Improving steam network performance in Shiraz Oil Refining Company

Master thesis

Trend of energy systems

Optimization of steam network in Shiraz oil refining company

Costs of providing power and power required for operational processes take a significant part of the financial resources and

costs of every industrial complex, and continuous supply of required energy is always one of the main concerns of designers and managers. It is industries. The waste of a significant part of the energy consumed by industries and the resulting environmental problems place the importance of optimizing energy consumption (as one of the main components of the country's sustainable development) in a very high position. Energy management is an activity aimed at reducing energy costs per unit of product production, and its main goals can be summarized as follows: 1-Reducing the costs of energy carriers and increasing the company's profitability in this way.

3-Reduction of repair and maintenance costs

4-Reduction of environmental pollutants

In this thesis, an effort is made to create a suitable platform for energy management in Shiraz Oil Refining Company and guide the thoughts and organizational behavior of personnel in this direction.

Shiraz Oil Refining Company, located at km 22 of the Shiraz-Takht Jamshid highway, is considered one of the important industrial units in the south of the country. The design and construction of this refinery belongs to the technology of the 1950s, and therefore the necessity of using new technologies to improve operational processes and optimal use of resources and facilities in the refinery is clearly seen. Steam, as the main carrier of energy used in the processes of this refinery, while driving the turbine generators that generate electricity, also provides the driving force for important machines. Optimizing steam consumption (and electricity consumption) using university learning, more than two decades of my work experience and computer modeling with the view of maximum profitability by selling energy carriers (more electricity) is the main point of view governing this thesis.

First, by reviewing practical sources, gather the previous works and then proceed to collect general information on energy carrier consumption and identify their production sources in the company and model the existing network. In this regard, with the help of information received from various sources, including the financial management of the company, especially the general accounting and industrial accounting units, the objective function has been defined and different operating scenarios have been examined using the built model and the results have been compared. Determining the total cost of the steam production and distribution network in different operational scenarios and taking action to reduce the total cost of steam based on the optimal conditions determined in each working condition and identifying valid parameters in the process of steam production and the work produced in the turbines and using them in order to reduce operating costs. And as a result, the economic profit of Shiraz Oil Refining Company is one of the main results of this project.

Optimization operation with the help of the proposed model shows the fact that, considering the investment costs in steam production and the price of buying and selling electricity (by the Iran Energy Supply Company) as well as the sale price of natural gas, currently the option of generating electricity using steam has no profit and economic justification, and the lowest operating cost of the steam production and distribution system in Shiraz Oil Refining Company is when steam loss and steam discharge to The atmosphere is completely removed and electricity production turbines are used to reduce the steam pressure from one level to a lower level, and the remaining electricity needed for the refining operation is purchased from the national electricity network. By doing these measures, the costs of the steam production and distribution system can be reduced from nearly four hundred and forty billion rials per year to six hundred and seventy million rials, i.e. 99.8%.

The impact of removing wastes and discharging into the atmosphere (second scenario) in reducing the costs of ancillary services in the Shiraz Oil Refining Company is close to two hundred and fifty billion rials per year and to use the additional capacity of turbogenerators and steam boilers (the third scenario) the impact of increasing costs to the amount of thirty eight billion rials per year and to remove turbo generators from the production and purchase circuit Electricity from the national grid (fourth scenario) is estimated to reduce operational costs by four billion five hundred and eighty million rials. The most effective in reducing the operating costs of the ancillary services system is the fifth suggestion, which is to eliminate losses and discharge to the atmosphere and replace the electricity generation turbine instead of the steam pressure reduction stations. The reduction of the operational costs of implementing this proposal compared to the current state of operation is estimated at four hundred and thirty-seven billion Rials per year. 

In 1977, Nishio for the first time raised the issue of choosing the optimal pressure levels of the main steam line and presented a direct search method that was coupled with the simultaneous solution of equations [1]. Then Nishio and Johnson[1] proposed a thermodynamic method, in this work Nishio and his colleagues also used an LP model in order to optimally select the equipment used in steam production and distribution systems and predict the cost of minimum ancillary services. (Utilities) used. This method tried to choose equipment for auxiliary service that minimizes the energy loss available for each unit and optimally determine the drivers used in the process, including turbines and electric motors, using linear programming (LP). Thermodynamic analysis of available energy was based on a set of innovative rules that were used to determine the plant structure and design conditions. Although the minimization of available energy loss leads to the maximization of plant efficiency, the investment costs related to ancillary service units were not considered in this section. Also, one of the weaknesses of this method was that some of the main decisions to determine the shape of the factory are based on heuristic rules [2] and as a result, it may miss a number of alternatives that include the optimal solution. Another important limitation was that the investment costs with the capacities were considered absolutely linear, and therefore the increase in production in order to reduce the overhead cost [3] was not included in this model [2].

Petrolas and Reklatis[4] proposed an analysis method for the ancillary services system based on the analysis of two sub-branches that are coupled together. The first subsection determined the number of steam mains plus the pressure in each main and was modeled as a dynamic program [5] that minimized the loss of available energies. The second sub-section included driver selection and was formulated as an LP with the aim of minimizing input energies (steam and electricity). In other words, they used a dynamic programming method to optimize the steam main line conditions as continuous variables and an LP method to determine the optimal location of the drivers with the general objective of minimizing the real work waste. In this method, it was stated that if there is a need to have a steam boiler, this steam boiler should produce steam at the highest pressure level, because the coupling of the two branches affected the efficiency of the drivers and the thermal load of the steam boiler. But in the optimization problem, there is a need to estimate the conditions of very high pressure steam (VHPS), the temperature of each steam surface, the heat load of the boiler, the auxiliary cooling service, and the central work produced by the steam turbine network in each region, which is not included in this method. Another limitation of this method was that it did not take into account the investment costs of the factory units and did not consider the possibility of using gas turbine drivers. Also, the LP formulation may not be suitable for the driver selection problem in some cases, for example, heat turbines with multiple inputs or two different drivers (steam turbine and electric motor) may be selected, but this model would give the same work and power requirements as before [3].