Methods, devices, and control systems for controlling the power consumption of multiple air conditioners

Abstract

This application provides a method, apparatus, and control system for regulating the power consumption of multiple air conditioners. The method includes: acquiring the current return air temperature and set temperature of each air conditioner, wherein the return air temperature is the current air temperature at the return air vent of the air conditioner; when the current return air temperature of a first target air conditioner is greater than the corresponding set temperature, determining at least one first expected energy saving degree based on the set temperature and temperature difference of each first target air conditioner; and generating a first regulation strategy when the cumulative value of all first expected energy saving degrees is greater than or equal to the regulation power consumption. The first regulation strategy is used to control the power consumption of all first target air conditioners to adjust the current return air temperature to the energy-saving temperature and maintain it at the energy-saving temperature within a predetermined time. The regulation power consumption is the power consumption that all air conditioners need to reduce within the predetermined time. This solves the problem in the prior art where cutting off part of the power supply to reduce power consumption and regulate power consumption leads to inconvenience in power use.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of air conditioner control, in particular to a multi-air-conditioner power regulation method and device, computer readable storage medium and multi-air-conditioner control system. BACKGROUND

[0002] Demand response, short for power demand response, refers to when the power wholesale market price rises or the system reliability is threatened, the power user receives the direct compensation notice or power price rise signal from the power supplier to induce the reduction of load, changes the inherent habit of power consumption mode, reduces or shifts the power load in a certain period of time to respond to the power supply, thereby ensuring the stability of the power grid and inhibiting the short-term behavior of the price rise.

[0003] Air conditioner load, as a load-side adjustable resource, has great potential for excavation and flexible scheduling, and is an excellent demand response resource. At the same time, the energy consumption of the air conditioning system accounts for more than half of the total building operation energy consumption. It is of great practical significance to study the demand response of air conditioners in a certain area. SUMMARY

[0004] The main purpose of the present application is to provide a multi-air-conditioner power regulation method and device, computer readable storage medium and multi-air-conditioner control system, so as to at least solve the problem of inconvenience in use caused by cutting off part of the power supply to reduce power consumption and achieve regulation of power consumption in the prior art.

[0005] In order to achieve the above object, according to one aspect of the present application, a method for regulating power consumption of multiple air conditioners is provided, comprising: obtaining current return air temperature and set temperature of each air conditioner, the return air temperature being current air temperature of a return air outlet of the air conditioner; in a case where the current return air temperature of a first target air conditioner is greater than the corresponding set temperature, determining at least one first predicted energy saving degree number according to the set temperature and temperature difference of each first target air conditioner, the first target air conditioner being one or more of the air conditioners, the temperature difference being a difference between the current return air temperature and a measuring point temperature when the current return air temperature reaches the corresponding set temperature, the measuring point temperature being air temperature at any point in a user activity area, the first predicted energy saving degree number being a difference between a first power consumption and a second power consumption, the first power consumption being power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption being power consumption for adjusting the current return air temperature to an energy saving temperature and maintaining the energy saving temperature within the predetermined time, the energy saving temperature being a sum of the set temperature and the temperature difference; in a case where a cumulative value of all the first predicted energy saving degree numbers is greater than or equal to a regulation power, generating a first regulation strategy, the first regulation strategy being used to control all the first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the energy saving temperature within the predetermined time, the regulation power being power consumption that needs to be reduced by all the air conditioners within the predetermined time.

[0006] Optionally, after obtaining the current return air temperature and the set temperature of each air conditioner, the method further comprises: in a case where a first condition or a second condition is met, determining whether the set temperature of each air conditioner is within an optimal set temperature range, the first condition being that all the current return air temperatures are less than or equal to the corresponding set temperature, the second condition being that a cumulative value of all the predicted energy saving degree numbers is less than the regulation power, the optimal set temperature range being a range of set temperature in which user comfort is optimal; in a case where the set temperature of all the air conditioners is within the optimal set temperature range, determining an air conditioner closing number according to the set temperature of each air conditioner, the air conditioner closing number being a number of air conditioners that are closed, which results in power consumption reduction greater than or equal to the regulation power; generating a second regulation strategy according to the air conditioner closing number, the second regulation strategy being used to control the air conditioners that are closed.

[0007] Optionally, after determining whether the set temperature of each air conditioner is in the optimal set temperature range, the method further comprises: in the case of simultaneously satisfying a third condition and a fourth condition, or simultaneously satisfying the third condition and a fifth condition, determining at least one second predicted energy saving degree number according to the set temperature and a first adjusted set temperature, the first adjusted set temperature being a temperature in the optimal set temperature range with the smallest absolute value of the difference from the set temperature, the second predicted energy saving degree number being the power consumption reduced by adjusting the target temperature of a second target air conditioner from the set temperature to the first adjusted set temperature, the first target air conditioner being one or more of the air conditioners, the third condition being that the set temperature of the second target air conditioner is not in the optimal set temperature range, the fourth condition being that the difference between the set temperature of the second target air conditioner and the maximum value of the optimal set temperature range is greater than 0 and less than a predetermined threshold, and the fifth condition being that the difference between the minimum value of the optimal set temperature range of the second target air conditioner and the set temperature is greater than 0 and less than the predetermined threshold; and in the case that the cumulative value of all the first predicted energy saving degree numbers and all the second predicted energy saving degree numbers is greater than or equal to the control power, generating a third control strategy, the third control strategy being used to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature.

