Cold and heat source flow control method and system of LNG and seawater heat exchange gasification output system, medium and equipment

Abstract

The invention relates to the field of automatic control, and discloses a cold and heat source flow control method and system of an LNG and seawater heat exchange gasification output system, a medium and equipment. Transmitting a dynamic matrix of seawater flow to a seawater temperature difference before and after heat exchange and a gasifier outlet natural gas temperature response to a multi-stage optimizer with constraint; transmitting the set values of the flow and the pressure of the output natural gas main pipe and the weight signal to a multi-stage optimizer with constraint; the multi-stage optimizer with constraints performs hierarchical optimization and solution model construction according to the received data under the principle of obeying flow equalization to obtain manipulated variable values of the gasifiers meeting multiple constraints, and performs feedback correction on real-time values of manipulated variables according to fixed time steps, so as to obtain a multi-stage optimization model. Therefore, the flow and the pressure of the output natural gas main pipe reach set values, and the seawater flow at the inlet of the gasifier reaches the minimum value.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control, and particularly to a method, a system, a medium and a device for controlling the flow rates of cold and heat sources of an LNG and seawater heat exchange and gasification and external transmission system. Background Art

[0002] Low-temperature liquefied natural gas (LNG) is often transported by ocean-going tankers to coastal receiving stations, where it is gasified and then supplied to natural gas users. Currently, receiving stations try to utilize seawater, a natural heat source, to achieve the gasification of LNG, such as by equipping open rack vaporizers (ORVs). In the process of LNG being gasified and externally transmitted through heat exchange with seawater in the ORV, it is necessary to regulate the flow rates of LNG and seawater to meet the following three requirements: (1) Respond to the downstream gas lifting requirement, that is, the flow rate and pressure of the externally transmitted natural gas meet a certain setting; (2) Ensure that the temperature of the natural gas at the outlet of the vaporizer is higher than 0 °C to avoid damage to the downstream natural gas external transmission pipeline; (3) Since the seawater after heat exchange will be directly discharged back into the ocean, it is required that the temperature difference between the seawater before and after heat exchange with LNG is less than 5 °C to reduce the impact on the marine environment.

[0003] When the LNG flow rate is constant, the greater the seawater temperature difference, the greater the required amount of seawater; and seawater enters the ORV after being pressurized by a seawater pump, and a greater seawater flow rate means that the pump needs to do more work, resulting in an increase in operating energy consumption. If the seawater flow rate decreases, it may cause insufficient supply of heat, resulting in the temperature of the natural gas at the outlet of the ORV not meeting the requirement of being higher than 0 °C, and even causing ice formation and damage to the ORV vaporizer. How to optimize the seawater flow rate on the premise of ensuring that the LNG and seawater gasification system can meet the above three operating requirements is a challenging task.

[0004] Currently, the methods for regulating the LNG flow rate and seawater flow rate in the LNG gasification and external transmission system are mainly PID single-loop control. Relying on PID control and manual operation, it is difficult to accurately and timely respond to the setting requirements of the external transmission flow rate and pressure of natural gas. In addition, due to safety considerations in on-site actual operations, the seawater flow rate is often controlled at a relatively high value, resulting in a large amount of energy waste. Summary of the Invention

[0005] In view of the above problems, the purpose of the present invention is to provide a method, a system, a medium and a device for controlling the flow rates of cold and heat sources of an LNG and seawater heat exchange and gasification and external transmission system, which can improve the control accuracy and control safety and achieve the purpose of energy conservation.

