Plant simulation and optimization software apparatus and method using dual execution models

• US 5,666,297 A
• Filed: 05/13/1994
• Issued: 09/09/1997
• Est. Priority Date: 05/13/1994
• Status: Expired due to Term

• Current Assignee: Aspentech Corporation
• Original Assignee: Aspen Technology Inc (Emerson Electric Company)
• Inventors: Venkataraman, Swaminathan, Mahalec, Vladimir, Piela, Peter C., Joshi, Amol P., Britt, Herbert I.
• Primary Examiner(s): Teska, Kevin J.
• Assistant Examiner(s): Walker, Tyrone V.
• Application Number:
  US08/242,269
• Time in Patent Office: 1,215 Days
• Field of Search: 364/578, 364/492, 364/495, 364/149, 364/150, 364/151, 396/500, 396/920
• US Class Current: 703/18
• CPC Class Codes: G06F 17/12 Simultaneous equations , e.g. systems of linear equations

Abstract

A software system simulates and optimizes a processing plant design. The software system includes a plurality of equipment models for simulating each piece of equipment in the processing plant design. A sequential modular simulation routine executes the equipment models in a first mode to define a first set of values of the operating parameters of the processing plant design. An optimization routine executes the equipment models in a second mode. The optimization routine utilizes the first set of values for the operating parameters from the sequential simulation routine and subsequently determines values of the operating parameters at which the processing plant design is optimized. The equipment models after execution by the sequential simulation routine and optimization routine store the first and second sets of values for the operating parameters in a common plant model file. Hence, the plant model file holds values computed during the sequential simulation routine as well as those computed during the optimization routine.

Claims

1. Apparatus for simulating and optimizing operation of a processing plant, the processing plant including a multiplicity of equipment and a multiplicity of operating parameters for the equipment, the apparatus comprising:

a digital processor having a working memory;

a plurality of dual mode equipment models for simulating each piece of equipment in the processing plant, the plurality of equipment models collectively forming a plant model of the processing plant, there being a different equipment model for different equipment of the desired processing plant, each equipment model being formed of a set of equations and each equipment model being executed in the working memory of the digital processor in one of two modes, for a given equipment model, execution in a first mode providing numerical definition of an output stream of the corresponding equipment, and execution in a second mode providing calculation data required for iterative simultaneous solution of a total set of equations describing the plant model;

a sequential simulation routine executed by the digital processor in the working memory for sequentially executing the equipment models in the first mode and obtaining therefrom numerical definitions of output streams of each corresponding piece of equipment to simulate the desired processing plant, said simulation being an initial simulation of the processing plant and including a first set of values for operating parameters of the processing plant defining operating conditions of the plant;

an optimization and solver routine executed by the digital processor for executing the equipment models in the second mode and obtaining calculation data, the optimization and solver routine utilizing the first set of values for the operating parameters from the initial simulation and the calculation data to determine values of the operating parameters at which operating conditions of the processing plant are optimal; and

a shared data storage area common to the sequential simulation routine and the optimization and solver routine for holding both (i) the first set of values for the operating parameters of the initial simulation and (ii) a second set of values of the operating parameters at which operating conditions of the processing plant are optimized as determined by the optimization routine such that the shared data storage area is common to execution of the equipment models in the first and second modes and enables the equipment models to interchange results from the first and second modes of execution in subsequent executions of the equipment models in the first and second modes.

2. Apparatus as claimed in claim 1 wherein upon the sequential simulation routine executing the equipment models in the first mode, the equipment models store the first set of values for the operating parameters in the shared data storage area, and

upon the optimization routine executing the equipment models in the second mode, the equipment models store the second set of values for the operating parameters in the shared data storage area, in a manner such that the shared data storage area enables the digital processor to sequentially execute the equipment models in the first mode for a second time using the determined values of the operating parameters held in the shared data storage area from execution of the equipment models in the second mode.

3. Apparatus as claimed in claim 1 wherein the shared data storage area holds values of the operating parameters according to variable name, each operating parameter having a corresponding variable name.

4. Apparatus as claimed in claim 1 wherein the calculation data from execution of the equipment models in the second mode includes Jacobian matrixes for the equipment models and equation residuals.

5. In a digital processor, a method for simulating and optimizing a processing plant design, the plant design including a multiplicity of equipment of a desired processing plant and a multiplicity of operating parameters for the equipment, the steps comprising:

providing a plurality of dual mode equipment models for simulating each piece of equipment in the processing plant design, a different equipment model for each different equipment of the desired processing plant, each equipment model being formed of a set of equations and being executed by the digital processor in one of two modes, for a given equipment model, execution in a first mode providing numerical definition of an output stream of the corresponding equipment, and execution in a second mode providing calculation data;

sequentially executing the equipment models in the first mode and obtaining therefrom numerical definitions of output streams of each corresponding piece of equipment to simulate the desired processing plant, said simulation being an initial simulation of the processing plant and including a first set of values for operating parameters of the processing plant design;

storing the first set of values in a shared data storage area;

executing the equipment models in the second mode including utilizing from the data file the first set of values for the operating parameters from the initial simulation, to determine values of the operating parameters at which the processing plant is optimized; and

storing the determined values for optimal operation of the processing plant in the shared data storage area, such that the shared data storage area is common to execution of the equipment models in the first and second modes.