[0008] Optionally, after determining whether the set temperature of each air conditioner is in the optimal set temperature range, the method further comprises: in the case of simultaneously satisfying a third condition and a fourth condition, or simultaneously satisfying the third condition and a fifth condition, determining at least one second predicted energy saving degree number according to the set temperature and a first adjusted set temperature, the first adjusted set temperature being a temperature in the optimal set temperature range with the smallest absolute value of the difference from the set temperature, the second predicted energy saving degree number being the power consumption reduced by adjusting the target temperature of a second target air conditioner from the set temperature to the first adjusted set temperature, the first target air conditioner being one or more of the air conditioners, the third condition being that the set temperature of the second target air conditioner is not in the optimal set temperature range, the fourth condition being that the difference between the set temperature of the second target air conditioner and the maximum value of the optimal set temperature range is greater than 0 and less than a predetermined threshold, and the fifth condition being that the difference between the minimum value of the optimal set temperature range of the second target air conditioner and the set temperature is greater than 0 and less than the predetermined threshold; and in the case that the cumulative value of all the first predicted energy saving degree numbers and all the second predicted energy saving degree numbers is greater than or equal to the control power, generating a third control strategy, the third control strategy being used to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature.

[0009] Optionally, the determining the at least one first predicted energy-saving degree number according to the set temperature and the temperature difference of each first target air conditioner comprises: determining the set temperature as a target measuring point temperature, and calculating a sum of the set temperature and the temperature difference to obtain a target return air temperature, the target measuring point temperature being a temperature at which the user activity area reaches the set temperature, and the target return air temperature being a return air temperature at which the user activity area reaches the set temperature; inputting the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, an outdoor temperature and humidity, and a compressor frequency of each first target air conditioner into an energy-saving model to obtain the at least one first predicted energy-saving degree number, the energy-saving model being trained by using a plurality of sets of training data, each set of the training data comprising the return air temperature, the corresponding target return air temperature, the corresponding measuring point temperature, the corresponding target measuring point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding first predicted energy-saving degree number at a historical time.

[0010] Optionally, the determining the at least one second predicted energy-saving degree number according to the set temperature and the first adjusted set temperature comprises: calculating a difference between the first adjusted set temperature and the temperature difference to obtain a target measuring point temperature, and determining the first adjusted set temperature as a target return air temperature, the target measuring point temperature being a temperature of the user activity area when the return air temperature reaches the first adjusted set temperature, and the target return air temperature being a temperature at which the return air temperature reaches the first adjusted set temperature; inputting the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, an outdoor temperature and humidity, and a compressor frequency of each second target air conditioner into an energy-saving model to obtain the at least one second predicted energy-saving degree number, the energy-saving model being trained by using a plurality of sets of training data, each set of the training data comprising the return air temperature, the corresponding target return air temperature, the corresponding measuring point temperature, the corresponding target measuring point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding second predicted energy-saving degree number at a historical time.

[0011] Optionally, determining at least one third predicted energy-saving degree according to the set temperature and the second adjusted set temperature comprises: calculating a difference between the second adjusted set temperature and the temperature difference to obtain a target measuring point temperature, and determining the second adjusted set temperature as a target return air temperature, the target measuring point temperature being a temperature of the user activity area when the return air temperature reaches the second adjusted set temperature, and the target return air temperature being a temperature of the return air temperature when the return air temperature reaches the second adjusted set temperature; inputting the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, outdoor temperature and humidity and compressor frequency of each third target air conditioner into an energy-saving model to obtain at least one third predicted energy-saving degree, the energy-saving model being obtained by training a plurality of sets of training data, each set of training data in the plurality of sets of training data comprising the return air temperature, the corresponding target return air temperature, the corresponding measuring point temperature, the corresponding target measuring point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency and the corresponding third predicted energy-saving degree at a historical time.

[0012] Optionally, before determining at least one first predicted energy-saving degree according to the set temperature and the temperature difference of each first target air conditioner, the method further comprises: controlling the air conditioner to operate until the return air temperature of the air conditioner reaches the set temperature; obtaining the return air temperature and the measuring point temperature once at a predetermined time interval during the operation of the air conditioner to obtain a plurality of return air temperatures and a plurality of corresponding measuring point temperatures; and calculating an average value of the difference between each return air temperature and the corresponding measuring point temperature to obtain the temperature difference.

