A control method, system, medium and electronic device for a fluid system

Abstract

An embodiment of this specification provides a fluid system control method, system, medium, and electronic device. The method includes: obtaining one or more energy parameters of multiple non-switching devices in a cold and heat source fluid system; generating one or more control models based on the positional relationship between the multiple non-switching devices and the one or more energy parameters; and controlling the multiple non-switching devices based on the one or more control models. This method can perform joint debugging and control of multiple non-switching devices in a cold and heat source fluid system, and has the advantages of reducing the overall system energy consumption and increasing the system flexibility.

Description

Technical Field

[0001] This specification relates to the field of fluid system control, and particularly to a control method, system, medium, and electronic device for a fluid system. Background Art

[0002] A non-switching device refers to a device whose output states are more than just "on" and "off". Existing group control technologies simply consider the number of devices that are turned on when dealing with multi-machine parallel connection in a cold heat source fluid system. First, one device is turned on at 100% power, then another device is turned on until 100% and the next device is turned on in sequence until all devices are turned on. This results in relatively low overall energy efficiency. When dealing with multi-machine series connection in a cold heat source fluid system, remote sensors are usually installed at the farthest position of the system being served, which leads to slow response, low overall energy efficiency of the system, and inflexible setting of requirements for supply and load.

[0003] Therefore, there is a need to provide a control method, system, medium, and electronic device for a fluid system to efficiently and flexibly control non-switching devices. Summary of the Invention

[0004] To address the deficiencies of existing non-switching device control, one embodiment of this specification provides a control method for a fluid system. The method includes: obtaining one or more energy parameters of a plurality of non-switching devices in a cold heat source fluid system; generating one or more control models based on the positional relationship between the plurality of non-switching devices and the one or more energy parameters; and controlling the plurality of non-switching devices based on the one or more control models.

[0005] In some embodiments, one embodiment of this specification provides a non-switching device control system. The system includes: an obtaining module for obtaining one or more energy parameters of a plurality of non-switching devices in a cold heat source fluid system; a first control model construction module for constructing one or more first control models based on the one or more control signal parameters and the status return signal; a control model generation module for generating one or more control models based on the positional relationship between the plurality of non-switching devices and the one or more energy parameters; and a control module for controlling the plurality of non-switching devices based on the one or more control models.

[0006] In some embodiments, one embodiment of this specification provides a storage medium storing program instructions, and a computer executes the above control method for a fluid system after reading the program instructions.

[0007] In some embodiments, one of the embodiments of this specification provides an electronic device, which includes at least one processor and at least one memory. Program instructions are stored in at least one of the memories, and after reading the program instructions, at least one of the processors executes the control method of the above-mentioned fluid system. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described by way of exemplary embodiments, which will be described in detail through the accompanying drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, where:

[0009] Figure 1 is a schematic diagram of an application scenario of a fluid system control system according to some embodiments of this specification;

[0010] Figure 2 is a schematic diagram of modules of a fluid system control system according to some embodiments of this specification;

[0011] Figure 3 is an exemplary flowchart of a fluid system control method according to some embodiments of this specification;

[0012] Figure 4 is an exemplary flowchart of obtaining a fourth control model according to some embodiments of this specification;

[0013] Figure 5 is a schematic diagram of the series positional relationship of multiple non-switching devices according to some embodiments of this specification;

[0014] Figure 6 is a schematic diagram of the parallel positional relationship of multiple non-switching devices according to some embodiments of this specification. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structures or operations.

[0016] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0017] As shown in this specification and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0018] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or subsequent operations do not necessarily need to be executed precisely in sequence. On the contrary, the steps can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or more steps can be removed from these processes.

[0019] Figure 1 It is a schematic diagram of application scenario 100 of a fluid system control system shown according to some embodiments of this application.

[0020] As Figure 1 shown, application scenario 100 may include a processing device 110, a network 120, a user terminal 130, a storage device 140, and a fluid system control system.

