Electric power regulation and control method and apparatus for air conditioning load, and computer device

Abstract

The present application relates to an electric power regulation and control method and apparatus for an air conditioning load, a computer device, a storage medium, and a computer program product. The method comprises: acquiring temperature parameters of each target space; inputting the temperature parameters into a pre-constructed air conditioner power prediction model to obtain target power curves corresponding to the target spaces, wherein the air conditioner power prediction model is used for representing an association relationship between the temperature parameters and the air conditioner power, and the target power curves are used for indicating the changes of the air conditioner power in a target time period; and determining an electric power regulation and control strategy on the basis of the target power curves corresponding to the plurality of target spaces.

Description

Power control methods, devices and computer equipment for air conditioning loads

[0001] Related applications

[0002] This application claims priority to Chinese patent application filed on May 29, 2024, application number 202410677413.7, entitled "Power Control Method, Apparatus and Computer Equipment for Air Conditioning Load", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of smart grid technology, and in particular to a power regulation method, device, computer equipment, storage medium and computer program product for air conditioning loads. Background Technology

[0004] With the rapid development of the national economy, the number of air conditioning units installed in buildings is constantly increasing. These units can include residential air conditioners, central air conditioning systems, ice storage air conditioners, and ground source heat pump air conditioners. Since adjusting the temperature inside a building using air conditioning equipment takes time, adjusting the operating status of the equipment in the short term will not have a significant impact on the building's temperature. Therefore, in maintaining the balance between power generation and consumption in the power system, the air conditioning load has a certain degree of adjustability.

[0005] However, due to the wide variety of air conditioning equipment models, rated power, building types, and building areas, the adjustability potential of air conditioning loads is difficult to determine, making it impossible to effectively utilize this potential for power regulation. Therefore, there is an urgent need for a power regulation method tailored to air conditioning loads, which can improve the flexibility and accuracy of power regulation. Summary of the Invention

[0006] According to various embodiments of this application, a power regulation method, apparatus, computer equipment, computer-readable storage medium, and computer program product for air conditioning loads are provided.

[0007] In a first aspect, this application provides a power regulation method for air conditioning loads, comprising:

[0008] Obtain the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature;

[0009] The temperature parameter is input into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between the temperature parameter and the air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period;

[0010] Based on the target power curves corresponding to multiple target spaces, a power regulation strategy is determined, which is used to increase / decrease the power supply of the multiple target spaces within the target time period.

[0011] In one embodiment, prior to inputting the temperature parameter into the pre-built air conditioning power prediction model, the following steps are included:

[0012] Identify the heat source of the target space and establish the correlation between the heat change caused by the heat source and the temperature parameter;

[0013] Based on the thermal balance relationship between the heat changes, an air conditioning power prediction model is constructed.

[0014] In one embodiment, the heat source includes the temperature difference between indoor and outdoor environments, and establishing the correlation between the heat change caused by the heat source and the temperature parameter includes:

[0015] Multiple sets of outdoor and indoor ambient temperatures are collected, along with the corresponding first heat change; wherein the first heat change is caused by the difference between the outdoor and indoor ambient temperatures.

[0016] A first correlation relationship is determined between the outdoor ambient temperature, the indoor ambient temperature, and the first change in heat by using data fitting.

[0017] In one embodiment, the heat source includes an air conditioning unit, and establishing the correlation between the heat change caused by the heat source and the temperature parameter includes:

[0018] Multiple sets of indoor ambient temperatures and target set temperatures are collected, along with the corresponding second heat change; wherein the second heat change is caused by the operation of the air conditioning equipment.

[0019] A second correlation relationship is determined by using data fitting to identify the indoor ambient temperature, the target set temperature, and the second change in heat.

[0020] In one embodiment, after inputting the temperature parameter into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space, the process includes:

[0021] Based on the target power curves corresponding to multiple target spaces, the operating status of the air conditioning equipment in the multiple target spaces is adjusted.

