Abstract:

Currently the evaluation of energy consumption of ethylene equipments does not consider the difference of raw materials, process technology and equipment size among ethylene units, and the statistical method is not uniform, so energy consumption indices are not unfair for different ethylene equipments.This paper proposes hierarchical linear optimal fusion algorithm to extract energy indices according to technologies, scales and data distribution of energy consumption including fuel, power, steam and water.The proposed algorithm has no strict limitation for the length and distribution of data, and can remove abnormal consumption data.Quality of data fusion can be ensured by optimal weights which are calculated by covariance.The validity of algorithm has been verified by actual application, which is obtained monthly and annual energy consumption indices from both various type plants and the ethylene industry.Such indices are helpful for decision-maker to identify the quantitative energy consumption targets and major factors, and the proposed method can also be used to other process units for evaluating energy consumption.