烟气脱硫系统中运行参数相对复杂,不同工况与参数直接影响脱硫效率与成本。
     本文通过对盘南电厂600MW湿法烟气脱硫进行研究,从理论和试验两方面分析了影响脱硫效率的因素,得到了系统运行参数吸收液PH值、温度、液气比等因素与脱硫效率的单值变化关系。通过试验分析得到循环吸收浆液pH值应控制在5.2-5.7较为合理;降低吸收液入口温度对脱硫效率的提高有明显的效果;在一定范围内增大液气比有利于提高脱硫效率。在对盘南电厂石灰石-石膏烟气脱硫系统性能测试和优化运行的基础上,系统的脱硫效率可达95%以上。
     在上述实验的基础上,建立了脱硫成本与运行调整参数的神经网络模型,应用该模型对盘南电厂600MW燃煤电站锅炉的石灰石—石膏湿法烟气脱硫系统进行优化控制研究,优化数值解表明:该模型可随时掌握和预测不同工况下的脱硫成本;且该模型和算法很好地解决了不同运行工况下的各参数的基准值问题;通过遗传算法对脱硫成本模型寻优,可获得出口烟气SO_2浓度达标状况下最佳的运行调整方式,以降低系统脱硫成本,指导运行人员优化运行,提高电厂经济性。
China is a country mainly energized by coal and coal maintains over 70 percent of our national energy production and consumption. Coal consumption continuously increases with rapid economy development. And the subsequent emission of SO_2 heavily polluted the atmosphere. The high density of SO_2 and acid-rain are greatly affecting the health of human beings, destroying the ecosystem and damaging the industrial and agricultural production. It was estimated that the annual loses caused by acid rains in Guangdong, Guangxi, Sichuan and Guizhou were exceeded RMB16 billion. The control and settlement of SO_2 emission become critical issues for our economy development.
     Power generation and coal mining are the major reasons for acid rains and SO_2 emission. Coal-fired power plants and all kinds of industrial boilers are the major origins for SO_2 emission and acid rains. By now, the emission from coal-fired power plants accounts for about two-third of national SO_2 emission. Therefore, desulphurization of coal-fired power plants, reducing the SO_2 emission is the key issue in the future.
     Lime/Limestone wet flue gas desulfurization (WFGD), as a mature and pretty high desulfurization efficiency technology, is widely applied in coal-fired power plants around the world. Because limestone - gypsum flue gas desulfurization system operating parameters is relatively complex, different conditions and parameters directly affect the desulfurization efficiency and cost.
     The thesis takes an academic and practical research on the effects of absorbefacient PH value, temperature, liquid-to-gas ratio etc. to the desulfurization efficiency and concludes their variety relationship. It is known from the experiment data that the PH value of absorbefacient should be controlled within 5.2 to 5.7. Lower the inlet temperature of absorbefacient may significantly increases the desulphurization efficiency. Based on the operation experiments and performance tests of WFGD system in Pannan Power Plant, the systemic desulphurization efficiency is calculated as 95 percent or above.
     Based on the above experimental, By establishing the Nerve Network Response Model on desulfurization costs and operational adjusted parameter, the thesis investigates control optimization of the WFGD system in Pannan Power Plant. The optimized solution indicates that the model can estimate and command the desulphurization costs, as well as solve the parameter benchmark in different operation conditions. With genetic arithmetic, and satisfying with outlet SO_2 emission requirements, it achieves the adjusted method with lowest operation costs which provides a theoretic basis for optimization of desulfurization system operation as well as economic improvement.
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