[0022] In one embodiment, the power regulation strategy includes at least one of the following:

[0023] The power supply systems corresponding to the multiple target spaces are subjected to a first frequency modulation, a second frequency modulation, and a third frequency modulation.

[0024] Secondly, this application also provides a power control device for air conditioning loads, comprising:

[0025] The acquisition module is used to acquire the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature.

[0026] The prediction module is used to input the temperature parameter into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between the temperature parameter and the air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period;

[0027] The first adjustment module is used to determine a power adjustment strategy based on the target power curves corresponding to multiple target spaces. The power adjustment strategy is used to increase / decrease the power supply of the multiple target spaces within the target time period.

[0028] In one embodiment, the device further includes:

[0029] The heat source determination module is used to determine the heat source of the target space;

[0030] The correlation determination module is used to establish the correlation between the amount of heat change caused by the heat source and the temperature parameter;

[0031] The model determination module is used to construct an air conditioning power prediction model based on the thermal balance relationship between the heat changes.

[0032] In one embodiment, the heat source includes the temperature difference between indoor and outdoor environments, and the correlation determination module includes:

[0033] The first acquisition submodule is used to acquire multiple sets of outdoor ambient temperature and indoor ambient temperature, as well as the corresponding first heat change; wherein, the first heat change is caused by the difference between the outdoor ambient temperature and the indoor ambient temperature.

[0034] The first determining submodule is used to determine a first correlation between the outdoor ambient temperature, the indoor ambient temperature and the first heat change by means of data fitting.

[0035] In one embodiment, the heat source includes an air conditioning unit, and the association determination module includes:

[0036] The second acquisition submodule is used to acquire multiple sets of indoor ambient temperature and target set temperature, as well as the corresponding second heat change; wherein, the second heat change is caused by the operation of the air conditioning equipment;

[0037] The second determining submodule is used to determine a second correlation between the indoor ambient temperature, the target set temperature and the second heat change by means of data fitting.

[0038] In one embodiment, the device further includes:

[0039] The second adjustment module is used to adjust the operating status of the air conditioning equipment in the multiple target spaces based on the target power curves corresponding to the multiple target spaces.

[0040] In one embodiment, the power regulation strategy includes at least one of the following:

[0041] The power supply systems corresponding to the multiple target spaces are subjected to a first frequency modulation, a second frequency modulation, and a third frequency modulation.

[0042] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the above-mentioned embodiments.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the preceding claims.

[0044] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the above claims.

[0045] Details of one or more embodiments of the present invention are set forth in the following drawings and description. Other features, objects, and advantages of the invention will become apparent from the specification, drawings, and claims. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the disclosed drawings without creative effort.

[0047] Figure 1 is a flowchart illustrating a power dispatching method for air conditioning load in one embodiment;

[0048] Figure 2 is a flowchart illustrating a power dispatching method for air conditioning load in another embodiment;

[0049] Figure 3 is a flowchart illustrating the process of establishing the correlation between the amount of heat change caused by the heat source and temperature parameters in one embodiment;

[0050] Figure 4 is a flowchart illustrating the process of establishing the correlation between the amount of heat change caused by the heat source and the temperature parameter in another embodiment;

[0051] Figure 5 is a flowchart illustrating a power dispatching method for air conditioning load in another embodiment;

[0052] Figure 6 is a structural block diagram of a power dispatching method device for air conditioning load in one embodiment;

[0053] Figure 7 is an internal structure diagram of a computer device in one embodiment. Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] In an exemplary embodiment, as shown in FIG1, a power regulation method for air conditioning load is provided. Taking the application of this method to a server as an example, it includes the following steps 202 to 206. Wherein:

[0056] Step 202: Obtain the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature.

