HFO-1234yf synthesis process parameter optimization control method and system

Abstract

The invention discloses an HFO-1234yf synthesis process parameter optimization control method and system, and relates to a heat exchange network control technology in a chemical production process, and the method comprises the steps: summarizing a plurality of heat exchange devices and shared fluid pump devices which share the same fluid loop in a heat exchange network in the HFO-1234yf synthesis process into the same heat association group; when a parameter adjusting instruction of the heat exchange equipment is received, the influence of the response is evaluated according to the real-time operation data and the physical model; and generating a coordination adjustment instruction according to the evaluation result and a preset target, and sending the coordination adjustment instruction to an execution mechanism of the related equipment. According to the parameter optimization control method and system for the HFO-1234yf synthesis process provided by the invention, the problem of global imbalance caused by local adjustment of a heat exchange network in the HFO-1234yf synthesis process is effectively solved by summarizing the equipment in the thermal association group, evaluating the linkage influence of local adjustment and generating the coordination adjustment instruction, and the stability and optimization of the system are improved.

Description

Technical Field

[0001] This application relates to the field of industrial process control technology, and in particular to heat exchanger network control technology in chemical production processes. Specifically, it relates to a parameter optimization control method and system for the HFO-1234yf synthesis process. Background Technology

[0002] The industrial synthesis of HFO-1234yf demands extremely precise temperature control, directly impacting product yield and purity. Maintaining stable temperatures in these critical processes relies on a sophisticated heat exchange network. However, in actual industrial production, this network faces a series of complex and intertwined challenges, making it difficult to consistently maintain optimal performance. For instance, the industrial production of HFO-1234yf involves multiple chemical transformations, imposing stringent requirements on reaction temperature and the precision of separation and purification. In the reaction unit, catalyst activity and reaction selectivity are directly affected by the temperature environment; deviations from the setpoint may lead to reduced yields of the target product or increased byproducts. In the subsequent distillation separation unit, the temperature gradient between the bottom and top of the column determines the effective separation of different components, directly affecting product purity. Temperature control in these critical process units depends on a sophisticated heat exchange network. This network, through a series of heat exchange devices, delivers hot or cold fluids at specific temperatures to each process point; for example, using steam to heat the reactants or using cooling water to remove heat from the top of the distillation column. In a heat exchange network, the operating conditions, such as fluid temperature, flow rate, and pressure, within each heat exchanger need to be maintained within a specific range. Deviations from these operating conditions will directly cause the temperature of the relevant process unit to deviate from the preset value, thereby affecting the synthesis efficiency and product quality of HFO-1234yf.

[0003] However, in the actual industrial production process of the HFO-1234yf, the heat exchange network does not operate under conventional steady-state conditions. With changes in market demand, production units require frequent load adjustments. For example, to respond to increased market orders, the production load may need to be increased rapidly in a short period; conversely, when market demand weakens, the production load needs to be quickly reduced. This rapid and significant adjustment of production load necessitates that the heat exchange network operate under continuously changing heat loads. Traditional control strategies based on steady-state conditions are insufficient to effectively cope with such continuous changes in operating conditions because the thermal equilibrium state is different at each load point, and simple fixed parameters cannot adapt to all situations.

[0004] Such frequent load adjustments pose a severe challenge to the rapid response capability of heat exchange networks. When production loads change rapidly, the heat required or removed by each process unit also fluctuates rapidly. However, heat exchange networks inherently possess thermal inertia; for example, the metal walls and internal fluids of a heat exchanger require time to reach a new thermal equilibrium, and there is also a time delay in fluid transport through pipes. These factors result in a significant hysteresis in the response of the heat exchange network to changes in heat load. If the control system cannot adjust the operating parameters of the heat exchanger, such as steam flow or cooling water flow, in a timely and accurate manner, it may lead to significant overshoot or fluctuations in the temperature of the process unit. For instance, when the load suddenly decreases, if the cooling water flow fails to decrease in time, the reactor temperature may drop excessively, affecting reaction efficiency; conversely, when the load suddenly increases, insufficient heat removal capacity may cause a temperature surge, even posing a safety risk. This lack of rapid response not only affects product quality but may also threaten the stability and safety of production.

[0005] To address temperature deviations during transient processes, operators or existing control systems often need to simultaneously adjust the operating parameters of multiple heat exchangers in the heat exchange network. However, the heat exchange network in the HFO-1234yf synthesis process is typically a highly interconnected system. Adjusting one heat exchanger can have a cascading effect on other related heat exchangers through the circulation of hot or cold fluids. This effect is not a simple linear superposition but exhibits complex, nonlinear interrelationships. For example, adjusting the cooling water flow rate of a distillation column condenser not only affects the column's top temperature but may also indirectly affect other heat exchangers using the same cooling water loop by influencing the total cooling water circulation volume and return water temperature. Traditional single-loop feedback control, such as proportional-integral-derivative (PID) controllers, typically adjusts a single controlled variable, making it difficult to effectively coordinate multiple interdependent heat exchangers. This can lead to a situation where correcting the temperature in one region may trigger new temperature deviations or fluctuations in another region, making it difficult to achieve global stability and optimization of the entire network's temperature control. In particular, when multiple heat exchangers and shared fluid pumps within a heat exchange network are grouped into the same thermally related group, adjustments to the parameters of one heat exchanger within the group will rapidly and complexly spread to other devices within the group, including other heat exchangers and shared fluid pumps. This will create a chain reaction affecting the total flow rate, pressure distribution, and fluid temperature of the entire shared fluid loop, as well as the fluid flow rate and temperature of other heat exchangers. Current technology lacks an effective method to accurately assess this chain reaction and generate coordinated adjustment instructions for all relevant devices within the group, thus preventing local adjustments from causing global imbalances.

[0006] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0007] The purpose of this application is to provide a method and system for optimizing and controlling parameters in the HFO-1234yf synthesis process. This method and system can effectively solve the problem of global imbalance caused by local adjustment of the heat exchange network in the HFO-1234yf synthesis process, and improve the stability and optimization of the system operation.

[0008] This application provides a method for optimizing and controlling parameters in the HFO-1234yf synthesis process, the technical solution of which is as follows: Includes the following steps: Multiple heat exchange devices sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process, as well as fluid pump devices sharing the fluid, are grouped into the same thermal association group. When a parameter adjustment command is received from a heat exchanger within a thermally correlated group, the system assesses the impact of responding to the parameter adjustment command on other devices within the thermally correlated group based on the real-time operating data of each device within the thermally correlated group and the preset physical model. Based on the assessment results and preset goals, a corresponding coordination and adjustment instruction is generated for each relevant device in the thermally related group; Each coordination and adjustment instruction is sent to the corresponding execution mechanism of the relevant equipment; In addition to a specific heat exchanger, the relevant equipment also includes other heat exchangers and / or shared fluid pumps within the thermally associated group.

[0009] The above scheme can accurately assess the cascading effects of local adjustments on the entire thermally correlated group and generate coordinated adjustment instructions, effectively avoiding global imbalances caused by local adjustments and improving the global stability and optimization of control.

[0010] Optionally, the step of evaluating the impact of the response parameter adjustment command on other devices in the thermally correlated group based on the real-time received operating data of each device in the thermally correlated group and the preset physical model specifically includes: Based on the real-time received inlet fluid temperature, outlet fluid temperature, inlet fluid flow rate, outlet fluid flow rate, and shared fluid loop pressure value of each heat exchanger in the thermal correlation group, the preset physical model is invoked to simulate the response parameter adjustment instructions. Calculate the impact of the response parameter adjustment command on other heat exchange equipment and / or shared fluid pump equipment within the thermally associated group.

[0011] The above approach enables more accurate simulation and calculation of the impact of local adjustments on other equipment based on detailed operational data and physical models, thereby improving the accuracy of the assessment.

[0012] Optionally, this application also proposes a step for generating a corresponding coordinated adjustment instruction for each relevant device within a thermally correlated group based on the evaluation results and preset objectives. This step specifically includes: Based on the impact on other heat exchangers and / or shared fluid pumps within the thermally correlated group, the preset optimization objectives, and the preset constraint objectives, a corresponding coordination adjustment instruction is generated for a specific heat exchanger and for the other affected heat exchangers and / or shared fluid pumps.

[0013] The above scheme can comprehensively consider the impact, optimization objectives, and constraint objectives, and generate coordinated adjustment instructions for all relevant equipment, ensuring the comprehensiveness and effectiveness of the control strategy.

[0014] Optionally, after the step of generating a corresponding coordination adjustment instruction for each relevant device in the thermally correlated group based on the evaluation results and preset targets, the method further includes: Real-time monitoring of the valve opening information of each heat exchanger in the thermally correlated group, as well as the speed information of the shared fluid pump equipment; Real-time monitoring of temperature measurements and corresponding temperature change rates of each heat exchanger and shared fluid pump within the thermally correlated group; Each coordinated adjustment command is calibrated based on the valve opening information, speed information, temperature measurement value, and corresponding temperature change rate. The specific steps for sending each coordination and adjustment instruction to the corresponding actuator of the relevant equipment are as follows: Each calibrated coordination adjustment instruction is sent to the corresponding actuator of the relevant equipment.

