Paper No. 256 Optimization of Naphtha Feedstock Blending for - PowerPoint PPT Presentation

Paper No. 256 Optimization of Naphtha Feedstock Blending for Integrated Olefins-Aromatics Plant Production Scheduling Y. Ota, K. Namatame, H. Hamataka, K. Nakagawa and H. Abe Mitsubishi Chemical Corporation A. Cervantes, I. B. Tjoa and F. Valli MC Research & Innovation Center

2 Hierarchy of Decisions in Business Activities � Optimization efforts for improving profitability Benefits Efforts Vs Future Strategic Planning Production Planning Time Production Scheduling Operation Now Here we focus on production scheduling

3 Issues in Ethylene Plant Production Scheduling Issues in Ethylene Plant Production Scheduling Daily Interaction between sections Vessel scheduling Blending Ethylene Plant Inventories ETY Demands PPY ETA BBP GSL How to allocate feedstock? Model requirement: - Accurate (rigorous) daily production model - Mixed Integer Nonlinear model Main Focus: Find optimal feedstock allocation for daily production scheduling, for meeting production demands

4 Case Study: Real Production Scheduling for 2 Ethylene and 2 Benzene Plants Production target? Byproducts No.1 Ethylene No.1 Ethylene Ethylene Light Naphtha Ethylene Plant Plant No.1 Benzene Plant No.1 Benzene Plant Gasoline No.2 Ethylene No.2 Ethylene No.2 Benzene No.2 Benzene Plant Plant Plant Plant Gasoline Benzene Heavy Naphtha Propylene Propylene Byproducts Utilities How to meet Production Objective? Optimal composition?

5 Modeling and Solution Approach � Modeling approach • Unit operation model building capability • Equation based modeling approach » MINLP model • Modeling platform: GAMS modeling language • Model size » Continuous variables ~ 60k » Binary variables ~ 1k � Solution approach » Process knowledge based decomposition strategy » Use standard solvers: – MILP: OSL – NLP: ConOpt

6 Naphtha Properties Composition of Charging Tanks 0.72 0.70 0.68 SG 0.66 0.64 0.62 0.60 0 5 10 15 20 25 30 Periods MAN_T1 MAN_T2 OPT_T1 OPT_T2

7 Naphtha Inventories � Fixed ETY & PPY Demands � Max ETY & PPY Productions % of total Inventory % of total Inventory 80 80 60 60 40 40 20 20 0 0 Base Opt Base Opt Light Medium Heavy Light Medium Heavy

8 Application Manager