[0021] In some embodiments, the processing device 110 may process the information or data in application scenario 100. For example, the processing device 110 may send a control signal to the control module of the fluid system control system, and the control module controls the acquisition module to acquire the energy parameters of non-switching devices, and generates a control model based on the positional relationship between multiple non-switching devices and the acquired energy parameters, so as to facilitate the control of non-switching devices.

[0022] In some embodiments, the processing device 110 may be local or remote. For example, the processing device 110 may access information and / or data stored in the user terminal 130 and the storage device 140 via the network 120. In some embodiments, the processing device 110 may be directly connected to the user terminal 130 and the storage device 140 to access the information and / or data stored therein. In some embodiments, the processing device 110 may be executed on a cloud platform. For example, the cloud platform may include one or any combination of a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, etc. In some embodiments, the processing device 110 may include a processor, and the processor may include one or more sub-processors (e.g., a single-core processing device or a multi-core multi-chip processing device). Merely by way of example, the processor may include a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, etc. or any combination of the above.

[0023] The network 120 may facilitate the exchange of data and / or information in the application scenario 100. In some embodiments, one or more components in the application scenario 100 (e.g., the processing device 110, the user terminal 130, the storage device 140, and the fluid system control system) may send data and / or information to other components in the application scenario 100 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network. For example, the network 120 may include a cable network, a wired network, an optical fiber network, a telecommunications network, an internal network, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, etc. or any combination of the above.

[0024] The user terminal 130 can obtain information or data in the application scenario 100, and the user (e.g., the user of the fluid system control system) can be the user of the user terminal 130. For example, the user terminal 130 can send a control instruction to the processing device 110 through the network 120. The processing device 110 can obtain energy parameters through the acquisition module of the fluid system control system according to the control instruction, and generate a control model based on the positional relationship and energy parameters between non-switching devices to control the non-switching devices. In some embodiments, the user terminal 130 can include one or any combination of a mobile device, a tablet computer, a laptop computer, etc. In some embodiments, the mobile device can include a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, etc. or any combination thereof.

[0025] In some embodiments, the storage device 140 can be connected to the network 120 to communicate with one or more components in the application scenario 100 (e.g., the processing device 110, the user terminal 130, etc.). One or more components in the application scenario 100 can access the data or instructions stored in the storage device 140 through the network 120. In some embodiments, the storage device 140 can be directly connected to or communicate with one or more components in the application scenario 100 (such as the processing device 110, the user terminal 130). In some embodiments, the storage device 140 can be a part of the processing device 110.

[0026] The fluid system control system is used to control multiple non-switching devices. Based on this, the fluid system control system can exchange data and / or information with one or more components in the application scenario 100 (e.g., the processing device 110, the user terminal 130, and the storage device 140). For more descriptions about the fluid system control system, reference can be made to Figure 2 and its related descriptions.

[0027] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of the present application. For those of ordinary skill in the art, various changes and modifications can be made under the guidance of the content of the present application. The features, structures, methods, and other features of the exemplary embodiments described in the present application can be combined in various ways to obtain additional and / or alternative exemplary embodiments. For example, the storage device 140 can be a data storage device including a cloud computing platform, such as a public cloud, a private cloud, a community cloud, and a hybrid cloud, etc. However, these changes and modifications do not depart from the scope of the present application.

[0028] It should be understood that Figure 1 The system and its modules shown can be implemented in various ways. It should be noted that the above description of the application scenario 100 is only for convenience of description and cannot limit this specification within the scope of the exemplified embodiments.

[0029] Figure 2 It is a schematic diagram of modules of a fluid system control system shown according to some embodiments of this specification.

[0030] As Figure 2 shown, a fluid system control system may include an acquisition module, a control model generation module, and a control module.

[0031] The acquisition module can be used to acquire one or more energy parameters of multiple non-switching devices in a cold and heat source fluid system. In some embodiments, the energy parameters of non-switching devices can be acquired through sensors. For more descriptions of the acquisition module, reference can be made to Figure 3 and its related descriptions, which will not be elaborated here.

