Method and device for determining regulation and control parameters of air conditioner load polymer and electronic equipment

Abstract

The invention discloses a method and device for determining regulation and control parameters of an air conditioner load polymer and electronic equipment. The method comprises the steps that operation state parameters of the air conditioner and environment condition parameters of the environment where the air conditioner is located are obtained; based on the operation state parameters and the environment condition parameters, a load equivalent thermal parameter model of the air conditioner is constructed; based on a preset comfort temperature range and the load equivalent thermal parameter model, a load polymer model of the air conditioner is constructed, and the preset comfort temperature range is used for representing a preset comfort temperature range of a user; and regulation and control parameters of the air conditioner are determined based on the load polymer model, and the regulation and control parameters are used for representing the regulation and control potential of the load polymer of the air conditioner. According to the method and the device, the technical problems of relatively low accuracy and efficiency of determining the regulation and control parameters of the air conditioner load polymer in related technologies are solved.

Description

Technical Field

[0001] The present invention relates to the field of air conditioning load aggregates, and in particular to a method, device and electronic equipment for determining control parameters of an air conditioning load aggregate. Background Art

[0002] With the development of new power system technologies and the continuous increase in the proportion of air conditioning load in the total power load, traditional power management and demand response strategies are facing severe challenges. Air conditioning load is affected by many factors such as ambient temperature and compressor operating status, which makes air conditioning load aggregation modeling a relatively complex and difficult task.

[0003] In the related art, the aggregation and adjustable potential evaluation method for central air-conditioning load usually evaluates the total amount, characteristics and adjustable potential of air-conditioning load by establishing an air-conditioning load model. For example, by establishing a first-order equivalent thermal parameter model, a mechanism model of a single air-conditioned room is obtained, and then an air-conditioning cluster control strategy is established, and a simulation experiment is conducted on the air-conditioning cluster to obtain the controllable proportional coefficient of the air-conditioning load and the actual demand response amount. The central air-conditioning load aggregate model established in this way is often relatively rough and difficult to accurately reflect the complexity and diversity of the actual system. The accuracy of air-conditioning load aggregation is low, and different users have different needs and preferences for temperature control loads such as air conditioning, which makes it difficult to meet the personalized needs of users, resulting in low accuracy and efficiency in determining the control parameters of the air-conditioning load aggregate in the related art.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device and electronic device for determining the control parameters of an air conditioning load aggregate, so as to at least solve the technical problem of low accuracy and efficiency in determining the control parameters of an air conditioning load aggregate in the related art.

[0006] According to one aspect of an embodiment of the present application, a method for determining control parameters of an air conditioning load aggregate is provided, comprising: obtaining operating state parameters of an air conditioner and environmental condition parameters of an environment in which the air conditioner is located; constructing a load equivalent thermal parameter model of the air conditioner based on the operating state parameters and the environmental condition parameters; constructing a load aggregate model of the air conditioner based on a preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent a preset user comfort temperature range; determining control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

[0007] Optionally, based on the operating state parameters and the environmental condition parameters, a load equivalent thermal parameter model of the air conditioner is constructed, including: based on the operating state parameters and the environmental condition parameters, constructing the relationship formula between room temperature and cooling capacity, the relationship formula between cooling capacity and frequency, the relationship formula between power and frequency, and the relationship formula between frequency and temperature deviation of the air conditioner; based on the relationship formula between room temperature and cooling capacity, the relationship formula between cooling capacity and frequency, the relationship formula between power and frequency, and the relationship formula between frequency and temperature deviation, constructing a load equivalent thermal parameter model.

[0008] Optionally, based on the operating state parameters and the environmental condition parameters, a relationship between the room temperature and the cooling capacity of the air conditioner is constructed, including: determining the equivalent thermal parameter model differential equation of the air conditioner based on the cooling capacity parameters in the operating state parameters, the indoor parameters in the environmental condition parameters, and the outdoor parameters in the environmental condition parameters; discretizing the equivalent thermal parameter model differential equation to obtain the relationship between the room temperature and the cooling capacity.

[0009] Optionally, based on a preset comfort temperature range and a load equivalent thermal parameter model, a load aggregate model of the air conditioner is constructed, including: determining a state of charge parameter based on a preset comfort temperature range and a load equivalent thermal parameter model; determining a power-state of charge relationship of the air conditioner based on the state of charge parameter and operating state parameters; and constructing a load aggregate model based on the power-state of charge relationship.

[0010] Optionally, based on a preset comfort temperature range and a load equivalent thermal parameter model, a state of charge parameter is determined, including: based on a preset comfort temperature range and a load equivalent thermal parameter model, a control quantity parameter and a control capacity parameter of the air conditioner are determined; based on a ratio of the control quantity parameter to the control capacity parameter, a state of charge parameter is determined.

[0011] Optionally, determining the control parameters of the air conditioner based on the load aggregate model includes: constructing an aggregate parameter identification objective function of the air conditioner based on the load aggregate model, the aggregate parameter identification objective function is used to represent an objective function constructed based on the error between actual data and predicted data of the control parameters, and the predicted data is used to represent data obtained by predicting the control parameters based on the load aggregate model; based on a preset bionic optimization algorithm, searching the aggregate parameter identification objective function to obtain the control parameters.

