Air conditioning system energy-saving optimization method based on system dynamics

Abstract

The invention relates to an air-conditioning system energy-saving optimization method based on system dynamics, which comprises the following steps: acquiring variables of a compressor, a water pump and a cooling tower in an air-conditioning system, and drawing a causal loop diagram of the air-conditioning system by adopting system dynamics software according to a feedback relationship among the variables of the compressor, the water pump and the cooling tower in the air-conditioning system, completing the construction of a system dynamics model; historical operation data of the air conditioning system are used as a training set to be input into the system dynamics model, and parameters of the system dynamics model are optimized and adjusted; and external environment parameters are obtained, the external environment parameters are input into the system dynamics model for calculation, an optimal control scheme is obtained, and the air conditioning system is regulated and controlled based on the optimal control scheme. According to the air conditioning system energy-saving optimization method based on system dynamics, global optimization is achieved by adjusting parameters of important components in the air conditioning system, and the optimal energy-saving effect is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of air - conditioning system optimization and energy management, and particularly to an energy - saving optimization method for an air - conditioning system based on system dynamics. Background Art

[0002] In modern buildings and industrial facilities, the heating, ventilation, and air - conditioning (HVAC) system is one of the main energy - consuming sources. Especially in large - scale central air - conditioning systems, the proportion of energy consumption is more significant. Traditional air - conditioning systems usually use preset fixed parameters to adjust the operation of equipment such as compressors, water pumps, and cooling towers. Although this method can achieve temperature control in some cases, its limitation is that it cannot effectively adapt to the dynamic changes of the external environment, resulting in energy waste.

[0003] In the prior art, most air - conditioning systems adopt simple feedback control mechanisms or experience - based parameter settings. For example, the power of the compressor may be roughly adjusted according to the feedback of the indoor temperature sensor, and the operating states of the water pump and the cooling tower are usually roughly adjusted according to the feedback of the indoor temperature sensor, while the operating states of the water pump and the cooling tower are usually simply adjusted according to the change of the external temperature. However, these adjustment methods do not fully consider the interactions between various components in the system and are difficult to achieve high - efficiency energy saving in a changing environment.

[0004] In addition, traditional air - conditioning system optimization methods usually rely on empirical formulas or static models and fail to capture the complex feedback loops and non - linear relationships inside the air - conditioning system. As a result, when factors such as the external temperature and humidity change drastically, the system shows a high energy consumption. Although existing air - conditioning systems achieve a certain degree of energy saving through simple logic control, they are still difficult to reach the best energy efficiency when facing a more complex usage environment. Summary of the Invention

[0005] In order to solve the problems existing in the above - mentioned background art, the present invention provides an energy - saving optimization method for an air - conditioning system based on system dynamics, which can effectively simulate and predict the dynamic response of the air - conditioning system under different environmental conditions, and achieve global optimization and the best energy - saving effect by adjusting the parameters of important components in the air - conditioning system.

[0006] In a first aspect, the present application provides an energy - saving optimization method for an air - conditioning system based on system dynamics, including:

[0007] Obtain the variables of the compressor, water pump, and cooling tower in the air - conditioning system; wherein, the variables include input variables and output variables;

[0008] According to the feedback relationships between the variables of the compressor, water pump, and cooling tower in the air - conditioning system, use system dynamics software to draw a causal loop diagram of the air - conditioning system and complete the construction of the system dynamics model;

[0009] Obtain multiple groups of preset environmental parameters as the training set and input them into the system dynamics model for simulation training to optimize and adjust the parameters of the system dynamics model;

[0010] Obtain the current external environmental parameters; wherein, the current external environmental parameters at least include the outside temperature, outside humidity and indoor load value;

[0011] Input the current external environmental parameters into the system dynamics model for calculation to obtain an optimal control scheme, and regulate the air conditioning system based on the optimal control scheme.