[0006] To achieve the above purpose, in a first aspect, the technical solution adopted by the present invention is: A method for controlling the flow rates of cold and heat sources of an LNG and seawater heat exchange and gasification and external transmission system, which includes: a dynamic matrix for characterizing the response of the LNG flow rate at the inlets of N vaporizers to the flow rate and pressure of the external transmission natural gas main pipeline , and the dynamic matrix of the response of the seawater flow rate to the temperature difference of seawater before and after heat exchange and the temperature of natural gas at the outlet of the vaporizer , and transmit it to the multi-level optimizer with constraints; where represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, represents the seawater flow rate; the set values of the flow rate and pressure of the main pipeline of the exported natural gas, as well as the weight signal for selecting control according to the flow rate or pressure, are transmitted to the multi-level optimizer with constraints through the DCS of the central control instruction; set the constraints of the multi-level optimizer, and the multi-level optimizer with constraints optimizes in stages and solves the model construction according to the received data while observing the principle of equal flow distribution, calculates the numerical values of the manipulated variables of each vaporizer that meet multiple constraints, and makes feedback corrections to the real-time values of the manipulated variables at fixed time steps, so that the flow rate and pressure of the main pipeline of the exported natural gas reach the set values while minimizing the seawater flow rate at the inlet of the vaporizer.

[0007] Further, the manipulated variables are the LNG flow rate and seawater flow rate at the inlet of each vaporizer.

[0008] Further, set the constraints of the multi-level optimizer, including: the temperature difference of seawater before and after heat exchange in the vaporizer and the temperature of the exported natural gas at the outlet of the vaporizer; among them, the requirement for the seawater temperature difference is not greater than 5 °C, and the temperature of the exported natural gas is not lower than 0 °C.

[0009] Further, the multi-level optimizer with constraints is based on the dynamic matrix and to construct a hierarchical control and solution model.

[0010] Further, the optimization problem in the multi-level optimizer with constraints is solved in two levels and a dynamic model is used for solution.

[0011] Further, the two-level solution includes: The first-level solution: on the premise of meeting the constraints, make the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, and on the premise that the mean deviation between the natural gas flow rate at the outlet of each vaporizer and the set value of the main pipeline flow rate is minimized, obtain the corresponding manipulated variable values; The second-level solution: on the premise of meeting the constraints, ensure that the seawater flow rate at the inlet of the ORV is minimized and obtain the final manipulated variable values.

[0012] In the second aspect, the technical solution adopted by the present invention is: a cold and heat source flow control system for an LNG heat exchange and vaporization export system with seawater, which includes: a dynamic matrix memory, which stores the dynamic matrix of the response of the LNG flow rate at the inlets of N vaporizers to the flow rate and pressure of the main pipeline of the exported natural gas , and the dynamic matrix of the response of seawater flow rate to the temperature difference of seawater before and after heat exchange and the temperature of natural gas at the outlet of the vaporizer , and transmitted to the constrained multi-level optimizer; where represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, represents the seawater flow rate; the central control command DCS transmits the set values of the flow rate and pressure of the main pipeline of the exported natural gas, as well as the weight signal for selecting control based on flow rate or pressure, to the constrained multi-level optimizer; the constrained multi-level optimizer sets the constraints of the multi-level optimizer. Under the principle of equal flow distribution, the constrained multi-level optimizer performs hierarchical optimization and solves the model construction according to the received data, calculates the manipulated variable values of each vaporizer that meet multiple constraints, and performs feedback correction on the real-time values of the manipulated variables at fixed time steps, so that the flow rate and pressure of the main pipeline of the exported natural gas reach the set values while minimizing the seawater flow rate at the inlet of the vaporizer.

[0013] Further, the optimization problem in the constrained multi-level optimizer is solved in two levels and a dynamic model is used for solving; The two-level solution includes: The first-level solution: Under the premise of meeting the constraints, make the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, and obtain the corresponding manipulated variable values on the premise that the mean deviation between the natural gas flow rate at the outlet of each vaporizer and the set value of the main pipeline flow rate is minimized. The second-level solution: Under the premise of meeting the constraints, ensure that the seawater flow rate at the inlet of the ORV is minimized and obtain the final manipulated variable values.

[0014] Thirdly, the technical solution adopted by the present invention is: a computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to execute any one of the above methods.