[0032] The control model generation module can be used to generate one or more control models based on the positional relationship between multiple non-switching devices and one or more energy parameters. Among them, the positional relationship between multiple non-switching devices can include a series relationship and a parallel relationship. For more descriptions of the control model generation module, reference can be made to Figure 3 and its related descriptions, which will not be elaborated here.

[0033] The control module can be used to control multiple non-switching devices based on one or more control models. In some embodiments, the control module can control the opening and closing of multiple non-switching devices according to the control models. For example: in a central air conditioning system, a heat exchanger is used when the temperature difference is large enough, and a refrigeration unit is used when the temperature difference is small. The heat exchanger and the refrigeration unit can be connected in parallel. According to the control model, different valves can be controlled to determine which device to use and switch between the two sets of devices. For more descriptions of the first control module, reference can be made to Figure 3 and its related descriptions, which will not be elaborated here.

[0034] It should be noted that the above descriptions of the acquisition module, the control model generation module, and the control module are only for the convenience of description and do not limit this specification within the scope of the examples given. It can be understood that for those skilled in the art, after understanding the principle of the system, they may, without departing from this principle, make any combination of each module, or form a subsystem and connect it with other modules. In some embodiments, Figure 2 the acquisition module, the control model generation module, and the control module disclosed in

[0035] Figure 3It is an exemplary flowchart of a fluid system control method shown in some embodiments of this specification.

[0036] As Figure 3 shown, a fluid system control method includes the following steps. In some embodiments, a fluid system control method can be executed by a fluid system control system and a processing device 110.

[0037] Step 310, obtain one or more energy parameters of multiple non-switching devices in a cold and heat source fluid system. In some embodiments, step 310 can be executed by an acquisition module.

[0038] A cold and heat source refers to a non-switching device that provides low-temperature fluid to remove heat or provides thermal energy to output energy. Among them, the fluid refers to flowing liquid or gas. A non-switching device refers to a device whose output state is more than just "on" or "off", such as: variable frequency pump, blower, variable frequency water pump, variable frequency chiller, dimming lamp, variable speed fan, etc. For example: The cold source can include a cooling tower, a condenser, etc. The heat source can include a boiler, a geothermal heat exchanger, etc. A cold and heat source fluid system refers to a fluid system that includes a cold source and / or a heat source. For example: a cooling system, a water cooling system, a heating system, a constant temperature system, an air conditioning system. An energy parameter refers to a parameter that can reflect the energy consumption of a non-switching device. The energy parameter can include voltage, current, power, duty cycle, temperature, flow rate, head, valve opening angle, and pressure. In some embodiments, the energy parameters of non-switching devices can be obtained through corresponding sensors. For example, temperature sensors, pressure sensors, current sensors, voltage sensors, power sensors, and flow meters can be used to obtain the temperature, pressure, current, voltage, power, and flow rate when the water pump is running.

[0039] Step 320, generate one or more control models based on the positional relationship between multiple non-switching devices and one or more energy parameters. In some embodiments, step 320 can be executed by a control model generation module.

[0040] In some embodiments, the positional relationship between multiple non-switching devices includes a series relationship and / or a parallel relationship. As Figure 5 shown, the series non-switching devices can include a cold / heat source, a pump, a heat exchanger, a refrigeration unit, a pump, and a cold / heat load. As Figure 6 shown, the parallel devices can include 1 to n refrigeration units. One or more first control models can be generated based on the series relationship and one or more energy parameters and / or one or more second control models can be generated based on the parallel relationship and one or more energy parameters. It can be understood that the appendix of this specification Figure 5 and 6A schematic diagram showing the series and parallel positional relationships of multiple non-switching devices. The positions and types of the non-switching devices can be adjusted, and the types of the non-switching devices can be the same or different. This embodiment is only for illustrative purposes and does not limit this specification to the scope of the examples given.

