Modeling tool for planning the operation of refineries

Abstract

A modeling tool for determining the operation of a production facility. A variety of different activities can be modeled by the present invention, including (a) feed material selection, including quantity and timing, (b) product sales, including quantity and timing, (c) process operations, including process conditions and timing, (d) blending operations, including process conditions and timing, and/or (e) inventory management. The modeling tool may represent time using continuous-time, discrete-time, asynchronous time periods, synchronous time periods, and combinations of these various approaches.

We claim: 
     
         1 . A method for operating a production facility, wherein the production facility includes at least one production entity, comprising:
 (a) programming a computer to construct a mathematical model of the production facility, wherein the mathematical model includes a representation of each of the at least one production entity;   wherein each of the at least one production entity is represented by a submodel containing a set of equations that model the behavior of the production entity, the number of equations in the submodel being related to the number of operational time intervals for the production entity;   (b) solving the mathematical model to obtain solution results for each of the at least one production entity;   (c) using the solution results to determine an operational plan for the production facility; and   (d) operating the production facility according to the operational plan.   
     
     
         2 . The method of  claim 1 , wherein the submodel for each production entity includes decision variables relating to the operation of such production entity. 
     
     
         3 . The method of  claim 1 , wherein production facility includes at least a first production entity and a second production entity, wherein the first production entity is represented by a first submodel containing a set of equations that model the behavior of the first production entity, wherein the number of equations in the first submodel being related to the number of operational time intervals for the first production entity, and the second production entity is represented by a second submodel containing a set of equations that model the behavior of the second production entity. 
     
     
         4 . The method of  claim 3 , wherein the number of operational time intervals for the first production entity, the second production entity, or both, are given as input. 
     
     
         5 . The method of  claim 3 , wherein the first production entity is operatively connected to the second production entity. 
     
     
         6 . The method of  claim 3 , wherein the production facility includes a third production entity, wherein the third production entity is represented by a third submodel containing a set of equations that model the behavior of the third production entity, wherein the number of equations in the third submodel being related to the number of operational time intervals for the first production entity, the second production entity and the third production entity. 
     
     
         7 . The method according to  claim 6 , wherein the number of equations in the second submodel being related to the number of operational time intervals for the third production entity 
     
     
         8 . The method of  claim 6 , wherein the number of operational time intervals for the first production entity, the second production entity, or both, are given as input. 
     
     
         9 . The method of  claim 6 , wherein the mathematical model further comprises variables or mathematical relationships that represent the relationships between the operational time intervals of the third production entity with the operational time intervals of the first production entity and the second production entity. 
     
     
         10 . The method of  claim 6 , further comprising calculating the number of operational time intervals for the third production entity using the number of operational time intervals for the first production entity and the number of operational time intervals for the second production entity. 
     
     
         11 . The method of  claim 1 , wherein the mathematical model further includes decision variables relating to the duration of each of the operational time intervals for each of the at least one production entity. 
     
     
         12 . The method of  claim 1 , wherein the mathematical model comprises an objective function for a performance metric of the production facility;
 wherein the objective function comprises terms from each submodel for each of the at least one production entity; and   wherein the mathematical model is solved for maximizing or minimizing the performance metric.   
     
     
         13 . The method of  claim 12 , wherein the mathematical model comprises:
 parameters relating to cost of feed materials;   parameters relating to cost of holding inventory in the tank entity; decision variables relating to selection of feed materials;   
     
     
         14 . The method of  claim 13 , wherein the mathematical model further comprises:
 parameters relating to the cost of transportation options; and   decision variables relating to transportation scheduling.   
     
     
         15 . The method of  claim 1 , wherein the mathematical model further includes decision variables relating to the transportation or purchase of feed material to at least one of the at least one production entity. 
     
     
         16 . The method of  claim 1 , wherein the mathematical model further includes decision variables relating the transportation or sale of products from at least one of the at least one production entity. 
     
     
         17 . The method of  claim 1 , wherein the mathematical model further includes decision ion variables relating to the transportation, sale, or purchase of a feed material that is an intermediate material for at least one of the at least one production entity. 
     
     
         18 . The method of  claim 1 , wherein the mathematical model further includes decision variables relating to a duration of each operational time interval. 
     
     
         19 . The method of  claim 18 , wherein the duration is a known quantity. 
     
     
         20 . The method of  claim 6 , wherein the mathematical model further includes decision variables relating to the transportation or purchase of feed material to at least one of at least one production entity. 
     
     
         21 . The method of  claim 6 , wherein the mathematical model further includes decision variables relating the transportation or sale of products from at least one of the at least one production entity. 
     
     
         22 . The method of  claim 6 , wherein the mathematical model further includes decision variables relating to the transportation, sale, or purchase of a feed material that is an intermediate material for at least one of the at least one production entity. 
     
     
         23 . The method of  claim 6 , wherein the mathematical model further includes decision variables relating to a duration of each operational time interval. 
     
     
         24 . The method of  claim 23 , wherein the duration is a known quantity.