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Statistical modeling of an integrated boiler for coal fired thermal power plant

机译:燃煤火力发电厂综合锅炉的统计模型

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摘要

The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.
机译:燃煤热电厂数量众多,在世界电力生产中起着重要作用。现有的许多发电厂都基于亚临界技术,该技术可以发电,效率约为33%。但是,新型工厂是建立在超临界或超超临界技术之上的,其效率可高达50%。这项工作的主要目的是提高现有的亚临界发电厂的效率,以弥补不断增长的需求。为了达到该目的,首先对诸如节能器,汽包和过热器之类的锅炉单元进行统计建模。使用诸如R 2 分析和ANOVA(方差分析)之类的分析方法来测试所开发模型的有效性。本文分析了过程变量(温度)对不同操纵变量的依赖性。该模型的验证与错误分析一起提供。执行DOE(实验设计)支持的响应面方法(RSM)以优化操作参数。单个模型与集成模型一起用于研究和设计燃煤热电厂的预测控制。

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