Parameter optimization method and device for chemical cooling system

Abstract

The embodiment of the invention provides a parameter optimization method and device for a chemical cooling system. By means of the method and device, the heat requirement for heat to be removed and a cooling path corresponding to a cooling system are obtained, and the cooling path is used for indicating an ordered combination of cooling devices in the cooling system used for conducting heat removal on all chemical devices generating the heat to be removed; establishing a heat exchange model according to the cooling path, wherein the heat exchange model comprises to-be-optimized parameters and the obtained associated data used for calculating the heat exchange amount; constructing an objective function based on the resources consumed by the cooling device for heat removal and the weights corresponding to the resources; and parameter values of the parameters in the cooling path are determined through an optimization algorithm, so that the value of the target function is made to be minimum under the condition that constraint conditions are met, and the constraint conditions include that the total heat capable of being removed by the heat exchange model under the condition that heat exchange is conducted on the cooling path and the given parameter values meets the heat requirement of the chemical device and safe and stable operation is achieved.

Description

Technical Field

[0001] The embodiments of this specification generally relate to the field of industrial optimization control, and in particular to a method and device for optimizing parameters of a cooling system in an industrial production device such as a chemical industry. Background Art

[0002] In the field of chemical production, the cooling system can effectively remove the heat generated by the operation of various equipment through various cooling technologies, which has a vital impact on ensuring the safe and stable operation of production, improving equipment efficiency, extending the service life of equipment, and improving the chemical production environment. With the continuous development of intelligent manufacturing technology and the increasing importance of energy conservation and emission reduction, how to optimize the cooling system has become a problem that needs to be solved.

[0003] At present, the optimization scheme for cooling system is mainly aimed at the design stage, and the best scheme is selected from a variety of alternative design schemes for implementation. Therefore, when the actual operating conditions are different from the design conditions, it is often difficult to find operating parameters suitable for the current conditions, and it is likely to cause resource waste in order to meet the heat removal requirements. Therefore, a parameter optimization method for chemical cooling system is needed to solve at least part of the above problems. Summary of the invention

[0004] In view of the above, the embodiments of this specification provide a parameter optimization method and device for a chemical cooling system. Using this method and device, a heat exchange model is established based on the heat requirements for the heat to be removed and the cooling path corresponding to the cooling system, and an objective function is constructed based on the resources consumed by the cooling device for heat removal and the corresponding weights, and then the parameter values ​​are determined using an optimization algorithm to achieve offline or online, static or dynamic optimization of the parameters of the cooling system. Furthermore, the parameter optimization requirements in different application scenarios can be adapted by adjusting the cooling path and weights, which has a wide range of application value.

[0005] According to one aspect of an embodiment of the present specification, a parameter optimization method for a chemical cooling system is provided, comprising: obtaining a heat requirement for heat to be removed and a cooling path corresponding to the cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed; establishing a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, and the parameters include operating variables for the cooling devices; constructing an objective function based on resources consumed by the cooling device for heat removal and weights corresponding to each resource; and determining parameter values ​​of the parameters under the cooling path using an optimization algorithm to minimize the value of the objective function while satisfying constraints, wherein the constraints include that the total heat that can be removed by the heat exchange model under the conditions of heat exchange in the cooling path and with the given parameter value meets the heat requirement and that each chemical device meets its own safe and stable operating conditions.

[0006] According to another aspect of an embodiment of the present specification, a parameter optimization device for a chemical cooling system is provided, comprising: an information acquisition unit, configured to acquire a heat requirement for heat to be removed and a cooling path corresponding to the cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed; a model construction unit, configured to establish a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data acquired for calculating the heat exchange amount, and the parameters include operating variables for the cooling devices; an objective function construction unit, configured to construct an objective function based on resources consumed by the cooling device for heat removal and weights corresponding to each resource; and an optimization calculation unit, configured to determine the parameter values ​​of the parameters under the cooling path using an optimization algorithm, so as to minimize the value of the objective function under the condition of satisfying constraints, wherein the constraints include that the total heat that can be removed by the heat exchange model under the condition of heat exchange in the cooling path and with the given parameter value meets the heat requirement and that each chemical device meets its own safe and stable operation conditions.

[0007] According to another aspect of an embodiment of the present specification, there is provided a parameter optimization device for a chemical cooling system, comprising: at least one processor, and a memory coupled to the at least one processor, the memory storing instructions, and when the instructions are executed by the at least one processor, the at least one processor executes the parameter optimization method for a chemical cooling system as described above.

[0008] According to another aspect of an embodiment of the present specification, there is provided a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the parameter optimization method for a chemical cooling system as described above is implemented.

[0009] According to another aspect of an embodiment of the present specification, a computer program product is provided, comprising a computer program, wherein the computer program is executed by a processor to implement the parameter optimization method for a chemical cooling system as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] A further understanding of the nature and advantages of the content of this specification may be achieved by referring to the following drawings. In the drawings, similar components or features may have the same reference numerals.

[0011] Figure 1 An exemplary architecture of a parameter optimization method and apparatus for a chemical cooling system according to an embodiment of the present specification is shown.

[0012] Figure 2 A flowchart of an example of a parameter optimization method for a chemical cooling system according to an embodiment of the present specification is shown.

[0013] Figure 3 A flowchart showing an example of a process for obtaining heat requirements and cooling paths according to an embodiment of the present specification.

[0014] Figure 4 A schematic diagram showing an example of a chemical plant according to an embodiment of the present specification.

[0015] Figure 5 A flowchart showing an example of a process for calculating a cooling demand value corresponding to a chemical plant according to an embodiment of the present specification.

[0016] Figure 6 A flowchart showing another example of a process for calculating a cooling demand value corresponding to a chemical plant according to an embodiment of the present specification.

[0017] Figure 7 A schematic diagram showing an example of a heat exchange model according to an embodiment of the present specification.

[0018] Figure 8 A flowchart showing an example of a process for determining weights corresponding to resources according to an embodiment of the present specification.

[0019] Fig. 9 A flowchart showing an example of a process of constructing an objective function according to an embodiment of the present specification.

[0020] Fig.10A block diagram showing an example of a parameter optimization device for a chemical cooling system according to an embodiment of the present specification.