[0041] In some embodiments, in response to the positional relationship between multiple non-switching devices being a series relationship, one or more first control models for controlling the non-switching devices in the subsequent circuit are generated based on one or more energy parameters corresponding to the non-switching devices in the previous circuit. In some embodiments, the first control model can be a machine learning model. Among them, the input of the machine learning model is the name of the non-switching device in the previous stage, the corresponding energy parameter, and the name of the non-switching device in the subsequent stage (for example, heat exchanger, flow rate, water pump), and the output of the machine learning model is the energy parameter (flow rate) corresponding to the non-switching device in the subsequent stage. The machine learning model can include, but is not limited to, neural network (NN), convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), etc. or any combination thereof. For example, the machine learning model can be a model formed by combining a convolutional neural network and a deep neural network.

[0042] The specific process of establishing the first control model can be as follows: An initial machine learning model is established in advance, the name of the non-switching device in the previous stage, the corresponding energy parameter, and the name of the non-switching device in the subsequent stage are obtained, and a first training sample is generated. The label of the first training sample is the energy parameter (for example, flow rate) corresponding to the non-switching device in the subsequent stage. Based on the first training sample, the parameters of the initial machine learning model are updated until the trained initial machine learning model meets the preset conditions, and a trained machine learning model is obtained. The preset conditions can be that the loss function converges, the value of the loss function is less than the preset value, or the number of iterations is greater than the preset number of times, etc.

[0043] For another example, if the device at the previous stage of the water pump is a heat exchanger, the flow rate inside the heat exchanger can be obtained through a sensor, and a first control model is established based on the flow rate of the heat exchanger to control the flow rate of the water pump. For example, if the flow rate of the heat exchanger does not meet the requirements, the first control model can be used to control the water pump to increase the flow rate. If the flow rate of the heat exchanger reaches the standard, the first control model can be used to control the water pump to maintain the flow rate.

[0044] Controlling the energy consumption of the non-switching device in the subsequent stage through the energy parameters of the non-switching device in the previous stage overcomes the drawback in the prior art that in order to meet the energy consumption of the non-switching device at the farthest end, the energy consumption of the remaining non-switching devices is increased. It has the advantages of reducing unnecessary energy consumption and increasing the flexibility of the system.

[0045] In some embodiments, in response to the positional relationship among the plurality of non-switching devices being a parallel relationship, one or more third control models are constructed. One or more fourth control models are obtained by adjusting one or more third control models based on one or more preset reference models; the global optimal solutions of one or more fourth control models are calculated to obtain one or more second control models.

[0046] In some embodiments, when the positional relationship among the plurality of non-switching devices is a parallel relationship, a third control model can be constructed according to the acquired energy parameters. In some embodiments, the corresponding relationship between the energy parameters of the non-switching devices and time can be obtained through linear regression fitting, non-linear regression fitting, exponential fitting, logarithmic fitting, etc. Taking the speed and load of a variable-frequency water pump as an example, after obtaining N data pairs of the speed and load of the variable-frequency water pump, the N data pairs are subjected to data fitting, and the function that most accurately describes the relationship between the speed and load is selected as the third control model. Specifically, a scatter plot can be first established based on the SPSS software according to the speed of the variable-frequency water pump at multiple time points and the load of the variable-frequency water pump corresponding to the multiple time points. Through various curve fitting forms (such as linear regression fitting, non-linear regression fitting, exponential fitting, logarithmic fitting, etc.), multiple candidate fitting curves are obtained, and the candidate fitting curve that best fits the scatter plot is selected as the third control model. It can be understood that different energy parameters of the selected non-switching devices result in different third control models. This embodiment is only for illustration and does not limit this specification within the scope of the examples given.

[0047] In some embodiments, one or more fourth control models can be obtained by adjusting one or more third control models based on one or more preset reference models. Among them, the preset reference models can be linear functions, other high-order functions, exponential functions, etc. The preset reference models can be obtained through linear regression methods. For example, the reference model of the current parameter and power signal of the variable-frequency water pump can be preset as: y = kx + b, where x can be the current parameter, y can be the power signal, and k and b can be obtained through sampling calculations. In some embodiments, the system may not only calculate k and b. The system may also add coefficients or constants, or may add variables. For more descriptions of the fourth control model, see Figure 4 and related descriptions.