[0012] Optionally, according to the feedback relationship between the variables of the compressor, water pump and cooling tower in the air conditioning system, use system dynamics software to draw a causal loop diagram of the air conditioning system to complete the construction of the system dynamics model, including:

[0013] Establish data models of the compressor, the water pump and the cooling tower respectively according to the variables of the compressor, the water pump and the cooling tower;

[0014] Merge the data models according to system dynamics to determine the feedback relationship between the variables of the data models;

[0015] Generate the causal relationship links of each variable in the data model according to the feedback relationship, and draw a causal loop diagram of the air conditioning system;

[0016] Set the mathematical relationship of each variable according to the causal loop diagram to complete the construction of the system dynamics model.

[0017] Optionally, the input variables of the data model of the compressor at least include the inlet water temperature, condenser temperature, indoor load value and outside temperature, and the output variables at least include the compressor power and the outlet water temperature;

[0018] The input variables of the data model of the water pump at least include the condenser temperature, cooling tower efficiency and compressor discharge heat, and the output variables at least include the water flow rate and the water pump power consumption;

[0019] The input variables of the data model of the cooling tower at least include the inlet water temperature, outside temperature, outside humidity and condenser temperature, and the output variables at least include the wind speed, heat dissipation efficiency and outlet water temperature.

[0020] Optionally, the generating the causal relationship links of each variable in the data model according to the feedback relationship and drawing a causal loop diagram of the air conditioning system includes:

[0021] Determine the system boundary of the air conditioning system according to the data model;

[0022] Generate the causal relationship links of each variable in the data model based on the system boundary and the feedback relationship; wherein, the arrow of the causal relationship link represents the direction of the causal relationship of the variable, and the polarity of the causal relationship link represents the feedback relationship of the variable, with the positive pole representing the positive feedback relationship and the negative pole representing the negative feedback relationship;

[0023] Form the causal relationship links into loops to draw the causal loop diagram of the air conditioning system.

[0024] Optionally, obtaining multiple sets of preset environmental parameters as a training set and inputting them into the system dynamics model for simulation training to optimize and adjust the parameters of the system dynamics model, including:

[0025] Obtain the historical environmental parameters of the air conditioning system as input values and the corresponding air conditioning system control schemes as output values, train the system dynamics model, and obtain the initial parameter values of the system dynamics model;

[0026] Obtain multiple sets of preset environmental parameters as a training set and input them into the system dynamics model for multiple rounds of simulation, optimize and adjust the initial parameter values to obtain optimized parameter values, and use the optimized parameter values as the parameter values of the system dynamics model; wherein, the multiple sets of preset environmental parameters are obtained by simulation according to different external environmental conditions.

[0027] Optionally, inputting the external environmental parameters into the system dynamics model for calculation to obtain an optimal control scheme, and regulating the air conditioning system based on the optimal control scheme, including:

[0028] Input the external environmental parameters into the system dynamics model for calculation, and calculate the parameter values corresponding to the variables of the compressor, water pump, and cooling tower;

[0029] Output the parameter values corresponding to the variables of the compressor, water pump, and cooling tower to generate an optimal control scheme, and regulate the air conditioning system based on the optimal control scheme.

[0030] Optionally, after completing the construction of the system dynamics model, it further includes:

[0031] Set the simulation parameters and initial conditions of the system dynamics model; wherein, the initial conditions include the initial parameter values of each variable.

[0032] Optionally, when inputting the current external environmental parameters into the system dynamics model for calculation, it further includes:

[0033] Input the current external environmental parameters, set the parameter values corresponding to the variables of the compressor, water pump, and cooling tower in the nodes of the causal loop diagram, and generate an air-conditioning system control scheme.