[0015] Fourthly, the technical solution adopted by the present invention is: a computing device, which includes: one or more processors, a memory, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any one of the above methods.

[0016] Since the present invention adopts the above technical solutions, it has the following advantages: 1. The present invention establishes a dynamic control matrix of two manipulated variables (LNG flow rate, seawater flow rate) for four controlled variables (temperature, pressure, flow rate of exported natural gas, and temperature difference of seawater before and after heat exchange) based on the multi-variable predictive control model technology, overcomes the problems of multi-variable coupling and multi-constraints, and can achieve good control of the LNG and seawater heat exchange and gasification process.

[0017] 2. The present invention adopts a constrained dynamic optimization model for the LNG and seawater heat exchange process, overcomes the situation that the conventional steady-state model may violate constraints in the dynamic process, ensures that the temperature difference of seawater before and after heat exchange and the temperature of exported natural gas always meet the constraint conditions during the regulation process, and greatly improves the control accuracy and control safety.

[0018] 3. The present invention realizes the trimming optimization of the seawater temperature difference through secondary optimization calculation, calculates the minimum seawater flow rate at the ORV inlet under the constraint conditions, and achieves the control goal of energy conservation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is the flowchart of the cold and heat source flow control method for the LNG and seawater heat exchange and gasification and export system in the embodiment of the present invention; Figure 2 is the overall drawing of the controller of the LNG and seawater heat exchange and gasification and export system in the embodiment of the present invention; Figure 3 is the structural diagram of the controller of the LNG and seawater heat exchange and gasification and export system in the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0020] In the process of LNG being gasified by heat exchange with seawater and exported, it is necessary to regulate the LNG and seawater flow rates to meet the above three requirements. In order to solve the problem that the existing methods for regulating the LNG flow rate and seawater flow rate in the LNG gasification and export system are difficult to accurately and timely respond to the set requirements of the exported natural gas flow rate and pressure, and there is a large amount of energy waste. The present invention proposes a cold and heat source flow control method, system, medium and equipment for the LNG and seawater heat exchange and gasification and export system based on dynamic matrix control, establishes a constrained multi-level optimization dynamic model, and can ensure that the temperature of the exported natural gas after gasification needs to be maintained above 0 °C and the temperature difference of seawater before and after the gasifier is less than 5 °C under the premise of double constraints, meet the dual optimization goals of tracking the set points of the exported natural gas flow rate and pressure and the lowest seawater flow rate, and realize the trimming optimization operation of the gasifier.

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present invention fall within the scope of protection of the present invention.

[0022] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] In one embodiment of the present invention, a method for controlling the flow rates of cold and heat sources of an LNG-seawater heat exchange and gasification and export system is provided. In this embodiment, as Figures 1 to 3 shown, the method includes the following steps: 1) Transmit the dynamic matrices representing the response of the inlet LNG flow rates of N (N≥2) vaporizers to the flow rate and pressure of the export natural gas main pipe, and the dynamic matrix representing the response of the seawater flow rate to the temperature difference of seawater before and after heat exchange and the temperature of the natural gas at the outlet of the vaporizer to a constrained multi-stage optimizer; where represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, and represents the seawater flow rate; 2) Transmit the set values of the flow rate and pressure of the export natural gas main pipe, as well as the weight signal for selecting control based on flow rate or pressure, to the constrained multi-stage optimizer through the central control instruction DCS;

[0024] In step 3) above, the manipulated variables are the LNG flow rate and seawater flow rate at the inlet of each vaporizer.

[0025] In step 3) above, the constraints of the multi-level optimizer are set, including: the temperature difference of seawater before and after heat exchange in the vaporizer (i.e., the temperature difference between the inlet and outlet seawater temperatures of the vaporizer) and the temperature of the exported natural gas at the outlet of the vaporizer (i.e., the temperature of the natural gas at the outlet of the vaporization). Among them, the requirement for the seawater temperature difference is not greater than 5°C, and the temperature of the exported natural gas is not lower than 0°C.

