Energy consumption analysis and evaluation of petrochemical industries using an improved fuzzy analytic hierarchy process approach

Abstract

The petrochemical data has characteristics of multi-dimensional, uncertainty and noisy. So it is difficult to accurately evaluate the energy consumption of the petrochemical plants based on the production data. In order to solve this problem, an improved fuzzy analytic hierarchy process (FAHP) algorithm based on data-driven with data fuzzification is proposed. The proposed algorithm can trade-off the subjective marks of experts’ opinions. Meanwhile, it is more efficient and accurate than other methods by using the airplane purchase data. Moreover, Monthly energy consumption data were disposed by the Gaussian membership function to obtain the minimum, median and maximum values of the multi-criteria evaluation matrix. On the basis of the multi-criteria fuzzy data, energy consumption evaluation indices and comparison of different petrochemical plants can be obtained by the improved FAHP based on the triangle fuzzy number to find the best production configurations. Finally, the experimental results have shown effectiveness and practicability of the improved FAHP method. Meanwhile, it is able to point out the opportunities for improving production and energy efficiency of ethylene plants in petrochemical industries.