[0013] According to another aspect of the present application, there is provided a regulating device for multiple air conditioners, comprising: an obtaining unit configured to obtain current return air temperature and set temperature of each air conditioner, the return air temperature being current air temperature of a return air outlet of the air conditioner; a first determining unit configured to determine at least one first predicted energy saving degree of each first target air conditioner according to the set temperature and temperature difference of each first target air conditioner, in a case that the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, the first target air conditioner being one or more of the air conditioners, the temperature difference being a difference between the current return air temperature and a measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature being air temperature at any point in a user activity area, the first predicted energy saving degree being a difference between a first power consumption and a second power consumption, the first power consumption being power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption being power consumption for adjusting the current return air temperature to an energy saving temperature and maintaining the energy saving temperature within the predetermined time, the energy saving temperature being a sum of the set temperature and the temperature difference; and a first generating unit configured to generate a first regulating strategy for controlling all the first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the energy saving temperature within the predetermined time, in a case that a cumulative value of all the first predicted energy saving degrees is greater than or equal to a regulating power.

[0014] According to still another aspect of the present application, there is provided a computer readable storage medium, comprising a stored program, wherein the computer readable storage medium is caused to perform any of the methods described when the program is run.

[0015] According to yet another aspect of the present application, there is provided a multiple air conditioner control system, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise instructions for performing any of the methods described.

[0016] According to the technical solution, the return air temperature sensing bag of the air conditioner wall-mounted machine is generally installed at the return air of the air conditioner, and is high from the ground and far from the user activity area. Because the air outlet temperature of the air conditioner is low, the cold air sinks, and thus there is a certain deviation between the return air temperature and the temperature of the actual activity position of the user, that is, the return air temperature is higher than the temperature of the measuring point, which leads to poor temperature control effect. The method can stop the temperature reduction when the return air temperature of the air conditioner is reduced to the energy-saving temperature above the set temperature, that is, the temperature of the measuring point reaches the set temperature, and the first expected energy-saving degree corresponding to each air conditioner is calculated. As long as the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, the first target air conditioner can be controlled to run in such an energy-saving mode. The cumulative value of all the first expected energy-saving degrees is greater than or equal to the regulated power, so that all the air conditioners running in such an energy-saving mode can reduce the power consumption to achieve the regulated power, thereby solving the problem of inconvenient power consumption caused by cutting off part of the power supply to achieve the regulated power consumption in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for executing a multi-air-conditioner power regulation method according to an embodiment of the present application is shown;

[0018] Figure 2 A flowchart of a multi-air-conditioner power regulation method according to an embodiment of the present application is shown;

[0019] Figure 3 A flowchart of another multi-air-conditioner power regulation method according to an embodiment of the present application is shown;

[0020] Figure 4 A distribution diagram of an air conditioner and a measuring point according to an embodiment of the present application is shown;

[0021] Figure 5 A federal model training flowchart according to an embodiment of the present application is shown;

[0022] Figure 6 A structure block diagram of a multi-air-conditioner power regulation device according to an embodiment of the present application is shown.

[0023] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0024] 1, room where indoor unit is located; 2, indoor unit position; 3, main user activity range; 4, measuring point position. DETAILED DESCRIPTION

[0025] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0026] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] As described in the background section, existing technologies that cut off part of the power supply to reduce power consumption and regulate power consumption cause inconvenience in electricity use. To solve this problem, embodiments of this application provide a method, apparatus, computer-readable storage medium, and multi-air conditioning power control system for regulating the power consumption of multiple air conditioners.

[0029] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0030] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of controlling the power consumption of multiple air conditioners according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1more or less components than those shown, or configured differently from those shown, as Figure 1 described.

[0031] The memory 104 can be used to store computer programs, such as software programs of application software and modules, such as a computer program corresponding to the method for displaying device information in the embodiments of the present application. The processor 102 can execute various functional applications and data processing, i.e., implement the above method, by running the computer program stored in the memory 104. The memory 104 can include a high-speed random access memory, and can further include a nonvolatile memory, such as one or more magnetic storage devices, a flash memory, or other nonvolatile solid-state memories. In some examples, the memory 104 can further include a memory remotely disposed relative to the processor 102, and the remote memory can be connected to the mobile terminal through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is configured to receive or send data via a network. The specific examples of the network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is configured to communicate with the Internet in a wireless manner.

[0032] In the present embodiment, a method for regulating a multi-air conditioner is provided, which is run on a mobile terminal, a computer terminal or a similar computing device. It should be noted 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 herein can be executed in an order different from that shown.

[0033] Figure 2 is a flowchart of the method for regulating a multi-air conditioner according to the embodiments of the present application. As Figure 2 shown, the method includes the following steps:

[0034] In step S201, the current return air temperature and the set temperature of each air conditioner are obtained. The return air temperature is the current air temperature at the return air outlet of the air conditioner.