[0026] Among them, the multi-level optimizer with constraints is based on the dynamic matrix and to construct a hierarchical control and solution model.

[0027] The optimization objective of the multi-level optimizer with constraints is to adjust N the LNG flow rate at the inlets of the vaporizers under the premise of meeting the constraints, so that the flow rate and pressure of the exported natural gas main pipe reach the set values (flow rate control or pressure control is set through weights). At the same time, considering energy conservation, it is necessary to ensure that the seawater flow rate is as small as possible.

[0028] In step 3) above, the optimization problem in the multi-level optimizer with constraints is solved in two levels, and a dynamic model is used for solution, which overcomes the situation that the conventional steady-state model may violate the constraints in the dynamic process, ensures that all variables in the system always meet the constraints during the adjustment process, and greatly improves the control accuracy and control safety. In this embodiment, using the dynamic model for solution means considering dynamic constraints to ensure that the constraints are always met during the dynamic response process (different from using the steady-state model for solution, which only ensures that the system finally stabilizes within the constraint range and does not guarantee the process).

[0029] In this embodiment, the two-level solution includes: The first-level solution: Under the premise of meeting the constraints, make the flow rate and pressure of the exported natural gas main pipe reach the set values, and obtain the corresponding manipulated variable values under the premise that the mean deviation between the outlet natural gas flow rate of each vaporizer and the set value of the main pipe flow rate is the smallest. For example, under the premise of meeting the double constraints that the seawater temperature difference before and after heat exchange does not exceed 5°C and the temperature of the exported natural gas at the outlet of the vaporizer is greater than 0°C, make the flow rate and pressure of the exported natural gas main pipe reach the set values, and obtain the corresponding manipulated variable values under the premise that the mean deviation between the outlet natural gas flow rate of each vaporizer and the set value of the main pipe flow rate is the smallest. The second-level solution: Under the premise of meeting the constraints, ensure that the seawater flow rate at the ORV inlet is the smallest, and obtain the final manipulated variable values.

[0030] For example, under the premise of meeting the two constraints that the seawater temperature difference before and after heat exchange does not exceed 5°C and the temperature of the exported natural gas is greater than 0°C, ensure that the seawater flow rate is the smallest.

[0031] In this embodiment, the multi-level optimizer with constraints uses methods such as the interior point method and the conjugate gradient method to solve the optimization problem.

[0032] Specifically, taking the LNG-vaporizing and seawater-heat-exchanging and outwards-transporting system with 5 vaporizers as an example, the two-stage solution is as follows: (1) On the premise of satisfying the two constraints that the temperature difference of seawater before and after heat exchange does not exceed 5°C and the temperature of the outwards-transported natural gas is greater than 0°C, make the flow rate and pressure of the outwards-transported natural gas main pipe reach the set values as much as possible, and the deviation between the natural gas flow rate at the outlet of each vaporizer and the average value of the natural gas flow rate in the main pipe is small. Specifically:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044] (2) On the premise of satisfying the two constraints that the temperature difference of seawater before and after heat exchange does not exceed 5°C and the temperature of the outwards-transported natural gas is greater than 0°C, ensure that the seawater flow rate is as small as possible. Specifically:

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056] wherein, represents the deviation between the predicted values and the set values of the flow rate and pressure of the main pipeline for exported natural gas; represents the LNG flow rate at the inlet of the i-th vaporizer; represents the real-time average value of the LNG flow rates at the inlets of N vaporizers; represents the control input increment at the current time k, that is, the increments of the LNG flow rate and the seawater flow rate of N vaporizers; represents the i increment of the LNG flow rate at the inlet of the -th vaporizer; i increment of the seawater flow rate at the inlet of the -th vaporizer; represents the output of the prediction model for the flow rate and pressure of the main pipeline for exported natural gas; represents the initial predicted values of the flow rate and pressure of the main pipeline for exported natural gas without input increment adjustment; represents the current control time k; is a part of the prediction model for the temperature difference before and after seawater heat exchange in each vaporizer and the temperature of the exported natural gas at the outlet; represents the initial predicted values of the temperature difference before and after seawater heat exchange in each vaporizer and the temperature of the exported natural gas at the outlet; represents the predicted output after feedback correction by dynamically correcting the flow rate and pressure of the main pipeline for exported natural gas combined with historical prediction errors; represents the displacement matrix; represents the response coefficients of the inlet LNG flow rate and seawater flow rate to the flow rate and pressure of the main pipeline for exported natural gas; represents the feedback correction coefficient; represents the predicted output for the flow rate and pressure of the main pipeline for exported natural gas after correction at time k; represents the predicted output for the seawater temperature difference before and after the i-th ORV and the seawater temperature at the outlet after correction at time k; represents the response coefficients of the inlet LNG flow rate and seawater flow rate of the i-th ORV to the seawater temperature difference before and after it and the LNG temperature at the outlet; represents the predicted output for the seawater temperature difference before and after the i-th ORV and the seawater temperature at the outlet at time k; represents the set values of the flow rate and pressure of the main pipeline for exported natural gas; Indicates the temperature difference of seawater before and after heat exchange in the i th vaporizer; Indicates the temperature of the exported natural gas at the outlet of the i th vaporizer.

[0057] Among them, is the prediction model part of the flow rate and pressure of the main pipeline of the exported natural gas; Indicates the flow rate of the main pipeline of the exported natural gas ( ) and the pressure ( ); Indicates the flow rate of the main pipeline of the exported natural gas ( ) and the pressure ( ) at time k. Have different meanings. is the result of actual measurement. is the result of model prediction. The difference between the two can be understood as an error similar to that used for feedback correction.

[0058] are the seawater temperature difference before and after the vaporizer ( ) and the natural gas temperature at the outlet of the vaporizer ( ). The subscript indicates the th vaporizer; are the seawater temperature difference before and after the vaporizer ( ) and the natural gas temperature at the outlet of the vaporizer ( ) at time k; Have different meanings. is the result of actual measurement. is the result of model prediction. The difference between the two can be understood as an error similar to that used for feedback correction.

[0059] Indicates the prediction initial value. Indicates the output prediction value under the action of and ; Indicates the zero-input response at the current moment. is the measurement value correction. is the feedback correction coefficient. is the displacement matrix. is to make the flow rate and pressure of the main pipeline of the exported natural gas reach the set value as much as possible.

[0060] The optimization problem in the multi-level optimizer with constraints, where indicates the flow rate of the main pipeline of the exported natural gas ( ) and the pressure of the main pipeline of the exported natural gas ( ); For the temperature difference between seawater before and after heat exchange in the vaporizer ( ) and the temperature of the exported natural gas at the outlet of the vaporizer ( ), the subscript represents the th vaporizer.

[0061] In an embodiment of the present invention, a cold and heat source flow control system for an LNG-seawater heat exchange and vaporization export system is provided, which includes: A dynamic matrix memory for storing a dynamic matrix, and transmitting the dynamic matrix for characterizing the response of the inlet LNG flow of N (N≥2) vaporizers to the flow and pressure of the exported natural gas main pipe , and the dynamic matrix for the response of seawater flow to the temperature difference between seawater before and after heat exchange and the temperature of natural gas at the outlet of the vaporizer to a constrained multi-stage optimizer; wherein, , represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, represents the seawater flow rate; The central control instruction DCS transmits the set values of the flow and pressure of the exported natural gas main pipe, and the weight signal for selecting control according to flow or pressure to the constrained multi-stage optimizer through the central control instruction DCS; The constrained multi-stage optimizer sets the constraints of the multi-stage optimizer. The constrained multi-stage optimizer performs hierarchical optimization and solves the model construction according to the received data under the principle of equal flow distribution, obtains the manipulated variable values of each vaporizer that meet multiple constraints, and performs feedback correction on the real-time values of the manipulated variables at fixed time steps, so that the flow and pressure of the exported natural gas main pipe reach the set values while minimizing the seawater flow rate at the inlet of the vaporizer.