[0021] Fig.11 A schematic diagram showing an example of a parameter optimization device for a chemical cooling system according to an embodiment of the present specification. DETAILED DESCRIPTION

[0022] The subject matter described herein will be discussed below with reference to example implementations. It should be understood that the discussion of these implementations is only to enable those skilled in the art to better understand and implement the subject matter described herein, and is not a limitation of the scope of protection, applicability or examples set forth in the claims. The functions and arrangements of the elements discussed may be changed without departing from the scope of protection of the embodiments of this specification. Various processes or components may be omitted, substituted or added to each example as needed. In addition, the features described relative to some examples may also be combined in other examples.

[0023] As used herein, the term "including" and its variations represent open terms, meaning "including but not limited to". The term "based on" means "based at least in part on". The terms "one embodiment" and "an embodiment" mean "at least one embodiment". The term "another embodiment" means "at least one other embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other definitions may be included below, whether explicit or implicit. Unless the context clearly indicates otherwise, the definition of a term is consistent throughout the specification.

[0024] The flowcharts used in this specification illustrate the operations implemented by the system according to some embodiments in this specification. It should be clearly understood that the operations of the flowcharts may not be implemented in sequence. On the contrary, the operations may be implemented in reverse order or simultaneously. In addition, one or more other operations may be added to the flowchart. One or more operations may be removed from the flowchart.

[0025] The parameter optimization method and device for a chemical cooling system according to an embodiment of the present specification will be described in detail below with reference to the accompanying drawings.

[0026] Figure 1 An exemplary architecture 100 of a parameter optimization method and apparatus for a chemical cooling system according to an embodiment of the present specification is shown.

[0027] exist Figure 1 In the embodiment, the network 110 is used to interconnect the terminal device 120 and the server 130 .

[0028] The network 110 may be any type of network capable of interconnecting network entities. The network 110 may be a single network or a combination of various networks. In terms of coverage, the network 110 may be a local area network (LAN), a wide area network (WAN), etc. In terms of carrier media, the network 110 may be a wired network, a wireless network, etc. In terms of data exchange technology, the network 110 may be a circuit switching network, a packet switching network, etc.

[0029] The terminal device 120 can be a control device for a cooling device in a cooling system. The control device can perform heat exchange control on the cooling device according to a given parameter value. The cooling device can be used to remove the heat generated by the production device. In some examples, if the given parameter value is the parameter value of the operating variable, the cooling device can be operated according to the parameter value of the given operating variable. For example, the opening of the make-up water valve can be controlled according to a given amount of make-up water. For another example, the fan can be operated according to the power of a given fan to cool the return water. In some examples, if the given parameter value is the parameter value of a key parameter setting variable (such as the water supply temperature of a cooling tower, etc.), the state represented by the parameter value can be achieved by automatic control, such as proportional-integral-derivative (PID) control or model predictive control (MPC).

[0030] The server 130 may interact with the terminal device 120 via the network 110. In some examples, the server 130 may execute a parameter optimization method for a chemical cooling system and send the determined parameter values ​​to the terminal device 120. In some examples, the terminal device 120 may execute a new control operation according to the sent parameters via an actuator and a control unit.

[0031] It should be understood that Figure 1 All network entities shown in the figure are exemplary. Any other network entities may be involved in the architecture 100 according to specific application requirements.

[0032] Figure 2 A flow chart of an example 200 of a parameter optimization method for a chemical cooling system according to an embodiment of the present specification is shown.

[0033] like Figure 2 As shown, at 210 , a heat requirement for heat to be removed and a cooling path corresponding to the cooling system are obtained.

[0034] In this embodiment, the cooling path can be used to indicate the ordered combination of cooling devices in the cooling system used to remove heat from each chemical device that generates heat to be removed. In some examples, the heat to be removed can be represented by Q. The heat requirement can be that the heat removed by the cooling system is not less than Q. In some examples, the heat to be removed can be represented by Q. The heat requirement can be that the heat removed by the cooling system is in the interval [Q-ΔQ1, Q+ΔQ2]. Among them, ΔQ1 and ΔQ2 can be used to indicate the possible fluctuation range of the heat to be removed. In some examples, ΔQ1 and ΔQ2 can be set according to actual production conditions or historical operating conditions. In some examples, the cooling system may include at least one cooling device, such as a cooling tower, a heat exchanger, a fan, an air cooler, etc. The chemical device may include various production devices, such as chemical production devices, etc. In one example, the cooling path can be used to indicate that the cooling device A and the cooling device B in the cooling system are used in sequence to remove heat from the chemical device X. In one example, the cooling path can be used to indicate that the cooling device C is used to remove heat from the chemical device Y and the chemical device Z, and so on. As an example, the amount of heat to be removed and the fluctuation range can be obtained from historical data or calculated theoretically. More specifically, in the case where the chemical plant is a chemical production plant, the amount of heat to be removed and its fluctuation range can be obtained based on historical data under normal production conditions. Alternatively, the amount of heat to be removed and the fluctuation range can also be calculated based on factors that affect heat, such as the amount and temperature of the inlet and outlet materials of the chemical production plant, the endothermic and exothermic heat of the chemical reaction, and the phase change heat.

[0035] Figure 3 A flow chart of an example of a process 300 for obtaining heat requirements and cooling paths according to an embodiment of the present specification is shown.

[0036] like Figure 3 As shown, at 310, the cooling demand values ​​corresponding to the respective chemical plants are obtained.

[0037] In this embodiment, the cooling requirement value can be used to indicate the amount of heat that needs to be removed from the corresponding chemical plant. In some examples, the corresponding cooling requirement value can be calculated through the design documents of the chemical plant, etc. It can be understood that a higher cooling requirement value generally means that the chemical plant has a larger heat production and thus has a higher cooling requirement.

[0038] Back to Figure 3 At 320, according to the optimization restrictions of the process flow corresponding to each chemical device on the cooling path, the corresponding cooling demand values ​​are adjusted accordingly to obtain the heat concern values ​​corresponding to each chemical device.

