Dual-radiation-chamber coordinated overall energy efficiency scheduling solution for ethylene cracking process regarding multi-parameter setting and multi-flow allocation

Abstract

This work proposes a novel energy efficiency scheduling solution for cracking process, which achieves energy efficiency improvement comprehensively and scientifically. The proposed solution reflects several significant features of process operation, for example, the impact of COT, COP, and dilution ratio on product output and energy utilization, the influence of SHS recycle energy and exhaust gas energy loss on fuel and DS consumption. Also, DRC independent parameter setting and asynchronous batch processing have also been taken into account with scheduling of cracking furnace groups. 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.