Parameter Optimization Method and Device for Chemical Industry Cooling System

Abstract

The embodiments of the present specification provide a parameter optimization method and apparatus for a chemical cooling system. Using this method and apparatus, a heat requirement for heat to be removed and a cooling path corresponding to the cooling system are obtained, the cooling path being used to indicate an ordered combination of cooling devices in the cooling system used to remove heat from each chemical device that generates the heat to be removed; a heat exchange model is established based on the cooling path, the heat exchange model including parameters to be optimized and associated data obtained for calculating the heat exchange amount; an objective function is constructed based on the resources consumed by the cooling device for heat removal and the weights corresponding to each resource; and an optimization algorithm is used to determine the parameter values of the parameters under the cooling path to minimize the value of the objective function while satisfying constraints, the constraints including that the total heat that can be removed by the heat exchange model under the conditions of heat exchange along the cooling path and the given parameter values meets the heat requirement of the chemical device and ensures safe and stable operation.

Description

Technical Field

[0001] The embodiments of this specification generally relate to the field of industrial optimization control, and more particularly to a method and apparatus for optimizing parameters of cooling systems used in industrial production equipment such as chemical industries. Background Art

[0002] In the chemical production sector, cooling systems effectively remove heat generated by various equipment through various cooling technologies. This plays a crucial role in ensuring safe and stable production operations, improving equipment efficiency, extending equipment life, and improving the chemical production environment. With the continuous development of intelligent manufacturing technology and the increasing importance of energy conservation and emission reduction, optimizing cooling systems has become a pressing issue.

[0003] Currently, optimization approaches for cooling systems primarily focus on the design phase, selecting the optimal solution from multiple design alternatives. Consequently, when actual operating conditions differ from the design, it can be difficult to find optimal operating parameters, potentially leading to wasted resources in pursuit of heat removal requirements. Therefore, a parameter optimization method for chemical cooling systems is needed to address at least some of these issues. Summary of the Invention

[0004] In view of the above, embodiments of this specification provide a parameter optimization method and apparatus for a chemical cooling system. Using this method and apparatus, a heat exchange model is established based on the heat requirements for heat to be removed and the corresponding cooling paths of the cooling system. An objective function is constructed based on the resources consumed by the cooling device for heat removal and the corresponding weights. An optimization algorithm is then used to determine parameter values, enabling offline or online, static, or dynamic optimization of the cooling system's parameters. Furthermore, the cooling paths and weights can be adjusted to meet the parameter optimization requirements of different application scenarios, thus possessing broad 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 based on the cooling path, wherein the heat exchange model includes parameters to be optimized and associated data obtained for calculating the heat exchange amount, the parameters including 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 values 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 based on 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 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 operation conditions.

[0007] According to another aspect of the embodiments of this specification, a parameter optimization device for a chemical cooling system is provided, comprising: at least one processor, and a memory coupled to the at least one processor, the memory storing instructions, which, when executed by the at least one processor, causes the at least one processor to execute the parameter optimization method for a chemical cooling system as described above.

[0008] According to another aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, it implements the parameter optimization method for a chemical cooling system as described above.

[0009] According to another aspect of the embodiments of this 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 present disclosure may be achieved by referring to the following drawings, in which 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 illustrating 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 flow chart illustrating 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 illustrating an example of a chemical plant according to an embodiment of the present specification.

[0015] Figure 5 A flowchart illustrating an example of a process for calculating a cooling requirement value corresponding to chemical equipment according to an embodiment of this specification.

[0016] Figure 6 A flowchart illustrating another example of a process for calculating a cooling requirement value corresponding to chemical equipment according to an embodiment of this 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 The flowchart shows an example of a process for determining weights corresponding to resources according to an embodiment of the present specification.

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

[0020] Figure 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] Figure 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 embodiments. It should be understood that the discussion of these embodiments is intended only to enable those skilled in the art to better understand and implement the subject matter described herein, and is not intended to limit 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 the various examples as needed. In addition, features described in some examples may also be combined in other examples.

[0023] As used herein, the term "including" and its variations are 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 operations implemented by systems according to some embodiments of the present specification. It should be clearly understood that the operations of the flowcharts may not be implemented in sequence. Rather, the operations may be implemented in reverse order or simultaneously. Furthermore, one or more additional operations may be added to the flowcharts. One or more operations may be removed from the flowcharts.