[0035] Specifically, the current return air temperature does not reach the set temperature, and the air conditioner can be stopped to reduce the temperature to the energy-saving temperature above the set temperature to save energy. The current return air temperature has reached the set temperature and cannot be saved in this way. Therefore, the current return air temperature and the set temperature of each air conditioner are obtained to determine the first target air conditioner that can be saved in this way.

[0036] In step S202, in the case that the above-mentioned current return air temperature of the first target air conditioner is greater than the above-mentioned set temperature corresponding thereto, at least one first predicted energy-saving degree number is determined according to the above-mentioned set temperature and the temperature difference of each of the above-mentioned first target air conditioners, the above-mentioned first target air conditioner is one or more of the above-mentioned air conditioners, the above-mentioned temperature difference is the difference between the above-mentioned current return air temperature and the measurement point temperature when the above-mentioned current return air temperature reaches the corresponding above-mentioned set temperature, the above-mentioned measurement point temperature is the air temperature at any point in the user activity area, the above-mentioned first predicted energy-saving degree number is the difference between the first power consumption and the second power consumption, the above-mentioned first power consumption is the power consumption for adjusting the above-mentioned current return air temperature to the above-mentioned set temperature and maintaining it at the above-mentioned set temperature within a predetermined time, and the above-mentioned second power consumption is the power consumption for adjusting the above-mentioned current return air temperature to the energy-saving temperature and maintaining it at the above-mentioned energy-saving temperature within the above-mentioned predetermined time, and the above-mentioned energy-saving temperature is the sum of the above-mentioned set temperature and the above-mentioned temperature difference.

[0037] Specifically, the trained federated learning model is used to obtain the energy-saving potential of all air conditioner devices in the region for m time, i.e. the energy-saving degree number n1. Because generally, the frequency conversion air conditioner enters high frequency operation for 10-20 minutes to reach the set temperature, and m is generally greater than 20 minutes, the corresponding predicted features after m time: outdoor temperature and humidity can be obtained from online data crawling, the return air temperature = the set temperature + the temperature difference, the measurement point temperature = the set temperature, and the running compressor frequency is obtained from the built-in compressor frequency program (which is the corresponding compressor frequency when the return air temperature = the set temperature in the original program).

[0038] In step S203, in the case that the cumulative value of all the above-mentioned first predicted energy-saving degree numbers is greater than or equal to the regulation power, a first regulation strategy is generated, the above-mentioned first regulation strategy is used to control all the above-mentioned first target air conditioners to adjust the above-mentioned current return air temperature to the energy-saving temperature and maintain it at the above-mentioned energy-saving temperature within the above-mentioned predetermined time, and the above-mentioned regulation power is the power consumption that all the above-mentioned air conditioners need to reduce within the above-mentioned predetermined time.

[0039] Specifically, the flow ends, and the server uniformly issues relevant energy-saving instructions to all air conditioners in the region, i.e. issues the temperature and humidity compensation instruction. The issuance of the temperature and humidity compensation instruction is to perform compressor frequency reduction according to the built-in compressor program in advance; in this way, the demand response requirement is met on the basis of not affecting the user experience and economic loss, i.e. reducing the power consumption to the regulation power.

[0040] In the above method for regulating power consumption of multiple air conditioners, first, the current return air temperature and the set temperature of each air conditioner are obtained, the return air temperature being the current air temperature at the return air outlet of the air conditioner; then, in the case where the current return air temperature of a first target air conditioner is greater than the corresponding set temperature, at least one first predicted energy saving degree is determined according to the set temperature and the temperature difference of each first target air conditioner, the first target air conditioner being one or more of the air conditioners, the temperature difference being the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature being the air temperature at any point in the user activity area, the first predicted energy saving degree being the difference between a first power consumption and a second power consumption, the first power consumption being the power consumption for adjusting the current return air temperature to the set temperature and maintaining it at the set temperature within a predetermined time, the second power consumption being the power consumption for adjusting the current return air temperature to an energy saving temperature and maintaining it at the energy saving temperature within the predetermined time, the energy saving temperature being the sum of the set temperature and the temperature difference; finally, in the case where the cumulative value of all the first predicted energy saving degrees is greater than or equal to the regulated power consumption, a first regulation strategy is generated, the first regulation strategy being used to control all the first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain it at the energy saving temperature within the predetermined time, the regulated power consumption being the power consumption that needs to be reduced by all the air conditioners within the predetermined time. Since the return air temperature sensor of a wall-mounted air conditioner is generally installed at the return air outlet of the air conditioner, it is located relatively high from the ground and far from the user activity area. Since the air outlet temperature of the air conditioner is relatively low and the cold air sinks, there is a certain deviation between the return air temperature and the temperature at the user's actual activity location, i.e., the return air temperature is higher than the measurement point temperature, which results in poor temperature control effect. This method stops the temperature reduction when the return air temperature of the air conditioner drops to the energy saving temperature above the set temperature, i.e., the measurement point temperature reaches the set temperature. The first predicted energy saving degree corresponding to each air conditioner is calculated, and the first target air conditioner is controlled to operate in this energy saving mode as long as the current return air temperature of the first target air conditioner is greater than the corresponding set temperature. The cumulative value of all the first predicted energy saving degrees is greater than or equal to the regulated power consumption, which controls all the air conditioners to operate in this energy saving mode to reduce the power consumption to the regulated power consumption, thereby solving the problem of inconvenience in power consumption caused by cutting off part of the power supply to achieve the regulated power consumption in the prior art.