[0015] By introducing a real-time monitoring and calibration mechanism through the above scheme, the commands can be corrected based on actual operational feedback, further improving the accuracy and adaptability of control commands and addressing sensor delays and errors.

[0016] Optionally, the step of calibrating each coordinated adjustment command based on the regulating valve opening information, rotational speed information, temperature measurement value, and corresponding temperature change rate specifically includes: For each coordinated adjustment command, based on the control valve opening information, speed information, temperature measurement value, and corresponding temperature change rate, assess the consequences of responding to the coordinated adjustment command. Determine the calibration strategy for coordinating and adjusting instructions based on the expected consequences. The coordinated adjustment instructions are calibrated according to the calibration strategy.

[0017] The above scheme provides a detailed method for determining calibration strategies, making the correction of coordinated adjustment commands more scientific and precise, and ensuring control effectiveness.

[0018] Optionally, the method for optimizing and controlling the parameters of the HFO-1234yf synthesis process further includes: When a load adjustment request is received, the target load and load increase rate are determined based on the load adjustment request; Based on the target load, load increase rate, and the inherent thermal inertia of each process unit and heat exchange network during the HFO-1234yf synthesis process, as well as the fluid transmission delay characteristics in the pipeline, the heat load demand trend of each heat exchange device in the thermally related group is predicted within a set time in the future. Based on the heat load demand trend of each heat exchanger in the thermally related group within a future set time, a sequence of adjustment instructions carrying timing is generated. Based on the timing sequence of each adjustment instruction in the adjustment instruction sequence, the corresponding adjustment instruction is sent to the execution mechanism of the corresponding device at the corresponding timing point.

[0019] The above scheme can predict future heat load demand trends and generate a sequence of adjustment instructions with timing, effectively addressing rapid adjustments in production load and the inherent thermal inertia and transmission delay of the system, thus achieving forward-looking control.

[0020] Optionally, the heat load demand trend of each heat exchanger is: the change trend of the heat load required by each heat exchanger or the heat that needs to be removed; The step of generating a sequence of adjustment instructions carrying time sequence based on the heat load demand trend of each heat exchanger in the thermally correlated group within a future set time period specifically includes: Based on the trend of heat load or heat to be removed required by each heat exchanger in the thermally related group within a future set time, determine the adjustment direction and adjustment range for each heat exchanger within the future set time. For each heat exchanger, a sequence of adjustment instructions carrying timing information is generated based on the determined adjustment method and adjustment range at a future set time. For each heat exchanger, the sequence of adjustment instructions carrying timing includes multiple adjustment instructions carrying different timing sequences.

[0021] The above scheme further refines the definition of heat load demand trends and the generation method of instruction sequences, making forward-looking adjustments more specific and operable.

[0022] Optionally, the physical model includes: a heat transfer model for each heat exchanger in the thermally associated group, a fluid resistance model for the pipes in the heat exchange network, and a performance curve model for the shared fluid pump equipment.

[0023] The above scheme clarifies the specific composition of the physical model, providing a solid foundation for accurate evaluation and simulation, and improving the reliability of control.

[0024] Optionally, the impact on other equipment within the thermally associated group refers to the impact on the total flow rate of the entire shared fluid loop, the pressure distribution of the shared fluid loop, the fluid temperature in the shared fluid loop, and the fluid flow rate and fluid temperature of other heat exchange equipment. The optimization objectives are: to minimize temperature fluctuations, maintain stable total fluid flow, and / or optimize the energy consumption of shared fluid pump equipment in each process unit of the HFO-1234yf synthesis process; The constraints are: the safe temperature range of each process unit in the HFO-1234yf synthesis process, and the operational limitations of the shared fluid pump equipment.

[0025] The above scheme defines the impact, optimization, and constraint objectives in detail, providing clear guidance for the formulation of control strategies and ensuring the comprehensiveness and security of control.

[0026] This invention also discloses a parameter optimization and control system for the HFO-1234yf synthesis process, comprising: The induction module is used to group multiple heat exchange devices that share the same fluid loop and fluid pump devices that share the fluid within the heat exchange network during the HFO-1234yf synthesis process into the same thermal association group. The evaluation module is used to evaluate the impact of responding to the parameter adjustment command on other devices in the thermally associated group when a parameter adjustment command is received from a heat exchanger in the thermally associated group, based on the real-time operating data of each device in the thermally associated group and the preset physical model. The generation module is used to generate a corresponding coordination and adjustment instruction for each relevant device in the thermally correlated group based on the evaluation results and preset goals; The sending module is used to send each coordination and adjustment instruction to the actuator of the corresponding relevant device; In addition to a specific heat exchanger, the relevant equipment also includes other heat exchangers and / or shared fluid pumps within the thermally associated group.

[0027] The above scheme provides a system for implementing the above control method, enabling the optimized control scheme to be practically deployed and operated.

[0028] As can be seen from the above, the HFO-1234yf synthesis process parameter optimization control method and system provided in this application effectively solves the problem of global imbalance caused by local adjustment of the heat exchange network during the HFO-1234yf synthesis process by summarizing the equipment in the thermally related group and evaluating the chain effect of local adjustment, thereby generating coordinated adjustment instructions, and improves the stability and optimization of system operation. Attached Figure Description

[0029] Figure 1A flowchart illustrating the parameter optimization and control method for the HFO-1234yf synthesis process provided in this application.

[0030] Figure 2 A schematic diagram of the structure of the parameter optimization control system for the HFO-1234yf synthesis process provided in this application.

[0031] Figure 2 In the diagram: 110 is the summarization module; 120 is the evaluation module; 130 is the generation module; and 140 is the sending module. Detailed Implementation

[0032] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0033] In traditional HFO-1234yf synthesis processes, the heat exchanger network faces continuously changing operating conditions during production load adjustments. This inherent thermal inertia and fluid transport delays lead to a lag in response to heat load changes. Furthermore, the heat exchanger network is a highly interconnected system; parameter adjustments in one heat exchanger can have complex nonlinear cascading effects on other related heat exchangers through fluid circulation. This makes traditional single-loop control ineffective in coordinating multiple interdependent devices, potentially causing local optimization to trigger global fluctuations. Simultaneously, sensors used to monitor operating status suffer from time delays and measurement errors, limiting the accuracy of real-time data and affecting the timeliness of control decisions. Over long-term operation, the performance of heat exchangers will continuously degrade, even leading to localized failures. Existing control systems struggle to identify these changes online, resulting in control strategies based on unrealistic models and failing to achieve optimal control.

[0034] Therefore, this application proposes a novel approach: identifying and grouping heat exchangers and shared fluid pumps that share the same fluid loop, treating them as a "thermally interconnected group." This approach decomposes the complex global control problem into a coordinated control problem for multiple relatively independent "thermally interconnected groups." When a heat exchanger within the group needs parameter adjustments, the adjustment is no longer performed in isolation. Instead, real-time operational data and a pre-defined physical model are used to assess the impact of the adjustment on other devices within the group. Based on this impact assessment and pre-defined optimization objectives, a set of coordinated adjustment instructions is generated for all relevant devices within the group. These instructions are then sent to their respective actuators, thereby achieving coordinated optimization control of the entire thermally interconnected group. This method effectively addresses the complex interrelationships between devices, avoids chain reactions caused by single-point adjustments, and ensures stable operation and global optimization of the entire heat exchange network under dynamic conditions.

[0035] To address this, this application proposes a method for optimizing and controlling the parameters of the HFO-1234yf synthesis process, see [link to relevant documentation]. Figure 1 The control method includes the following steps: S110. Multiple heat exchange devices sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process, as well as fluid pump devices sharing the fluid, are grouped into the same thermal association group. S120. When a parameter adjustment instruction is received for a heat exchanger within a thermally correlated group, the impact on other devices within the thermally correlated group after responding to the parameter adjustment instruction is evaluated based on the real-time operating data of each device within the thermally correlated group and the preset physical model. S130. Based on the evaluation results and preset targets, generate a corresponding coordination and adjustment instruction for each relevant device in the thermal association group; S140. Send each coordination and adjustment instruction to the corresponding relevant equipment's actuator; The related equipment includes, in addition to a specific heat exchange device, other heat exchange devices and / or shared fluid pump devices within the thermal association group.

[0036] This application aims to provide a parameter optimization control method for the HFO-1234yf synthesis process. By dividing and coordinating the thermally related groups of the heat exchange network, it solves the complex operating conditions that traditional control methods cannot handle and achieves global optimization.