[0057] The target space can be any space that can be uniformly controlled by the installed air conditioning equipment. For example, the target space may include all or part of the space inside the target building. Methods for obtaining the outdoor ambient temperature may include: obtaining real-time outdoor ambient temperature through real-time data released by a weather station, or measuring the outdoor ambient temperature through an outdoor temperature sensor. The indoor ambient temperature can be the initial set temperature of the air conditioning equipment when its operating conditions are stable.

[0058] For example, the server can collect the outdoor and indoor ambient temperatures of the target space at preset time intervals and determine the target set temperature for the target space. In one possible implementation, the target set temperature can be determined by the total predicted electricity consumption of the power consumption area to which the target space belongs. For example, if the predicted electricity consumption of the power consumption area to which the target space belongs is high, the difference between the target set temperature and the outdoor ambient temperature is small; if the predicted electricity consumption of the power consumption area to which the target space belongs is low, the difference between the target set temperature and the outdoor ambient temperature is large.

[0059] Step 204: Input the temperature parameters into the pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between temperature parameters and air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period.

[0060] The air conditioner power prediction model can be a mathematical model, a machine learning model, etc. One possible implementation is to use a hybrid data model-driven approach to construct the air conditioner power prediction model. This approach allows for the combination of multiple models and the processing of data from different data sources and formats, thus improving the prediction accuracy of the air conditioner power prediction model and reducing the difficulty of constructing it.

[0061] For example, the air conditioning power prediction model can be stored on a server. The server can input temperature parameters such as the obtained outdoor ambient temperature, indoor ambient temperature, and target set temperature into the air conditioning power prediction membrane. The air conditioning power prediction model can output predicted air conditioning power values ​​based on the temperature parameters and their characteristics. Based on the predicted air conditioning power values ​​at different times, a target power curve can be formed. Here, the temperature parameters can be real-time data, historical data, or predicted data. In one possible implementation, the temperature parameters may also include humidity, timestamps, etc.

[0062] Step 206: Based on the target power curves corresponding to multiple target spaces, determine the power regulation strategy. The power regulation strategy is used to increase / decrease the power supply of multiple target spaces within the target time period.

[0063] For example, the server can integrate the target power curves corresponding to multiple target spaces to obtain the air conditioning load characteristics of the target building or target area. The air conditioning load characteristics can be high load, medium load, or low load. Power control strategies can include at least one of the following: reducing the power supply to the low-load target building or target area; transferring the power supply of the low-load and medium-load target buildings or target areas to the high-load target buildings or target areas when the power supply to the high-load target buildings or target areas is insufficient; and temporarily reducing the power supply to each target building or target area when the overall power supply is insufficient, with the largest reduction in power supply to the low-load target buildings or target areas and the smallest reduction in power supply to the high-load target buildings or target areas.

[0064] In the aforementioned power regulation method for air conditioning load, temperature parameters affecting air conditioning power are acquired in real time and input into a pre-built air conditioning power prediction model. This allows the air conditioning power prediction model to capture information affecting air conditioning power and make accurate predictions of air conditioning power in the short term based on this information, thereby determining the size of the adjustable potential of the air conditioning load. Furthermore, by using the predicted air conditioning power to finely regulate the overall power supply of multiple target spaces, the adjustable potential of the air conditioning load can be efficiently utilized, improving the flexibility and accuracy of power regulation.

[0065] In an exemplary embodiment, as shown in FIG2, prior to step 202 above, the power regulation method for air conditioning load may include:

[0066] Step 2011: Determine the heat source of the target space and establish the correlation between the heat change caused by the heat source and the temperature parameters.

[0067] The heat sources in the target space can include the temperature difference between indoor and outdoor environments, air conditioning equipment, building heat capacity, and other indoor heat sources such as lighting equipment and electrical appliances. Building heat capacity can be determined by the building's volume and materials, and it characterizes the building's ability to absorb or release heat under a unit temperature change. The heat generated by indoor heat sources such as lighting equipment and electrical appliances per unit time can be a constant.

[0068] Step 2012: Based on the thermal balance relationship between heat changes, construct an air conditioning power prediction model.

