Tupras Izmit Refinery

İzmit, Turkey

Tupras Izmit Refinery

İzmit, Turkey

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Sildir H.,Koç University | Arkun Y.,Koç University | Cakal B.,Tupras Izmit Refinery | Gokce D.,Tupras Izmit Refinery | Kuzu E.,Tupras Izmit Refinery
Journal of Process Control | Year: 2013

Hydrocracking is a crucial refinery process in which heavy hydrocarbons are converted to more valuable, low-molecular weight products. Hydrocracking plants operate with large throughputs and varying feedstocks. In addition the product specifications change due to varying economic and market conditions. In such a dynamic operating environment, the potential gains of real-time optimization (RTO) and control are quite high. At the same time, real-time optimization of hydrocracking plants is a challenging task. A complex network of reactions, which are difficult to characterize, takes place in the hydrocracker. The reactor effluent affects the operation of the fractionator downstream and the properties of the final products. In this paper, a lumped first-principles reactor model and an empirical fractionation model are used to predict the product distribution and properties on-line. Both models have been built and validated using industrial data. A cascaded model predictive control (MPC) structure is developed in order to operate both the reactor and fractionation column at maximum profit. In this cascade structure, reactor and fractionation units are controlled by local decentralized MPC controllers whose set-points are manipulated by a supervisory MPC controller. The coordinating action of the supervisory MPC controller accomplishes the transition between different optimum operating conditions and helps to reject disturbances without violating any constraints. Simulations illustrate the applicability of the proposed method on the industrial process. © 2013 Elsevier Ltd. All rights reserved.


Kucuk S.,TUPRAS Izmit Refinery | Fernandez L.F.,Técnicas Reunidas | Bayrak M.,Sakarya University | Yilmaz A.S.,Kahramanmaras Sutcu Imam University
ELECO 2015 - 9th International Conference on Electrical and Electronics Engineering | Year: 2015

A primary goal of an industrial electric power system is to minimize production losses in industrial facilities maintaining the industrial process running after the occurrence of certain supply disturbances. The automatic motor restarting is one of the strategies used in the industrial facilities, especially in Oil and Gas facilities, in order to achieve this goal. Aim of this strategy is to allow that after a voltage dip or disturbance, the medium voltage and low voltage motors will be automatically reenergized within predetermined time and in a certain order when voltage is restored. These abnormal voltage conditions may be caused by cleared short-circuits upstream, generation and public supply voltage outages or a simple automatic transfer system of a selective secondary substation operation. This paper presents the automatic motor restarting scheme applied at a large oil refinery where more than 600 motors are assigned to automatic restarting. Application criteria for motor restarting, power system simulations and physical implementation of this scheme are discussed in this paper. © 2015 Chamber of Electrical Engineers of Turkey.


Sildir H.,Koç University | Arkun Y.,Koç University | Cakal B.,Tupras Izmit Refinery | Gokce D.,Tupras Izmit Refinery | Kuzu E.,Tupras Izmit Refinery
Journal of Process Control | Year: 2012

Hydrocracking is an important refinery process which is carried out in catalytic reactors to convert heavy petroleum fractions into valuable products. Because of the large number of species and complex reactions involved, modeling of hydrocracking is a challenging task. In this paper a dynamic, non-isothermal reactor model has been constructed using the method of continuous lumping which treats the complex reactive mixture as a continuum. In doing so concentrations are characterized in terms of reactivity which is a monotonic function of the true boiling point of the mixture. The material and energy balances are developed in the form of integro-differential equations. The significant modeling parameters are identified and estimated using data from an industrial reactor. Steady-state and dynamic predictions of the model outputs such as reactor temperature, product yields and hydrogen consumption are shown to be in good agreement with plant data. © 2012 Elsevier Ltd.

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