[0039] In this embodiment, the size of the heat concern value can be used to reflect the degree of concern for the corresponding chemical plant and the tendency to adjust during the optimization of the cooling path. In some examples, different process flows may have different degrees of restrictions on the optimization of the cooling path. In some examples, the restriction of the process flow on the optimization of the cooling path can be determined according to the correlation between the process flow and the main process and / or the sensitivity of the chemical equipment required by the process flow to temperature changes. In one example, the higher the correlation between a chemical plant and the main process of reaction production and / or the higher the sensitivity of the chemical equipment required by the process flow to temperature changes, the higher the degree of restriction on the optimization of the cooling path, which means that the cooling path is more inclined not to change, so that the heat concern value corresponding to the chemical plant can be relatively reduced. Correspondingly, the lower the correlation between a chemical plant and the main process of reaction production and / or the lower the sensitivity of the chemical equipment required by the process flow to temperature changes, the lower the degree of restriction on the optimization of the cooling path, which means that the cooling path is allowed to be optimized to a greater extent, so that the heat concern value corresponding to the chemical plant can be relatively increased. For example, in the case where a chemical device is a reactor, changes in its cooling path will affect the temperature stability of the main production circuit and / or the reactor, thereby causing a greater impact on smooth production and / or affecting the production capacity and quality of the product. Therefore, the benefits and risks brought by the change of the cooling path need to be evaluated and disclosed as much as possible, and the heat concern value can be relatively reduced accordingly, for example, the cooling demand value corresponding to the chemical device is multiplied by an adjustment coefficient between 0 and 1 to obtain the corresponding heat concern value. It can be understood that in some examples, the higher the degree of restriction of the process flow on the optimization of the cooling path, the closer the value of the above adjustment coefficient is to 0. For another example, in the case where a chemical device is a steam storage tank, it is not located in the main process flow, and even if the change of the cooling path causes a temporary or permanent change in cooling capacity, it can be adapted by adjusting the steam receiving amount and the discharge amount, and the main process of producing the product has little impact, but the optimization of the cooling path can greatly save resource consumption, then the heat concern value can be appropriately increased, for example, the cooling demand value corresponding to the chemical device is multiplied by a coefficient greater than 1 to obtain the corresponding heat concern value. For another example, if the equipment required by the process flow of a chemical plant is less sensitive to temperature changes, its cooling path can be adjusted more frequently, so that the heat concern value can be appropriately increased. On the contrary, if the equipment required by the process flow of a chemical plant is more sensitive to temperature changes, for example, the temperature change of the equipment will cause serious safety or quality problems or shutdown, then the cooling path should be adjusted as little as possible, so that the heat concern value can be appropriately reduced.

[0040] At 330 , a target chemical plant whose cooling path is to be optimized is determined from among various chemical plants according to the heat concern value.

[0041] In some examples, the target chemical plant may be a chemical plant with a maximum heat concern value. In some examples, the target chemical plant may be a chemical plant with a heat concern value greater than a preset threshold.

[0042] For each target chemical plant, execute 340-350.

[0043] At 340 , a heat removal requirement of the device is determined based on a design range of heat to be removed corresponding to the target chemical device.

[0044] In some examples, the design interval of heat to be removed corresponding to the target chemical device may be [Q-ΔQ1, Q+ΔQ2], and the device heat removal requirement may be that the heat removed by the cooling system is in the interval [Q-ΔQ1, Q+ΔQ2]. In some examples, the device heat removal requirement may be that the heat removed by the cooling system is not less than Q+ΔQ2.

[0045] Figure 4 A schematic diagram of an example of a chemical plant 400 according to an embodiment of the present specification is shown.

[0046] like Figure 4 As shown, a set of chemical plant 400 may be composed of multiple process units (e.g., process unit 410, process unit 420, etc.). Each process unit may include multiple chemical equipment (e.g., chemical equipment 411, chemical equipment 412, etc.). For example, the chemical plant may be a chemical production plant. The process unit may include a low-pressure steam power generation unit, a reaction unit, a distillation unit, etc. The chemical equipment may include a steam turbine, a generator, a reactor, a chemical separation equipment, etc.

[0047] For example Figure 4The chemical plant 400 shown can calculate the cooling demand value corresponding to each chemical plant, and then combine and calculate the cooling demand values ​​corresponding to each chemical plant (such as chemical plant 411, chemical plant 412, etc.) belonging to the same process unit (such as process unit 410, etc.) to obtain the cooling demand value corresponding to each process unit. Then, the cooling demand values ​​corresponding to each process unit are combined and calculated to obtain the cooling demand value corresponding to the chemical plant 400. Afterwards, the heat removal requirement of the device can be determined according to the cooling demand value corresponding to the chemical plant 400 and the obtained cooling demand fluctuation amount. In some examples, the cooling demand value can be used to indicate the estimated value of the heat to be removed. In some examples, the heat removal requirement of the device can be expressed in the form of a heat design interval to be removed. The cooling demand value can also have a corresponding cooling demand fluctuation amount. For example, the heat design interval to be removed can be expressed as [Q-ΔQ1, Q+ΔQ2]. Among them, Q can be the corresponding cooling demand value, and ΔQ1 and ΔQ2 can be the corresponding cooling demand fluctuation amounts. ΔQ1 can be used to indicate the amplitude of downward fluctuation, and ΔQ2 can be used to indicate the amplitude of upward fluctuation. In some examples, the values ​​of ΔQ1 and ΔQ2 can be set according to at least one of the following, for example: actual production conditions, historical operating conditions, process requirements, sensitivity of the equipment to temperature, etc. For example, if the actual production conditions or historical operating conditions show that the cooling demand of the device does not change much, then ΔQ1 and ΔQ2 can be set to smaller values ​​accordingly, otherwise vice versa. For another example, if the process has stricter temperature requirements or the corresponding chemical equipment is more sensitive to temperature changes, then ΔQ1 and ΔQ2 can be set to larger values ​​accordingly, otherwise vice versa. It can be understood that the values ​​of ΔQ1 and ΔQ2 can be the same or different, and are not limited here.

[0048] Through the above method, a method for determining the heat removal requirement of a chemical plant is provided.

[0049] Figure 5 A flowchart showing an example of a calculation process 500 of a cooling demand value corresponding to a chemical plant according to an embodiment of the present specification.

[0050] like Figure 5 As shown, at 510, the product design output associated with the chemical equipment is obtained.

[0051] In this embodiment, the association relationship between the chemical equipment and the product can be preset. In some examples, it can be determined based on the association relationship between the chemical equipment and the chemical equipment that produces the product. For example, if the chemical equipment is a reactor, the associated product design output can be the design output of the product obtained based on the product corresponding to the reactor. For another example, if the chemical equipment is a steam turbine, the associated product design output can be the design output of the product obtained based on the power or power generated by the steam turbine.

[0052] At 520 , a cooling requirement value corresponding to the chemical equipment is calculated according to the type of the chemical equipment and the designed product output, so as to achieve the designed product output.