[0037] In this context, a thermally correlated group refers to a collection of multiple heat exchangers and fluid pumps sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process. The purpose is to treat physically coupled devices as a whole, simplifying subsequent control complexity and more accurately capturing the interactions between devices. A parameter adjustment command is a command or signal indicating a change in the operating parameters of a specific heat exchanger. This command can originate from manual input by the operator, the upper-level process control system, or automated optimization algorithms. Its primary purpose is to initiate a control sequence for a specific device, thereby triggering a coordinated response across the entire group. A pre-defined physical model is a tool for mathematically describing the physical behavior and interdependencies of devices within the thermally correlated group. This model can be constructed using first-principles heat transfer models, fluid dynamics models, device performance curve models, etc., with the aim of accurately simulating and predicting the dynamic responses and interactions of devices within the group during parameter adjustments. Evaluating the impact of responding to parameter adjustment commands on other devices refers to the process of quantitatively determining how changes in the parameters of a heat exchanger propagate through the shared fluid loop and affect the operating status of other devices within the same thermally correlated group. This process is achieved by processing real-time operational data and performing simulations using physical models. Its aim is to comprehensively understand the cascading effects of local adjustments, thereby proactively mitigating adverse consequences and promoting coordinated control. Coordinated adjustment commands refer to a specific and synchronized set of commands generated for multiple related devices within a thermally correlated group, designed to achieve a predefined overall objective while considering the interactions between devices. These commands can be changes to control valve setpoints, pump speed adjustments, or target temperature / flow rate settings. Their purpose is to ensure that adjustments to individual devices contribute to the global optimization of the thermally correlated group, prevent adverse interactions, and maintain process stability. Related devices refer to the set of devices within the thermally correlated group that are subject to coordinated control, including heat exchangers that receive initial parameter adjustment commands, as well as other heat exchangers and / or shared fluid pumps within the group. The goal is to ensure that all interconnected components affected or contributing to the overall thermal balance of the group are considered and controlled uniformly.

[0038] The core innovation of this application lies in the fact that by grouping the interconnected heat exchange equipment and shared fluid pump equipment in the HFO-1234yf synthesis process into a thermally related group, and introducing an evaluation mechanism based on real-time operating data and a preset physical model, it is possible to predict the impact of local parameter adjustments on the entire group, thereby generating coordinated adjustment commands. This achieves the effect of global optimization control of the heat exchange network under complex dynamic conditions, effectively solving the problem of multi-device linkage and transient response that is difficult to handle with traditional control methods.

[0039] This application's solution involves systematically optimizing and controlling the heat exchange network during the HFO-1234yf synthesis process. First, multiple heat exchange devices sharing the same fluid loop and fluid pumps within the heat exchange network are logically grouped into a single thermally correlated group. This grouping aims to treat physically coupled devices as a whole, simplifying subsequent control complexity and more accurately capturing the interactions between devices. When a parameter adjustment command is received from a heat exchange device within the thermally correlated group, the system immediately initiates an evaluation process. During this process, real-time operating data from each device within the thermally correlated group, such as temperature, flow rate, and pressure, are input into a pre-set physical model. This physical model can simulate and predict the potential impact on other devices within the thermally correlated group after responding to the initial parameter adjustment command, such as the impact on total fluid flow rate, pressure distribution, fluid temperature, and the fluid flow rate and temperature of other heat exchange devices. This predictive capability is the foundation for coordinated control, avoiding the chain reaction of negative effects that may occur with traditional single-point adjustments. Based on this evaluation result, and combined with preset optimization objectives (such as minimizing temperature fluctuations, maintaining stable total fluid flow, and optimizing the energy consumption of shared fluid pump equipment) and constraint objectives (such as safe temperature range and pump operation limits), the system generates a corresponding coordinated adjustment instruction for each relevant device within the thermally correlated group, including the heat exchanger initially adjusted, other affected heat exchangers, and shared fluid pump equipment. These instructions are derived after global optimization considerations, aiming to ensure the optimal operating state of the entire group. Ultimately, these generated coordinated adjustment instructions are sent to the actuators of the corresponding relevant devices, thereby achieving accurate and coordinated control of the entire thermally correlated group, ensuring the stable operation of the HFO-1234yf synthesis process and the achievement of optimization objectives.

[0040] For example, in the control system of the HFO-1234yf synthesis process, multiple heat exchange devices sharing the same cooling water or steam loop in the heat exchange network, such as reactor jacketed heat exchangers, distillation column reboilers, condensers, etc., and shared fluid pump devices that provide power to this loop, such as cooling water circulation pumps or steam booster pumps, are logically grouped into a thermally related group through configuration modules or preset topology recognition algorithms. When an operator issues a parameter adjustment command for cooling water flow rate to a heat exchange device in this group, such as a distillation column condenser, through a human-machine interface (HMI) or upper-level process control system (PCS), the control system immediately collects its operating data in real time from the sensor network connected to each heat exchange device and the shared fluid pump device. This data includes, but is not limited to, inlet temperature, outlet temperature, flow rate, pressure, and pump speed. This real-time data is then input into a preset physical model, which can be a dynamic simulation model built based on programming languages ​​such as MATLAB / Simulink or Python. This model includes the heat transfer characteristics of each heat exchange device, the fluid resistance characteristics of the pipes, and the performance curves of the shared fluid pump. The model simulates and evaluates the impact on the temperature, flow, and pressure distribution of the condenser itself and other heat exchangers (e.g., another reactor cooler) and shared fluid pumps (e.g., cooling water pumps) within the group after receiving a cooling water flow adjustment command. Based on this evaluation, and combined with preset process optimization objectives, such as minimizing energy consumption in the entire HFO-1234yf synthesis process or maintaining stable critical reaction temperatures, an optimization algorithm module generates a series of coordinated adjustment commands for the condenser, other affected heat exchangers, and shared fluid pumps. These commands include adjusting the opening of the condenser cooling water regulating valve, adjusting the opening of related valves in other heat exchangers, and adjusting the speed of the cooling water pumps. Finally, these coordinated adjustment commands are sent to the corresponding programmable logic controllers (PLCs) or intelligent actuators via industrial Ethernet or fieldbus protocols. These PLCs drive the regulating valves or frequency converters, thereby achieving accurate and synchronous control of the relevant equipment and ensuring that the entire thermally related group maintains optimal operating conditions during dynamic changes.

[0041] The steps described in this application for evaluating the impact of response parameter adjustment commands on other devices within the thermally correlated group based on real-time received operating data of each device in the thermally correlated group and a preset physical model include: Based on the real-time received inlet fluid temperature, outlet fluid temperature, inlet fluid flow rate, outlet fluid flow rate, and shared fluid loop pressure value of each heat exchanger in the thermal correlation group, the preset physical model is invoked to simulate the response parameter adjustment instructions. Calculate the impact of the response parameter adjustment command on other heat exchange equipment and / or shared fluid pump equipment within the thermally associated group.

[0042] The pre-set physical model refers to the mathematical description of the equipment and fluid loops in the heat exchange network during the synthesis of HFO-1234yf. It can be implemented using a mechanism model based on first principles, a data-driven black box model, or a gray box model combining both. Its purpose is to accurately reflect the physical behavior and interactions of the system under different operating conditions. Among them, the simulated response parameter adjustment command refers to using the above physical model, inputting the current real-time running data and the parameter command to be adjusted, to predict the dynamic response and steady-state performance of the system after parameter adjustment. Specifically, it can be achieved by numerically solving the model equations, iterative calculation, or running simulation software. Its purpose is to predict the potential consequences of the adjustment before actual operation. The impact of the parameter adjustment command on other heat exchange equipment and / or shared fluid pump equipment in the thermally associated group refers to the quantitative change caused by the parameter adjustment command to the key variables (such as temperature, flow rate, pressure, etc.) of the operating status of other equipment in the thermally associated group. Specifically, it can be determined by comparing the differences in system state parameters before and after the simulation adjustment, or by sensitivity analysis. The purpose is to fully understand the chain effect of the adjustment command on the entire thermally associated group.

[0043] This application's scheme receives detailed real-time operational data from each heat exchanger within a thermally correlated group, including inlet and outlet fluid temperatures, inlet and outlet flow rates, and shared fluid loop pressure. This data comprehensively reflects the current thermodynamic and hydrodynamic state of the heat exchangers, providing accurate initial conditions for subsequent simulations. Based on this, the scheme invokes a pre-set physical model that accurately describes the inherent physical laws and interrelationships of the heat exchangers, pipes, and shared fluid pumps. By inputting real-time data into the physical model and simulating the effects of parameter adjustment commands, the system can predict the dynamic behavior of each device and the shared fluid loop within the thermally correlated group under new operating conditions. This simulation method considers the complex nonlinear interactions between devices in the heat exchange network; for example, a change in the flow rate of one heat exchanger may cause fluctuations in the shared fluid loop pressure, thus affecting the flow distribution to other heat exchangers. It is precisely this simulation based on detailed real-time data and an accurate physical model that enables the system to accurately calculate the impact of responding to parameter adjustment commands on other heat exchangers and / or shared fluid pumps within the thermally correlated group. This calculation of impact not only focuses on the directly affected equipment, but more importantly, it quantifies the cascading effects of adjustments on the entire thermally related group, such as changes in the total flow rate, pressure distribution of shared fluid loops, and the fluid temperature and flow rate of other heat exchangers. This precise impact assessment provides a reliable basis for generating coordinated adjustment commands, thus avoiding control deviations caused by inaccurate assessments and ensuring optimized control of the HFO-1234yf synthesis process. This meticulous assessment mechanism enables the system to more comprehensively understand the potential consequences of parameter adjustments, allowing for a more effective balancing of the needs of various equipment when generating coordinated adjustment commands, achieving global optimized control rather than merely focusing on local adjustments.