[0025] The parameter optimization method and device for a chemical cooling system according to an embodiment of this 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] Network 110 may be any type of network capable of interconnecting network entities. Network 110 may be a single network or a combination of various networks. In terms of coverage, network 110 may be a local area network (LAN), a wide area network (WAN), or the like. In terms of carrier media, network 110 may be a wired network, a wireless network, or the like. In terms of data exchange technology, network 110 may be a circuit switching network, a packet switching network, or the like.

[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 make-up water amount. 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 through automatic control, such as proportional-integral-derivative (PID) control or model predictive control (MPC).

[0030] Server 130 can interact with terminal device 120 via network 110. In some examples, server 130 can execute a parameter optimization method for a chemical cooling system and transmit the determined parameter values to terminal device 120. In some examples, terminal device 120 can execute new control operations according to the transmitted parameters through actuators and control units.

[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 corresponding cooling path of the cooling system are obtained.

[0034] In this embodiment, a cooling path can be used to indicate the ordered combination of cooling devices in a cooling system used to remove heat from various chemical plants generating 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 no 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 within the range [Q - ΔQ1, Q + ΔQ2]. ΔQ1 and ΔQ2 can represent the possible fluctuation range of the heat to be removed. In some examples, ΔQ1 and ΔQ2 can be set based on actual production conditions or historical operating conditions. In some examples, the cooling system can include at least one cooling device, such as a cooling tower, a heat exchanger, a fan, or an air cooler. A chemical plant can include various production plants, such as chemical production plants. In one example, a cooling path can be used to sequentially remove heat from chemical plant X using cooling devices A and B. In another example, a cooling path can be used to sequentially remove heat from chemical plant Y and chemical plant Z using cooling device C, and so on. For example, the amount of heat to be removed and its fluctuation range can be obtained from historical data or theoretically calculated. More specifically, if 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 its fluctuation range can be calculated based on factors that affect heat, such as the amount and temperature of the incoming and outgoing materials of the chemical production plant, the endothermic and exothermic properties of chemical reactions, and phase change heat.

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

[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 based on the design documents of the chemical plant. It will be understood that a higher cooling requirement value generally indicates that the chemical plant generates more heat 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 value is adjusted accordingly to obtain the heat concern value corresponding to each chemical device.

[0039] In this embodiment, the magnitude of the thermal concern value can be used to reflect the degree of concern for the corresponding chemical plant during the cooling path optimization process and the tendency to make adjustments. In some examples, different process flows may have different degrees of restrictions on cooling path optimization. In some examples, the restrictions on cooling path optimization by a process flow can be determined based on the degree of relevance of the process flow to 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 relevance of a chemical plant to the main process of the 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 cooling path optimization, which means that the cooling path is more likely to be unchanged, thereby relatively reducing the thermal concern value corresponding to the chemical plant. Correspondingly, the lower the relevance of a chemical plant to the main process of the 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 cooling path optimization, which means that the cooling path can be optimized to a greater extent, thereby relatively increasing the thermal concern value corresponding to the chemical plant. For example, if a chemical plant is a reactor, changes to its cooling pathway can affect the temperature stability of the main production circuit and / or the reactor, thereby significantly impacting smooth production and / or affecting product capacity and quality. Therefore, the benefits and risks of changing the cooling pathway need to be assessed and disclosed as much as possible. The corresponding thermal concern value can be lowered accordingly, for example, by multiplying the cooling demand value of the chemical plant by an adjustment coefficient between 0 and 1 to obtain the corresponding thermal concern value. It is understood that in some examples, the greater the degree of process flow constraints on cooling pathway optimization, the closer the adjustment coefficient is to 0. For another example, if a chemical plant is a steam storage tank, it is not located in the main process flow, and even if changes to the cooling pathway result in temporary or permanent changes in cooling capacity, this can be accommodated by adjusting the steam intake and discharge rates, with minimal impact on the main process of producing the product. However, optimizing the cooling pathway can significantly save resource consumption. In this case, the thermal concern value can be appropriately increased, for example, by multiplying the cooling demand value of the chemical plant by a coefficient greater than 1 to obtain the corresponding thermal concern value. For example, if a chemical plant's process requires equipment with low temperature sensitivity, frequent cooling path adjustments can be made, appropriately raising the thermal concern value. Conversely, if a chemical plant's process requires equipment with high temperature sensitivity, such as equipment temperature fluctuations that could cause serious safety or quality issues or even production halts, then adjustments to the cooling path should be avoided, appropriately lowering the thermal concern value.