[0053] In some examples, the cooling requirement value can be determined based on the correlation between the chemical equipment and the chemical equipment that produces the product. For example, if the chemical equipment is a reactor, the reaction heat of the reactor can be calculated based on the product design output, reaction temperature, and reaction heat per unit product output, thereby combining the temperature and amount of each input and output material, estimated or measured natural heat dissipation and other factors to obtain the corresponding cooling requirement value of the chemical equipment. For another example, if the chemical equipment is a steam turbine, the required driving steam volume and exhaust gas conditions can be calculated based on the product design output, thereby obtaining the corresponding cooling requirement value.

[0054] Through the above method, a calculation method for the cooling demand value corresponding to the chemical equipment is provided.

[0055] Figure 6 A flowchart showing another example of a process for calculating a cooling demand value corresponding to a chemical plant according to an embodiment of the present specification.

[0056] like Figure 6 As shown, at 610, an adjustable process parameter group corresponding to the type of the chemical equipment is obtained.

[0057] In this embodiment, the adjustable process parameter group may include at least one process parameter that can be adjusted within the allowable range. For example, if the chemical equipment is a reactor, the adjustable process parameter group may include pressure and temperature. For another example, if the chemical equipment is a steam turbine, the adjustable process parameter group may include back pressure.

[0058] At 620, the parameter value of each process parameter in the adjustable process parameter group is determined within the corresponding upper and lower limit ranges, so that the chemical equipment can meet the upper and lower limits when operating according to the parameter value of the process parameter and can achieve the designed product output.

[0059] It can be understood that under the condition that the chemical equipment meets the upper and lower limits when operating according to the parameter values ​​of the process parameters and can safely and stably achieve the designed output of the product, the parameter values ​​of each process parameter in the adjustable process parameter group can have different combinations. For example, for a heat exchanger, the water supply temperature in the process parameters can be lowered. For another example, for a steam turbine, the back pressure can be increased.

[0060] At 630 , a cooling demand value corresponding to the chemical equipment is calculated according to the parameter value of the process parameter and the designed output of the product.

[0061] In this embodiment, according to the parameter value of the process parameter and the product design output, the cooling requirement value corresponding to the chemical equipment can be calculated according to the corresponding process. It can be understood that the adjustable process parameter group composed of different parameter values ​​of the process parameters can correspond to different cooling requirement values ​​respectively.

[0062] Through the above method, a method for calculating the cooling demand value corresponding to the chemical equipment according to different parameter values ​​of the process parameters is provided, and then a two-stage optimization method is provided, which combines parameter optimization during the operation of the cooling device with process parameter optimization of the chemical equipment, thereby improving the optimization effect.

[0063] Back to Figure 3 At 350 , a device-level cooling path search is performed based on the candidate cooling devices in the cooling system to determine a device-level cooling path that meets the device heat removal requirements.

[0064] In the present embodiment, the device-level cooling path is used to indicate the ordered combination of cooling devices in the cooling system used to remove heat from the target chemical plant. The cooling device in the cooling system may have a maximum heat removal amount and a minimum heat removal amount. By carrying out different ordered combinations of the cooling devices in the cooling system, an alternative device-level cooling path that meets the heat removal requirements of the device can be obtained. For example, the alternative device-level cooling path 1 may be {heat exchanger a}, which may be used to indicate that only heat exchanger a is used to remove heat from the target chemical plant. For another example, the alternative device-level cooling path 2 may be {heat exchanger c, fan f}, which may be used to indicate that heat exchanger c and fan f are used in sequence to remove heat from the target chemical plant. For another example, the alternative level cooling path 3 may be {fan m}, which may be used to indicate that only fan m is used to remove heat from the target chemical plant. It can be understood that the above-mentioned different alternative device-level cooling paths may be used to indicate different ways of removing the heat generated by the target chemical plant.

[0065] In some examples, if there are multiple alternative device-level cooling paths that meet the device heat removal requirements, one of them can be selected in various ways, such as by the principle of proximity, cost saving, heat exchange matching, etc.

[0066] At 360 , a combined calculation is performed based on the heat removal requirements of the target chemical plants to determine the heat output requirements.

[0067] In some examples, the heat removal requirements of the devices corresponding to each target chemical device can be accumulated to obtain the overall heat requirements for each of the above target chemical devices. For example, the heat to be removed Q corresponding to each chemical device can be accumulated to obtain the overall heat to be removed ∑Q, so that the determined heat requirement can be that the heat removed by the cooling system is not less than ∑Q. For another example, the determined heat requirement can be that the heat removed by the cooling system is in the interval [∑Q-ΔQ'1, ∑Q+ΔQ'2]. Among them, ΔQ'1 and ΔQ'2 can be set according to the actual production conditions or historical operating conditions of each of the above target chemical devices as a whole.

[0068] At 370 , path search and feasibility analysis are performed based on the device-level cooling paths corresponding to each target chemical device to determine a cooling path that meets the heat requirement and conforms to the cooling path optimization target.

[0069] In some examples, the path search and feasibility analysis may include, for example, selecting alternative cooling devices in the cooling system nearby, increasing or decreasing the ordered combination of cooling devices accordingly by balancing the consumption of different resources as much as possible in combination with process characteristics under the premise of meeting the heat requirements, or modifying the connection relationship between the cooling devices, and determining a cooling path that meets the cooling path optimization goal. In some examples, the cooling path optimization goal may be, for example, minimizing resource consumption, minimizing total cost, etc.

[0070] Back to Figure 2 , at 220 , a heat exchange model is established according to the cooling path.

[0071] In this embodiment, the heat exchange model may refer to a mathematical and physical model for simulating and analyzing the transfer of heat between different media. The heat exchange model may include parameters to be optimized and associated data obtained for calculating the heat exchange amount. The above parameters may include operating variables for the cooling device. In some examples, the cooling path can be modeled based on the heat transfer principle with the help of simulation software. In some examples, the modeling can be combined with the heat transfer principle and the machine learning model. Specifically, for some processes involving complex formula calculations, a machine learning model can be pre-trained to approximate the mapping relationship between the physical quantities in the above process, thereby simplifying the calculation.

[0072] In some examples, the operating variables may refer to variables that can directly affect the operating state of the cooling device, such as the power of the fan of the cooling tower, the number of cooling units in use, the water consumption, etc. The associated data used to calculate the heat exchange amount may be non-optimized variables that need to be known for calculating the heat exchange amount, which may be obtained in various ways, such as obtaining the inlet water temperature of the cooling tower through a temperature sensor, obtaining the supplementary water flow of the cooling tower through a flow sensor, and obtaining the current operating power of the fan, power consumption, etc. through a dashboard.