[0041] To ensure that the power consumption is reduced to the regulated power consumption, in an optional solution, after obtaining the current return air temperature and the set temperature of each air conditioner, the method further comprises:

[0042] Step S301, in the case of meeting the first condition or the second condition, determine whether the set temperature of each air conditioner is within the optimal set temperature range, the first condition is that all the current return air temperatures are less than or equal to the corresponding set temperature, the second condition is that the cumulative value of all the predicted energy saving degrees is less than the regulated power, and the optimal set temperature range is the range of the set temperature with the best user comfort;

[0043] Step S302, in the case that the set temperature of all the air conditioners is within the optimal set temperature range, determine the number of air conditioners to be turned off according to the set temperature of each air conditioner, the number of air conditioners to be turned off is the number of air conditioners whose shutdown leads to a reduction in power consumption greater than or equal to the regulated power;

[0044] Step S303, generate a second control strategy according to the number of air conditioners to be turned off, the second control strategy is used to control the shutdown of the air conditioners to be turned off.

[0045] Specifically, all the current return air temperatures are less than or equal to the corresponding set temperature, so that energy saving cannot be achieved by increasing the target return air temperature, and the cumulative energy saving degree n1 of this energy saving method is less than the regulated power, so that the target of reducing power consumption is not achieved, then determine whether the set temperature of all the air conditioners is between 26 and 28 degrees, i.e. within the optimal set temperature range, if so, there is no room for energy saving, and the number of air conditioners to be turned off is directly determined to achieve the reduction in power consumption to reach the regulated power. The set temperature of the air conditioner should not be too high or too low. The temperature of the general air conditioner is preferably recommended to be between 26 and 28 degrees. In a refrigeration environment, the ideal set temperature of the air conditioner is 26 degrees, and for each increase of 1 degree of the household air conditioner, the power consumption is saved by about 7% to 10%.

[0046] Of course, the air conditioner needs to be turned off to give economic compensation for regulation, use the trained federated learning model to obtain the energy saving potential of a single air conditioner in the region, i.e. the energy saving degree n3, under the corresponding feature data of m duration: the outdoor temperature and humidity crawled on the network, the return air temperature = the set temperature, the measurement point temperature = the set temperature - the temperature difference, and the running compressor frequency is obtained in the built-in compressor frequency program, and then determine the number x of air conditioners to be turned off.

[0047] To ensure that the reduction in power consumption reaches the regulated power, in one optional solution, after determining whether the set temperature of each air conditioner is within the optimal set temperature range, the method further comprises:

[0048] In step S401, in a case that the third condition and the fourth condition are satisfied simultaneously or the third condition and the fifth condition are satisfied simultaneously, at least one second predicted energy saving degree number is determined according to the set temperature and a first adjusted set temperature, the first adjusted set temperature is a temperature in the optimal set temperature range with the minimum absolute value of the difference from the set temperature, the second predicted energy saving degree number is the power consumption reduced when the target temperature of the second target air conditioner is adjusted from the set temperature to the first adjusted set temperature, the first target air conditioner is one or more of the air conditioners, the third condition is that the set temperature of the second target air conditioner is not in the optimal set temperature range, the fourth condition is that the difference between the set temperature of the second target air conditioner and the maximum value of the optimal set temperature range is greater than 0 and less than a predetermined threshold, and the fifth condition is that the difference between the minimum value of the optimal set temperature range of the second target air conditioner and the set temperature is greater than 0 and less than the predetermined threshold.

[0049] In step S402, in a case that the cumulative value of all the first predicted energy saving degree numbers and all the second predicted energy saving degree numbers is greater than or equal to the regulated power consumption, a third regulation strategy is generated, the third regulation strategy is used to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature.