[0044] In some embodiments of this application, the step of generating a corresponding coordination adjustment instruction for each relevant device in the thermally related group based on the evaluation results and preset goals can specifically involve analyzing the operating data of each device in the thermally related group and a preset physical model, evaluating the impact of the response parameter adjustment instruction on other devices in the thermally related group, and generating a unified or preliminary coordination adjustment instruction for all relevant devices in the group based on this evaluation result and preset goals. This allows for preliminary overall control of the thermally related group. However, in its implementation, it is not enough to simply generate coordination adjustment instructions for all relevant devices. It is also necessary to consider how to generate more targeted coordination adjustment instructions for different devices, such as a heat exchange device, other affected heat exchange devices, and / or shared fluid pump devices, in combination with optimization goals and constraint goals, to achieve more refined control.

[0045] The steps described in this application for generating a corresponding coordination and adjustment instruction for each relevant device within a thermally correlated group based on the evaluation results and preset targets include: Based on the impact on other heat exchangers and / or shared fluid pumps within the thermally correlated group, the preset optimization objectives, and the preset constraint objectives, a corresponding coordination adjustment instruction is generated for a specific heat exchanger and for the other affected heat exchangers and / or shared fluid pumps.

[0046] The impact on other heat exchangers and / or shared fluid pumps within the thermally correlated group refers to the chain reaction or disturbance caused by adjusting the parameters of a particular heat exchanger on the fluid state parameters in the shared fluid loop, such as fluid temperature, flow rate, and pressure, as well as on the operating parameters of other heat exchangers, such as heat load, heat transfer efficiency, and outlet temperature. The purpose is to comprehensively assess the impact of local adjustments on the overall system stability and performance, providing a basis for subsequent refined instruction generation.

[0047] The preset optimization objective refers to the ideal operating state or performance index that the system is expected to achieve during the HFO-1234yf synthesis process. For example, this may include maximizing product yield, minimizing system energy consumption, extending equipment lifespan, or ensuring the temperature stability of a specific process unit. Its purpose is to guide the generation of coordinated adjustment instructions, causing the system to operate towards optimal conditions. The preset constraint objective refers to the operational restrictions or safety boundaries that must be strictly observed during the HFO-1234yf synthesis process. For example, this may include the maximum / minimum operating temperature of the equipment, pressure limits, flow range, pump speed limits, valve opening limits, and safety interlock conditions in the process flow. Its purpose is to ensure that the system operates within a safe and stable range, avoiding equipment damage or production accidents. Generating a corresponding coordinated adjustment instruction for a specific heat exchanger and for other affected heat exchangers and / or shared fluid pumps means that, for each affected device within the thermally correlated group, based on its specific role in the group, the degree of impact, and its own characteristics, an independent, customized adjustment instruction is calculated and determined to guide it towards the overall optimization objective. This differs from uniform instructions; instead, it emphasizes the personalization and matching of instructions. Its purpose is to achieve refined, distributed control of complex interconnected systems, avoiding suboptimal solutions or negative impacts caused by a "one-size-fits-all" approach.

[0048] This application's solution achieves refined control of the thermally correlated group in the HFO-1234yf synthesis process by comprehensively considering multiple factors when generating coordinated adjustment instructions. Specifically, upon receiving a parameter adjustment instruction from a heat exchanger within the thermally correlated group, the system first assesses the impact of the instruction on other devices within the group based on real-time received operating data from each device and a preset physical model. Building upon this assessment, the solution further incorporates the impact on other heat exchangers and / or shared fluid pumps, preset optimization objectives, and preset constraint objectives as key inputs for instruction generation. Thus, the system no longer generates a uniform instruction based solely on a general assessment result and preset objectives, but can specifically analyze the specific status and needs of each affected device (including the heat exchanger that initially issued the adjustment instruction, and other affected heat exchangers and / or shared fluid pumps). By considering the impact on other devices (e.g., the total flow rate, pressure distribution, fluid temperature of the shared fluid loop, and the fluid flow rate and temperature of other heat exchangers), it ensures that local adjustments do not trigger a global negative chain reaction. Simultaneously, by incorporating preset optimization objectives (e.g., minimizing temperature fluctuations, maintaining stable total fluid flow, and / or optimizing the energy consumption of shared fluid pumps), the generation of instructions is guided towards the optimal direction of overall system performance. Furthermore, by strictly adhering to preset constraints (e.g., the safe temperature range of process units, operating limitations of shared fluid pumps), it is ensured that any adjustments are made within safe boundaries, avoiding potential risks. It is precisely because of this multi-dimensional and personalized consideration that the system can generate a corresponding coordinated adjustment instruction for each relevant device within the group. This means that each instruction is tailored to a specific device, precisely guiding how that device should adjust its operating parameters to collectively achieve the overall optimization objective while meeting safety and constraint conditions. This refined instruction generation mechanism effectively solves the problems of insufficient control precision, inability to fully utilize device characteristics, and difficulty in handling complex operating conditions that may arise when generating coordinated adjustment instructions only for all relevant devices, thereby significantly improving the control effect and operating efficiency of the HFO-1234yf synthesis process.

[0049] Through the above technical solution, during the HFO-1234yf synthesis process, a corresponding coordinated adjustment command can be generated for a specific heat exchanger and for each of the affected heat exchangers and / or shared fluid pumps, based on the impact on other heat exchangers and / or shared fluid pumps within the thermally correlated group, preset optimization objectives, and preset constraint objectives. This enables the system to achieve fine-grained control of the thermally correlated group, avoiding suboptimal operation or local instability that might result from a "one-size-fits-all" command. By tailoring adjustment commands to each device, the mutual influence between devices can be balanced more effectively, ensuring that the entire heat exchange network maintains stable operation under complex conditions, while also considering production efficiency, energy consumption optimization, and operational safety. This personalized command generation mechanism significantly improves the control accuracy and adaptability of the HFO-1234yf synthesis process.

[0050] In some embodiments described above in this application, based on the impact on other heat exchangers and / or shared fluid pumps within the thermally correlated group, preset optimization objectives, and preset constraint objectives, a corresponding coordinated adjustment instruction is generated for a specific heat exchanger and for the other affected heat exchangers and / or shared fluid pumps. Specifically, generating this coordinated adjustment instruction can involve analyzing the complex coupling relationships between devices within the thermally correlated group, combining preset optimization objectives (e.g., minimizing energy consumption, maintaining stable total fluid flow) and constraint objectives (e.g., safe temperature range, device operating limitations), and calculating the adjustment amount and direction that each relevant device (including the heat exchanger that initially triggered the adjustment, the other affected heat exchangers, and the shared fluid pumps) should perform. This allows for preliminary optimized control of the HFO-1234yf synthesis process. However, in its implementation, coordinated adjustment instructions generated solely based on preset models and evaluation results may not fully adapt to real-time changes in system operation. Due to factors such as sensor measurement delays and errors, device performance degradation, and unmodeled disturbances, the system state may deviate from model predictions, resulting in coordinated adjustment instructions that are not optimal or even have a counterproductive effect. Therefore, how to calibrate the coordinated adjustment commands based on real-time feedback information to improve the accuracy and adaptability of control is a problem that needs to be solved.

[0051] In this regard, after the step of generating a corresponding coordination and adjustment instruction for each relevant device in the thermally related group based on the evaluation results and preset goals, this application further includes: Real-time monitoring of the valve opening information of each heat exchanger in the thermally correlated group, as well as the speed information of the shared fluid pump equipment; Real-time monitoring of temperature measurements and corresponding temperature change rates of each heat exchanger and shared fluid pump within the thermally correlated group; Each coordinated adjustment command is calibrated based on the valve opening information, speed information, temperature measurement value, and corresponding temperature change rate. Each calibrated coordination adjustment instruction is sent to the corresponding actuator of the relevant equipment.

[0052] Calibration refers to the process of correcting or adjusting the generated coordination and adjustment instructions based on the deviation between the actual operating state of the system and the expected target. Specifically, it can be achieved through feedback control algorithms, adaptive control strategies, or data-driven machine learning models. Its purpose is to improve the accuracy and adaptability of the instructions and ensure that the control system can make precise adjustments according to the real-time changing environment.