[0073] In some optional implementations, the above parameters may also include key control parameter setting variables of the cooling device. In some examples, the key control parameter setting variables may refer to variables that can reflect the operating objectives of the cooling device, such as the water supply temperature of the cooling tower.

[0074] Figure 7 A schematic diagram showing an example of a heat exchange model 700 according to an embodiment of the present specification.

[0075] like Figure 7 As shown, the heat exchange model 700 may include a first cooling loop 710, a second cooling loop 720 and a cooling tower 730. In the first cooling loop 710, the cooling tower 730 performs a cooling cycle on the first cooling liquid. In the second cooling loop 720, the second cooling liquid removes heat from each chemical plant. The chemical plant may include multiple process units. The second cooling liquid can cool down by exchanging heat with the first cooling liquid. For example, the second cooling liquid can exchange heat with the first cooling liquid through a heat exchanger 740.

[0076] In some optional implementations, the above parameters also include water supply temperature, and the above operating variables include at least one of the following: make-up water volume, fan power in the cooling tower. The first cooling liquid includes seawater. The second cooling liquid includes demineralized water, wastewater, process stream, etc.

[0077] In the above manner, a heat exchange model consisting of a cooling tower and a two-stage cooling loop can be constructed. By comprehensively utilizing seawater and desalted water as cooling liquids, the cooling and circulation process not only reduces the demand for seawater, reduces the temperature rise of the discharged water, but also reduces the amount of sewage discharged.

[0078] Back to Figure 2 At 230, an objective function is constructed based on the resources consumed by the cooling device to remove heat and the weights corresponding to the various resources.

[0079] In some examples, the consumed resources may include, but are not limited to, at least one of the following: seawater, desalted water, coolant, electricity, coal, steam, etc. The objective function may be expressed as min w1·x1+…+w n ·x n Among them, x1~x n It can be used to indicate the resources consumed, such as the total amount of seawater, the total amount of desalted water, the total amount of coolant, the total amount of electricity, the total amount of coal, the total amount of steam, etc., w1~w nIt can be used to represent the corresponding weight. In one example, the consumed resources can also be used to represent the total emissions, the total amount of raw materials used, etc. Among them, the total emissions can include, for example, the total amount of waste gas, the total amount of waste water, the total amount of solid waste, etc. Correspondingly, the total amount of waste gas, the total amount of waste water, the total amount of solid waste, etc. can also each have a corresponding weight. In one example, the above weights can correspond to the amount of resources, so that the function value of the objective function can be used to measure the amount of resources consumed. In one example, the above weights can also correspond to resource costs (such as electricity prices, water prices, etc.), so that the function value of the objective function can be used to measure the cost of the consumed resources.

[0080] Figure 8 The flowchart shows an example of a process 800 for determining weights corresponding to resources according to an embodiment of the present specification.

[0081] like Figure 8 As shown, at 810, system operation data of the industrial system where each chemical plant is located is obtained.

[0082] In this embodiment, the system operation data includes data for indicating the operating status of the chemical plant. In some examples, the system operation data may include but is not limited to at least one of the following: power consumption, coal consumption, water consumption, product output, equipment operation status, carbon emissions, and material balance.

[0083] At 820 , based on the system operation data, the operation status of each chemical plant is evaluated and the utilization status of each resource is determined.

[0084] In this embodiment, the operating status of the chemical plant can be used to indicate whether the equipment is running and the current operating status. The utilization status of a resource can be used to indicate the need to save the resource. In some examples, the system operation data can be compared with the historical data. If there is a resource consumption that is significantly higher than the historical level of the same period when the chemical plant is operating normally, the utilization status of the resource can be used to indicate the need to save this resource. For example, when the cooling water consumption is significantly higher than the water consumption under normal system operation in the historical chemical system operation data, the utilization status of the cooling water consumption can be used to indicate the need to save cooling water. In some examples, for a certain resource, relevant data can be selected from the system operation data for analysis to determine whether it is necessary to save this resource. For example, if the equipment operation status indicates that the operation capacity of the power generation equipment has been significantly reduced, the utilization status of the electricity can be used to indicate the need to save electricity.

[0085] At 830 , based on the operating status of each chemical plant and the utilization status of each resource, a weight corresponding to each resource is determined.

[0086] In this embodiment, the size of the weight value can match the saving demand for the resource indicated by the operating status of each chemical plant and the utilization status of the resource. In some examples, if the minimum value of the objective function is solved, the higher the saving demand for the resource indicated by the utilization status of a resource, the higher the weight can be given to the resource.

[0087] Through the above method, it is creatively proposed to determine the weights of corresponding resources according to the system operation data of the industrial system, which can make the optimization target more adapted to the objective current operation status, for example, making the target tend to be more energy-saving, more water-saving, etc., thereby improving the optimization effect.

[0088] Fig. 9 A flowchart showing an example of a process 900 for constructing an objective function according to an embodiment of the present specification is shown.

[0089] like Fig. 9 As shown, at 910, a safety margin weight corresponding to the heat requirement is determined based on system operation data.

[0090] In this embodiment, the corresponding relationship between the system operation data and the safety margin weight corresponding to the heat requirement can be preset. In some examples, when the system operation data indicates that the system operation state meets the preset conditions, it is necessary to give priority to leaving enough safety margin for heat removal, and at this time, the safety margin weight corresponding to the heat requirement can be determined as a higher value.

[0091] At 920 , a heat removal safety margin is determined according to a difference between the total heat that can be removed under heat exchange conditions with given parameters based on the heat exchange model and the heat requirement.

[0092] In some examples, the heat removal safety margin can be expressed as Q'-Q. Wherein, Q' can be used to represent the total heat that can be removed under the condition of heat exchange with given parameters based on the heat exchange model. Q can be used to represent the heat to be removed as indicated by the heat requirement. In some examples, Q' can be expressed as an expression containing the parameters to be optimized.

[0093] At 930, an objective function is constructed based on the resources consumed by the cooling device for heat removal, the heat removal safety margin, the weights corresponding to the various resources, and the safety margin weight.

[0094] In some examples, the objective function can be expressed as min w0·x0+w1·x1+…+w n ·x n. Among them, x0 can be used to represent the heat removal safety margin, and w0 can be used to represent the safety margin weight. The meanings of the remaining symbols can refer to the corresponding descriptions in the aforementioned step 230. In these examples, the heat removal safety margin can be set based on experience. For example, if the heat to be removed usually does not fluctuate much, the heat removal safety margin can take a smaller value; if the heat to be removed may fluctuate greatly, the heat removal safety margin can take a larger value.