[0069] For example, the heat balance relationship between changes in heat can be: Q in +Q heat =Q AC ;

[0070] Among them, Q inQ represents the change in heat related to temperature parameters over the target time period. heat Q represents the change in heat independent of temperature parameters over the target time period. AC Q represents the cooling capacity of the air conditioner during the target time period. heat It can be the first constant determined experimentally. AC The calculation formula can be:

[0071] Among them, P AC Here, COP is the cooling performance coefficient of the air conditioning equipment. The rated COP of the air conditioning equipment is a second constant and is independent of the load size of the air conditioning equipment.

[0072] Q heat The formula for calculating Q can be: heat =P AC0 COP-Q H ;

[0073] Among them, P AC0 Q represents the air conditioning power when the air conditioning equipment is operating stably under stable cooling conditions in the experimental environment. When the air conditioning equipment is operating stably under stable cooling conditions, the air conditioning power remains essentially constant. H This is a constant obtained from an experiment.

[0074] In one possible implementation, the above thermal equilibrium relationship can be: Q T =Q C +Q heat =Q AC ;

[0075] Among them, Q T Q represents the first change in heat caused by the temperature difference between indoor and outdoor environments during the target time period. C This represents the second change in heat caused by the air conditioning equipment during the target time period.

[0076] In this embodiment, by determining the heat source of the target space and establishing the heat balance relationship between the heat changes in the target space, the correlation between the real-time acquired temperature parameters, the experimentally determined constant parameters, and the predicted air conditioning power can be determined, thus realizing the construction of the air conditioning power prediction model.

[0077] In an exemplary embodiment, the heat source may include the ambient temperature difference, as shown in FIG3, and step 2011 may include:

[0078] Step A1: Collect multiple sets of outdoor and indoor ambient temperatures, as well as the corresponding first heat change; wherein, the first heat change is caused by the difference between the outdoor and indoor ambient temperatures.

[0079] Step A2: Using data fitting, determine the first correlation between outdoor ambient temperature, indoor ambient temperature and the first change in heat.

[0080] For example, an experiment can be conducted by turning off the air conditioning equipment and indoor heat sources, collecting multiple sets of experimental data on outdoor and indoor ambient temperatures, as well as the corresponding changes in the first heat source. The first correlation between the outdoor and indoor ambient temperatures and the changes in the first heat source can then be fitted. In this case, the temperature difference between the outdoor and indoor ambient temperatures is the only influencing factor on the change in indoor ambient temperature, and the indoor ambient temperature will gradually approach the outdoor ambient temperature.

[0081] In one possible implementation, the first association can be determined by a first formula, which may include:

[0082] Among them, Q T Let A be the first change in heat, and T be the third constant. out The outdoor ambient temperature, T in,0 ρVc is the indoor ambient temperature, ρVc is the space heat capacity constant, and τ is time.

[0083] In an exemplary embodiment, the heat source may include the ambient temperature difference, as shown in FIG4, and step 2011 may include:

[0084] Step B1: Collect multiple sets of indoor ambient temperature and target set temperature, as well as the corresponding second heat change; wherein, the second heat change is caused by the operation of the air conditioning equipment.

[0085] Step B2 involves using data fitting to determine the second correlation between indoor ambient temperature, target set temperature, and the second change in heat.

[0086] For example, an experiment can be conducted by turning on the air conditioning equipment and maintaining the target set temperature. Multiple sets of experimental data on outdoor and indoor ambient temperatures, as well as the corresponding changes in the second heat, can be collected. The second correlation between the outdoor and indoor ambient temperatures and the changes in the second heat can then be fitted. In this case, the operation of the air conditioning equipment is the only influencing factor on the change in indoor ambient temperature, and the indoor ambient temperature will gradually approach the target set temperature.

[0087] In one possible implementation, the second association can be determined by a second formula, which may include:

[0088] Among them, Q c The second change in heat, B is the fourth constant, and T in,0 Indoor ambient temperature, T setSet the target temperature, ρVc is the space heat capacity constant, and τ is time.

