Ethylene cracking process is the core production process in ethylene industry

and is paid more attention to reduce high energy consumption. Because of the interdependent relationships between multi-flow allocation and multi-parameter setting in cracking process

it is difficult to find the overall energy efficiency scheduling for the purpose of saving energy. The traditional scheduling solutions with optimal economic benefit are not applicable for energy efficiency scheduling issue due to the neglecting of recycle and lost energy

as well as critical operation parameters as coil outlet pressure (COP) and dilution ratio. In addition

the scheduling solutions mostly regard each cracking furnace as an elementary unit

regardless of the coordinated operation of internal dual radiation chambers (DRC). Therefore

to improve energy utilization and production operation

a novel energy efficiency scheduling solution for ethylene cracking process is proposed in this paper. Specifically

steam heat recycle and exhaust heat loss are considered in cracking process based on 6 types of extreme learning machine (ELM) based cracking models incorporating DRC operation and three operation parameters as coil outlet temperature (COT)

COP

and dilution ratio according to semi-mechanism analysis. Then to provide long-term decision-making basis for energy efficiency scheduling

overall energy efficiency indexes

including overall output per unit net energy input (OONE)

output-input ratio per unit net energy input (ORNE)

exhaust gas heat loss ratio (EGHL)

are designed based on input–output analysis in terms of material and energy flows. Finally

a multi-objective evolutionary algorithm based on decomposition (MOEA/D) is employed to solve the formulated multi-objective mixed-integer nonlinear programming (MOMINLP) model. The validities of the proposed scheduling solution are illustrated through a case study. The scheduling results demonstrate that an optimal balance between multi-flow allocation

multi-parameter setting

and DRC coordinated operation is reached

which achieves 3.37% and 2.63% decreases in net energy input for same product output and conversion ratio

as well as the 1.56% decrease in energy loss ratio.