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

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

[0042] For each target chemical plant, execute steps 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 heat removal interval for the target chemical plant may be [Q - ΔQ1, Q + ΔQ2], and the plant heat removal requirement may be that the heat removed by the cooling system is within the interval [Q - ΔQ1, Q + ΔQ2]. In some examples, the plant heat removal requirement may be that the heat removed by the cooling system is no less than Q + ΔQ2.

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

[0046] like Figure 4 As shown, a 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 units 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, chemical separation equipment, etc.

[0047] For example Figure 4The chemical plant 400 shown can calculate the cooling requirement value corresponding to each chemical plant, then combine the cooling requirement values corresponding to each chemical plant (e.g., chemical plant 411, chemical plant 412, etc.) belonging to the same process unit (e.g., process unit 410) to obtain the cooling requirement value corresponding to each process unit. Furthermore, the cooling requirement values corresponding to each process unit are combined to obtain the cooling requirement value corresponding to chemical plant 400. The heat removal requirement of the plant can then be determined based on the cooling requirement value corresponding to chemical plant 400 and the obtained cooling requirement fluctuation. In some examples, the cooling requirement value can be used to indicate an estimated amount of heat to be removed. In some examples, the heat removal requirement of the plant can be expressed in the form of a design range of heat to be removed. The cooling requirement value can also have a corresponding cooling requirement fluctuation. For example, the design range of heat to be removed can be expressed as [Q - ΔQ1, Q + ΔQ2]. Where Q is the corresponding cooling requirement value, and ΔQ1 and ΔQ2 are the corresponding cooling requirement fluctuations. ΔQ1 can be used to indicate the magnitude of the downward fluctuation, and ΔQ2 can be used to indicate the magnitude of the upward fluctuation. In some examples, the values of ΔQ1 and ΔQ2 can be set based on at least one of the following: actual production conditions, historical operating conditions, process requirements, and the equipment's sensitivity to temperature. For example, if actual production conditions or historical operating conditions indicate that the cooling demand for the device has not changed much, then ΔQ1 and ΔQ2 can be set to smaller values accordingly, and vice versa. For another example, if the process has strict temperature requirements or the corresponding chemical equipment is sensitive to temperature changes, then ΔQ1 and ΔQ2 can be set to larger values accordingly, and vice versa. It will be understood that the values of ΔQ1 and ΔQ2 can be the same or different, and this is 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 illustrating an example of a process 500 for calculating a cooling requirement value corresponding to a chemical plant according to an embodiment of the present specification is shown.

[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 between the chemical equipment and the product can be pre-set. In some examples, the association can be determined based on the association 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 product design output based on the reactor's corresponding product. For another example, if the chemical equipment is a steam turbine, the associated product design output can be the product design output based on the power or electricity generated by the steam turbine.

[0052] At 520 , a cooling requirement value corresponding to the chemical equipment is calculated based on 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 can be determined based on the relationship between the chemical equipment and the chemical equipment producing the product. For example, if the chemical equipment is a reactor, the reactor's heat of reaction can be calculated based on the designed product output, reaction temperature, and the heat of reaction per unit of product output. This can then be combined with factors such as the temperature and amount of each input and output material, and estimated or measured natural heat dissipation to determine the corresponding cooling requirement for the chemical equipment. For another example, if the chemical equipment is a steam turbine, the required steam volume and exhaust gas conditions can be calculated based on the designed product output to determine the corresponding cooling requirement.

[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 illustrating another example of a process for calculating a cooling requirement value corresponding to chemical equipment according to an embodiment of this 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 an 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 to be within the corresponding upper and lower limit ranges, so that the chemical equipment can meet the upper and lower limit values and achieve the designed product output when operating according to the parameter value of the process parameter.

[0059] It is understood that, as long as the chemical equipment operates within these process parameter values, meeting upper and lower limits and safely and stably achieving the designed product output, the values of the individual process parameters in the adjustable process parameter group can be combined in various ways. For example, for a heat exchanger, the water supply temperature in the process parameter can be lowered. For another example, for a steam turbine, the back pressure can be increased.

[0060] At 630 , a cooling requirement value corresponding to the chemical equipment is calculated based on the parameter values of the process parameters and the designed product output.