[0012] According to another aspect of an embodiment of the present invention, a device for determining control parameters of an air conditioning load aggregate is provided, comprising: an acquisition module for acquiring operating state parameters of an air conditioner and environmental condition parameters of an environment in which the air conditioner is located; a first construction module for constructing a load equivalent thermal parameter model of the air conditioner based on the operating state parameters and the environmental condition parameters; a second construction module for constructing a load aggregate model of the air conditioner based on a preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent a preset user comfort temperature range; a determination module for determining the control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

[0013] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0017] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0018] In an embodiment of the present invention, a method for determining the control parameters of an air conditioning load aggregate is provided, comprising: obtaining the operating state parameters of the air conditioner and the environmental condition parameters of the environment in which the air conditioner is located; constructing a load equivalent thermal parameter model of the air conditioner based on the operating state parameters and the environmental condition parameters; constructing a load aggregate model of the air conditioner based on a preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent a preset user's comfort temperature range; determining the control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner. It is easy to notice that the present application can more accurately evaluate the adjustable potential of the air conditioning system by obtaining the operating state parameters and environmental condition parameters of the air conditioner, constructing the load equivalent thermal parameter model, and constructing the load aggregate model in combination with the preset comfort temperature range. Considering that different users have different needs and preferences for temperature control loads such as air conditioners, the present application can set a suitable temperature range according to the personalized needs of the user by presetting the comfort temperature range, thereby improving the user's comfort experience. By obtaining the adjustable potential of the air conditioning load aggregate on the basis of taking into account the user's comfort, the personalized needs of the user can be better met and the user satisfaction can be increased. It can effectively improve the intelligent control capability of the air-conditioning system, meet the personalized needs of users, optimize energy utilization efficiency, improve the flexibility and response speed of the system, and thus solve the technical problems of low accuracy and efficiency in determining the control parameters of air-conditioning load aggregates in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 is a flow chart of a method for determining control parameters of an air conditioning load aggregate according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of a step of searching for a polymer parameter identification objective function according to an embodiment of the present invention;

[0022] Figure 3 4 is a schematic diagram of a device for determining control parameters of an air conditioning load aggregate according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present invention, an embodiment of a method for determining control parameters of an air conditioning load aggregate is provided. It can be explained that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] Figure 1 is a flow chart of a method for determining control parameters of an air conditioning load aggregate according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0027] Step S102, obtaining the operating state parameters of the air conditioner and the environmental condition parameters of the environment in which the air conditioner is located.

[0028] In an optional embodiment, the operation state parameters and environmental condition parameters of the air conditioner can be obtained by real-time monitoring and data collection of the air conditioning system and its environment through various sensors and monitoring equipment. Specifically, for the operation state parameters of the air conditioner, the operation state of the air conditioner can be monitored in real time by sensors installed on the air conditioning system. The sensors can collect data regularly and transmit the data to the data collection system through the communication module. The environmental condition parameters may include parameters such as indoor and outdoor temperature, sunshine intensity, wind direction and wind speed of the environment where the air conditioner is located. The environmental condition parameters can be monitored in real time by sensors installed inside and outside the building, or obtained by equipment such as a meteorological station. Through the data collected by these sensors, the condition of the environment where the air conditioner is located can be more accurately understood. By accurately obtaining the operation state parameters and environmental condition parameters of the air conditioner, accurate data support can be provided for the determination of the subsequent air conditioning load aggregate control parameters. Accurately obtaining the operation state parameters and environmental condition parameters of the air conditioner can help the system better adjust the air conditioning load, realize the effective use and conservation of energy, and provide an important data basis for the determination of the air conditioning load aggregate control parameters, thereby realizing the intelligent control and optimization adjustment of the air conditioning system, and improving energy utilization efficiency and user comfort.

[0029] Step S104: constructing a load equivalent thermal parameter model of the air conditioner based on the operating state parameters and the environmental condition parameters.

[0030] In an optional embodiment, the operating state parameters and environmental condition parameters of the air conditioner that have been obtained can be processed and cleaned to ensure the accuracy and integrity of the data. When determining the load equivalent thermal parameter model of the air conditioner, appropriate parameters can be selected according to the actual situation, and a mathematical model can be established to describe the thermal load characteristics of the air conditioning system. The model can be established by using methods such as heat transfer principles and thermodynamic equations, and the operating state parameters and environmental condition parameters can be incorporated into the model. After the model is established, it can be verified and adjusted, and the accuracy and reliability of the model can be verified by comparing and analyzing with actual data. If there is a deviation or error in the model, it can be adjusted and optimized to improve the fit and prediction accuracy of the model. In the above process, by constructing a load equivalent thermal parameter model, the thermal load characteristics of the air conditioning system can be more accurately described, and the control accuracy and intelligence level of the system can be improved. The accurate load equivalent thermal parameter model can help the system more effectively adjust the air conditioning load, achieve optimal utilization and conservation of energy, and reduce energy consumption costs. It can provide a scientific basis for determining the control parameters of the air conditioning load aggregate, realize intelligent control and energy utilization optimization of the air conditioning system, and further improve the performance and efficiency of the system.

[0031] Step S106: constructing a load aggregation model of the air conditioner based on the preset comfort temperature range and the load equivalent thermal parameter model.

[0032] The preset comfort temperature range is used to represent a preset comfort temperature range for the user.

[0033] In an optional embodiment, the user's comfort temperature range can be preset according to the user's comfort requirements and standards. This range can be comprehensively considered based on factors such as indoor and outdoor temperature, humidity, season, etc. to ensure that the user can feel comfortable under different environmental conditions. Then, the preset comfort temperature range can be combined with the established load equivalent thermal parameter model. The load equivalent thermal parameter model describes the thermal load characteristics of the air-conditioning system, including parameters such as heat conduction and heat radiation, and the preset comfort temperature range describes the user's comfort demand index. On the basis of considering the preset comfort temperature range and the load equivalent thermal parameter model, a load aggregation model of the air conditioner is constructed. The load aggregation model comprehensively considers the user's comfort requirements and the thermal load characteristics of the air-conditioning system to achieve the regulation of the air-conditioning system under the premise of ensuring the user's comfort. In the above process, by presetting the comfort temperature range, a suitable temperature range can be set according to the user's needs, the user's comfort experience can be improved, and the user can feel more comfortable in the air-conditioned environment. Combining the load equivalent thermal parameter model and the user's comfort requirements, the load aggregation model of the air conditioner is constructed, and the precise regulation of the air-conditioning system can be achieved. The system can adjust the air-conditioning working mode and parameters according to user needs and heat load characteristics to improve the system's operating efficiency. It can effectively balance user comfort and the energy efficiency of the air-conditioning system, and improve system performance and user experience.

