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Energy structure analysis and energy saving of complex chemical industries: A novel fuzzy interpretative structural model

机译:复杂化学工业的能结构分析与节能:一种新型模糊解释结构模型

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摘要

Chemical production plays a key effect in energy saving and the sustainable development. However, the uncertain data has a direct impact on the production and the energy efficiency of complex chemical industries. Therefore, in order to analyze the energy structure and improve the energy efficiency of complex chemical industries, this paper proposes a novel interpretative structural model (ISM) integrated the fuzzy theory (FISM). The production data are divided into the upper limit value, the lower limit value and the most probable value based on the data fuzzification. And then energy structures and energy saving potentials in different production configurations are obtained by using the FISM. Finally, the proposed method is applied to analyze the energy structure and obtain energy saving potentials of the ethylene production process in complex chemical industries. The experimental results show that the key impact factors of influencing the ethylene production in different production configurations can be obtained to improve the energy efficiency. Moreover, compared with the benchmarking of the best production configuration, the raw materials can be saved about 10-30% and the carbon emissions can be reduced about 0.3-0.45 Ton when producing one Ton ethylene.
机译:化学生产在节能和可持续发展中起着关键影响。然而,不确定的数据对复杂化学工业的生产和能效具有直接影响。因此,为了分析能量结构和提高复杂化学工业的能源效率,本文提出了一种新颖的解释结构模型(ISM)综合模糊理论(塑料)。基于数据模糊化,生产数据分为上限值,下限值和最可能值。然后通过使用塑料获得不同生产配置中的能量结构和节能电位。最后,应用了该方法以分析能量结构,并在复杂化学工业中获得乙烯生产过程的节能电位。实验结果表明,可以获得影响不同生产配置中乙烯生产的关键影响因素以提高能量效率。此外,与最佳生产配置的基准相比,原料可节省约10-30%,在生产一吨乙烯时,碳排放可降低约0.3-0.45吨。

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