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Forecasting CO2 emissions due to gasifier degradation by time-series analysis

机译:通过时序分析预测气化器降解引起的二氧化碳排放

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There is a growing interest in the use of gasification to contribute to the energy share, as a more efficient alternative to fossil fuels combustion, especially with coal and biomass in large power plants. In order to unveil the effect of time in the degradation of the gasifier operation and the influence that operating conditions have over reactor performance, the evolution of controlled and observed variables should be studied. Two statistical techniques are used in the present work: (i) multiple regression analysis, which provides information about the relationship between several predictor variables and a dependent variable, and (ii) time series analysis, which may allow identifying the nature of the phenomenon associated with reactor degradation as a function of time. The final goal consists of evaluating and predicting the reactor natural instability by monitoring CO2 emissions. Results demonstrate the capability of forecasting techniques to predict reactor degradation with time. Thus, the tendencies of the variables and parameters in the gasifier may be better determined to avoid faulty operation.
机译:对于使用气化来促进能源份额越来越感兴趣,作为化石燃料燃烧的更有效的替代品,特别是在大型发电厂中的煤和生物量。为了推出在气化器操作的降解中的时间效果和操作条件对反应堆性能的影响,应研究受控和观察变量的演变。在本作工作中使用了两个统计技术:(i)多元回归分析,其提供有关若干预测变量与从属变量之间的关系的信息,以及(ii)时间序列分析,其可以允许识别相关现象的性质随着时间的函数,反应器降解。最终目标包括通过监测二氧化碳排放来评估和预测反应堆天然不稳定性。结果证明预测技术预测反应堆劣化的能力。因此,可以更好地确定气化器中变量和参数的趋势以避免故障操作。

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