[0034] Step S108: determining the control parameters of the air conditioner based on the load aggregate model.

[0035] Among them, the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

[0036] In an optional embodiment, based on the constructed load aggregate model, an optimization algorithm, such as a genetic algorithm, a particle swarm optimization algorithm, etc., can be used to optimize and adjust the parameters in the model. These parameters include air conditioning operation mode, wind speed, temperature setting, etc., which can be adjusted according to the model output results and user comfort requirements. The control parameters of the air conditioning system can be determined according to the optimized load aggregate model. These control parameters can include switching of air conditioning operation mode, adjustment of temperature setting value, wind speed control, etc., to achieve precise control of air conditioning load. Then, the determined control parameters can be applied to the actual air conditioning system, and the control parameters can be continuously adjusted and optimized based on real-time monitoring of air conditioning operation status and environmental parameters. Through real-time monitoring and feedback information, dynamic adjustment of the air conditioning system is achieved to keep the system in a good operating state. And the control potential of the air conditioning system can be evaluated by optimizing and adjusting the control parameters in real time. The control potential reflects the ability of the air conditioning system to achieve effective utilization and conservation of energy while meeting the user's comfort requirements. In the above process, the control parameters are determined based on the load aggregate model to realize intelligent control of the air-conditioning system, improve the response speed and accuracy of the system, realize precise control of the air-conditioning system, improve the system performance and energy utilization efficiency, and ensure user comfort.

[0037] In an embodiment of the present invention, a method for determining the control parameters of an air conditioning load aggregate is provided, comprising: obtaining the operating state parameters of the air conditioner and the environmental condition parameters of the environment in which the air conditioner is located; constructing a load equivalent thermal parameter model of the air conditioner based on the operating state parameters and the environmental condition parameters; constructing a load aggregate model of the air conditioner based on a preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent a preset user's comfort temperature range; determining the control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner. It is easy to notice that the present application can more accurately evaluate the adjustable potential of the air conditioning system by obtaining the operating state parameters and environmental condition parameters of the air conditioner, constructing the load equivalent thermal parameter model, and constructing the load aggregate model in combination with the preset comfort temperature range. Considering that different users have different needs and preferences for temperature control loads such as air conditioners, the present application can set a suitable temperature range according to the personalized needs of the user by presetting the comfort temperature range, thereby improving the user's comfort experience. By obtaining the adjustable potential of the air conditioning load aggregate on the basis of taking into account the user's comfort, the personalized needs of the user can be better met and the user satisfaction can be increased. It can effectively improve the intelligent control capability of the air-conditioning system, meet the personalized needs of users, optimize energy utilization efficiency, improve the flexibility and response speed of the system, and thus solve the technical problems of low accuracy and efficiency in determining the control parameters of air-conditioning load aggregates in related technologies.

[0038] Optionally, based on the operating state parameters and the environmental condition parameters, a load equivalent thermal parameter model of the air conditioner is constructed, including: based on the operating state parameters and the environmental condition parameters, constructing the relationship formula between room temperature and cooling capacity, the relationship formula between cooling capacity and frequency, the relationship formula between power and frequency, and the relationship formula between frequency and temperature deviation of the air conditioner; based on the relationship formula between room temperature and cooling capacity, the relationship formula between cooling capacity and frequency, the relationship formula between power and frequency, and the relationship formula between frequency and temperature deviation, constructing a load equivalent thermal parameter model.

[0039] In an optional embodiment, constructing a load equivalent thermal parameter model of an air conditioner based on operating state parameters and environmental condition parameters can more accurately describe the thermal load characteristics of the air conditioning system, so as to realize intelligent control and energy efficiency optimization of the system. Specifically, by analyzing the cooling capacity data of the air conditioning system at different room temperatures, a relationship between room temperature and cooling capacity can be established, and mathematical methods such as curve fitting and regression analysis can be used to determine the influence of room temperature on cooling capacity. Frequency is the main parameter of the operation of the air conditioning compressor and is closely related to the cooling capacity. Through experimental data or simulation calculation, a relationship between cooling capacity and frequency can be established to express the influence of frequency on cooling capacity. There is a certain relationship between the power and frequency consumption of the air conditioning system. Power consumption is an important reference indicator of cooling capacity. Based on experimental data or model analysis, a relationship between power and frequency can be established to express the influence of power on cooling capacity. Considering that frequency regulation will affect the temperature control effect of the air conditioning system. The influence of frequency regulation on temperature deviation can be determined, and a relationship between frequency and temperature deviation can be established to express the influence of frequency regulation on temperature control. Based on the above relationship, a load equivalent thermal parameter model can be constructed, and the operating state and environmental conditions of the air conditioning system are comprehensively considered to realize accurate prediction and regulation of air conditioning load. In the above process, by establishing a load equivalent thermal parameter model, the thermal load characteristics of the air-conditioning system can be described more accurately, and intelligent control and optimized operation can be achieved. Based on the established relationship and model, the cooling capacity and power consumption of the air-conditioning system can be accurately predicted, and effective energy utilization and conservation can be achieved.