[0061] In this embodiment, based on the parameter values of the process parameters and the designed product output, the cooling requirement value corresponding to the chemical equipment can be calculated according to the corresponding process. It can be understood that for adjustable process parameter groups composed of different parameter values of the process parameters, different cooling requirement values can be respectively corresponding.

[0062] Through the above method, a method is provided for calculating the cooling demand value corresponding to the chemical equipment according to different parameter values of the process parameters, 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 heat removal requirements of the device.

[0064] In the present embodiment, the device-level cooling path is used to indicate an ordered combination of cooling devices in the cooling system used to remove heat from the target chemical plant. The cooling devices in the cooling system may have a maximum heat removal amount and a minimum heat removal amount. By performing different ordered combinations of the cooling devices in the cooling system, an alternative device-level cooling path that meets the device heat removal requirements can be obtained. For example, 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, 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, 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 will 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 proximity, cost savings, 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 corresponding to each target chemical plant can be accumulated to obtain an overall heat requirement for each target chemical plant. For example, the heat to be removed Q corresponding to each chemical plant can be accumulated to obtain an overall heat to be removed ∑Q. Thus, the heat requirement determined can be that the heat removed by the cooling system is not less than ∑Q. For another example, the heat requirement determined can be that the heat removed by the cooling system is within the interval [∑Q-ΔQ'1,∑Q+ΔQ'2]. ΔQ'1 and ΔQ'2 can be set based on the actual production conditions or historical operating conditions of each target chemical plant as a whole.

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

[0069] In some examples, the path search and feasibility analysis may include selecting nearby alternative cooling devices in the cooling system, adding or removing cooling devices from the ordered combination, or modifying the connections between cooling devices by balancing resource consumption while meeting thermal requirements and taking into account process characteristics, thereby determining a cooling path that meets the cooling path optimization objective. In some examples, the cooling path optimization objective may be, for example, minimizing resource consumption or total cost.

[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 used to simulate and analyze 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 performed by combining 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, operational variables may refer to variables that directly affect the operating status of the cooling device, such as the power of the cooling tower's fan, the number of cooling units in use, water consumption, etc. The associated data used to calculate the heat exchange rate may be non-optimized variables required for calculating the heat exchange rate. These variables can be obtained in various ways, such as the cooling tower's inlet water temperature via a temperature sensor, the cooling tower's make-up water flow rate via a flow sensor, and the fan's current operating power and power consumption via 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 illustrating an example of a heat exchange model 700 according to an embodiment of the present specification.

[0075] like Figure 7 As shown, heat exchange model 700 may include a first cooling loop 710, a second cooling loop 720, and a cooling tower 730. In first cooling loop 710, cooling tower 730 circulates a first cooling liquid. In second cooling loop 720, a second cooling liquid removes heat from various chemical plants. A chemical plant may include multiple process units. The second cooling liquid can be cooled by exchanging heat with the first cooling liquid. For example, the second cooling liquid can exchange heat with the first cooling liquid via heat exchanger 740.

[0076] In some optional implementations, the aforementioned parameter also includes supply water temperature, and the aforementioned operating variable includes at least one of the following: makeup water volume, fan power in the cooling tower. The first cooling liquid includes seawater, and the second cooling liquid includes demineralized water, wastewater, a process stream, etc.

[0077] Through the above method, 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 for heat removal 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, desalinated 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 represent the consumed resources, 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. 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 the cost of resources (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 FIG. 8 is a flowchart illustrating 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 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 remaining.

[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 operating and its 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 that the resource needs to be saved. For example, when the cooling water consumption is significantly higher than the water consumption under normal operation of the system in the historical chemical system operation data, the utilization status of the cooling water consumption can be used to indicate that cooling water needs to be saved. In some examples, for a certain resource, relevant data can be selected from the system operation data for analysis to determine whether this resource needs to be saved. 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 that electricity needs to be saved.

[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 weight value can be matched to the resource conservation requirement indicated by the operating status of each chemical plant and the resource utilization status. In some examples, when solving for the minimum value of the objective function, a higher weight can be assigned to a resource if the resource conservation requirement indicated by the resource utilization status is higher.

[0087] Through the above method, it is creatively proposed to determine the weights of corresponding resources based on 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] Figure 9 FIG. 1 is a flowchart illustrating an example of a process 900 for constructing an objective function according to an embodiment of the present specification.