[0034] In a second aspect, the present application provides an energy-saving optimization device for an air-conditioning system based on system dynamics, which is characterized by including:

[0035] A variable acquisition module for acquiring the variables of the compressor, water pump, and cooling tower in the air-conditioning system;

[0036] A system dynamics model construction module for drawing a causal loop diagram of the air-conditioning system using system dynamics software according to the feedback relationship between the variables of the compressor, water pump, and cooling tower in the air-conditioning system, and completing the construction of the system dynamics model;

[0037] A simulation module for obtaining multiple groups of preset environmental parameters as a training set and inputting them into the system dynamics model for simulation training to optimize and adjust the parameters of the system dynamics model;

[0038] An environmental parameter acquisition module for acquiring the current external environmental parameters; wherein, the current external environmental parameters at least include the outside temperature, outside humidity, and indoor load value;

[0039] A calculation module for inputting the current external environmental parameters into the system dynamics model for calculation to obtain an optimal control scheme, and regulating the air-conditioning system based on the optimal control scheme.

[0040] In a third aspect, the present application provides a computer device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0041] An energy-saving optimization method for an air-conditioning system based on system dynamics provided by the present application, by acquiring the input variables and output variables of important components in the air-conditioning system, namely the compressor, water pump, and cooling tower, establishing a causal loop diagram of the air-conditioning system according to the feedback relationship between the component variables, and establishing a system dynamics model, inputting the set environmental parameters as a training set into the system dynamics model for simulation, observing the change trend of the variables and the dynamic behavior of the system, optimizing and adjusting the parameters of the system dynamics model, by inputting the acquired current external environmental parameters into the system dynamics model for calculation, obtaining the optimal operating state of the components in the system under the current environment, and outputting the parameter values of the component parameters, and regulating the air-conditioning system according to the output parameter values, thereby significantly reducing energy consumption and improving the overall operating efficiency of the system. Description of the Drawings

[0042] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0043] Figure 1 It is a flowchart of an energy-saving optimization method for an air-conditioning system based on system dynamics provided by an embodiment of the present application;

[0044] Figure 2 It is a step flowchart for drawing a causal loop diagram of an air-conditioning system provided by an embodiment of the present application;

[0045] Figure 3 It is a step flowchart for optimizing and adjusting the parameters of a system dynamics model provided by an embodiment of the present application;

[0046] Figure 4 It is a structural diagram of an energy-saving optimization device for an air-conditioning system based on system dynamics provided by an embodiment of the present application. Specific embodiments

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention. The flowcharts used in the present application illustrate the operations implemented according to some embodiments of the embodiments of the present application. It should be understood that the operations in the flowchart may not be implemented in sequence, and steps without logical context relationships may be reversed or implemented simultaneously. In addition, those skilled in the art can add at least one other operation to the flowchart or remove at least one operation from the flowchart under the guidance of the content of the present application.

[0048] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of these features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0049] In the first aspect, please refer to Figure 1, Figure 1 It is a flowchart of an energy-saving optimization method for an air-conditioning system based on system dynamics provided by an embodiment of this application. An energy-saving optimization method for an air-conditioning system based on system dynamics includes:

[0050] S101, obtaining variables of a compressor, a water pump, and a cooling tower in the air-conditioning system; wherein, the variables include input variables and output variables;

[0051] S102, according to the feedback relationship between the variables of the compressor, the water pump, and the cooling tower in the air-conditioning system, using system dynamics software to draw a causal loop diagram of the air-conditioning system, and completing the construction of the system dynamics model;

[0052] S103, obtaining multiple groups of preset environmental parameters as a training set and inputting them into the system dynamics model for simulation training, and optimizing and adjusting the parameters of the system dynamics model;

[0053] S104, obtaining current external environmental parameters; wherein, the current external environmental parameters at least include the external temperature, the external humidity, and the indoor load value;

[0054] S105, inputting the current external environmental parameters into the system dynamics model for calculation, obtaining an optimal control scheme, and regulating the air-conditioning system based on the optimal control scheme.