[0040] Optionally, based on the operating state parameters and the environmental condition parameters, a relationship between the room temperature and the cooling capacity of the air conditioner is constructed, including: determining the equivalent thermal parameter model differential equation of the air conditioner based on the cooling capacity parameters in the operating state parameters, the indoor parameters in the environmental condition parameters, and the outdoor parameters in the environmental condition parameters; discretizing the equivalent thermal parameter model differential equation to obtain the relationship between the room temperature and the cooling capacity.

[0041] In an optional embodiment, the room temperature and cooling capacity relationship of the air conditioner can be constructed based on the operating state parameters and the environmental condition parameters to achieve precise control and energy efficiency optimization of the air conditioning system. Specifically, first, the equivalent thermal parameter model differential equation of the air conditioning system can be determined based on the cooling capacity parameters in the operating state parameters and the indoor parameters and outdoor parameters in the environmental condition parameters. Then, the determined differential equation can be discretized to discretize the continuous time variable into discrete time steps for numerical calculation and simulation. In this way, the differential equation can be converted into a difference equation, which is more suitable for simulation and analysis on a computer. Finally, based on the equivalent thermal parameter model after discretization, the relationship between room temperature and cooling capacity is obtained through numerical calculation or simulation. This room temperature and cooling capacity relationship can describe the dynamic change law between room temperature and cooling capacity, thereby representing the heat load characteristics of the air conditioning system. Through the above steps, the room temperature and cooling capacity relationship of the air conditioning system can be established to achieve modeling and analysis of the heat load characteristics of the air conditioning system. By establishing the room temperature and cooling capacity relationship, the relationship between the cooling capacity and room temperature of the air conditioning system can be more accurately predicted, and the precise control of the air conditioning system can be achieved, thereby improving the operating efficiency of the system. Establishing the relationship between room temperature and cooling capacity can better control the air-conditioning system, improve the user's comfort experience in the air-conditioned environment, meet the user's comfort needs, and provide important technical support for the system's intelligent regulation and energy efficiency optimization.

[0042] Optionally, based on a preset comfort temperature range and a load equivalent thermal parameter model, a load aggregate model of the air conditioner is constructed, including: determining a state of charge parameter based on a preset comfort temperature range and a load equivalent thermal parameter model; determining a power-state of charge relationship of the air conditioner based on the state of charge parameter and operating state parameters; and constructing a load aggregate model based on the power-state of charge relationship.

[0043] In an optional embodiment, the load aggregation model of the air conditioner can be constructed based on the preset comfort temperature range and the load equivalent thermal parameter model to comprehensively consider the user comfort requirements and the thermal load characteristics of the air conditioning system, so as to realize the intelligent regulation and energy efficiency optimization of the air conditioning system. Specifically, the state of charge parameter can be determined based on the preset comfort temperature range and the load equivalent thermal parameter model. Then, the relationship between the power and the state of charge of the air conditioner can be determined based on the state of charge parameter and the operating state parameter. By analyzing the power consumption of the air conditioning system under different states of charge, the relationship between power and state of charge is established to represent the influence of power on the state of charge. Finally, the load aggregation model of the air conditioner can be constructed based on the determined power and state of charge relationship. This model load aggregation model comprehensively considers the user comfort requirements, the thermal load characteristics and power consumption of the air conditioning system, so as to realize the comprehensive regulation of the air conditioning system. In the above steps, by constructing the load aggregation model, the user comfort requirements and the thermal load characteristics of the air conditioning system can be comprehensively considered to realize the intelligent regulation of the system and improve the operating efficiency and stability of the system. By considering user comfort requirements and load characteristics, building a load aggregation model can better control the air-conditioning system, improve the user's comfort experience in the air-conditioned environment, and enhance user satisfaction.

[0044] Optionally, based on a preset comfort temperature range and a load equivalent thermal parameter model, a state of charge parameter is determined, including: based on a preset comfort temperature range and a load equivalent thermal parameter model, a control quantity parameter and a control capacity parameter of the air conditioner are determined; based on a ratio of the control quantity parameter to the control capacity parameter, a state of charge parameter is determined.

[0045] In an optional embodiment, first, the control quantity parameter and control capacity parameter of the air conditioner can be determined based on the preset comfort temperature range and the load equivalent thermal parameter model. The control quantity parameter may refer to the control quantity that can be adjusted by the air conditioning system, such as the temperature setting value, wind speed, etc.; the control capacity parameter may refer to the control capacity of the air conditioning system, that is, the actual control capacity that the system can provide. Next, the state of charge parameter can be determined based on the ratio of the control quantity parameter and the control capacity parameter. This ratio can reflect the relationship between the control capacity of the air conditioning system and the actual demand, thereby determining the current state of charge of the system. By analyzing the ratio between the control quantity parameter and the control capacity parameter, it can be understood whether the current control capacity of the system meets the user's comfort requirements. According to the analysis results, the state of charge parameter is adjusted. If it is found that the system's control capacity is insufficient to meet user needs, the control performance of the system and user comfort can be improved by adjusting the control quantity parameter or increasing the control capacity parameter. In the above process, by analyzing the ratio of the control quantity parameter and the control capacity parameter, the system control capability can be evaluated, the energy utilization efficiency of the system can be optimized, and the energy consumption cost can be reduced. Adjusting the charge state parameters can ensure that the system control capability matches the user's comfort requirements, improve the user's comfort experience in the air-conditioned environment, and enhance user satisfaction.

[0046] Optionally, determining the control parameters of the air conditioner based on the load aggregate model includes: constructing an aggregate parameter identification objective function of the air conditioner based on the load aggregate model, the aggregate parameter identification objective function is used to represent an objective function constructed based on the error between actual data and predicted data of the control parameters, and the predicted data is used to represent data obtained by predicting the control parameters based on the load aggregate model; based on a preset bionic optimization algorithm, searching the aggregate parameter identification objective function to obtain the control parameters.