[0050] Specifically, it is judged whether the set temperature is 25 degrees or 29 degrees, if yes, the set temperature is increased by 1 degree or decreased by 1 degree, which has little influence on the user and does not affect the comfort. Specifically, the trained federated learning model is used to obtain the feature data corresponding to the m time length: the outdoor temperature and humidity are crawled from the network, the return air temperature is the set temperature, the measurement point temperature is the set temperature minus the temperature difference, the running compressor frequency is obtained in the built-in compressor frequency program, and the energy saving potential of all air conditioning equipment in this area, i.e. the energy saving degree number n2, is obtained. It is judged whether the demand response regulation requirement is met, i.e. whether n1+n2 or n2 is greater than or equal to n, if yes, a third regulation strategy is generated to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature, so as to ensure that the power consumption is reduced to the regulated power consumption.

[0051] In order to ensure that the power consumption is reduced to the regulated power consumption, in an optional solution, after it is determined whether the set temperature of each air conditioner is in the optimal set temperature range, the method further comprises:

[0052] Step S501, in the case of simultaneously satisfying the third condition and the sixth condition, or simultaneously satisfying the third condition and the seventh condition, determining at least one third expected energy saving degree number according to the set temperature and a second adjustment set temperature, the second adjustment set temperature being a temperature in the optimal set temperature range with the smallest absolute value of the difference from the set temperature, the third expected energy saving degree number being the power consumption reduced when the target temperature of the third target air conditioner is adjusted from the set temperature to the second adjustment set temperature, the third target air conditioner being one or more of the air conditioners, the third condition being that the set temperature of the third target air conditioner is not in the optimal set temperature range, the sixth condition being that the difference between the set temperature of the third target air conditioner and the maximum value of the optimal set temperature range is greater than or equal to a predetermined threshold, and the seventh condition being that the difference between the minimum value of the optimal set temperature range of the third target air conditioner and the set temperature is greater than or equal to the predetermined threshold;

[0053] Step S502, in the case of the cumulative value of all the first expected energy saving degree numbers and all the third expected energy saving degree numbers being greater than or equal to the regulated power consumption, generating a fourth regulation strategy, the fourth regulation strategy being used to control all the third target air conditioners to adjust the target temperature from the set temperature to the second adjustment set temperature.

[0054] Specifically, the set temperature is far away from the optimal set temperature range, and the set temperature is increased or decreased by n degrees (the set temperature is at most 30 degrees), which has a relatively obvious influence on the user, and economic compensation is given for regulation. Specifically, the trained federated learning model is used to obtain the energy saving potential of all air conditioning equipment in the region, i.e., the energy saving degree number n2, corresponding to the feature data in m time length: the outdoor temperature and humidity crawled from the network, the return air temperature = the set temperature, the measurement point temperature = the set temperature - the temperature difference, the running compressor frequency is obtained from the built-in compressor frequency program, and the energy saving potential of all air conditioning equipment in the region, i.e., the energy saving degree number n2. Determine whether the demand response regulation requirement is met, i.e., whether n1+n2 or n2 is greater than or equal to n, if so, generate a third regulation strategy to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjustment set temperature, so as to ensure that the power consumption is reduced to reach the regulated power consumption.

[0055] In order to ensure that the power consumption is reduced to reach the regulated power consumption, in an optional solution, the step S202 comprises:

[0056] The step S2021 determines the set temperature as a target measurement point temperature, and calculates the sum of the set temperature and the temperature difference to obtain a target return air temperature, the target measurement point temperature being a temperature at which the user activity area reaches the set temperature, and the target return air temperature being the return air temperature at which the user activity area reaches the set temperature.

[0057] The step S2022 inputs the return air temperature, the measurement point temperature, the target return air temperature, the target measurement point temperature, the outdoor temperature and humidity, and the compressor frequency of each of the first target air conditioners into an energy saving model to obtain at least one first predicted energy saving degree, wherein the energy saving model is trained by using a plurality of sets of training data, and each set of the training data includes the return air temperature, the corresponding target return air temperature, the corresponding measurement point temperature, the corresponding target measurement point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding first predicted energy saving degree at a historical time.

[0058] Specifically, the energy saving is analyzed by using machine learning, a trained federated learning model is used as the energy saving model, the energy saving potential of all air conditioning devices in the region is obtained within m time, that is, the energy saving degree n1, that is, the first predicted energy saving degree, and the corresponding predicted features after m time, that is, the outdoor temperature and humidity, the return air temperature = the set temperature + the temperature difference, the measurement point temperature = the set temperature, and the running compressor frequency is obtained from the built-in compressor frequency program (which is the corresponding compressor frequency when the return air temperature = the set temperature in the original program).

[0059] In order to ensure that the power consumption is reduced to regulate the power, in an optional solution, the step S401 includes:

[0060] The step S4011 calculates the difference between the first adjusted set temperature and the temperature difference to obtain a target measurement point temperature, and determines the first adjusted set temperature as a target return air temperature, wherein the target measurement point temperature is the temperature of the user activity area when the return air temperature reaches the first adjusted set temperature, and the target return air temperature is the temperature when the return air temperature reaches the first adjusted set temperature.

