Industrial Engineering MS Thesis Defense by Elif Mete

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KOÇ UNIVERSITY

GRADUATE SCHOOL OF SCIENCES & ENGINEERING

INDUSTRIAL ENGINEERING

MS THESIS DEFENSE BY ELIF METE

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Title: ENERGY NETWORK OPTIMIZATION OF AN OIL REFINERY

Speaker: Elif Mete

Time: September 15, 2017 09:30

Place: ENG-208

Koç University

Rumeli Feneri Yolu

Sariyer, Istanbul

Thesis Committee Members:

Prof. Dr. Metin Türkay ( Advisor, Koç University)

Asst Prof. Dr. Sibel Salman ( Koç University)

Asst Prof. Dr. Burak Alakent (Boğaziçi University)

Abstract:

Energy consumption is a critical factor in refinery operations, having a significant impact on production costs. The effective management of the energy system in the refinery can improve the economic performance significantly. Energy demand in refineries does not stay constant due to change in crude oil properties, operation conditions of process units and cost of fuels. Tupras Izmit Refinery operates a complex utility system to satisfy its energy demand in the form of steam and electricity.  The design of the utility plants allows multiple operational configurations to secure the continuity and flexibility of refinery processes in different operating conditions.  The main objective of the work is developing a decision support system to manage the complex energy network of the refinery by determining the optimum operational combinations of the equipment for achieving a global minimum in terms of energy costs. In the scope of the work, first of all, the steam and power production equipment in the refinery are analyzed, thermodynamically to determine the variables which have an impact on the equipment efficiency. The determined variables are evaluated by regression analysis and the efficiency models of the equipment are developed.  In the second part of the work, the optimization problem is formulated as mixed integer linear programming model. The model contains all operational constraints, efficiency models, mass balances, operational status of the equipment and demand satisfaction constraints of the refinery. The developed approach is analyzed and tested with a real case of the refinery.  MILP model scenarios are solved by using GAMS CPLEX solver. In scenario analysis, the economic impact of optimization is evaluated by comparing the optimal solutions with online refinery operations. As a result, up to 3.5 % cost reduction is achieved without making an investment.