基于改进DEA交叉模型的工业过程节能与管理

Zhiqiang Geng, Ju Bai, Qunxiong Zhu, Yuan Xu, Yangming Han
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引用次数: 1

摘要

数据包络分析(DEA)已广泛应用于企业厂房的节能管理。然而,传统的DEA模型在分析决策单元的有效性时,超过1/3的决策单元的效率值为1,因此传统的DEA模型无法区分决策单元的优劣。而DEA交叉模型(DEACM)虽然能够区分有效dmu的优劣,但无法获得无效dmu的改进方向。因此,本文提出了一种基于改进DEACM的节能管理方法,该方法可以利用更高的效率区分来识别dmu的效率状态。同时,通过改进后的DEACM的自评价,可以找到失效DMU的改进方向。最后,将改进的DEACM应用于工业过程中PTA溶剂系统的能源配置的节约和管理。实验结果表明,该方法的实用性和有效性得到了验证,效率判别效果良好。此外,所提出的模型可以为PTA生产的节能量化目标找到方向,从而提高PTA生产的能效。
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Energy Saving and Management of the Industrial Process Based on An Improved DEA Cross-model
Data envelopment analysis (DEA) has been commonly used in the energy saving of enterprise plants. Nevertheless, when the traditional DEA model analyzes the effectiveness of decision-making units (DMUs), over 1/3 of the DMUs’ efficiency values are 1, so the traditional DEA model cannot distinguish the cons and pros of the DMUs. And although the DEA cross-model(DEACM) is able to differentiate the cons as well as pros of the effective DMUs, it can’t obtain the improvement direction of the ineffective DMUs. Therefore, an energy saving and management method based on an improved DEACM, which can use the higher efficiency distinction to identify the efficiency state of the DMUs, is proposed in this paper. Meanwhile, the improvement direction of the ineffective DMU can be found by the self-evaluation of the improved DEACM. Finally, the improved DEACM is utilized to save and manage the energy configuration of the PTA solvent system in the industrial process. The experimental results reveal that the practicality and effectiveness of the proposed method are verified, and in addition, the efficiency discrimination is well. Moreover, the proposed model can find the direction of the quantitative targets of energy saving to improve the energy efficiency of PTA production.
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