[0053] This application's solution improves the accuracy and adaptability of parameter optimization control in the HFO-1234yf synthesis process by introducing a real-time feedback-based calibration step after generating the coordinated adjustment command. Specifically, after the system initially generates the coordinated adjustment command based on the evaluation results and preset targets, the solution immediately initiates real-time monitoring of the valve opening information of each heat exchanger in the thermally correlated group and the rotational speed information of the shared fluid pump. The real-time data of these operating parameters directly reflects the current operating status of the equipment and the actual adjustment effect on fluid flow, providing a direct basis for subsequent calibration. Simultaneously, the solution also monitors the temperature measurements and corresponding temperature change rates of each heat exchanger and shared fluid pump in real time. Temperature, as a key process parameter in the HFO-1234yf synthesis process, accurately reflects the heat load status and trend of the process unit through its measured values ​​and change rates. By comprehensively utilizing these real-time acquired valve opening information, rotational speed information, temperature measurements, and temperature change rates, the system can perform refined calibration on each initially generated coordinated adjustment command. This calibration process identifies deviations between the actual system state and model predictions caused by factors such as sensor latency, equipment performance degradation, or unmodeled disturbances, and corrects the commands accordingly. For example, if monitoring data shows that the actual temperature change rate of a heat exchanger does not match the expected effect of the command, the system can dynamically adjust the amplitude or direction of the command to eliminate the deviation. Finally, these calibrated commands are sent to the actuators of the corresponding equipment to ensure that the control system can accurately adjust according to the actual operating state of the HFO-1234yf synthesis process. This real-time feedback calibration mechanism, together with the previous steps of evaluating and generating commands based on the physical model, forms a closed-loop optimized control system. This makes the control commands no longer static preset values, but dynamically adaptable to transient changes and uncertainties, thereby continuously maintaining the stable operation of the HFO-1234yf synthesis process in complex and ever-changing industrial environments and further optimizing its performance.

[0054] The step of calibrating each coordinated adjustment command based on the control valve opening information, rotational speed information, temperature measurement value, and corresponding temperature change rate, as described in this application, includes: For each coordinated adjustment command, based on the control valve opening information, speed information, temperature measurement value, and corresponding temperature change rate, assess the consequences of responding to the coordinated adjustment command. Determine the calibration strategy for coordinating and adjusting instructions based on the expected consequences. The coordinated adjustment instructions are calibrated according to the calibration strategy.

[0055] The assessment of the consequences of responding to coordinated adjustment commands refers to the prediction of potential changes in the system state after executing a specific coordinated adjustment command. This can be achieved by establishing predictive models, such as physical models, data-driven models, or hybrid models, to analyze real-time operating data such as valve opening information, rotational speed information, temperature measurements, and corresponding temperature change rates. The aim is to simulate the dynamic response of the system after command execution, identifying potential deviations or risks in advance to provide a basis for subsequent command calibration. The anticipated consequences refer to the predicted future state of the system, specifically temperature overshoot, insufficient flow, and pressure fluctuations. The purpose is to clarify the potential impact of command execution on system stability and performance. The calibration strategy for coordinated adjustment commands refers to the specific correction schemes developed based on the assessed anticipated consequences to correct the coordinated adjustment commands. This can be achieved through a pre-set rule base, expert system, or optimization algorithm, selecting or generating corresponding adjustment rules based on the nature and severity of the consequences. For example, if temperature overshoot is predicted, the strategy might be to reduce the command amplitude; if insufficient flow is predicted, the strategy might be to increase the command amplitude. The purpose is to provide targeted correction guidance to ensure the effectiveness of calibration.

[0056] Through the above technical solution, this application overcomes the limitations of calibrating commands solely based on current operating data, effectively avoiding control deviations caused by insufficient prediction of command execution consequences. By introducing prediction and evaluation of the system state after responding to coordination and adjustment commands during the calibration process, and formulating targeted calibration strategies accordingly, it can be ensured that the impact of coordination and adjustment commands on the future operation of the system has been fully considered before being sent to the actuator. This significantly improves the accuracy and stability of parameter optimization control in the HFO-1234yf synthesis process, reduces the risk of process fluctuations, and helps maintain the system in a more optimized operating state.

[0057] In some embodiments described above in this application, a coordinated control of heat exchange equipment and shared fluid pump equipment within a thermally correlated group during the HFO-1234yf synthesis process is proposed. Specifically, this coordinated control involves assessing the impact on other equipment based on real-time operating data and a preset physical model when a parameter adjustment command is received from a heat exchange equipment within the thermally correlated group, and generating a coordinated adjustment command to optimize process parameters. This ensures the stable operation and parameter optimization of the entire thermally correlated group during local adjustments. However, in its implementation, when the production load needs to be adjusted, the response to load changes is delayed due to thermal inertia and fluid transmission delay in the heat exchange network. If adjustments are made only based on current operating data, future load demands may not be met, leading to system instability or reduced efficiency. Therefore, how to predict heat load demand trends in advance based on load adjustment requests and make forward-looking adjustments is a technical problem that needs to be solved.

[0058] In response, this application further proposes a method for optimizing and controlling the parameters of the HFO-1234yf synthesis process, which also includes: When a load adjustment request is received, the target load and load increase rate are determined based on the load adjustment request; Based on the target load, load increase rate, and the inherent thermal inertia of each process unit and heat exchange network during the HFO-1234yf synthesis process, as well as the fluid transmission delay characteristics in the pipeline, the heat load demand trend of each heat exchange device in the thermally related group is predicted within a set time in the future. Based on the heat load demand trend of each heat exchanger in the thermally related group within a future set time, a sequence of adjustment instructions carrying timing is generated. Based on the timing sequence of each adjustment instruction in the adjustment instruction sequence, the corresponding adjustment instruction is sent to the execution mechanism of the corresponding device at the corresponding timing point.

[0059] Inherent thermal inertia refers to the hysteresis of the temperature response of heat exchange equipment or process units when heat input or output changes. It can be reflected in factors such as the heat capacity of the equipment materials, fluid retention, and heat transfer resistance, and its purpose is to characterize the system's response speed to changes in heat load. Fluid transport delay characteristics in pipes refer to the time required for fluid to travel from one point to another, which can be determined by factors such as pipe length, fluid velocity, and fluid viscosity. Its purpose is to reflect the hysteresis of heat or pressure transfer in the heat exchange network. Future set time refers to a predetermined period of time after the current moment, which can be determined based on production plans and load. The adjustment urgency and system response time are set to provide a time window for forward-looking prediction. Among them, the heat load demand trend refers to the direction and magnitude of the change in the heat required or the heat to be removed from each heat exchanger in the heat-related group within a set future time. It can be expressed as an increase, decrease or stabilization of the heat load. Its purpose is to guide the generation of subsequent adjustment instructions. Among them, the time-series adjustment instruction sequence refers to a set of multiple adjustment instructions. Each adjustment instruction is accompanied by a predetermined execution time point, which can be a timestamp or a delay relative to the current time. Its purpose is to realize time-sharing control of equipment operating parameters.

[0060] This application's solution effectively addresses the load adjustment challenges during the HFO-1234yf synthesis process by introducing a forward-looking control strategy. Specifically, upon receiving a load adjustment request, the system first clarifies the target load and load increase rate based on the request, providing a benchmark for subsequent prediction and control. Building upon this, the solution further considers the inherent thermal inertia of each process unit and heat exchange network during HFO-1234yf synthesis, as well as the fluid transport delay characteristics in pipelines. Due to these physical characteristics, the system can predict the heat load demand trends of each heat exchanger in the thermally correlated group within a set future timeframe. This predictive mechanism enables the control system to overcome the response lag problem caused by thermal inertia and transport delays in traditional control, thereby avoiding system instability or efficiency reduction during load changes. Based on the prediction of future heat load demand trends, the system can generate a sequence of adjustment commands with timing information. This sequence not only includes adjustments to equipment operating parameters but, more importantly, assigns a predetermined execution time point to each adjustment command. This time-sequential instruction design enables the system to adjust equipment within the thermally correlated group in stages and rhythmically according to a predetermined schedule, thereby achieving more precise and proactive control of the heat exchange network. Ultimately, based on the timing of each instruction in the adjustment instruction sequence, the system sends the corresponding adjustment instruction to the actuator of the relevant equipment at the corresponding time point. This time-sequential execution mechanism ensures that the heat exchange network can respond to load changes promptly and accurately, maintaining stable system operation and optimized performance. Combined with previous technical solutions, this approach achieves a more comprehensive and robust control effect. Previous technical solutions focused on real-time coordination and calibration of other equipment within the thermally correlated group upon receiving a single equipment parameter adjustment instruction to maintain local stability and optimization. This solution, however, at the macro-load adjustment level, generates a global, time-sequential adjustment strategy by predicting future heat load demands. When these time-sequential adjustment instructions are sent to the equipment actuators, they can be received and processed by the real-time coordination and calibration mechanisms of previous technical solutions. This means that the predictive adjustment commands provided by this solution can serve as input or guidance for previous technical solutions, enabling real-time coordination of those solutions to move beyond passively responding to adjustments of individual devices and instead operate within a more forward-looking framework. In this way, the system can not only cope with sudden local disturbances but also proactively adapt to overall changes in production load. This ensures stable operation of the HFO-1234yf synthesis process while further improving overall energy efficiency and production efficiency, effectively solving the technical problems of system response lag, operational instability, and difficulty in achieving global optimization under rapid load changes.