[0062] In the above embodiment, the manipulated variables are the LNG flow rate and seawater flow rate at the inlet of each vaporizer.

[0063] In the above embodiment, setting the constraints of the multi-stage optimizer includes: the temperature difference between seawater before and after heat exchange in the vaporizer and the temperature of the exported natural gas at the outlet of the vaporizer; wherein, the requirement for the seawater temperature difference is not greater than 5°C, and the temperature of the exported natural gas is not lower than 0°C.

[0064] In the above embodiment, the constrained multi-stage optimizer constructs a hierarchical control and solution model based on the dynamic matrix and .

[0065] In the above embodiment, the optimization problem in the constrained multi-stage optimizer is solved in two levels and a dynamic model is used for the solution.

[0066] In this embodiment, the two-stage solution includes: The first-stage solution: On the premise of satisfying the constraints, make the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, and obtain the corresponding control variable values on the premise that the mean deviation between the natural gas flow rate at the outlet of each vaporizer and the set value of the main pipeline flow rate is minimized. The second-stage solution: On the premise of satisfying the constraints, ensure that the seawater flow rate at the ORV inlet is minimized, and obtain the final control variable values.

[0067] The system provided in this embodiment is used to execute the above method embodiments. For the specific process and detailed content, please refer to the above embodiments and will not be elaborated here.

[0068] In an embodiment of the present invention, a computing device is provided. The computing device may be a terminal, and it may include: a processor, a communications interface, a memory, a display screen, and an input device. Among them, the processor, the communications interface, and the memory complete mutual communication through a communication bus. The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. When the computer program is executed by the processor, the methods in the above embodiments are implemented; the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communications interface is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen may be a liquid crystal display screen or an electronic ink display screen. The input device may be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computing device, or an external keyboard, a touchpad, or a mouse, etc. The processor can call the logical instructions in the memory.

[0069] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0070] In an embodiment of the present invention, a computer program product is provided. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided in the above-mentioned method embodiments.

[0071] In an embodiment of the present invention, a non-transitory computer-readable storage medium is provided. The non-transitory computer-readable storage medium stores server instructions. The computer instructions cause the computer to execute the methods provided in the above-mentioned embodiments.

[0072] For the computer-readable storage medium provided in the above-mentioned embodiment, its implementation principle and technical effects are similar to those of the above-mentioned method embodiment, and will not be elaborated here.

[0073] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0074] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in the process(es) Figure 1 one process or multiple processes and / or block(s) Figure 1 the function(s) specified in one block or multiple blocks.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the process(es) Figure 1 one process or multiple processes and / or block(s) Figure 1 the function(s) specified in one block or multiple blocks.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the flow rates of cold and heat sources in an LNG heat exchange and gasification external transmission system, characterized in that, Including: The dynamic matrices used to characterize the responses of the LNG flow rates at the inlets of N vaporizers to the flow rate and pressure of the exported natural gas main pipeline , and the dynamic matrices of the seawater flow rate to the temperature difference of the seawater before and after heat exchange and the response of the natural gas temperature at the outlet of the vaporizer , are transmitted to the constrained multi-stage optimizer; where , represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, represents the seawater flow rate; The DCS of the central control instruction transmits the set values of the flow rate and pressure of the main pipeline of the exported natural gas, as well as the weight signal for selecting control based on flow rate or pressure, to the multi-level optimizer with constraints. Set the constraints of the multi-level optimizer. The multi-level optimizer with constraints performs hierarchical optimization and solves the model construction according to the received data while observing the principle of flow rate equalization, calculates the manipulated variable values of each vaporizer that meet multiple constraints, and performs feedback correction on the real-time values of the manipulated variables at fixed time steps, so that while the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, the seawater flow rate at the inlet of the vaporizer reaches the minimum value.