[0095] In the above manner, by incorporating the safety margin of heat removal into the objective function, the applicable scenarios of this solution can be further enriched, greatly adapting to the cooling system parameter optimization requirements in different application scenarios.

[0096] Back to Figure 2 At 240, an optimization algorithm is used to determine parameter values ​​of the parameters in the cooling path so as to minimize the value of the objective function while satisfying the constraint conditions.

[0097] In this embodiment, the constraint condition includes that the total heat that can be removed by the heat exchange model under the condition of heat exchange with the cooling path and the given parameter value meets the heat requirement and makes each chemical device meet its own safe and stable operation conditions. In some examples, the safe and stable operation conditions of each chemical device may include, for example, that the heat that can be removed by each chemical equipment included in the chemical device meets the heat interval required to be removed by the chemical device, and the operating temperature, pressure, flow rate, etc. of each chemical device meet the corresponding predetermined safety range of the chemical device. In some examples, the safe and stable operation conditions of each chemical device may also include, for example, parameter ranges that meet the excellent working conditions in the past history, product output and specifications (concentration, color, density, etc.) meet the standards. Various optimization algorithms can be used to determine the parameter values ​​of the above parameters, such as Stochastic Gradient Descent (SGD), Genetic Algorithm (Genetic Algorithm), Particle Swarm Optimization (PSO) algorithm, etc. In one example, the value of the objective function (e.g., the sum of the total water consumption and the total electricity consumption) can be minimized by optimizing the parameter values ​​of the parameters (e.g., the fan power of the cooling tower, the number of cooling tower operating units, the water consumption, etc.) given the above cooling path. It can be understood that, in combination with the corresponding description in the above embodiments, the above parameters and objective functions can also exist in other forms, which will not be repeated here.

[0098] In some optional implementations, the parameter values ​​of the parameters can also be sent to the control devices of the corresponding cooling devices to control the corresponding cooling devices to remove heat according to the mode indicated by the parameter values, thereby achieving automatic control and optimization of the operation of the cooling devices.

[0099] use Figure 1-Figure 9 The parameter optimization method for chemical cooling system disclosed in the article establishes a heat exchange model based on the heat requirements for the heat to be removed and the cooling path corresponding to the cooling system, and constructs an objective function based on the resources consumed by the cooling device for heat removal and the weights corresponding to each resource, and then uses the optimization algorithm to determine the parameter values ​​to achieve dynamic optimization of the parameters of the cooling system. Furthermore, the parameter optimization requirements under different application scenarios (such as various operating conditions such as production increase, production reduction, and even parking of some circuits in the cooling system) can also be adapted by adjusting the cooling path and weights, which has a wide range of application value.

[0100] Fig.10 FIG. 1 is a block diagram showing an example 1000 of a parameter optimization device for a chemical cooling system according to an embodiment of the present specification. The device embodiment can be used with Figure 2-Figure 9 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0101] like Fig.10 As shown, the parameter optimization device 1000 for a chemical cooling system may include an information acquisition unit 1010 , a model construction unit 1020 , an objective function construction unit 1030 and an optimization calculation unit 1040 .

[0102] The information acquisition unit 1010 is configured to acquire the heat requirement for the heat to be removed and the cooling path corresponding to the cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed.

[0103] In some examples, the information acquisition unit 1010 is further configured to: obtain the cooling demand values ​​corresponding to the respective chemical devices; adjust the cooling demand values ​​corresponding to the respective chemical devices according to the optimization restrictions of the process flow corresponding to the respective chemical devices on the cooling path, and obtain the heat attention value corresponding to the respective chemical devices, wherein the size of the heat attention value is used to reflect the degree of attention to the corresponding chemical device during the optimization process of the cooling path; determine the target chemical device of the cooling path to be optimized from the various chemical devices according to the heat attention value; for each target chemical device, based on the cooling demand value and the cooling demand corresponding to the target chemical device fluctuation amount, determine the heat removal requirement of the device; and perform a device-level cooling path search based on the alternative cooling devices in the chemical cooling system to determine the device-level cooling path that meets the heat removal requirement of the device, wherein the device-level cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from the target chemical device; perform a combined calculation based on the device heat removal requirements corresponding to each target chemical device to determine the heat requirement; and perform a path search and feasibility analysis based on the device-level cooling paths corresponding to each target chemical device to determine a cooling path that meets the heat requirement and meets the cooling path optimization goal.

[0104] In some examples, the information acquisition unit 1010 is further configured to: for each chemical plant and for each process unit of the chemical plant, calculate the cooling demand value corresponding to each chemical equipment in the process unit; and combine the cooling demand values ​​corresponding to each chemical equipment to obtain the cooling demand value corresponding to the process unit; combine the cooling demand values ​​corresponding to each process unit to obtain the cooling demand value corresponding to the chemical plant; and determine the heat removal requirement of the plant based on the cooling demand values ​​corresponding to each chemical plant and the obtained cooling demand fluctuation.

[0105] In some examples, the information acquisition unit 1010 is further configured to: obtain a product design output associated with the chemical equipment; and calculate a cooling requirement value corresponding to the chemical equipment to achieve the product design output based on the type of the chemical equipment and the product design output.

[0106] In some examples, the information acquisition unit 1010 is further configured to: obtain an adjustable process parameter group corresponding to the type of chemical equipment; determine the parameter values ​​of each process parameter in the adjustable process parameter group within the corresponding upper and lower limit ranges, so that the chemical equipment meets the upper and lower limits when operating according to the parameter values ​​of the process parameters and can achieve the product design output; and calculate the cooling requirement value corresponding to the chemical equipment based on the parameter values ​​of the process parameters and the product design output.

[0107] In some examples, the cooling device includes a cooling tower, and the heat exchange model includes a first cooling circuit and a second cooling circuit, the first cooling circuit uses the cooling tower to cool a first cooling liquid, the second cooling circuit uses a second cooling liquid to remove heat from each chemical device, and the second cooling liquid is cooled by exchanging heat with the first cooling liquid.

[0108] In some examples, the parameters also include supply water temperature, the operating variables include at least one of the following: make-up water volume, fan power, the first cooling liquid includes seawater, the second cooling liquid includes desalted water, wastewater, process stream, etc.

[0109] The model building unit 1020 is configured to establish a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, and the parameters include operating variables for the cooling device.

[0110] The objective function constructing unit 1030 is configured to construct an objective function based on the resources consumed by the cooling device for removing heat and the weights corresponding to each resource.