[0047] In an optional embodiment, determining the control parameters of the air conditioner based on the load aggregate model can achieve accurate control and optimization of the air conditioning system. Specifically, first, the aggregate parameter identification objective function of the air conditioner can be constructed based on the load aggregate model. The aggregate parameter identification objective function can be used to represent the error between the actual data and the predicted data based on the control parameters, that is, the difference between the actual data and the model predicted data. The optimization of the aggregate parameter identification objective function will help adjust the parameters of the air conditioning system to reduce the error and achieve better system performance. The predicted data is the data obtained by predicting the control parameters based on the load aggregate model. Through model prediction, the predicted data generated according to the change of the control parameters can be obtained, which is used to compare with the actual data, and then optimize the control parameters. Then, the preset bionic optimization algorithm, such as genetic algorithm, particle swarm algorithm, etc., can be used to search the aggregate parameter identification objective function to achieve the optimization of the control parameters. The preset bionic optimization algorithm simulates the evolution mechanism of nature and finds the optimal solution through iteration. By searching the aggregate parameter identification objective function, the optimized control parameters are finally obtained. These parameters will be used to adjust the operating state of the air-conditioning system to minimize the error between the actual data and the predicted data, thereby improving the performance and efficiency of the system. In the above process, by searching the polymer parameter identification objective function based on the preset bionics optimization algorithm, the intelligent control of the air-conditioning system is realized, the intelligence level of the system is improved, the adaptability and response speed of the system are enhanced, and the intelligent control and energy efficiency optimization of the air-conditioning system can be realized, and the performance of the system and user experience can be improved.

[0048] The technical solution proposed in this application is described below in combination with an optional embodiment. This application proposes a method for evaluating the adjustable potential of central air-conditioning load aggregates that takes into account user comfort. User comfort is used as an important constraint in the air-conditioning load aggregate model, and the black-winged kite optimization algorithm is proposed to identify the parameters of the air-conditioning load aggregate model. This solution adopts a bottom-up air-conditioning load aggregation modeling approach, starting from the special effects of a single air-conditioning load, to establish an air-conditioning load aggregate model that takes into account both air-conditioning load characteristics and user comfort, and uses a new intelligent algorithm to optimize and identify the model parameters. This solution effectively taps the adjustable potential of air-conditioning load aggregates and provides technical support for the effective use of temperature-controlled load resources such as air-conditioning.

[0049] The technical solution of this application is as follows: First, an equivalent thermal parameter model of air conditioning load is established. The actual power consumption of the central air conditioner is mainly related to the cooling capacity and heating capacity. The cooling capacity required indoors in the building is mainly related to factors such as the room area and the room heat dissipation coefficient. Generally, there are actual models and equivalent thermal parameter models to describe it. The equivalent thermal parameter model is used to describe the temperature changes in the air-conditioned room under the influence of various factors such as outdoor temperature and indoor equipment heat dissipation. The relevant working conditions of the air conditioning load can be simulated more accurately, and the differential equation of the equivalent thermal parameter model of the central air conditioner can be obtained, that is, the differential equation of the equivalent thermal parameter model, which is expressed as shown in the following formula:

[0050]

[0051] Where, C is the equivalent heat capacity of the building, unit: F; T i (t) is the indoor temperature at time t, in °C; T o (t) is the outdoor temperature at time t, unit: ℃; R is the equivalent thermal resistance of the building, unit: Ω; Q(t) is the cooling capacity of the air conditioner at time t, unit: kW.

[0052] Discretizing the above equivalent thermal parameter model differential equation, the relationship between room temperature and air conditioning cooling capacity, that is, the relationship between room temperature and cooling capacity, is expressed as follows:

[0053]

[0054] The actual operating power and cooling capacity of the variable frequency central air conditioner are approximately linearly related to the frequency. As the frequency increases, the power and cooling capacity of the variable frequency central air conditioner will increase. The relationship between the frequency and the cooling capacity and actual power of the variable frequency central air conditioner, that is, the relationship between cooling capacity and frequency and the relationship between power and frequency, can be expressed as follows:

[0055] Q(t) = a·f(t) + b;

[0056] P(t) = m·f(t) + n;

[0057] In the formula, Q(t) represents the cooling capacity of the central air-conditioning unit at time t, unit: kW, P(t) represents the actual electric power of the central air-conditioning unit at time t, unit: kW; f represents the frequency of the compressor, unit: Hz; a and b represent the constant coefficients of cooling capacity; m and n represent the constant coefficients of electric power.

[0058] Inverter central air conditioner according to the set temperature T s and indoor temperature T i The frequency of the compressor is adjusted by the change of the air conditioning frequency. Assume that the range of the air conditioning frequency change, that is, the preset comfort temperature range is [f min ,f max ], at room temperature T iGreater than the upper limit of the set temperature deviation T s +ΔT + When the frequency conversion central air conditioner is at the highest frequency f max Run until the room temperature reaches the set temperature range; when T i The deviation lower limit T is lower than the set temperature s -ΔT - When the lowest frequency f min run.

[0059] The relationship between the frequency and temperature deviation of the variable frequency central air conditioning load, that is, the relationship between the frequency and temperature deviation can be expressed as:

[0060]

[0061] In the formula, ΔT is the deviation between the indoor temperature and the set temperature, ΔT = T i -T s ; K is a constant.

[0062] The load equivalent thermal parameter model of the variable frequency central air conditioner can be composed of the above-mentioned room temperature and cooling capacity relationship formula, cooling capacity and frequency relationship formula, power and frequency relationship formula and frequency and temperature deviation relationship formula.