[0055] System Dynamics (SD) is a method for understanding the nonlinear behavior of complex systems over time by using information such as stocks, flows, internal feedback loops, table functions, and time delays. It is not only a methodology for constructing, understanding, and discussing complex problems, but also a mathematical modeling technique. Software such as DYNAMO / Powersim / Vensim can be used to establish a system dynamics model. In this embodiment, Vensim software is used to establish the system dynamics model.

[0056] An energy-saving optimization method for an air-conditioning system based on system dynamics provided by this application, by obtaining the input variables and output variables of important components such as a compressor, a water pump, and a cooling tower in the air-conditioning system, establishing a causal loop diagram of the air-conditioning system according to the feedback relationship between the component variables, and establishing a system dynamics model, inputting the set environmental parameters as a training set into the system dynamics model for simulation, observing the change trend of variables and the dynamic behavior of the system, optimizing and adjusting the parameters of the system dynamics model, by inputting the obtained current external environmental parameters into the system dynamics model for calculation, obtaining the optimal operating state of the components in the system under the current environment, and outputting the parameter values of the component parameters, regulating the air-conditioning system according to the output parameter values, thereby significantly reducing energy consumption and improving the overall operating efficiency of the system.

[0057] The main energy consumption in the air - conditioning system comes from the working power of the compressor, the operating efficiency of the cooling tower, and the energy consumption of the water pump. By selecting components in the air - conditioning system, namely the compressor, the water pump, and the cooling tower, to establish a system dynamics model, the energy consumption situation of the air - conditioning system can be effectively reflected. The method of the present application is not limited to the compressor, the water pump, and the cooling tower in the air - conditioning system. In other embodiments, other components in the air - conditioning system can also be included to construct the system dynamics model.

[0058] For step S101, obtain the variables of the compressor, the water pump, and the cooling tower in the air - conditioning system; wherein, the variables include input variables and output variables.

[0059] In this embodiment, the input variables of the compressor at least include the inlet water temperature, the condenser temperature, the indoor load value, and the outside temperature, and the output variables at least include the compressor power and the outlet water temperature.

[0060] The input variables of the water pump at least include the condenser temperature, the cooling tower efficiency, and the compressor discharge heat, and the output variables at least include the water flow rate and the water pump power consumption.

[0061] The input variables of the cooling tower at least include the inlet water temperature, the outside temperature, the outside humidity, and the condenser temperature, and the output variables at least include the wind speed, the heat dissipation efficiency, and the outlet water temperature.

[0062] The present application conducts system dynamics analysis on the air - conditioning system, selects components of the compressor, the water pump, and the cooling tower in the air - conditioning system as the system boundary of the air - conditioning system, and based on the system dynamics principle of the physical models of the components, clarifies the relationships between the variables of the components, and clarifies the stocks and flows in the air - conditioning system.

[0063] For step S102, according to the feedback relationships between the variables of the compressor, the water pump, and the cooling tower in the air - conditioning system, use system dynamics software to draw a causal loop diagram of the air - conditioning system to complete the construction of the system dynamics model.

[0064] Please refer to Figure 2 , Figure 2 is a step - flow chart for drawing a causal loop diagram of an air - conditioning system provided by an embodiment of the present application. Specifically, step S102 includes the following steps:

[0065] S201, according to the variables of the compressor, the water pump, and the cooling tower, respectively establish data models of the compressor, the water pump, and the cooling tower.

[0066] The present application clarifies the key variables of the air - conditioning components, determines the input variables and output variables of each component, and respectively establishes data models for each component to describe the behavior or performance of the component, so as to understand how the components respond to changes within the system.

[0067] S202. Merge the data model according to system dynamics to determine the feedback relationships between the variables of the data model.

[0068] Use system dynamics tools to merge the models of the compressor, water pump, and cooling tower, and clarify the feedback relationships between the variables. In one embodiment, when the external temperature rises, the operating energy consumption of the compressor increases, and the operating energy consumption of the compressor is reduced by increasing the water pump flow rate and increasing the cooling tower wind speed; when the external temperature drops, the system reduces the water pump flow rate and reduces the compressor power to achieve energy-saving effects.

