Application of Linear Programming Methods for Refining Operations Planning and Management

he main objective of this research is to enhance the quality of processing and refinery production planning, through savings in energy and materials consumption and to improve refining profitability through the minimization of refinery operating cost. The main tool used in this research is linear programming methods, which deal with allocation of resources and seeking their optimization. In the context of an oil refinery, Linear Programming mathematical model is used as a tool for simulating all refinery units yields, unit capacities, utility consumption as well as product blending operations. Using Linear Programming, each equation is subject to a number of constraints, usually the number of unknowns is more than that of constraints relating to them; a large number of solutions might satisfy different parameters. The optimal solution is chosen from among those which satisfy different parameters and, at the same time, maximize refinery profit or minimize operating cost. To aid the search for an optimum solution, LP is driven by a row in the matrix containing cost and revenue. Usually, several manual calculations and tedious trail and error methods are used to conduct optimization studies, in this research an attempt was made to use LP and computerization for a faster and simple reach of optimal solution. The refinery LP model, in fact, is simply a set of data tables in the form of spreadsheets that are converted into a matrix using special programming languages. As many solutions to the problem are possible, the criteria for choosing an optimum solution are that which, a part from satisfying all equations, give a maximum profit to the refinery. The optimum solution of a refinery LP model yields the following: o A complete unit yields material balance of all refinery units (by volume or weight). o An optimum unit capacity o An optimum feedstock for processing or blending o Utilities consumption of fuel, electricity, steam, cooling water, etc... o Chemical and catalyst consumption for processing units. 8 o A Blend composition of different products and the properties of the resulting blended products. Using the above methods and tools, a brief summary could be obtained including the cost of crude, other feedstock, utilities, chemicals, and catalyst consumed and the prices of blended finished product. The associated program with LP model “the report writer” retrieves data from the unscrambled solution and rearranges them in a more user-friendly- format using a special programming language. Taking the above into consideration, the matrix solution report is presented as follows: 1. A summary report, showing an overall material balance, starting with crude and other inputs; the overall production plan; and the refinery profits. 2. The material balance of different refinery units. 3. A product blending report, showing the blend composition and the properties of different blended product grades. In conclusion, it is proved that one can attain an economically viable solution for refinery operations by selecting an optimal quality of the crude, the refining operations and the proper planning and scheduling for its different operation units. The Linear Programming model of a refinery leads to a reduced operation & production costs and eventually a profitable system