[0061] The step S4012 inputs the return air temperature, the measurement point temperature, the target return air temperature, the target measurement point temperature, the outdoor temperature and humidity, and the compressor frequency of each of the second target air conditioners into an energy saving model to obtain at least one second predicted energy saving degree, wherein the energy saving model is trained by using a plurality of sets of training data, and each set of the training data includes the return air temperature, the corresponding target return air temperature, the corresponding measurement point temperature, the corresponding target measurement point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding second predicted energy saving degree at a historical time.

[0062] Specifically, the energy saving is analyzed by using machine learning, a trained federated learning model is used as an energy saving model, the trained federated learning model is used to obtain, under m time length, corresponding feature data: outdoor temperature and humidity obtained by crawling the network, return air temperature = set temperature, measured point temperature = set temperature - temperature difference, running compressor frequency obtained in the built-in compressor frequency program, and energy saving potential of all air conditioning equipment in the region, i.e. energy saving degree n2, i.e. the second predicted energy saving degree.

[0063] To ensure that the power consumption is reduced to the regulated power, in an optional solution, the step S501 includes:

[0064] In step S5011, the difference between the second adjusted set temperature and the temperature difference is calculated to obtain a target measured point temperature, and the second adjusted set temperature is determined as a target return air temperature, the target measured point temperature is the temperature of the user activity area when the return air temperature reaches the second adjusted set temperature, and the target return air temperature is the temperature when the return air temperature reaches the second adjusted set temperature;

[0065] In step S5012, the return air temperature, the measured point temperature, the target return air temperature, the target measured point temperature, the outdoor temperature and humidity, and the compressor frequency of each third target air conditioner are input into an energy saving model to obtain at least one third predicted energy saving degree, the energy saving model is trained using a plurality of sets of training data, and each set of training data in the plurality of sets of training data includes the return air temperature at a historical time, the corresponding target return air temperature, the corresponding measured point temperature, the corresponding target measured point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding third predicted energy saving degree.

[0066] Specifically, under m time length, corresponding feature data is obtained: outdoor temperature and humidity obtained by crawling the network, return air temperature = set temperature, measured point temperature = set temperature - temperature difference, running compressor frequency obtained in the built-in compressor frequency program, and energy saving potential of all air conditioning equipment in the region, i.e. energy saving degree n2, i.e. the third predicted energy saving degree.

[0067] To ensure that the power consumption is reduced to the regulated power, in an optional solution, after the step S201, the method further includes:

[0068] In step S601, the air conditioner is controlled to operate until the return air temperature of the air conditioner reaches the set temperature.

[0069] In step S602, the return air temperature and the measured point temperature are obtained once at a predetermined time interval during the operation of the air conditioner to obtain a plurality of return air temperatures and corresponding a plurality of measured point temperatures.

[0070] Step S603, calculate the average value of the difference between the return air temperature and the corresponding measurement point temperature, and obtain the temperature difference.

[0071] Specifically, the set temperature, operation time, return air temperature, and measurement point temperature of a certain air conditioning device are selected, the difference (temperature difference) between the return air temperature and the measurement point temperature is calculated every n time, when the return air temperature = set temperature, the timing and calculation are stopped. The average value of the temperature difference in this period is obtained as the return air temperature compensation value; that is, instead of return air temperature = set temperature, the compressor frequency reduction is return air temperature - temperature difference = set temperature, and the compressor frequency reduction, so as to achieve the effect of energy saving.

[0072] In order to enable those skilled in the art to more clearly understand the technical solutions of the present application, the implementation process of the multi-air-conditioning power regulation method of the present application will be described in detail below in conjunction with specific embodiments.

[0073] The present embodiment relates to a specific multi-air-conditioning power regulation method, as shown in Figure 3 The method comprises the following steps:

[0074] Step 1: Obtain the demand response regulation demand. The demand response regulation will issue a reduction of n degrees of power load within m time (usually in hours), that is, the regulation power is n degrees.

[0075] Step 2: Determine the relationship between the set temperature and the return air temperature; when the return air temperature > set temperature, go to step 3, otherwise go to step 6;

[0076] Step 3: Use the temperature and humidity compensation method to calculate the demand regulation. Use the trained federated learning model to obtain the energy saving potential of all air conditioning devices in this area within m time, that is, n1 degrees of energy saving. Because generally, the frequency conversion air conditioner starts to run at high frequency for 10-20 minutes to reach the set temperature, and m is generally greater than > 20 min, therefore, the corresponding prediction features after m time: outdoor temperature and humidity can be obtained from the online data, return air temperature = set temperature + temperature difference, measurement point temperature = set temperature, and the running compressor frequency is obtained from the built-in compressor frequency program (which is the corresponding compressor frequency when the return air temperature = set temperature in the original program);

