Energy Efficiency Estimation Based on Data Fusion Strategy: Case Study of Ethylene Product Industry

Abstract

Data fusion is an emerging technology to fuse data from multiple data or information of the environment through measurement and detection to make a more accurate and reliable estimation or decision. In this Article, energy consumption data are collected from ethylene plants with the high temperature steam cracking process technology. An integrated framework of the energy efficiency estimation is proposed on the basis of data fusion strategy. A Hierarchical Variable Variance Fusion (HVVF) algorithm and a Fuzzy Analytic Hierarchy Process (FAHP) method are proposed to estimate energy efficiencies of ethylene equipments. For different equipment scales with the same process technology, the HVVF algorithm is used to estimate energy efficiency ranks among different equipments. For different technologies based on HVVF results, the FAHP method based on the approximate fuzzy eigenvector is used to get energy efficiency indices (EEI) of total ethylene industries. The comparisons are used to assess energy utilization states of different equipments and technologies. It is helpful to decision-makers to identify quantitative energy consumptions and major influence factors to improve energy-saving chances. Furthermore, the proposed strategy can be used to evaluate energy efficiencies in other process units too.