[0069] S203. Generate the causal relationship links of each variable in the data model according to the feedback relationships, and draw the causal loop diagram of the air conditioning system.

[0070] Specifically, step S203 further includes the steps of:

[0071] S2031. Determine the system boundary of the air conditioning system according to the data model. In this application, the compressor, water pump, and cooling tower are selected as the system boundary of the air conditioning system to construct a system dynamics model.

[0072] S2032. Generate the causal relationship links of each variable in the data model based on the system boundary and the feedback relationships; wherein, the arrow of the causal relationship link represents the direction of the causal relationship between the variables, and the polarity of the causal relationship link represents the feedback relationship of the variables, with the positive pole representing the positive feedback relationship and the negative pole representing the negative feedback relationship.

[0073] S2033. Combine the causal relationship links into a loop to draw the causal loop diagram of the air conditioning system.

[0074] A causal relationship link refers to a relationship chain composed of variables with causal relationships and the connections between them. The causal relationship link reflects the interaction relationship between events. In the causal relationship link, variables represent entities, attributes, or elements in the system. They may affect other variables or be affected by other variables. These variables can be specific events, states, or processes. Further, the causal relationship link also has an arrow and a polarity. Among them, the arrow represents the direction of the causal relationship, that is, from "cause" to "effect", and the polarity (i.e., plus or minus sign) beside the arrow represents the feedback relationship of the variable, with the plus sign representing the positive feedback relationship and the minus sign representing the negative feedback relationship.

[0075] S204. Set the mathematical relationship of each variable according to the causal loop diagram to complete the construction of the system dynamics model.

[0076] In a causal loop diagram, variables are usually classified into stocks, flows, and auxiliary variables. Stocks represent the quantities that accumulate or deplete over time in the system, flows represent the rates of change of stocks, and auxiliary variables are used to calculate other variables or parameters. In one embodiment, the variable type of each said variable is determined, and based on the causal relationships in the causal loop diagram and the type of the variable, a mathematical relationship for each said variable is set.

[0077] In some embodiments, after the construction of the system dynamics model is completed, it further includes:

[0078] Obtain the historical operation data of the air conditioning system, and input the historical operation data into the system dynamics model for verification. After the construction of the system dynamics model is completed, the accuracy and reliability of the constructed model are verified through the actual operation data of the air conditioning system.

[0079] In some embodiments, after the verification of the system dynamics model is completed, it further includes:

[0080] Set the simulation parameters and initial conditions of the system dynamics model; wherein, the initial conditions include the initial parameter values of each said variable.

[0081] The simulation parameters may include simulation time, step size, number of iterations, etc.

[0082] Please refer to Figure 3 , Figure 3 which is a flowchart of steps for optimizing and adjusting the parameters of the system dynamics model provided by the embodiments of the present application. For step S103, obtain multiple sets of preset environmental parameters as a training set and input them into the system dynamics model for simulation training to optimize and adjust the parameters of the system dynamics model. Specifically, it includes the following steps:

[0083] S301, obtain the historical environmental parameters of the air conditioning system as input values and the corresponding air conditioning system control schemes of the historical environmental parameters as output values, train the system dynamics model to obtain the initial parameter values of the system dynamics model.

[0084] S302, obtain multiple sets of preset environmental parameters as a training set and input them into the system dynamics model for multiple rounds of simulation, optimize and adjust the initial parameter values to obtain optimized parameter values, and use the optimized parameter values as the parameter values of the system dynamics model; wherein, the multiple sets of preset environmental parameters are obtained by simulation according to different external environmental conditions.

[0085] In this embodiment, by simulating the external environment, according to conditions such as season, weather, temperature and humidity, and time in the external environment, the operation of the air-conditioning system under different external environmental conditions is simulated, environmental parameters are generated, and input into the system dynamics model for simulation analysis to correct and optimize the parameters in the system dynamics model.