[0048] In some embodiments, the global optimal solutions of one or more fourth control models can be calculated to obtain one or more second control models. In some embodiments, a high-dimensional control model can be obtained by superimposing one or more fourth control models of multiple non-switching devices, and the highest energy efficiency point of the high-dimensional control model is selected as the global optimal solution to obtain the second control model.

[0049] Step 330, controlling a plurality of non-switching devices based on one or more control models. In some embodiments, step 330 may be performed by a control module.

[0050] In some embodiments, a plurality of non-switching devices may be controlled according to a first control model and / or a second control model. For example, when the non-switching devices in a cold and heat source fluid system are in series, the non-switching devices may be controlled by the first control model; when the non-switching devices in a cold and heat source fluid system are in parallel, the non-switching devices may be controlled by the second control model; when the non-switching devices in a cold and heat source fluid system have both series and parallel relationships, the first control model and the second control model may be used for joint control. By using the first control model and the second control model to perform joint adjustment and control on the non-switching devices in the cold and heat source fluid system, the overall system energy consumption can be reduced and the system flexibility can be increased.

[0051] Figure 4 is an exemplary flowchart of obtaining a fourth control model according to some embodiments of the present specification.

[0052] As Figure 4 shown, the method for obtaining the fourth control model includes the following steps.

[0053] Step 410, comparing one or more third control models with corresponding preset one or more reference models. Step 410 may be performed by a control model generation module.

[0054] Among them, the preset reference model may be a linear function, other higher-order functions, exponential functions, etc. The preset reference model may be obtained by a linear regression method. For example, the reference model of the current parameter and power signal of a variable-frequency water pump may be preset as: y = kx + b, where x may be the current parameter, y may be the power signal, and k and b may be obtained by sampling calculation.

[0055] Step 420, performing data sampling on the data interval of one or more third control models that are closest to the preset one or more reference models. Step 420 may be performed by a control model generation module.

[0056] In some embodiments, the power change curve of a preset reference model can be compared with the third control model by fitting. Taking the current and voltage of a variable-frequency water pump as independent variables and the flow rate and head as dependent variables as an example, in the initial deployment, N test independent variable data points are uniformly input into the control range of the control components. After each change in the dependent variable stabilizes, the response timestamps from the start of the change to the next stable state are recorded, and the stable rotational speed is also recorded. After obtaining N state points in sequence, the power efficiency curve of the preset reference model is fitted, and the control interval with the mapping relationship y = f(x) obtained by fitting is intercepted.

[0057] Step 430: Perform data fitting based on the sampled data to obtain one or more fourth control models. Step 430 can be executed by the control model generation module.

[0058] Based on the obtained linear control interval above, read the change and stable intervals between each common control point, and further take values and fit the control curve within this interval to obtain the fourth control model. It can be understood that in order to improve the control accuracy, after reading the change and stable intervals between each common control point, more than one fitting can be performed, and the third control model can be continuously adjusted to obtain a more accurate fourth control model.

[0059] It should be noted that the above description of a control method for a fluid system is only for illustration and explanation, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to a control method for a fluid system under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0060] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are proposed in this specification, so such modifications, improvements, and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0061] Meanwhile, this specification uses specific terms to describe the embodiments of this specification. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "an embodiment" or "one embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0062] In addition, unless otherwise expressly stated in the claims, the order of the processing elements and sequences, the use of numerical and alphabetical characters, or the use of other names described in this specification are not used to limit the order of the processes and methods in this specification. Although some currently useful embodiments of the invention are discussed by way of various examples in the above disclosure, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by a software solution, such as installing the described system on an existing server or mobile device.

[0063] Similarly, it should be noted that, in order to simplify the presentation of the disclosure in this specification and thus assist in the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of this specification, various features are sometimes grouped together in one embodiment, drawing, or description thereof. However, this method of disclosure does not mean that the features required by the subject matter of this specification are more than those mentioned in the claims. In fact, the features of the embodiments are fewer than all the features of the individual embodiments disclosed above.