[0063] Next, a single air conditioner regulation potential model can be established. From the power-frequency relationship, it can be seen that the electric power of the variable frequency central air conditioner is proportional to the compressor operating frequency. This section proposes a control method for the central air conditioner load based on its working characteristics, and calculates its regulation potential on this basis. According to the central air conditioner set temperature T s and outdoor temperature T o Calculate the operating frequency f corresponding to the central air conditioning load. Assume that in a short period of time T o Remain unchanged, that is:

[0064] T o (t+1)=T o (t) = T;

[0065] When the central air conditioner is running stably, the room temperature is equal to the set temperature, that is:

[0066] T i (t+1)=T i (t) = T s ;

[0067] Combining the above relationship between room temperature and cooling capacity, we can get:

[0068]

[0069] Substituting the above formula into the relationship between cooling capacity and frequency, we can get:

[0070]

[0071] Combining the above formula with the relationship between power and frequency, the electric power of the central air conditioner is obtained as:

[0072]

[0073] From the above, we can see that the control potential of a single central air conditioner can be expressed by the following formula.

[0074] ΔP=P(T s ,T o )-P min =P(T s ,T o )-(m·f min +n);

[0075] Maximum controllable duration of air conditioning t control for:

[0076]

[0077] Where, T0 is the room temperature at the beginning of the control, unit: °C; T1 is the room temperature at the end of the control, unit: °C; Q min It is the cooling capacity corresponding to the lowest operating frequency, unit: kW.

[0078] Next, an air conditioning load aggregation model that takes user comfort into consideration can be established, namely, a load aggregation model. According to the relationship between cooling capacity and frequency, and the relationship between power and frequency, the relationship between the central air conditioning cooling capacity Q and the electric power P is:

[0079]

[0080] Considering the user's comfort temperature range is [T min ,T max ], the regulation potential of central air conditioning is linearly related to the central air conditioning set temperature. When the indoor temperature is T max When the adjustable amount of the central air conditioner is 0, then when the indoor temperature is T min The maximum adjustable amount of the central air conditioner is S max . So the indoor temperature is T i Time control amount S in , which is the control parameter, can be expressed as:

[0081] S in =λ(T max -T i );

[0082] Where λ is the control coefficient, unit: kW / ℃.

[0083] The maximum adjustable amount Smax , that is, the control capacity parameter is:

[0084] S max =λ(T max -T min );

[0085] The state of charge SOC can be defined, that is, the state of charge parameter is the control quantity S in and control capacity S max Ratio of:

[0086]

[0087] When the room temperature T i When the temperature is constant, the cooling capacity Q can be obtained according to the differential equation of the equivalent thermal parameter model:

[0088]

[0089] Substituting the control quantity parameters into the above formula, the central air conditioning power P can be obtained as:

[0090]

[0091] Will Substituting into the above formula, the relationship between P and SOC is:

[0092] P=αSOC+βT o +γ;

[0093] The calculation formulas for α, β, and γ are as follows:

[0094]

[0095] According to the definition of state of charge SOC, the value range of SOC is [0, 1]. The central air conditioners are divided into N groups according to SOC, and the number of central air conditioners in each group is m1, m2, ..., m i ,…,m N When m i When the charge state of the central air conditioners in the i-th group is larger, the charge state of the central air conditioners in the i-th group can be unified as SOC i :

[0096]

[0097] Aggregate the central air conditioning load of group i to get:

[0098] P i =α i SOC i +β i T o +γ i ;

[0099]

[0100] Where P i is the total aggregate power of the i-th group; α i_k , β i_k and γ i_k They are α, β and γ of the kth central air conditioner in the ith group respectively.

[0101] Next, the air conditioning load aggregate regulation potential model can be established.

[0102] Assuming that the relevant data of central air conditioning is known, the total regulation potential of central air conditioning load aggregate can be calculated according to the above model. The total aggregate power is:

[0103]

[0104] Where P i is the total aggregate power of the i-th load group.

[0105] Assuming that the outdoor temperature remains unchanged, when the operating state of all central air conditioners in the i-th interval is adjusted to the j-th interval, the aggregate power change of the i-th group of central air conditioner loads ΔP i→j for:

[0106] ΔPi→j=αi(SOCj-SOCi);

[0107] When the temperature adjustment range required by human comfort is certain, the state of charge of the central air-conditioning load depends on the indoor temperature. Since the indoor temperature does not change suddenly but changes continuously over time, the central air-conditioning load SOC is also time-varying. Therefore, there is a transient process in the process of adjusting the operating state in the i-th interval to the j-th interval, and the duration of the transient is:

[0108]

[0109] Where, T i (i) and T i (j) are the indoor temperatures corresponding to the i-th and j-th intervals, respectively. i =α i SOC i +β i T o +γ i We can get:

[0110] T i (i) = T max -SOC i (T max -T min );

[0111] T i (j) = T max -SOC j (T max -T min );

[0112] Since the peak load regulation time of the system is relatively long, the regulation time of the aggregate central air conditioner is much longer than the transient process time when the central air conditioner load is regulated. Therefore, this paper does not consider the transient process generated when the charge state of the aggregate central air conditioner load changes. Only the charge state values ​​corresponding to the two intervals before and after the change are considered. The maximum regulation potential is:

[0113]

[0114] Finally, the adjustable potential parameters of the air conditioning load aggregate can be identified based on the black-winged kite optimization algorithm. The above adjustable potential assessment is obtained under the assumption that the relevant parameters are known, and the aggregate parameters are the key to affecting the regulation potential. The aggregate parameters to be identified include the total number of air conditioning aggregates, the user's optimal interval temperature, the building equivalent heat capacity, the building equivalent thermal resistance, etc. This application can use a preset bionic optimization algorithm, for example, the black-winged kite optimization algorithm (abbreviated as BKA) to identify relevant parameters.