[0086] Among them, the air-conditioning system control scheme includes variables of each component in the air-conditioning system. For example, in one embodiment, the air-conditioning system control scheme includes compressor power, water pump speed, cooling tower power, etc. In other embodiments, it can also include flow rate, such as refrigerant flow rate.

[0087] For steps S104 and S105, obtain the current external environmental parameters; input the current external environmental parameters into the system dynamics model for calculation to obtain the optimal control scheme, and regulate the air-conditioning system based on the optimal control scheme.

[0088] Among them, step S105 includes the following steps:

[0089] S501, input the current external environmental parameters into the system dynamics model for calculation, and calculate the parameter values corresponding to the variables of the compressor, water pump, and cooling tower.

[0090] S502, output the parameter values corresponding to the variables of the compressor, water pump, and cooling tower to generate the optimal control scheme, and regulate the air-conditioning system based on the optimal control scheme.

[0091] In some embodiments, the inputting the current external environmental parameters into the system dynamics model for calculation further includes:

[0092] Input the current external environmental parameters, set the parameter values corresponding to the variables of the compressor, water pump, and cooling tower in the nodes of the causal loop diagram to generate the air-conditioning system control scheme.

[0093] The nodes in the causal loop diagram represent components or parameter values. After inputting the external environmental parameters, by manually setting the parameter values of the variables of the components, the air-conditioning system control scheme can be correspondingly generated. By manually changing the values of the variables, the change in the energy consumption of the air-conditioning system can be dynamically and intuitively observed.

[0094] The method of this application is not limited to three types of components, namely the compressor, water pump, and cooling tower. It can also include more components in the air-conditioning system to construct the system dynamics model, so as to implement more precise regulation of the air-conditioning system.

[0095] In this embodiment, a system dynamics model is constructed, and the mathematical relationship corresponding to each variable is set. During the simulation calculation process of the system dynamics model, the power consumption values of the compressor, water pump, and cooling tower in the air conditioning system can be obtained. With the goal of minimizing energy consumption, the parameters in the system dynamics model are adjusted through multiple rounds of simulation, and finally the optimal parameters of the mathematical relationship corresponding to the variables of each component are determined. By performing system dynamics model calculations with the optimized parameter values, and comparing the calculated energy consumption values with the preset initial parameter values, the energy-saving effect of this solution on the air conditioning system can be obtained.

[0096] After multiple rounds of simulation tests of this application, by adopting the energy-saving optimization method of this application, the energy consumption reduction range of the air conditioning system under various external environmental conditions can reach 10 - 30%.

[0097] An energy-saving optimization method for an air conditioning system based on system dynamics provided by this application constructs a system dynamics model of the air conditioning system through key components in the air conditioning system, namely the compressor, water pump, and cooling tower. A causal loop diagram is drawn according to the feedback relationship between its variables, and the mathematical relationships and simulation parameters of each variable in the model are set. The accuracy of the model is verified and optimized through simulation based on the historical operation data of the air conditioning system and the preset environmental parameter data, so as to optimize and adjust the parameters in the model. After adjustment, by obtaining the current external environmental parameters and inputting them into the model, the optimal adjustment parameters of each component under the current external environmental conditions can be obtained, and the air conditioning system can be dynamically adjusted, thereby effectively reducing energy consumption.

[0098] The present invention models and simulates multiple components in the air conditioning system through a system dynamics model, realizing multi-variable collaborative optimization and real-time feedback control of the system. This optimization algorithm can automatically adjust the operating states of the compressor, water pump, and cooling tower in the system according to changes in external environmental conditions, thereby significantly reducing energy consumption and improving the overall operating efficiency of the air conditioning system.

