Cyclic scheduling for best profitability of industrial cracking furnace system

Abstract

An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules, mostly ethylene and propylene. The continuous operational performance of cracking furnaces gradually decays because of coke formation in the reaction coils, which requires each furnace to be periodically shut down for decoking. Given multiple feeds and different cracking furnaces as well as various product prices and manufacturing costs, the operational scheduling for the entire furnace system should be optimized to achieve the best economic performance. In this paper, a new MINLP (mixed-integer nonlinear programming) model has been developed to obtain cyclic scheduling strategies for cracking furnace systems. Compared to previous studies, the new model has more capabilities to address operation profitability of multiple feeds cracked in multiple furnaces. Meanwhile, it inherently avoids unpractical conditions such as simultaneous shutdown of multiple furnaces. Case studies demonstrate the efficacy of the developed methodology.