(417c) Optimal Design of Pipeline System for Flare Minimization in Multiple Chemical Plants | AIChE

(417c) Optimal Design of Pipeline System for Flare Minimization in Multiple Chemical Plants


Cai, T., Lamar University
Zhenlei, W., East China University of Science and Technology
Xu, Q., Lamar University
Flare minimization (FM) in large-scale industry takes increasingly engineers’ concerns nowadays. It is a win-win practice for not only environmental sustainability but also industrial profitability. A lot of researches have already focused on FM problems with many FM strategies for a single plant. However, there are few FM works focusing on multiple plants’ FM issues. Material exchanges (ME) among plants provide a new degree of freedom for material savings and flare reductions. For example, a start-up plant can borrow materials from another normal-working plant to help the plant compressor start-up, or a normal-working plant can receive off-spec materials from another plant undergoing the shutdown operation to help recover potential products. Such ME operations could be designed and scheduled based on plants’ operational flexibilities. Certainly, different plants may have different operating statuses when interplant ME are considered. The design of a pipeline system that satisfies different plant operating statuses is a must.

This work developed a general methodology for the optimal pipeline system design for FMs via interplant ME, which can be used for FMs under planed turnaround and emergency turnaround operations in multiple chemical plants. The operational scheduling together with the pipeline system design fully take interplant ME advantages while all possible plant operating scenarios have been considered. The methodology will provide a conceptual pipeline system design with the minimum capital cost, containing the information of detailed pipeline distributions and connections; control valve placements, and valve switching strategies under different interplant ME strategies for FMs. The efficacy of the developed method will be demonstrated by two case studies.