[0089] like Figure 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, a correspondence between the system operating data and the safety margin weight corresponding to the heat requirement can be pre-set. In some examples, when the system operating data indicates that the system operating status meets the preset conditions, it is necessary to prioritize leaving a sufficient safety margin for heat removal. In this case, the safety margin weight corresponding to the heat requirement can be determined to be a higher value.

[0091] At 920 , a heat removal safety margin is determined based on 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. Q' can be used to represent the total heat that can be removed based on the heat transfer model under given parameters. Q can be used to represent the amount of heat to be removed as indicated by the heat requirement. In some examples, Q' can be expressed as an expression including 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 way, 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 constraints.

[0097] In this embodiment, 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 given parameter values meets the heat requirements and makes each chemical plant meet its own safe and stable operation conditions. In some examples, the safe and stable operation conditions of each chemical plant can include, for example, that the heat that can be removed by each chemical equipment included in the chemical plant meets the heat range required to be removed by the chemical equipment, and that the operating temperature, pressure, flow rate, etc. of each chemical equipment meet the corresponding predetermined safety range of the chemical equipment. In some examples, the safe and stable operation conditions of each chemical plant can also include, for example, parameter ranges that meet past historical excellent working conditions, 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, given the aforementioned cooling path, the objective function value (e.g., the sum of total water consumption and total electricity consumption) can be minimized by optimizing the parameter values of parameters (e.g., the fan power of the cooling tower, the number of cooling tower operating units, water consumption, etc.). It will be appreciated that, in conjunction with the corresponding descriptions in the aforementioned embodiments, the aforementioned parameters and objective function may also take other forms, which will not be further elaborated here.

[0098] In some optional implementations, the parameter values can 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. This can achieve automatic control and optimization of the operation of the cooling devices.

[0099] use Figures 1-9 The parameter optimization method for chemical cooling systems disclosed in [1] establishes a heat exchange model based on the heat requirements for heat to be removed and the corresponding cooling paths of the cooling system. It also constructs an objective function based on the resources consumed by the cooling device for heat removal and the weights corresponding to each resource. An optimization algorithm is then used to determine parameter values, achieving dynamic optimization of the cooling system parameters. Furthermore, the parameter optimization requirements for different application scenarios (such as increasing or decreasing production of certain circuits in the cooling system, or even stopping the system) can be adapted by adjusting the cooling paths and weights, thus having broad application value.

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

[0101] like Figure 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 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 generating 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 plants; adjust the cooling demand values corresponding to the respective chemical plants according to the optimization restrictions of the process flow for the cooling path corresponding to the respective chemical plants, and obtain the heat attention value corresponding to the respective chemical plants, wherein the size of the heat attention value is used to reflect the degree of attention paid to the corresponding chemical plant in the process of optimizing the cooling path; determine the target chemical plant for the cooling path to be optimized from the various chemical plants according to the heat attention value; for each target chemical plant, based on the cooling demand value and cooling demand corresponding to the target chemical plant, 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: calculate, for each chemical plant and for each process unit of the chemical plant, the cooling demand value corresponding to each chemical equipment in the process unit; and combine and calculate the cooling demand value corresponding to each chemical equipment to obtain the cooling demand value corresponding to the process unit; combine and calculate the cooling demand value 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 value corresponding to each chemical plant and the obtained cooling demand fluctuation amount.

[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 limit values 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, 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.

[0108] In some examples, the parameters further 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, wherein 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 the various resources.

[0111] In some examples, the weights corresponding to the resources are determined by: obtaining system operation data of the industrial system in which 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 the chemical plants and determining the utilization status of the resources; and determining the weights corresponding to the resources based on the operating status of the chemical plants and the utilization status of the resources.

[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 values of the parameters in the cooling path using an optimization algorithm to minimize the value of the objective function while satisfying constraints. 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.

[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 Figure 10 The operation of each unit in the parameter optimization device for chemical cooling system described above can refer 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 embodiments of this specification can be implemented using hardware, software, or a combination of hardware and software. Taking software implementation as an example, as a logical device, the device is formed by the processor of the device in which it is located reading the corresponding computer program instructions from the memory into the memory and executing them. In the embodiments of this specification, the parameter optimization device for a chemical cooling system can be implemented, for example, using an electronic device.