[0115] First, construct the objective function of polymer parameter identification, as shown in the following formula:

[0116]

[0117] Where: N is the total number of air conditioners participating in the aggregation; T max ,T min is the maximum and minimum value of the user's comfort temperature; C is the equivalent heat capacity of the room; R is the equivalent thermal resistance of the room; P(t) is the actual operating power of the air conditioning load aggregate; is the power calculated during the iteration of the Black Kite Optimization (BKA) algorithm; T is the time window length.

[0118] The specific steps of parameter identification are as follows: determine the parameters to be optimized and their ranges, and initialize the parameters to be optimized. Calculate the fitness value and execute the attack behavior phase of the BKA algorithm. Execute the migration behavior phase of the BKA algorithm. Determine whether the maximum number of iterations has been reached. If so, output the optimal parameter result. Otherwise, jump to calculate the fitness value and execute the attack behavior phase of the BKA algorithm. Finally, output the optimal parameter combination, and then calculate and analyze the adjustable potential of the air-conditioning load aggregate. According to the aggregate regulation potential model and model parameter identification results, calculate the adjustable potential of the regional load aggregate.

[0119] The technical solution proposed in this application can improve the accuracy of the central air-conditioning load aggregate model: by taking user comfort as an important constraint and using a new intelligent algorithm to optimize and identify the model parameters, the accuracy and reliability of the model can be significantly improved. It helps to more accurately predict and control the behavior of air-conditioning load aggregates and provide strong support for the effective use of air-conditioning resources. The adjustable potential of central air-conditioning load aggregates can be effectively evaluated. Through precise modeling and parameter identification, the adjustable potential of air-conditioning load aggregates can be more effectively explored and utilized. It helps to maximize energy efficiency and improve resource utilization efficiency while meeting user comfort. It can provide technical support for the effective response of temperature-controlled load resources such as air conditioning. The proposal of this application provides new ideas and methods for the effective response and utilization of temperature-controlled load resources such as air conditioning. Through precise modeling and optimized control, these resources can be better utilized to achieve efficient use of energy and sustainable development. In summary, the technical means of this application produce certain technical effects in improving model accuracy, exploring adjustable potential, and providing technical support for the effective utilization of temperature-controlled load resources.

[0120] Figure 2 FIG. 1 is a schematic diagram of a step of searching for a polymer parameter identification objective function according to an embodiment of the present invention. Figure 2 As shown, at the beginning, determine the parameters to be optimized and initialize the parameter range; calculate the fitness value and execute the attack behavior stage; execute the migration behavior stage; determine whether the maximum number of iterations has been reached. When the maximum number of iterations has not been reached, jump to the step of calculating the fitness value and executing the attack behavior stage; when the maximum number of iterations has been reached, output the load aggregate parameter identification results, including the total number of aggregated air conditioners N, the comfort temperature Tmax / min, the building equivalent heat capacity C and the building equivalent thermal resistance R.

[0121] According to another aspect of an embodiment of the present application, a device for determining the control parameters of an air conditioning load aggregate is also provided. The device can execute the method for determining the control parameters of the air conditioning load aggregate of the above embodiment. The specific implementation method and preferred application scenario are the same as those of the above embodiment and will not be repeated here.

[0122] Figure 3 is a schematic diagram of a device for determining control parameters of an air conditioning load aggregate according to an embodiment of the present application, such as Figure 3 As shown, the device includes the following: an acquisition module 302 , a first construction module 304 , a second construction module 306 and a determination module 308 .

[0123] Among them, the acquisition module is used to obtain the operating status parameters of the air conditioner and the environmental condition parameters of the environment in which the air conditioner is located; the first construction module is used to construct a load equivalent thermal parameter model of the air conditioner based on the operating status parameters and the environmental condition parameters; the second construction module is used to construct a load aggregate model of the air conditioner based on the preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent the preset user's comfort temperature range; the determination module is used to determine the control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

[0124] Among them, the first construction module is also used to construct the relationship between room temperature and cooling capacity, the relationship between cooling capacity and frequency, the relationship between power and frequency, and the relationship between frequency and temperature deviation of the air conditioner based on the operating status parameters and environmental condition parameters; based on the relationship between room temperature and cooling capacity, the relationship between cooling capacity and frequency, the relationship between power and frequency, and the relationship between frequency and temperature deviation, a load equivalent thermal parameter model is constructed.

[0125] Among them, the first construction module is also used to determine the equivalent thermal parameter model differential equation of the air conditioner based on the cooling capacity parameters in the operating state parameters, the indoor parameters in the environmental condition parameters, and the outdoor parameters in the environmental condition parameters; the equivalent thermal parameter model differential equation is discretized to obtain the relationship between room temperature and cooling capacity.

[0126] Among them, the second construction module is also used to determine the state of charge parameters based on the preset comfort temperature range and the load equivalent thermal parameter model; determine the power and state of charge relationship of the air conditioner based on the state of charge parameters and the operating status parameters; and construct a load aggregate model based on the power and state of charge relationship.

[0127] Among them, the second construction module is also used to determine the control quantity parameter and control capacity parameter of the air conditioner based on the preset comfort temperature range and the load equivalent thermal parameter model; and determine the charge state parameter based on the ratio of the control quantity parameter and the control capacity parameter.

[0128] Among them, the determination module is also used to construct an aggregate parameter identification objective function of the air conditioner based on the load aggregate model. The aggregate parameter identification objective function is used to represent an objective function constructed based on the error between the actual data and the predicted data of the control parameters. The predicted data is used to represent the data obtained by predicting the control parameters based on the load aggregate model. Based on the preset bionic optimization algorithm, the aggregate parameter identification objective function is searched to obtain the control parameters.