[0064] For each patent, patent application, patent application publication, and other materials cited in this specification, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated into this specification by reference. This excludes the application history files that are inconsistent with or conflict with the content of this specification, as well as the files that limit the broadest scope of the claims of this specification (currently or subsequently appended to this specification). It should be noted that if there are any inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the supplementary materials of this specification and the content described in this specification, the descriptions, definitions, and / or uses of terms in this specification shall prevail.

Claims

1. A fluid system control method, characterized in that, Including: Obtaining one or more energy parameters of multiple non-switching devices in a cold and heat source fluid system; Generating one or more control models based on the positional relationship between the multiple non-switching devices and the one or more energy parameters, including: The positional relationship includes a parallel relationship; Generating one or more second control models based on the parallel relationship and the one or more energy parameters, specifically including: When the positional relationship between the multiple non-switching devices is the parallel relationship, constructing one or more third control models; Adjusting the one or more third control models based on one or more preset reference models to obtain one or more fourth control models, specifically including: Comparing the one or more third control models with the corresponding one or more preset reference models; Performing data sampling on the data interval of the one or more third control models that are closest to the one or more preset reference models; Performing data fitting based on the sampled data to obtain the one or more fourth control models; Calculating the global optimal solution of the one or more fourth control models to obtain one or more second control models; Controlling the multiple non-switching devices based on the one or more second control models.

2. The method according to claim 1, wherein The positional relationship further includes a series relationship; Generating one or more first control models based on the series relationship and the one or more energy parameters.

3. The method according to claim 2, wherein The generating one or more first control models based on the series relationship and the one or more energy parameters includes: When the positional relationship between the multiple non-switching devices is the series relationship, generating one or more first control models for controlling the non-switching devices in the subsequent loop according to the one or more energy parameters corresponding to the non-switching devices in the previous loop.

4. The method according to claim 1, wherein The calculating the global optimal solution of the one or more fourth control models includes: Superimposing the one or more fourth control models of the multiple non-switching devices to obtain a high-dimensional control model; Selecting the highest energy efficiency point of the high-dimensional control model as the global optimal solution.

5. A fluid system control system, characterized in that, Including: An acquisition module for obtaining one or more energy parameters of multiple non-switching devices in a cold and heat source fluid system; A control model generation module for generating one or more control models based on the positional relationship between the multiple non-switching devices and the one or more energy parameters; The positional relationship includes a parallel relationship, and the control model generation module is further used for: Generating one or more second control models based on the parallel relationship and the one or more energy parameters; When the positional relationship between the multiple non-switching devices is the parallel relationship, constructing one or more third control models; Adjusting the one or more third control models based on one or more preset reference models to obtain one or more fourth control models, specifically including: Comparing the one or more third control models with the corresponding one or more preset reference models; Performing data sampling on the data interval of the one or more third control models that are closest to the one or more preset reference models; Perform data fitting on the sampled data to obtain the one or more fourth control models; Calculate the global optimal solutions of the one or more fourth control models to obtain one or more second control models; A control module, configured to control the plurality of non-switching devices based on the one or more second control models.

6. The system according to claim 5, characterized in that The positional relationship further includes a series relationship, and the control model generation module is further configured to, Generate one or more first control models based on the series relationship and the one or more energy parameters.

7. The system according to claim 6, characterized in that, The control model generation module is further configured to, When the positional relationship between the plurality of non-switching devices is a series relationship, generate one or more first control models for controlling the non-switching devices in the subsequent circuit according to one or more energy parameters corresponding to the non-switching devices in the previous circuit.

8. The system according to claim 5, wherein The control model generation module is further configured to, Superimpose the one or more fourth control models of the plurality of non-switching devices to obtain a high-dimensional control model; Select the highest energy efficiency point of the high-dimensional control model as the global optimal solution.

9. A storage medium, characterized in that, Program instructions are stored in the storage medium, and the computer executes the method according to any one of claims 1-4 after reading the program instructions.

10. An electronic device, characterized in that, Comprising at least one processor and at least one memory, program instructions are stored in at least one of the memories, and at least one of the processors executes the method according to any one of claims 1-4 after reading the program instructions.

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