[0089] Furthermore, the above thermal equilibrium relationship can be expressed as:

[0090] Where A is the third constant, T out The outdoor ambient temperature, T in，0 The indoor ambient temperature is given by ρVc, the space heat capacity constant is given by τ, time is given by B, and T is given by T. set Set the target temperature, Q heat P is the first constant. AC Here, represents the air conditioner power, and COP is the second constant.

[0091] In an exemplary embodiment, the air conditioning load can be flexibly adjusted on the power consumption side. As shown in Figure 5, after step 204 above, the power regulation method for air conditioning load can include:

[0092] Step 205: Based on the target power curves corresponding to multiple target spaces, adjust the operating status of the air conditioning equipment in the multiple target spaces.

[0093] For example, a target power curve can be determined by a third formula, and the operating mode or set temperature of air conditioning equipment in multiple target spaces can be changed according to the target power curve. For instance, the operating mode of the air conditioning equipment can be adjusted to an energy-saving mode, or the difference between the set temperature and the outdoor ambient temperature can be reduced. The third formula may include: P AC =f(T) out ,T in,0 ,T set ,τ);

[0094] Among them, P AC Let T be the air conditioner power, f be the relationship between temperature parameter and air conditioner power, and T be the air conditioner power. out The outdoor ambient temperature, T in,0 Indoor ambient temperature, T set Set the target temperature, and τ as the time.

[0095] In an exemplary embodiment, the power regulation strategy described above may include at least one of the following: performing primary frequency regulation on the power supply systems corresponding to multiple target spaces, performing secondary frequency regulation on the power supply systems corresponding to multiple target spaces, and performing frequency regulation on the power supply systems corresponding to multiple target spaces.

[0096] For example, since the adjustment time of primary frequency regulation is relatively short, a rigid adjustment method can be used to achieve primary frequency regulation. In one possible implementation, the power change of primary frequency regulation can be determined by a fourth formula, which may include: ΔP AC =PAC1 ;

[0097] Where, ΔP AC For the power variation of the power supply system, P AC1 It can be the average power of the air conditioner within the target time period.

[0098] Secondary frequency regulation has a longer settling time than primary frequency regulation, allowing it to adapt to various factors such as load changes, fuel efficiency, renewable energy integration, and short- and medium-term plans. It can be implemented using flexible regulation methods. In one possible implementation, the power variation of secondary frequency regulation can be determined by a fifth formula, which may include:

[0099] ΔP AC =f(T) out ,T in,0 ,T set ,15min)-P AC2 ;

[0100] Where, ΔP AC For the power variation of the power supply system, T out The outdoor ambient temperature, T in,0 Indoor ambient temperature, T set Set the target temperature, P ACI It could be the power of the power supply system after the previous round of power changes.

[0101] Peak shaving requires a longer adjustment time compared to secondary frequency regulation. It necessitates adjusting the power system's operation based on multiple factors, including peak load variations, renewable energy fluctuations, demand-side management, and fuel efficiency, to ensure reliable power supply and reduce costs. Flexible regulation can be employed to achieve peak shaving. In one possible implementation, the power variation for peak shaving can be determined by a sixth formula, which may include:

[0102] P AC =f(T) out ,T in,0 ,T set1 ,30min)-P AC3 ;

[0103] Where, ΔP AC For the power variation of the power supply system, T out The outdoor ambient temperature, T in，0 Indoor ambient temperature, T set Set the target temperature, P AC3 It could be the power of the power supply system after the previous round of power changes.

[0104] In this embodiment, by integrating the predicted air conditioning power of multiple target spaces, the adjustable potential of a target building or target area including multiple target spaces can be predicted. By performing primary frequency regulation, secondary frequency regulation, and peak regulation on the power supply system according to the predicted results of the adjustable potential, the flexibility and accuracy of power regulation can be further improved.