[0099] In a second aspect, please refer to Figure 4 , Figure 4 which is a structural diagram of an energy-saving optimization device for an air conditioning system based on system dynamics provided by an embodiment of this application. This application provides an energy-saving optimization device for an air conditioning system based on system dynamics, including:

[0100] A variable acquisition module 11, configured to acquire the variables of the compressor, water pump, and cooling tower in the air conditioning system; wherein, the variables include input variables and output variables.

[0101] A system dynamics model construction module 12, configured to draw a causal loop diagram of the air conditioning system by using system dynamics software according to the feedback relationship between the variables of the compressor, water pump, and cooling tower in the air conditioning system, and complete the construction of the system dynamics model.

[0102] A simulation module 13, configured to obtain multiple sets of preset environmental parameters as a training set and input the training set into the system dynamics model for simulation training, and optimize and adjust the parameters of the system dynamics model.

[0103] An environmental parameter acquisition module 14, configured to obtain current external environmental parameters; wherein, the current external environmental parameters at least include the external temperature, the external humidity, and the indoor load value.

[0104] A calculation module 15, configured to input the current external environmental parameters into the system dynamics model for calculation to obtain an optimal control scheme, and regulate the air conditioning system based on the optimal control scheme.

[0105] An energy-saving optimization device for an air conditioning system based on system dynamics in this embodiment is basically similar to the embodiment of the above-mentioned energy-saving optimization method for an air conditioning system. For the related parts, please refer to the introduction of the above method embodiment, and details will not be repeated here.

[0106] In a third aspect, the present application provides a processing device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor can execute the steps of the above method.

[0107] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0108] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the steps of the above method.

[0109] The above embodiments are only used to introduce the technical solutions of the present application in detail, but the descriptions of the above embodiments are only used to help understand the method of the embodiments of the present application, and should not be construed as a limitation of the present application. Any transformation or replacement that can be easily thought of by those skilled in the art should be covered by the protection scope of the embodiments of the present application.

Claims

1. An air conditioning system energy-saving optimization method based on system dynamics, characterized in that: include: Obtaining variables of a compressor, a water pump and a cooling tower in an air conditioning system; wherein the variables include input variables and output variables; According to the feedback relationship between the variables of the compressor, water pump and cooling tower in the air-conditioning system, a causal loop diagram of the air-conditioning system is drawn using system dynamics software to complete the construction of the system dynamics model; Acquire multiple sets of preset environmental parameters as training sets and input them into the system dynamics model for simulation training, and optimize and adjust the parameters of the system dynamics model; Acquire current external environment parameters; wherein the current external environment parameters at least include external temperature, external humidity and indoor load value; The current external environmental parameters are input into the system dynamics model for calculation to obtain an optimal control scheme, and the air conditioning system is regulated based on the optimal control scheme.

2. The air conditioning system energy saving optimization method based on system dynamics according to claim 1 is characterized in that: According to the feedback relationship between the variables of the compressor, the water pump and the cooling tower in the air-conditioning system, the causal loop diagram of the air-conditioning system is drawn using system dynamics software to complete the construction of the system dynamics model, including: According to the variables of the compressor, the water pump and the cooling tower, respectively establish data models of the compressor, the water pump and the cooling tower; Merging the data models according to system dynamics to determine feedback relationships between variables in the data models; Generate a causal relationship link of each variable in the data model according to the feedback relationship, and draw a causal loop diagram of the air conditioning system; The mathematical relationship of each variable is set according to the causal loop diagram to complete the construction of the system dynamics model.

3. The air conditioning system energy saving optimization method based on system dynamics according to claim 2 is characterized in that: The input variables of the data model of the compressor include at least inlet water temperature, condenser temperature, indoor load value and outside temperature, and the output variables include at least compressor power and outlet water temperature; The input variables of the data model of the water pump include at least condenser temperature, cooling tower efficiency and compressor exhaust heat, and the output variables include at least water flow and water pump power consumption; The input variables of the data model of the cooling tower include at least inlet water temperature, outside temperature, outside humidity and condenser temperature, and the output variables include at least wind speed, heat dissipation efficiency and outlet water temperature.