[0129] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0130] The above-mentioned memory may refer to a device inside a computer for storing data and programs, and may include memory, hard disk, etc., wherein the memory may be used to temporarily store running programs and data, the hard disk may be used to store programs and data for a long time, and the memory may be used to enable the computer to read and write data, and execute programs; the above-mentioned processor may be responsible for executing instructions in computer programs and performing data processing, and may be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0131] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0132] The above-mentioned computer storage medium may refer to a medium in a computer memory used to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc.; the stored program included in the computer-readable storage medium may be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0133] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0134] The above-mentioned computer program product may refer to a software program that has been written, tested and released and can be run on a computer or other device. The computer program product may include an application, an operating system, tool software, etc., which is used to implement specific functions or solve specific problems.

[0135] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0136] The above-mentioned non-volatile computer-readable storage medium may refer to a medium for storing data. The non-volatile computer-readable storage medium can keep the data from being lost when the power is off, and can be used to store long-term data, such as operating systems, applications, and user files. The non-volatile storage medium may include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0137] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0138] The above-mentioned computer program may refer to a collection of instructions used to tell a computer to perform a specific task or operation. A computer program may be written by a programmer using a specific programming language and may include algorithms, data structures, logic, and control flows. A computer program may be used for a variety of purposes, including application software, operating systems, and the like.

[0139] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0140] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0141] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0142] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0143] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0144] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining control parameters of air conditioning load aggregates, characterized in that: include: Acquiring operating status parameters of the air conditioner and environmental condition parameters of the environment in which the air conditioner is located; Based on the operating state parameters and the environmental condition parameters, constructing a load equivalent thermal parameter model of the air conditioner; Based on a preset comfort temperature range and the load equivalent thermal parameter model, a load aggregate model of the air conditioner is constructed, wherein the preset comfort temperature range is used to represent a preset user's comfort temperature range; The control parameters of the air conditioner are determined based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

2. The method for determining the control parameters of the air conditioning load aggregate according to claim 1, characterized in that: Based on the operating state parameter and the environmental condition parameter, a load equivalent thermal parameter model of the air conditioner is constructed, including: Based on the operating state parameters and the environmental condition parameters, constructing a relationship between room temperature and cooling capacity, a relationship between cooling capacity and frequency, a relationship between power and frequency, and a relationship between frequency and temperature deviation of the air conditioner; The load equivalent thermal parameter model is constructed based on the relationship between room temperature and cooling capacity, the relationship between cooling capacity and frequency, the relationship between power and frequency, and the relationship between frequency and temperature deviation.

3. The method for determining the control parameters of the air conditioning load aggregate according to claim 2, characterized in that: Based on the operating state parameter and the environmental condition parameter, a relationship between the room temperature and the cooling capacity of the air conditioner is constructed, including: Determining an equivalent thermal parameter model differential equation of the air conditioner based on a cooling capacity parameter in the operating state parameter, an indoor parameter in the environmental condition parameter, and an outdoor parameter in the environmental condition parameter; The differential equation of the equivalent thermal parameter model is discretized to obtain the relationship between the room temperature and the cooling capacity.

4. The method for determining the control parameters of the air conditioning load aggregate according to claim 1, characterized in that: Based on the preset comfort temperature range and the load equivalent thermal parameter model, a load aggregate model of the air conditioner is constructed, including: Determining a state of charge parameter based on the preset comfort temperature range and the load equivalent thermal parameter model; Determining a power-state-of-charge relationship of the air conditioner based on the state-of-charge parameter and the operating state parameter; Based on the power and state of charge relationship, the load aggregate model is constructed.

5. The method for determining the control parameters of the air conditioning load aggregate according to claim 4, characterized in that: Determining a state of charge parameter based on the preset comfort temperature range and the load equivalent thermal parameter model includes: Determining a control amount parameter and a control capacity parameter of the air conditioner based on the preset comfort temperature range and the load equivalent thermal parameter model; The state of charge parameter is determined based on the ratio of the control quantity parameter to the control capacity parameter.

6. The method for determining the control parameters of the air conditioning load aggregate according to claim 1, characterized in that: Determining the control parameters of the air conditioner based on the load aggregate model includes: Constructing an aggregate parameter identification objective function of the air conditioner based on the load aggregate model, wherein the aggregate parameter identification objective function is used to represent an objective function constructed based on an error between actual data and predicted data of the control parameter, and the predicted data is used to represent data obtained by predicting the control parameter based on the load aggregate model; Based on a preset bionics optimization algorithm, the polymer parameter identification objective function is searched to obtain the control parameters.

7. A device for determining control parameters of air conditioning load aggregates, characterized in that: include: An acquisition module, used to acquire operating status parameters of the air conditioner and environmental condition parameters of the environment in which the air conditioner is located; A first building module, configured to build a load equivalent thermal parameter model of the air conditioner based on the operating state parameter and the environmental condition parameter; a second building module, configured to build a load aggregate model of the air conditioner based on a preset comfort temperature range and the load equivalent thermal parameter model, wherein the preset comfort temperature range is used to represent a preset user's comfort temperature range; A determination module is used to determine the control parameters of the air conditioner based on the load aggregate model, wherein the control parameters are used to characterize the control potential of the load aggregate of the air conditioner.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein when the program is running, the method for determining the air conditioning load aggregate control parameters described in any one of claims 1 to 6 is executed.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the method for determining the air conditioning load aggregate control parameters described in any one of claims 1 to 6.

10. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the method for determining the air conditioning load aggregate control parameters according to any one of claims 1 to 6.

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