[0061] The heat load demand trend of each heat exchanger described in this application is: the change trend of the heat load required by each heat exchanger or the heat that needs to be removed; the step of generating a sequence of adjustment instructions carrying time according to the heat load demand trend of each heat exchanger in the heat-related group within a future set time period specifically includes: determining the adjustment direction and adjustment range for each heat exchanger within a future set time period based on the change trend of the heat load required by each heat exchanger in the heat-related group within a future set time period; for each heat exchanger, generating a sequence of adjustment instructions carrying time according to the determined adjustment method and adjustment range within the future set time period; for each heat exchanger, the sequence of adjustment instructions carrying time includes: multiple adjustment instructions carrying different time sequences.

[0062] Among them, the trend of heat load or heat removal required by each heat exchanger refers to the change pattern of heat demand or heat removal capacity of each heat exchanger within a set time in the future. It can be manifested as a continuous increase, a continuous decrease, an increase followed by a decrease, a decrease followed by an increase, or fluctuation within a certain range, etc. The purpose is to provide a basis for the generation of subsequent adjustment instructions and ensure that the control strategy can respond to different types of heat load changes.

[0063] This application's solution improves the accuracy and effectiveness of control by defining the heat load demand trend by type and refining the generation process of adjustment instructions. Specifically, firstly, the heat load demand trend of each heat exchanger is defined as the change trend of the required heat load or the heat that needs to be removed from each heat exchanger. This allows the system to distinguish whether the equipment needs to absorb or dissipate heat, providing classification information for subsequent control decisions. Secondly, based on the change trend of the required heat load or the heat that needs to be removed from each heat exchanger in the heat-related group within a future set time, the adjustment direction and adjustment magnitude for each heat exchanger at the future set time are determined. This step transforms the trend information into executable control parameters, clarifying whether to increase or decrease the heat load and the intensity of the adjustment, thereby ensuring that the control action matches the heat load demand. Then, for each heat exchanger, a sequence of adjustment instructions carrying a time sequence is generated based on the determined adjustment method and adjustment magnitude at the future set time. This process transforms the control parameters into a series of instructions that take effect at different times, enabling the system to dynamically adjust. Finally, for each heat exchanger, the timing-based adjustment command sequence includes multiple adjustment commands with different timing sequences. This means the system can generate a schedule for each device, executing specific adjustment actions at predetermined times to better adapt to changing heat load demands and maintain stable system operation. Through the above refinement and improvement, this solution, based on the original prediction of heat load demand trends, further clarifies the types of trends and transforms them into specific, timing-based adjustment commands, enabling the overall control strategy to move from prediction to execution guidance. This understanding of heat load demand trends and the generation of adjustment command sequences allow the system to predict and respond to the transient behavior of the heat exchange network during load adjustments during the HFO-1234yf synthesis process. This overcomes the problem of insufficient command generation in traditional methods when dealing with complex operating conditions, ensuring that the adjustment command sequence accurately guides the operation of heat exchangers and thus achieves continuous optimization of the operating parameters of the entire heat exchange network.

[0064] The physical model described in this application includes: a heat transfer model for each heat exchanger in a thermally correlated group, a fluid resistance model for pipes in the heat exchange network, and a performance curve model for shared fluid pump equipment.

[0065] In this context, the heat transfer model of each heat exchanger in the thermal correlation group refers to a mathematical or physical expression describing the heat transfer law within the heat exchanger. It can reflect the relationship between key parameters such as heat transfer efficiency, heat transfer coefficient, and heat transfer area and operating conditions. It can be implemented using steady-state or dynamic heat transfer equations based on the principle of energy conservation, or heat transfer coefficient calculation methods based on empirical correlations. The purpose is to accurately predict the heat load changes and outlet temperature response of the heat exchanger under different operating conditions.

[0066] In a heat exchanger network, the fluid resistance model in a pipe refers to a mathematical model that describes the frictional resistance, local resistance, and resulting pressure loss experienced by a fluid flowing through a pipe. It can be implemented using the Darcy-Wiesbach formula, the Fanning friction coefficient formula, or empirical formulas based on the Reynolds number and relative roughness. The purpose is to accurately calculate the pressure drop and flow distribution of the fluid during its transmission within the heat exchanger network, thereby assessing its impact on the operating status of other equipment.

[0067] A performance curve model for a shared fluid pump system refers to a curve or mathematical expression describing the relationship between the pump's head, flow rate, efficiency, and shaft power at different speeds or operating conditions. It can be implemented using a multiple regression model fitted to experimental data provided by the pump manufacturer, or a scaling model based on the law of similarity. The aim is to accurately predict the pump's operating point under different loads, thereby assessing its impact on the flow rate and pressure of the entire fluid loop.

[0068] This application's solution improves the accuracy of assessing the inter-device interactions in the heat exchanger network during the HFO-1234yf synthesis process by constructing a more refined and comprehensive physical model. Specifically, when a parameter adjustment command is received from a heat exchanger within a thermally correlated group, the system no longer relies on a simplified general model. Instead, it comprehensively utilizes the heat transfer model of each heat exchanger within the thermally correlated group, the pipe fluid resistance model in the heat exchanger network, and the performance curve model of the shared fluid pump. These models work together to more accurately simulate the cascading effects of the parameter adjustment command on the total flow rate, pressure distribution, fluid temperature, and fluid flow rate and temperature of other heat exchangers within the entire thermally correlated group. For example, the heat transfer model can accurately predict the changes in heat load and outlet temperature of a specific heat exchanger after adjustment, the pipe fluid resistance model can calculate the pressure loss and flow redistribution of fluid in complex pipe networks, and the performance curve model of the shared fluid pump can reflect the impact of the pump on fluid dynamics under different operating conditions. It is precisely because these models accurately characterize the complex characteristics of the system that the assessment results of the impact of the parameter adjustment command are closer to reality, thereby enabling the generation of more accurate and effective coordinated adjustment commands for each relevant device within the thermally correlated group. This precise evaluation capability enables the entire parameter optimization control method to more effectively cope with frequent load adjustments and complex inter-equipment relationships during the HFO-1234yf synthesis process, avoiding evaluation deviations caused by inaccurate models, thereby improving the overall effect and stability of coordinated control.

[0069] In some embodiments described above, a corresponding coordination adjustment instruction is generated for each relevant device within a thermally correlated group based on evaluation results and preset targets. Specifically, this generation of the coordination adjustment instruction can be achieved by conducting a preliminary assessment of the impact on other devices within the thermally correlated group, using simple temperature stability and flow balance as optimization targets, while considering the basic operational limitations of the devices as constraint targets. This allows for preliminary coordinated control of the heat exchange network. However, in its implementation, the definition of "impact on other devices within the thermally correlated group" is not specific enough, and the optimization and constraint targets are set too generally, failing to fully consider the complexity and variability of the HFO-1234yf synthesis process. This results in the generated coordination adjustment instruction potentially being unable to effectively address issues such as frequent load adjustments, rapid response lag, nonlinear correlations between multiple heat exchangers, data delays and errors, and device performance degradation, leading to unsatisfactory optimized control of the heat exchange network. Therefore, how to more specifically define "impact on other devices within the thermally correlated group," and how to set "optimization targets" and "constraint targets" to ensure that the coordination adjustment instruction can effectively solve the above problems, is the technical problem this solution aims to solve.

[0070] This application further proposes specific definitions for the impact on other devices within the thermally correlated group, the optimization objective, and the constraint objective when generating coordinated adjustment instructions: The impact on other equipment within the thermally associated group refers to the impact on the total flow rate of the entire shared fluid loop, the pressure distribution of the shared fluid loop, the fluid temperature in the shared fluid loop, and the fluid flow rate and fluid temperature of other heat exchange equipment. The optimization objectives are: to minimize temperature fluctuations, maintain stable total fluid flow, and / or optimize energy consumption of shared fluid pump equipment in each process unit of the HFO-1234yf synthesis process; The constraints are: the safe temperature range for each process unit in the HFO-1234yf synthesis process, and the operational limitations of the shared fluid pump equipment.

[0071] The impact on other equipment within the thermally correlated group refers to the chain reaction triggered by the adjustment of the operating parameters of a heat exchanger within the group during the HFO-1234yf synthesis process. This impact affects other equipment sharing the same fluid loop and the overall loop operation. Specifically, it manifests as changes in the total flow rate, pressure distribution, and fluid temperature within the shared fluid loop, as well as the flow rate and temperature of other heat exchangers. The aim is to comprehensively quantify the multi-dimensional effects of a single equipment adjustment on the entire interconnected system, providing an accurate assessment basis for subsequent coordinated control. The optimization objective refers to adjusting equipment parameters during the operation of the heat exchange network in the HFO-1234yf synthesis process to achieve optimal performance. The desired performance indicators can specifically include minimizing temperature fluctuations, maintaining stable total fluid flow, and / or optimizing the energy consumption of shared fluid pump equipment in each process unit of the HFO-1234yf synthesis process. The purpose is to guide the generation of coordinated adjustment instructions so that they can develop in the direction of improving product quality and reducing energy consumption. Among them, the constraint objectives refer to the operating restrictions that must be strictly followed in the operation of the heat exchange network in the HFO-1234yf synthesis process. Specifically, these can include the safe temperature range of each process unit in the HFO-1234yf synthesis process and the operating restrictions of shared fluid pump equipment. The purpose is to ensure that the generation of coordinated adjustment instructions does not violate safety regulations and equipment restrictions, thereby ensuring the stability and safety of production.

