(80a) Scheduling and Purchasing Optimization for Olefin Plants with Downstream Constraints

Olefin cracking takes an important role in chemical industry. Efforts are made to develop new technology to increase its production. Multiple cracking furnaces are employed in parallel to convert various hydrocarbon feed stocks to smaller hydrocarbon molecules such as ethylene, propylene, and butadiene. Each furnace is required to be cleaned up periodically because of coke formation in the reaction coils which decays furnace performance. Thus, production scheduling for a furnace system is a complex task, which provides information of feed type, feed flowrate starting and ending time for each batch of each furnace. Due to the large production volume, olefin plants can make hundreds of thousands of profits by optimal scheduling without any investment. The optimal production scheduling can further give direction for raw material purchasing. Currently, most scheduling models focus on maximizing profit without downstream consideration. However, when an ethylene plant is set up, the downstream component separation ability is limited within a certain range. Thus a scheduling and purchasing model should consider not only maximizing its profit but also downstream restrictions. In this paper, a MILP (mixed integer linear programming) model was built for scheduling and purchasing optimization of an olefin plant with consideration of downstream constraints and other constraints, such as non-simultaneous cleaning, recycling ethane relaying cracking. The efficacy of the model is demonstrated by case studies.