[0111] In some examples, the weights corresponding to the resources are determined in the following manner: obtaining system operation data of the industrial system where the chemical plants are located, wherein the system operation data includes data for indicating the operating status of the chemical plants; based on the system operation data, evaluating the operating status of each chemical plant and determining the utilization status of each resource; and determining the weights corresponding to each resource based on the operating status of each chemical plant and the utilization status of each resource.

[0112] In some examples, the objective function construction unit 1030 is further configured to: determine the safety margin weight corresponding to the heat requirement based on the system operation data; determine the heat removal safety margin based on the difference between the total heat that can be removed under the conditions of heat exchange based on the heat exchange model given the parameters and the heat requirement; and construct the objective function based on the resources consumed by the cooling device for heat removal, the heat removal safety margin, the weights corresponding to each resource and the safety margin weight.

[0113] The optimization calculation unit 1040 is configured to determine the parameter value of the parameter under the cooling path by using an optimization algorithm to minimize the value of the objective function under the constraint condition. The constraint condition includes that the total heat that can be removed by the heat exchange model under the condition of heat exchange in the cooling path and with the given parameter value meets the heat requirement and that each chemical device meets its own safe and stable operation conditions.

[0114] In some examples, the parameter optimization device 1000 for a chemical cooling system may also include: an information sending unit configured to send the parameter values ​​of the parameters to the control devices of the corresponding cooling devices respectively to control the corresponding cooling devices to remove heat according to the mode indicated by the parameter values.

[0115] It should be noted that Fig.10 The operation of each unit in the parameter optimization device for chemical cooling system described above can be referred to. Figure 2-Figure 9 Description of the corresponding steps in .

[0116] Reference above Figures 1 to 10 , an embodiment of a parameter optimization device for a chemical cooling system according to an embodiment of this specification is described.

[0117] The parameter optimization device for a chemical cooling system in the embodiment of this specification can be implemented by hardware, or by software or a combination of hardware and software. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of the device in which it is located reading the corresponding computer program instructions in the memory into the memory and running them. In the embodiment of this specification, the parameter optimization device for a chemical cooling system can be implemented, for example, using an electronic device.

[0118] Fig.11 A schematic diagram showing an example of a parameter optimization device 1100 for a chemical cooling system according to an embodiment of the present specification.

[0119] like Fig.11 As shown, the parameter optimization device 1100 for a chemical cooling system may include at least one processor 1110, a memory (e.g., a non-volatile memory) 1120, a memory 1130, and a communication interface 1140, and the at least one processor 1110, the memory 1120, the memory 1130, and the communication interface 1140 are connected together via a bus 1150. At least one processor 1110 executes at least one computer-readable instruction stored or encoded in the memory (i.e., the above-mentioned element implemented in the form of software).

[0120] In one embodiment, computer executable instructions are stored in a memory, which when executed cause at least one processor 1110 to: obtain a heat requirement for heat to be removed and a cooling path corresponding to the cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed; establish a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, and the parameters include operating variables for the cooling devices; construct an objective function based on resources consumed by the cooling device for heat removal and weights corresponding to each resource; and determine parameter values ​​of the parameters under the cooling path using an optimization algorithm to minimize the value of the objective function while satisfying constraints, wherein the constraints include that the total heat that can be removed by the heat exchange model under the conditions of heat exchange in the cooling path and with the given parameter values ​​meets the heat requirement and that each chemical device meets its own safe and stable operating conditions.

[0121] It should be understood that the computer executable instructions stored in the memory, when executed, cause at least one processor 1110 to perform the above combined operations in various embodiments of the present specification. Figure 1-Figure 9 Describes the various operations and functions.

[0122] According to one embodiment, a program product such as a computer-readable medium is provided. The computer-readable medium may have instructions (i.e., the above-mentioned elements implemented in the form of software), which, when executed by a computer, causes the computer to perform the above-mentioned combination of various embodiments of this specification. Figure 1-Figure 9 Describes the various operations and functions.

[0123] Specifically, a system or device equipped with a readable storage medium can be provided, on which software program codes that implement the functions of any of the above-mentioned embodiments are stored, and a computer or processor of the system or device can read and execute instructions stored in the readable storage medium.

[0124] In this case, the program code itself read from the machine-readable medium can realize the function of any one of the above-mentioned embodiments, and thus the machine-readable code and the machine-readable storage medium storing the machine-readable code constitute a part of the present invention.

[0125] The computer program code required for the operation of each part of this specification can be written in any one or more programming languages, including object-oriented programming languages, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB, NET and Python, conventional procedural programming languages ​​such as C language, Visual Basic 2003, Perl, COBOL 2002, PHP and ABAP, dynamic programming languages ​​such as Python, Ruby and Groovy, or other programming languages. The program code can be run on the user's computer, or run on the user's computer as an independent software package, or run partly on the user's computer and another part on the remote computer, or all on the remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service, such as software as a service (SaaS).

[0126] Examples of readable storage media include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD-RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or a cloud via a communication network.

[0127] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0128] Not all steps and units in the above-mentioned processes and system structure diagrams are necessary, and some steps or units can be ignored according to actual needs. The execution order of each step is not fixed and can be determined according to needs. The device structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some units may be implemented by the same physical entity, or some units may be implemented by multiple physical entities, or some components in multiple independent devices may be implemented together.

[0129] The term "exemplary" as used throughout this specification means "serving as an example, instance, or illustration" and does not imply "preferred" or "advantageous" over other embodiments. The detailed description includes specific details for the purpose of providing an understanding of the described techniques. However, the techniques may be implemented without these specific details. In some instances, in order to avoid obscuring the concepts of the described embodiments, well-known structures and devices are shown in block diagram form.

[0130] The optional implementation modes of the embodiments of the present specification are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present specification are not limited to the specific details in the above implementation modes. Within the technical concept of the embodiments of the present specification, various simple modifications can be made to the technical solutions of the embodiments of the present specification, and these simple modifications all belong to the protection scope of the embodiments of the present specification.

[0131] The above description of the contents of this specification is provided to enable any person of ordinary skill in the art to implement or use the contents of this specification. Various modifications to the contents of this specification will be apparent to those of ordinary skill in the art, and the general principles defined herein may be applied to other variations without departing from the scope of protection of the contents of this specification. Therefore, the contents of this specification are not limited to the examples and designs described herein, but are consistent with the widest range of principles and novel features disclosed herein.