[0072] This application's solution achieves precise generation of coordinated adjustment commands by finely defining the operating parameters of the thermally correlated groups within the heat exchanger network during the HFO-1234yf synthesis process. Specifically, when a heat exchanger within the thermally correlated group receives a parameter adjustment command, the system first assesses the impact of the adjustment on other devices within the group based on real-time operating data and a preset physical model. During this assessment, this solution clarifies the specific dimensions of the "impact on other devices within the thermally correlated group," including the impact on the total flow rate of the entire shared fluid loop, the pressure distribution of the shared fluid loop, the fluid temperature in the shared fluid loop, and the fluid flow rate and temperature of other heat exchangers. It is precisely this comprehensive consideration of these key influencing factors that enables the system to accurately capture the chain reaction triggered by a single device adjustment in a highly interconnected heat exchanger network, avoiding the global imbalance caused by local optimization in traditional control. Based on this, when generating coordinated adjustment commands, the system no longer relies solely on general preset targets but introduces explicit optimization and constraint targets. The optimization objectives were set to minimize temperature fluctuations, maintain stable total fluid flow, and / or optimize the energy consumption of shared fluid pumps in each process unit of the HFO-1234yf synthesis process. These objectives directly address the stringent temperature control requirements, system operational stability, and energy efficiency improvement needs of the HFO-1234yf synthesis process. Simultaneously, constraint objectives were set as the safe temperature range for each process unit and the operational limitations of shared fluid pumps in the HFO-1234yf synthesis process. This ensures that while pursuing optimization effects, the production process remains within a safe and controllable range, avoiding safety risks or equipment damage caused by over-optimization. It is precisely this specific and multi-dimensional consideration of the influencing, optimization, and constraint objectives that makes the generated coordination and adjustment instructions more targeted and effective. This refined definition and evaluation, combined with the instruction generation steps, enables the system to overcome complex problems faced by the heat exchange network in the HFO-1234yf synthesis process, such as frequent load adjustments, rapid response lag, nonlinear correlations between multiple heat exchangers, data latency and errors, and equipment performance degradation. In this way, the system can achieve continuous and global optimization of the operating parameters of the entire heat exchange network, thereby further improving production efficiency and economic benefits while ensuring product quality and production safety.

[0073] In some embodiments described above, this application proposes a method for parameter optimization control of the heat exchanger network during the HFO-1234yf synthesis process. Specifically, this method can achieve optimized control of the heat exchanger network by identifying thermally correlated groups, assessing the impact of parameter adjustments, generating coordinated adjustment instructions, and sending these instructions. This enables continuous and global optimization of the heat exchanger network's operating parameters. However, its implementation merely provides a control logic or operational process, lacking specific hardware or software to support and execute these calculations and instruction distributions. This may lead to difficulties in efficiently and stably deploying and operating the method in real industrial environments, failing to adequately address the challenges faced by the heat exchanger network during HFO-1234yf synthesis, and hindering the continuous and global optimization of the entire heat exchanger network's operating parameters while simultaneously satisfying multiple objectives such as maximizing product yield, minimizing energy consumption, extending equipment life, and ensuring stable process operation.

[0074] In response, this application further proposes a parameter optimization and control system for the HFO-1234yf synthesis process, see [link to relevant documentation]. Figure 2 It includes: a summarization module 110, an evaluation module 120, a generation module 130, and a sending module 140. The summarization module 110 is used to summarize multiple heat exchange devices sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process, as well as fluid-sharing pump devices, into a single thermally related group. The evaluation module 120, upon receiving a parameter adjustment instruction from a heat exchange device within the thermally related group, evaluates the impact of responding to the parameter adjustment instruction on other devices within the thermally related group based on real-time received operating data of each device and a preset physical model. The generation module 130, based on the evaluation results and preset targets, generates a corresponding coordination adjustment instruction for each related device within the thermally related group. The sending module 140 sends each coordination adjustment instruction to the corresponding execution mechanism of the related device. The related devices, in addition to a specific heat exchange device, also include other heat exchange devices and / or shared fluid pump devices within the thermally related group.

[0075] The induction module 110 is a functional unit within the system. Its function is to logically group devices with thermodynamic or fluid connectivity within the heat exchange network during the HFO-1234yf synthesis process. Specifically, it can be a software program running on an industrial control computer or dedicated controller. Through preset configuration rules or topology analysis algorithms, it identifies and defines these thermally related groups. The purpose is to provide a foundation for subsequent overall optimization control, ensuring coordinated management of mutually influencing devices. A thermally related group refers to a collection of multiple heat exchange devices and fluid pumps sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process. These devices influence each other due to sharing the fluid loop, forming a unit requiring overall coordinated control. The evaluation module 120 is a functional unit within the system. Its function is to receive parameter adjustment commands from a specific heat exchanger and, using real-time operating data and a pre-set physical model, predict the potential impact of the adjustment on other devices within the thermally correlated group. Specifically, it can be a software module based on a model predictive control algorithm, running on a computing platform. By simulating the system response under different parameter adjustment scenarios, it quantifies the chain reaction on the operating status of other devices. Its purpose is to avoid global imbalance caused by local adjustments and to provide a predictive basis for generating coordinated adjustment commands. The parameter adjustment command refers to a control command issued to a specific heat exchanger within the thermally correlated group, aimed at changing its operating state. Specifically, it can be a setpoint signal, such as a regulating valve opening, pump speed, or target temperature, intended to initiate local optimization or corrective operations on that device. Operating data refers to the real-time operating parameter information collected from each device within the thermally correlated group, specifically including sensor measurements such as temperature, flow rate, pressure, and liquid level. Its purpose is to provide information on the current state of the system as a basis for evaluation and decision-making. The physical model refers to the mathematical model describing the behavior of equipment and fluids in the heat exchange network of the HFO-1234yf synthesis process. Specifically, it may include heat transfer models of the heat exchange equipment, fluid resistance models of the pipelines, and performance curve models of the shared fluid pump equipment. Its purpose is to simulate the system's response under different operating conditions, supporting the evaluation module 120 in predicting impacts. The preset objectives refer to the performance indicators to be achieved in the parameter optimization and control of the HFO-1234yf synthesis process. Specifically, these may include maximizing product yield, minimizing energy consumption, extending equipment lifespan, and ensuring stable process operation. Their purpose is to provide the generation module 130 with optimization directions and decision-making basis.The generation module 130 is a functional unit in the system. Its function is to calculate and generate coordinated adjustment instructions for all relevant devices within the thermally correlated group based on the prediction results of the evaluation module 120 and the preset optimization objectives. Specifically, it can be an optimization algorithm module, such as an algorithm based on multi-objective optimization or model predictive control, running on an industrial control computer. Based on the evaluated impact and preset objectives, it calculates the adjustment amount for each device. Its purpose is to achieve global optimization control of the entire thermally correlated group and ensure the coordinated achievement of multiple objectives. The coordinated adjustment instruction refers to the control command calculated and generated by the generation module 130 for each relevant device within the thermally correlated group, which aims to coordinately adjust its operating state. Specifically, it can be a setpoint signal, such as the valve opening, pump speed, or target temperature. Its purpose is to ensure that all devices within the group can cooperate with each other when adjusting parameters, jointly moving towards the optimization objective. The sending module 140 is a functional unit in the system. Its function is to transmit the generated coordination adjustment instructions to the actuators of the corresponding devices. Specifically, it can be a communication interface module that sends the instructions to a DCS (Distributed Control System) or PLC (Programmable Logic Controller) via industrial Ethernet, fieldbus, or wireless communication protocols. Its purpose is to translate the control instructions into actual equipment actions, thereby achieving physical control of the heat exchange network. The actuator refers to the equipment component that receives and executes the coordination adjustment instructions. Specifically, it can include regulating valves, frequency converter-controlled pumps, heaters, or coolers, etc. Its purpose is to change the operating state of the equipment according to the instructions, thereby affecting the parameters of the heat exchange network. Related equipment refers to other affected heat exchange devices and shared fluid pump devices within the thermally correlated group, in addition to the heat exchange device that initially received the parameter adjustment instruction. Its purpose is to clarify the scope of application of the coordination adjustment instructions and ensure control of the entire thermally correlated group.