[0105] In summary, the aforementioned power regulation method for air conditioning load acquires temperature parameters affecting air conditioning power in real time and inputs them into a pre-built air conditioning power prediction model. This allows the model to capture information affecting air conditioning power and make accurate predictions of air conditioning power in the short term, thereby determining the size of the adjustable potential of the air conditioning load. Furthermore, by using the predicted air conditioning power to finely regulate the overall power supply of multiple target spaces, the adjustable potential of the air conditioning load can be efficiently utilized, improving the flexibility and accuracy of power regulation.

[0106] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0107] Based on the same inventive concept, this application also provides an air conditioning load-oriented power regulation device for implementing the above-mentioned power regulation method for air conditioning loads. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more air conditioning load-oriented power regulation device embodiments provided below can be found in the limitations of the air conditioning load-oriented power regulation method described above, and will not be repeated here.

[0108] In an exemplary embodiment, as shown in FIG6, a power regulation device 300 for air conditioning load is provided, including: an acquisition module 301, a prediction module 302, and a first adjustment module 303, wherein:

[0109] The acquisition module 301 is used to acquire the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature.

[0110] The prediction module 302 is used to input temperature parameters into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between temperature parameters and air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period;

[0111] The first adjustment module 303 is used to determine a power control strategy based on the target power curves corresponding to multiple target spaces. The power control strategy is used to increase / decrease the power supply of multiple target spaces within a target time period.

[0112] In one exemplary embodiment, the power regulation device 300 for air conditioning loads described above includes:

[0113] The correlation determination module is used to determine the heat source of the target space and establish the correlation between the heat change caused by the heat source and the temperature parameters.

[0114] The model determination module is used to construct an air conditioning power prediction model based on the thermal balance relationship between changes in heat volume.

[0115] In one exemplary embodiment, the aforementioned association determination module includes:

[0116] The first acquisition submodule is used to acquire multiple sets of outdoor and indoor ambient temperatures, as well as the corresponding first heat change; wherein, the first heat change is caused by the difference between the outdoor and indoor ambient temperatures.

[0117] The first determination submodule is used to determine the first correlation between outdoor ambient temperature, indoor ambient temperature and first heat change by means of data fitting.

[0118] In one exemplary embodiment, the aforementioned association determination module includes:

[0119] The second acquisition submodule is used to acquire multiple sets of indoor ambient temperature and target set temperature, as well as the corresponding second heat change; wherein, the second heat change is caused by the operation of the air conditioning equipment;

[0120] The second determination submodule is used to determine the second correlation between indoor ambient temperature, target set temperature and second heat change by using data fitting.

[0121] In one exemplary embodiment, the power regulation device 300 for air conditioning loads described above includes:

[0122] The second adjustment module is used to adjust the operating status of the air conditioning equipment in multiple target spaces based on the target power curves corresponding to multiple target spaces.

[0123] In one exemplary embodiment, the above-mentioned power regulation strategy includes at least one of the following:

[0124] The power supply systems corresponding to multiple target spaces are subjected to primary frequency regulation, secondary frequency regulation, and frequency regulation.

[0125] The modules in the aforementioned power control device for air conditioning loads can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0126] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram is shown in Figure 7. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store data. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a power regulation method for air conditioning loads.

[0127] Those skilled in the art will understand that the structure shown in Figure 7 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0128] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0129] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method embodiments.

[0130] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0131] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0132] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A power regulation method for air conditioning loads, characterized in that, The method includes: Obtain the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature; The temperature parameter is input into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between the temperature parameter and the air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period; Based on the target power curves corresponding to multiple target spaces, a power regulation strategy is determined, which is used to increase / decrease the power supply of the multiple target spaces within the target time period.

2. The method according to claim 1, characterized in that, Before inputting the temperature parameter into the pre-built air conditioning power prediction model, the following steps are included: Identify the heat source in the target space; Establish the correlation between the change in heat caused by the heat source and the temperature parameter; Based on the thermal balance relationship between the heat changes, an air conditioning power prediction model is constructed.