2. The cold and heat source flow control method of the LNG-seawater heat exchange and gasification and external transportation system according to claim 1, characterized in that The manipulated variables are the LNG flow rate and seawater flow rate at the inlet of each vaporizer.

3. The cold and heat source flow control method of the LNG and seawater heat exchange and gasification and external transportation system according to claim 1, wherein Set the constraints of the multi-level optimizer, including: the seawater temperature difference before and after heat exchange in the vaporizer and the temperature of the exported natural gas at the outlet of the vaporizer; among them, the requirement for the seawater temperature difference is not greater than 5°C, and the temperature of the exported natural gas is not lower than 0°C.

4. The cold and heat source flow control method of the LNG and seawater heat exchange and gasification and external transportation system according to claim 3, characterized in that, Constrained Multistage Optimizer, Based on Dynamic Matrix and Construct a hierarchical control and solution model.

5. The cold and heat source flow control method of the LNG-vaporizing and exporting system by heat exchange with seawater according to claim 4, characterized in that The optimization problem in the multi-level optimizer with constraints is solved in two levels and a dynamic model is used for solving.

6. The cold and heat source flow control method of the LNG and seawater heat exchange and gasification and external transportation system according to claim 5, characterized in that The two-level solution includes: The first-level solution: On the premise of meeting the constraints, make the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, and on the premise that the mean deviation between the outlet natural gas flow rate of each vaporizer and the set value of the main pipeline flow rate is minimized, obtain the corresponding manipulated variable values. The second-level solution: On the premise of meeting the constraints, ensure that the seawater flow rate at the inlet of the ORV is minimized and obtain the final manipulated variable values.

7. A cold and heat source flow control system for an LNG heat exchange and gasification and external transmission system, characterized in that, Including: A dynamic matrix memory will be used to represent the dynamic matrix of the inlet LNG flow rate of N vaporizers in response to the flow rate and pressure of the exported natural gas main pipeline , as well as the dynamic matrix of the seawater flow rate in response to the temperature difference of seawater before and after heat exchange and the temperature of the natural gas at the outlet of the vaporizer , and transmit it to a constrained multi-stage optimizer; among them, , represents the serial number of the vaporizer, N is the total number of vaporizers, represents the LNG flow rate, represents the seawater flow rate; The DCS of the central control instruction. The DCS of the central control instruction transmits the set values of the flow rate and pressure of the main pipeline of the exported natural gas, as well as the weight signal for selecting control based on flow rate or pressure, to the multi-level optimizer with constraints. The multi-level optimizer with constraints. Set the constraints of the multi-level optimizer. The multi-level optimizer with constraints performs hierarchical optimization and solves the model construction according to the received data while observing the principle of flow rate equalization, calculates the manipulated variable values of each vaporizer that meet multiple constraints, and performs feedback correction on the real-time values of the manipulated variables at fixed time steps, so that while the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, the seawater flow rate at the inlet of the vaporizer reaches the minimum value.

8. The cold and heat source flow control system of the LNG heat exchange and gasification for external transportation system according to claim 7, characterized in that The optimization problem in the multi-level optimizer with constraints is solved in two levels and a dynamic model is used for solving; The two-level solution includes: The first-level solution: On the premise of meeting the constraints, make the flow rate and pressure of the main pipeline of the exported natural gas reach the set values, and on the premise that the mean deviation between the outlet natural gas flow rate of each vaporizer and the set value of the main pipeline flow rate is minimized, obtain the corresponding manipulated variable values. The second-level solution: On the premise of meeting the constraints, ensure that the seawater flow rate at the inlet of the ORV is minimized and obtain the final manipulated variable values.

9. A computer-readable storage medium storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to execute any of the methods described in claims 1 to 6.

10. A computing device, characterized in that, Including: One or more processors, a memory, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods described in claims 1 to 6.

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