[0118] Figure 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 Figure 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 storage 1130, and a communication interface 1140, and the at least one processor 1110, the memory 1120, the storage 1130, and the communication interface 1140 are connected together via a bus 1150. The 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 based on 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; construct an objective function based on resources consumed by the cooling device for heat removal and weights corresponding to each resource; and use an optimization algorithm to determine the parameter values of the parameters under the cooling path 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 operation 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 this specification. Figures 1-9 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 elements implemented in software form) that, when executed by a computer, cause the computer to perform the above-mentioned combined functions in various embodiments of this specification. Figures 1-9 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 embodiments, and thus the machine-readable code and the machine-readable storage medium storing the machine-readable code constitute part of the present invention.

[0125] The computer program code required for the operation of the various parts 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, 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 a separate software package, or run partly on the user's computer and partly on a remote computer, or all on a 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 (e.g., CD-ROMs, CD-Rs, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs, DVD-RWs), 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 foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0128] Not all steps and units in the above processes and system structure diagrams are required, and some steps or units can be omitted according to actual needs. The execution order of each step is not fixed and can be determined as needed. The device structure described in the above 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 may be implemented by certain components in multiple independent devices.

[0129] The term "exemplary" is used throughout this specification to mean "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, these techniques can be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form to avoid obscuring the concepts of the described embodiments.

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

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

Claims

1. A parameter optimization method for a chemical cooling system, comprising: Obtaining a heat requirement for 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 heat exchange amount, wherein 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 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. The constructing objective function includes: Determining a safety margin weight corresponding to the heat requirement based on the acquired system operation data of the industrial system where each chemical plant is located, wherein the system operation data includes data indicating an operating status of the chemical plant; determining a heat removal safety margin based on a difference between a total amount of heat that can be removed under heat exchange conditions given the 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.

2. The parameter optimization method according to claim 1, wherein: Obtaining the heat requirement and the cooling path includes: Obtaining cooling demand values corresponding to each of the chemical plants; According to the optimization constraints of the process flow for the cooling path corresponding to each chemical device, 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 cooling path optimization process; Determining a target chemical plant whose cooling path is to be optimized from among the chemical plants according to the heat concern value; 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 candidate 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 requirement; and Path search and feasibility analysis are performed based on the device-level cooling paths corresponding to each target chemical plant to determine a cooling path that meets the heat requirements and conforms to the cooling path optimization goal.

3. The parameter optimization method according to claim 2, wherein: Determining the heat removal requirement of the device based on the cooling demand value and cooling demand fluctuation corresponding to the target chemical device includes: For each chemical plant, 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; Calculate the cooling demand values corresponding to each process unit together to obtain the cooling demand value corresponding to the chemical plant; and The heat removal requirements of each chemical plant are determined based on the cooling demand values corresponding to each plant and the obtained cooling demand fluctuations.

4. The parameter optimization method according to claim 3, wherein: Calculation of cooling requirements for 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 chemical equipment to achieve the designed output of the product is calculated.

5. The parameter optimization method according to claim 4, wherein: Calculating the cooling requirement value corresponding to the designed output of the product for 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 parameter values of each process parameter in the adjustable process parameter group within corresponding upper and lower limits, so that the chemical equipment, when operating according to the parameter values of the process parameters, meets the upper and lower limits and can achieve the designed product output; and The cooling demand value corresponding to the chemical equipment is calculated based on the parameter value of the process parameter and the designed output of the product.

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 the first cooling liquid, and the second cooling circuit uses the 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 further 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, and 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 plant is located, wherein the system operation data includes data indicating the operating status of the chemical plant; Based on the system operation data, evaluate the operating status of each chemical plant and determine the utilization status of each resource; and Based on the operating status of each chemical plant and the utilization status of each resource, a weight corresponding to each resource is determined.

9. The parameter optimization method according to claim 1, wherein: The parameter optimization method further includes: 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.

10. A parameter optimization device for a chemical cooling system, comprising: an information acquisition unit configured to acquire a heat requirement for 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, the parameters including 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 removing heat and weights corresponding to various resources; and The optimization calculation unit is configured to determine the parameter values of the parameters in the cooling path using an optimization algorithm 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. The objective function construction unit is further configured to: Determining a safety margin weight corresponding to the heat requirement based on the acquired system operation data of the industrial system where each chemical plant is located, wherein the system operation data includes data indicating an operating status of the chemical plant; determining a heat removal safety margin based on a difference between a total amount of heat that can be removed under heat exchange conditions given the 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.

11. 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 according to any one of claims 1 to 9.

12. 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 9.

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