Claims

1. A parameter optimization method for a chemical cooling system, comprising: Obtaining a heat requirement for the heat to be removed and a cooling path corresponding to the chemical cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed; Establishing a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, and the parameters include operating variables for the cooling device; constructing an objective function based on the resources consumed by the cooling device for heat removal and the weights corresponding to the various resources; and An optimization algorithm is used to determine the parameter values ​​of the parameters in the cooling path so as to minimize the value of the objective function under the constraints, wherein the constraints include that the total heat that can be removed by the heat exchange model under the conditions of heat exchange in the cooling path and with the given parameter values ​​meets the heat requirement and that each chemical device meets its own safe and stable operation conditions.

2. The parameter optimization method according to claim 1, wherein: Obtaining the heat requirement and the cooling path includes: Obtain cooling demand values ​​corresponding to each of the chemical plants; According to the optimization restrictions of the process flow corresponding to each chemical device on the cooling path, the corresponding cooling demand value is adjusted accordingly to obtain the heat attention value corresponding to each chemical device, wherein the size of the heat attention value is used to reflect the degree of attention paid to the corresponding chemical device during the optimization process of the cooling path; According to the heat concern value, determining a target chemical plant whose cooling path is to be optimized from various chemical plants; For each target chemical plant, Determining a heat removal requirement for the target chemical plant based on the cooling demand value and cooling demand fluctuation corresponding to the target chemical plant; and Performing a device-level cooling path search based on the alternative cooling devices in the chemical cooling system to determine a device-level cooling path that meets the heat removal requirements of the device, wherein the device-level cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from the target chemical device; Performing a combined calculation based on the heat removal requirements of each target chemical plant to determine the heat requirements; and Path search and feasibility analysis are performed according to the device-level cooling paths corresponding to each target chemical device to determine a cooling path that meets the heat requirement and conforms to the cooling path optimization goal.

3. The parameter optimization method according to claim 2, wherein: The determining of the heat removal requirement of the device based on the cooling demand value and the cooling demand fluctuation amount corresponding to the target chemical device includes: For each chemical plant, For each process unit of the chemical device, the cooling demand value corresponding to each chemical equipment in the process unit is calculated; and the cooling demand value corresponding to each chemical equipment is combined and calculated to obtain the cooling demand value corresponding to the process unit; The cooling demand values ​​corresponding to each process unit are combined and calculated to obtain the cooling demand value corresponding to the chemical plant; and The heat removal requirements of the devices are determined based on the cooling demand values ​​corresponding to each chemical device and the obtained cooling demand fluctuations.

4. The parameter optimization method according to claim 3, wherein: Calculation of cooling demand values ​​corresponding to chemical equipment includes: Obtaining the product design output associated with the chemical equipment; and According to the type of the chemical equipment and the designed output of the product, the cooling demand value corresponding to the designed output of the product for the chemical equipment is calculated.

5. The parameter optimization method according to claim 4, wherein: The step of calculating the cooling requirement value corresponding to the designed output of the product by the chemical equipment according to the type of the chemical equipment and the designed output of the product includes: Obtaining an adjustable process parameter group corresponding to the type of the chemical equipment; Determining the parameter value of each process parameter in the adjustable process parameter group within the corresponding upper and lower limit ranges, so that the chemical equipment meets the upper and lower limits when operating according to the parameter value of the process parameter and can achieve the designed output of the product; and According to the parameter value of the process parameter and the designed output of the product, the cooling demand value corresponding to the chemical equipment is calculated.

6. The parameter optimization method according to claim 1, wherein: The cooling device includes a cooling tower, and the heat exchange model includes a first cooling circuit and a second cooling circuit. The first cooling circuit uses the cooling tower to cool a first cooling liquid, and the second cooling circuit uses a second cooling liquid to remove heat from each chemical device. The second cooling liquid is cooled by exchanging heat with the first cooling liquid.

7. The parameter optimization method according to claim 6, wherein: The parameters also include supply water temperature, the operating variables include at least one of the following: make-up water volume, fan power; and wherein the first cooling liquid includes seawater, and the second cooling liquid includes at least one of the following: desalted water, wastewater, process stream.

8. The parameter optimization method according to claim 1, wherein: The weights corresponding to the resources are determined in the following way: Acquiring system operation data of the industrial system where each chemical device is located, wherein the system operation data includes data for indicating the operation status of the chemical device; Based on the system operation data, evaluating the operation status of each chemical plant and determining the utilization status of each resource; and Based on the operating status of each chemical plant and the utilization status of each resource, the weight corresponding to each resource is determined.

9. The parameter optimization method according to claim 8, wherein: The constructing objective function comprises: Determining a safety margin weight corresponding to the heat requirement according to the system operation data; Determining a heat removal safety margin according to a difference between a total amount of heat that can be removed under the condition of heat exchange with given parameters based on the heat exchange model and the heat requirement; and The objective function is constructed based on the resources consumed by the cooling device for heat removal, the heat removal safety margin, the weights corresponding to various resources and the safety margin weight.

10. The parameter optimization method according to claim 1, wherein: The parameter optimization method further comprises: The parameter values ​​of the parameters are respectively sent to the control devices of the corresponding cooling devices to control the corresponding cooling devices to remove heat according to the mode indicated by the parameter values.

11. A parameter optimization device for a chemical cooling system, comprising: an information acquisition unit, configured to acquire a heat requirement for the heat to be removed and a cooling path corresponding to the chemical cooling system, wherein the cooling path is used to indicate an ordered combination of cooling devices in the chemical cooling system used to remove heat from each chemical device that generates the heat to be removed; a model building unit configured to establish a heat exchange model according to the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, and the parameters include operating variables for the cooling device; an objective function constructing unit, configured to construct an objective function based on resources consumed by the cooling device for heat removal and weights corresponding to various resources; and The optimization calculation unit is configured to use an optimization algorithm to determine the parameter value of the parameter under the cooling path so as to minimize the value of the objective function under the constraint conditions, wherein the constraint conditions include that the total heat that can be removed by the heat exchange model under the conditions of heat exchange in the cooling path and with the given parameter value meets the heat requirement and that each chemical device meets its own safe and stable operation conditions.

12. A parameter optimization device for a chemical cooling system, comprising: At least one processor, a memory coupled to the at least one processor, and a computer program stored on the memory, wherein the at least one processor executes the computer program to implement the parameter optimization method for a chemical cooling system as described in any one of claims 1 to 10.

13. A computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the parameter optimization method for a chemical cooling system according to any one of claims 1 to 10.

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