4. The air conditioning system energy-saving optimization method based on system dynamics according to claim 2 is characterized in that: Generating the causal relationship link of each variable in the data model according to the feedback relationship and drawing a causal loop diagram of the air conditioning system includes: determining a system boundary of the air conditioning system according to the data model; Generate a causal relationship link of each variable in the data model based on the system boundary and the feedback relationship; wherein the arrow of the causal relationship link represents the direction of the causal relationship of the variable, and the polarity of the causal relationship link represents the feedback relationship of the variable, the positive pole represents a positive feedback relationship, and the negative pole represents a negative feedback relationship; The causal relationship links are combined into a loop to draw a causal loop diagram of the air-conditioning system.

5. The air conditioning system energy saving optimization method based on system dynamics according to claim 1, characterized in that: The obtaining of multiple sets of preset environmental parameters as training sets and inputting them into the system dynamics model for simulation training, and optimizing and adjusting the parameters of the system dynamics model, includes: Acquire historical environmental parameters of the air-conditioning system as input values ​​and air-conditioning system control schemes corresponding to the historical environmental parameters as output values, train the system dynamics model, and obtain initial parameter values ​​of the system dynamics model; A plurality of sets of preset environmental parameters are obtained as training sets and input into the system dynamics model for multiple rounds of simulation, the initial parameter values ​​are optimized and adjusted to obtain optimized parameter values, and the optimized parameter values ​​are used as parameter values ​​of the system dynamics model; wherein the plurality of sets of preset environmental parameters are obtained by simulation according to different external environmental conditions.

6. The air conditioning system energy saving optimization method based on system dynamics according to claim 1, characterized in that: The inputting the current external environment parameters into the system dynamics model for calculation to obtain an optimal control scheme, and regulating the air conditioning system based on the optimal control scheme includes: Inputting the current external environmental parameters into the system dynamics model for calculation, and calculating the parameter values ​​corresponding to the variables of the compressor, the water pump and the cooling tower; Outputting parameter values ​​corresponding to the variables of the compressor, water pump and cooling tower to generate an optimal control scheme, and regulating the air-conditioning system based on the optimal control scheme.

7. The air conditioning system energy saving optimization method based on system dynamics according to claim 1, characterized in that: After the system dynamics model is constructed, the method further includes: The simulation parameters and initial conditions of the system dynamics model are set; wherein the initial conditions include the initial parameter value of each of the variables.

8. The air conditioning system energy-saving optimization method based on system dynamics according to claim 1, characterized in that: The inputting the current external environment parameters into the system dynamics model for calculation further includes: The current external environment parameters are input, and the parameter values ​​corresponding to the variables of the compressor, water pump and cooling tower are set in the nodes of the causal loop diagram to generate an air conditioning system control plan.

9. An air conditioning system energy-saving optimization device based on system dynamics, characterized in that: include: A variable acquisition module, used to acquire variables of a compressor, a water pump and a cooling tower in an air-conditioning system; wherein the variables include input variables and output variables; A system dynamics model building module is used to draw a causal loop diagram of the air-conditioning system using system dynamics software according to the feedback relationship between the variables of the compressor, water pump and cooling tower in the air-conditioning system, so as to complete the construction of the system dynamics model; A simulation module, used to obtain multiple sets of preset environmental parameters as training sets and input them into the system dynamics model for simulation training, and optimize and adjust the parameters of the system dynamics model; An environmental parameter acquisition module is used to acquire current external environmental parameters; wherein the current external environmental parameters at least include external temperature, external humidity and indoor load value; The calculation module is used to input the current external environment parameters into the system dynamics model for calculation, obtain an optimal control scheme, and regulate the air-conditioning system based on the optimal control scheme.

10. A computer device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when executing the computer program.

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