[0076] This application's solution achieves parameter optimization control of the heat exchange network during HFO-1234yf synthesis by introducing a modular system architecture. The system first uses an induction module 110 to group multiple heat exchange devices sharing the same fluid loop and fluid pumps within the HFO-1234yf synthesis heat exchange network into a single thermally related group. This induction is based on an understanding of the inherent thermodynamic and fluid dynamic relationships between these devices, ensuring the integrity and coordination of subsequent control. When a heat exchange device within the thermally related group receives a parameter adjustment command, an evaluation module 120 immediately activates. Based on real-time received operating data from each device within the group and a preset physical model, it evaluates the potential impact of the parameter adjustment on other devices within the group. This evaluation process predicts the cascading effects of the parameter adjustment command on the overall system state, thus avoiding the global fluctuations or deviations that may occur with traditional single-point control. Based on the prediction results of the evaluation module 120 and the preset optimization objectives, a generation module 130 generates a corresponding coordinated adjustment command for each relevant device within the thermally related group. These instructions are not isolated but calculated to achieve synergistic optimization of the entire group under multiple objectives, such as maximizing product yield, minimizing energy consumption, extending equipment life, and ensuring stable process operation. Finally, the sending module 140 sends these coordinated adjustment instructions to the actuators of the corresponding relevant equipment, thereby translating the calculated optimization strategy into actual equipment actions. The relevant equipment includes not only the initially adjusted heat exchangers but also other affected heat exchangers and shared fluid pumps within the group, ensuring comprehensive control. Through this systematic operation, the system of this application provides the physical and logical carrier for the parameter optimization control method of the HFO-1234yf synthesis process. It transforms control logic into an executable automated process, enabling complex method steps to operate efficiently and stably in a real industrial environment. This combination of system and method overcomes the limitations of implementing a single method, making continuous and global optimization of the operating parameters of the heat exchanger network during the HFO-1234yf synthesis process possible, thus effectively addressing a series of challenges such as frequent load adjustments, transient response lags, complex multi-equipment relationships, data latency and errors, and equipment performance degradation. The system is capable of real-time sensing, decision-making, and coordinated control, ensuring the stability, efficiency, and safety of the HFO-1234yf production process.

[0077] Through the above technical solution, this application provides a parameter optimization control system for the HFO-1234yf synthesis process. This system achieves automated, global parameter optimization control of the heat exchange network during the HFO-1234yf synthesis process through the identification of thermally related groups by the induction module 110, the prediction of the impact of parameter adjustments by the evaluation module 120, the calculation of coordinated adjustment commands by the generation module 130, and the execution of commands by the sending module 140. This system provides a physical carrier and execution platform for complex methods, overcoming the limitations of simple methods in efficient and stable deployment in practical industrial applications. The system can sense and respond to dynamic changes in the heat exchange network in real time, effectively coordinating multiple interconnected devices. Therefore, it ensures the stable operation of the HFO-1234yf synthesis process while addressing challenges such as frequent load adjustments, transient response lags, complex multi-device relationships, sensor data delays and errors, and equipment performance degradation. Simultaneously, it improves product yield, reduces energy consumption, and extends equipment lifespan.

[0078] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for optimizing and controlling parameters in the synthesis process of HFO-1234yf, characterized in that, Includes the following steps: Multiple heat exchange devices sharing the same fluid loop within the heat exchange network during the HFO-1234yf synthesis process, as well as the fluid pump devices sharing the fluid, are grouped into the same thermal association group. When a parameter adjustment command is received from a heat exchanger within the thermally correlated group, the impact on other devices within the thermally correlated group after responding to the parameter adjustment command is evaluated based on the real-time operating data of each device within the thermally correlated group and the preset physical model. Based on the evaluation results and preset goals, a corresponding coordination and adjustment instruction is generated for each relevant device in the thermal association group; Each coordination and adjustment instruction is sent to the corresponding execution mechanism of the relevant equipment; The related equipment, in addition to the aforementioned heat exchange equipment, also includes other heat exchange equipment within the thermal association group and / or the shared fluid pump equipment.

2. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 1, characterized in that, The steps for evaluating the impact on other devices within the thermally correlated group based on the real-time received operating data of each device in the thermally correlated group and the preset physical model specifically include: Based on the inlet fluid temperature, outlet fluid temperature, inlet fluid flow rate, outlet fluid flow rate, and shared fluid loop pressure value of each heat exchanger in the thermally correlated group received in real time, a preset physical model is invoked to simulate the response to the parameter adjustment command. Calculate the impact on other heat exchange devices and / or the shared fluid pump device within the thermally associated group after responding to the parameter adjustment command.

3. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 1, characterized in that, Based on the evaluation results and preset goals, the specific steps for generating a corresponding coordination and adjustment instruction for each relevant device within the thermally correlated group include: Based on the impact on other heat exchange devices and / or the shared fluid pump device within the thermally related group, the preset optimization objectives, and the preset constraint objectives, a corresponding coordination adjustment instruction is generated for each heat exchange device, as well as for the other affected heat exchange devices and / or the shared fluid pump device.

4. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 1, characterized in that, Following the step of generating a corresponding coordination adjustment instruction for each relevant device within the thermally correlated group based on the evaluation results and preset targets, the process further includes: Real-time monitoring of the valve opening information of each heat exchanger in the thermally correlated group, as well as the rotational speed information of the shared fluid pump; Real-time monitoring of the temperature measurements and corresponding temperature change rates of each heat exchanger and shared fluid pump within the thermally correlated group; Each coordinated adjustment command is calibrated based on the valve opening information, the rotation speed information, the temperature measurement value, and the corresponding temperature change rate. The specific steps for sending each coordination and adjustment instruction to the corresponding relevant device's actuator are as follows: Each calibrated coordination adjustment instruction is sent to the corresponding actuator of the relevant equipment.

5. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 4, characterized in that, The step of calibrating each coordinated adjustment command based on the regulating valve opening information, the rotational speed information, the temperature measurement value, and the corresponding temperature change rate specifically includes: For each coordinated adjustment command, based on the regulating valve opening information, the rotation speed information, the temperature measurement value, and the corresponding temperature change rate, the consequences of responding to the coordinated adjustment command are evaluated. Based on the expected consequences, determine the calibration strategy for coordinating and adjusting the instructions; The coordinated adjustment instructions are calibrated according to the calibration strategy.

6. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to any one of claims 1 to 5, characterized in that, Also includes: When a load adjustment request is received, the target load and load increase rate are determined based on the load adjustment request; Based on the target load, load increase rate, inherent thermal inertia of each process unit and heat exchange network during HFO-1234yf synthesis, and fluid transport delay characteristics in pipelines, the heat load demand trend of each heat exchange device in the thermally related group is predicted within a set time period in the future. Based on the heat load demand trend of each heat exchanger in the thermally related group within a future set time period, a sequence of adjustment instructions carrying timing is generated; Based on the timing sequence of each adjustment instruction in the adjustment instruction sequence, the corresponding adjustment instruction is sent to the execution mechanism of the corresponding device at the corresponding timing point.

7. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 6, characterized in that, The heat load demand trend of each heat exchanger is: the change trend of the heat load required by each heat exchanger or the heat that needs to be removed. The step of generating a time-series adjustment instruction sequence based on the heat load demand trend of each heat exchanger in the thermally correlated group within a future set time period specifically includes: Based on the trend of heat load or heat to be removed required by each heat exchanger in the thermally related group within a future set time period, determine the adjustment direction and adjustment range for each heat exchanger within the future set time period. For each heat exchanger, a sequence of adjustment instructions carrying timing is generated based on the determined adjustment method and adjustment range at the future set time. For each heat exchanger, the sequence of adjustment instructions carrying timing includes: multiple adjustment instructions carrying different timing sequences.

8. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 1, characterized in that, The physical model includes: the heat transfer model of each heat exchanger in the thermally associated group, the fluid resistance model of the pipes in the heat exchange network, and the performance curve model of the shared fluid pump device.

9. The method for optimizing and controlling parameters in the HFO-1234yf synthesis process according to claim 3, characterized in that, The impact on other equipment within the thermally associated group refers to the impact on the total flow rate of the entire shared fluid loop, the pressure distribution of the shared fluid loop, the fluid temperature in the shared fluid loop, and the fluid flow rate and fluid temperature of other heat exchange equipment. The optimization objectives are: to minimize temperature fluctuations, maintain stable total fluid flow, and / or optimize the energy consumption of shared fluid pump equipment in each process unit of the HFO-1234yf synthesis process; The constraints are: the safe temperature range of each process unit in the HFO-1234yf synthesis process, and the operational limitations of the shared fluid pump equipment.

10. A parameter optimization and control system for the HFO-1234yf synthesis process, characterized in that, include: The induction module is used to group multiple heat exchange devices that share the same fluid loop in the heat exchange network during the HFO-1234yf synthesis process, as well as the fluid pump devices that share the fluid, into the same thermal association group. The evaluation module is used to evaluate the impact of responding to the parameter adjustment command on other devices in the thermally associated group when it receives a parameter adjustment command for a heat exchanger in the thermally associated group, based on the real-time operating data of each device in the thermally associated group and the preset physical model. The generation module is used to generate a corresponding coordination and adjustment instruction for each relevant device in the thermally correlated group based on the evaluation results and preset goals; The sending module is used to send each coordination and adjustment instruction to the actuator of the corresponding relevant device; The related equipment, in addition to the aforementioned heat exchange equipment, also includes other heat exchange equipment within the thermal association group and / or the shared fluid pump equipment.

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