3. The method according to claim 2, characterized in that, The heat source includes the temperature difference between indoor and outdoor environments, and establishing the correlation between the heat change caused by the heat source and the temperature parameter includes: Multiple sets of outdoor and indoor ambient temperatures are collected, along with the corresponding first heat change; wherein the first heat change is caused by the difference between the outdoor and indoor ambient temperatures. A first correlation relationship is determined between the outdoor ambient temperature, the indoor ambient temperature, and the first change in heat by using data fitting.

4. The method according to claim 2, characterized in that, The heat source includes air conditioning equipment, and establishing the correlation between the heat change caused by the heat source and the temperature parameter includes: Multiple sets of indoor ambient temperatures and target set temperatures are collected, along with the corresponding second heat change; wherein the second heat change is caused by the operation of the air conditioning equipment. A second correlation relationship is determined by using data fitting to identify the indoor ambient temperature, the target set temperature, and the second change in heat.

5. The method according to claim 1, characterized in that, After inputting the temperature parameters into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space, the process includes: Based on the target power curves corresponding to multiple target spaces, the operating status of the air conditioning equipment in the multiple target spaces is adjusted.

6. The method according to claim 5, characterized in that, The power regulation strategy includes at least one of the following: The power supply systems corresponding to the multiple target spaces are subjected to a first frequency modulation, a second frequency modulation, and a third frequency modulation.

7. A power control device for air conditioning loads, characterized in that, The device includes: The acquisition module is used to acquire the temperature parameters of the target space, including the outdoor ambient temperature, the indoor ambient temperature, and the target set temperature. The prediction module is used to input the temperature parameter into a pre-built air conditioning power prediction model to obtain the target power curve corresponding to the target space; wherein, the air conditioning power prediction model is used to characterize the correlation between the temperature parameter and the air conditioning power, and the target power curve is used to indicate the change of air conditioning power within the target time period; The first adjustment module is used to determine a power regulation strategy based on the target power curves corresponding to multiple target spaces. The power regulation strategy is used to increase / decrease the power supply of the multiple target spaces within the target time period.

8. The apparatus according to claim 7, characterized in that, The device further includes: The heat source determination module is used to determine the heat source of the target space; The correlation determination module is used to establish the correlation between the amount of heat change caused by the heat source and the temperature parameter; The model determination module is used to construct an air conditioning power prediction model based on the thermal balance relationship between the heat changes.

9. The apparatus according to claim 8, characterized in that, The heat source includes the temperature difference between indoor and outdoor environments, and the correlation determination module includes: The first acquisition submodule is used to acquire multiple sets of outdoor ambient temperature and indoor ambient temperature, as well as the corresponding first heat change; wherein, the first heat change is caused by the difference between the outdoor ambient temperature and the indoor ambient temperature. The first determining submodule is used to determine a first correlation between the outdoor ambient temperature, the indoor ambient temperature and the first heat change by means of data fitting.

10. The apparatus according to claim 8, characterized in that, The heat source includes air conditioning equipment, and the correlation determination module includes: The second acquisition submodule is used to acquire multiple sets of indoor ambient temperature and target set temperature, as well as the corresponding second heat change; wherein, the second heat change is caused by the operation of the air conditioning equipment; The second determining submodule is used to determine a second correlation between the indoor ambient temperature, the target set temperature and the second heat change by means of data fitting.

11. The apparatus according to claim 7, characterized in that, The device further includes: The second adjustment module is used to adjust the operating status of the air conditioning equipment in the multiple target spaces based on the target power curves corresponding to the multiple target spaces.

12. The apparatus according to claim 7, characterized in that, The power regulation strategy includes at least one of the following: The power supply systems corresponding to the multiple target spaces are subjected to a first frequency modulation, a second frequency modulation, and a third frequency modulation.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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