6. A method as claimed in claim 5 further comprising the step of sequentially executing the equipment models in the first mode for a second time using the determined values of the operating parameters as stored in the data file from execution of the equipment models in the second mode, to further define values of the operating parameters of the processing plant design.

7. A method as claimed in claim 5 further comprising the step of interchanging results of the first and second mode executions of the equipment models through the shared data storage area in subsequent executions of the equipment models in the first and second modes.

8. A method is claimed in claim 5 wherein the steps of storing include providing each operating parameter with a variable name and storing values of the operating parameters according to respective variable name.

9. A method is claimed in claim 5 wherein the step of executing equipment models in the second mode includes defining Jacobian matrixes for the equipment models and equation residuals.

10. In a digital processor, a method for simulating and optimizing a processing plant design, the plant design including a multiplicity of equipment of a desired processing plant and a multiplicity of operating parameters for the equipment, the steps comprising:

providing a plurality of equipment models for simulating each piece of equipment in the processing plant design, a different equipment model for each different equipment of the desired processing plant, each equipment model being formed of a set of equations and being executed by the digital processor in one of two modes, for a given equipment model, execution in a first mode providing numerical definition of an output stream of the corresponding equipment, and execution in a second mode providing calculation data;

sequentially executing the equipment models in the first mode and obtaining therefrom numerical definitions of output streams of each corresponding piece of equipment to simulate the desired processing plant, said simulation being an initial simulation of the processing plant and including a first set of values for operating parameters of the processing plant design;

storing the first set of values in a data storage;

executing the equipment models in the second mode including utilizing from the data storage the first set of values for the operating parameters from the initial simulation, to determine values of the operating parameters at which the processing plant is optimized;

storing the determined values for optimal operation of the processing plant in the data storage; and

sequentially executing the equipment models in the first mode for a second time using the determined values of the operating parameters as stored in the data storage from execution of the equipment models in the second mode, to further define values of the operating parameters of the processing plant design.

11. In a digital processor, a method for simulating and optimizing a processing plant design, the plant design including a multiplicity of equipment of a desired processing plant and a multiplicity of operating parameters for the equipment, the steps comprising:

providing a plurality of equipment models for simulating each piece of equipment in the processing plant design, a different equipment model for each different equipment of the desired processing plant, each equipment model being formed of a set of equations and being executed by the digital processor in one of two modes, for a given equipment model, execution in a first mode providing numerical definition of an output stream of the corresponding equipment, and execution in a second mode providing calculation data;

sequentially executing the equipment models in the first mode and obtaining therefrom numerical definitions of output streams of each corresponding piece of equipment to simulate the desired processing plant, said simulation being an initial simulation of the processing plant and including a first set of values for operating parameters of the processing plant design;

storing the first set of values in a data storage;

executing the equipment models in the second mode including utilizing from the data storage the first set of values for the operating parameters from the initial simulation, to determine values of the operating parameters at which the processing plant is optimized, said executing models in the second mode including defining Jacobian matrices for the equipment models and equation residuals; and

storing the determined values for optimal operation of the processing plant in the data storage.

12. Apparatus for simulating and optimizing operation of a processing plant, the processing plant including a multiplicity of equipment and a multiplicity of operating parameters for the equipment, the apparatus comprising:

a digital processor having a working memory;

a plurality of equipment models for simulating each piece of equipment in the processing plant, the plurality of equipment models collectively forming a plant model of the processing plant, there being a different equipment model for different equipment of the desired processing plant, each equipment model being formed of a set of equations and each equipment model being executed in the working memory of the digital processor in one of two modes, for a given equipment model, execution in a first mode providing numerical definition of an output stream of the corresponding equipment, and execution in a second mode providing calculation data required for iterative simultaneous solution of a total set of equations describing the plant model;

a sequential simulation routine executed by the digital processor in the working memory for sequentially executing the equipment models in the first mode and obtaining therefrom numerical definitions of output streams of each corresponding piece of equipment to simulate the desired processing plant, said simulation being an initial simulation of the processing plant and including a first set of values for operating parameters of the processing plant defining operating conditions of the plant;

an optimization and solver routine executed by the digital processor for executing the equipment models in the second mode and obtaining calculation data, the calculation data including Jacobian matrices for the equipment models and equation residuals, the optimization and solver routine utilizing the first set of values for the operating parameters from the initial simulation and the calculation data to determine values of the operating parameters at which operating conditions of the processing plant are optimal; and

a data storage common to the sequential simulation routine and the optimization and solver routine for holding both (i) the first set of values for the operating parameters of the initial simulation and (ii) a second set of values of the operating parameters at which operating conditions of the processing plant are optimized as determined by the optimization routine.