[0077] Step 4: Determine whether the demand response regulation demand is met, that is, whether n1 is equal to or greater than n, if yes, go to step 5, otherwise, go to step 6;

[0078] Step 5: The end of the process, the server issues relevant energy-saving instructions to all air conditioners in the region, i.e. issues humidity compensation instructions or / and issues air conditioning set temperature or / and issues shutdown instructions. The issuance of humidity compensation instructions is to perform compressor frequency reduction processing in advance according to the built-in compressor program; in this way, the requirements of demand response are met on the basis of not affecting user experience and economic loss;

[0079] Step 6: Determine whether the air conditioning set temperature is less than 26 degrees or greater than 28 degrees. If yes, go to step 7, otherwise go to step 11; because the air conditioning set temperature should not be too high or too low. The temperature of general air conditioners is best recommended to be between 26 and 28 degrees. In a refrigeration environment, the ideal air conditioning set temperature is 26 degrees, and for every 1 degree increase in a home air conditioner, the power consumption is about 7% to 10% saved;

[0080] Step 7: Determine whether the set temperature is 25 degrees or 29 degrees; if yes, go to step 8, otherwise go to step 9;

[0081] Step 8: The set temperature is increased or decreased by 1 degree, which has little effect on the user and will not affect their comfort. Specifically, use the trained federated learning model to obtain the energy-saving potential of all air conditioning devices in the region, i.e. the energy-saving degree number n2, under the corresponding feature data: outdoor temperature and humidity crawled from the Internet, return air temperature = set temperature, measurement point temperature = set temperature - temperature difference, and running compressor frequency obtained from the built-in compressor frequency program, for m duration; use the calculated energy-saving degree number to go to step 11 for judgment;

[0082] Step 9: The set temperature is increased or decreased by n degrees (the set temperature is at most 30 degrees), which has a more obvious effect on the user, and economic compensation is given for regulation and control. Specifically, use the trained federated learning model to obtain the energy-saving potential of all air conditioning devices in the region, i.e. the energy-saving degree number n2, under the corresponding feature data: outdoor temperature and humidity crawled from the Internet, return air temperature = set temperature, measurement point temperature = set temperature - temperature difference, and running compressor frequency obtained from the built-in compressor frequency program, for m duration; use the calculated energy-saving degree number to go to step 11 for judgment;

[0083] Step 10: The air conditioner is turned off, and economic compensation is given for regulation and control. Specifically, use the trained federated learning model to obtain the energy-saving potential of a single air conditioning device in the region, i.e. the energy-saving degree number n3, under the corresponding feature data: outdoor temperature and humidity crawled from the Internet, return air temperature = set temperature, measurement point temperature = set temperature - temperature difference, and running compressor frequency obtained from the built-in compressor frequency program, for m duration; then determine the number x of air conditioners to be turned off; after the number of air conditioners to be turned off is determined, go to step 5;

[0084] Step 11: judging whether the demand response regulation requirement is met, i.e. whether n1+n2 or n2 is greater than or equal to n, if yes, going to step 5, otherwise going to step 10.

[0085] It should be noted that, as shown in Figure 4 Figure 4 The room where the indoor unit is located 1, the indoor unit position 2, the user's main activity range 3 and the measuring point position 4 are shown in FIG. 1. The indoor unit is installed at a certain height on one side of the room, and a return air temperature and humidity sensing bag is installed thereon for collecting the return air temperature and relative humidity of the indoor environment. The user's main activity range 3 can be considered as the surrounding of the office table if the room is the user's office room. The temperature and humidity sensor is installed at the measuring point position 4, which is located in the user's main activity range, at the middle position and at a distance of 0.6 meters from the ground, for collecting the temperature and relative humidity at the measuring point.

[0086] In the framework of federated learning, data from different data owners can be used safely, which can effectively prevent privacy leakage. Generally, the federated learning framework includes K participants, and the goal of the participants is to train a better machine learning model by safely using their own data through a certain method to complete the prediction or classification task. The federated learning framework is essentially a model training paradigm, that is, all participants jointly train a federated model (with better performance than the model trained using the participant's own data) with the help of the cloud or a third party, while not exposing their original data to other participants or the third party. The specific training process of the federated model is shown in FIG. 1. Figure 5

[0087] Figure 5 In FIG. 1, ①, ②, ③ and ④ respectively represent: ① calculating the training gradient of the local model, ② securely aggregating and updating the federated model, ③ issuing the federated model, and ④ updating the local model.

[0088] Figure 5 There are four levels in FIG. 1: the participant layer, the local model layer, the communication layer and the cloud layer. In the participant layer, each participant has data stored in its local server, and does not send any data containing sensitive information to the cloud or other participants; in the local model layer, each participant stores its own local model in its local server; in the communication layer, the participant and the cloud transmit information; in the cloud layer, the cloud server stores the federated model. The interaction between the four levels includes the following four steps:

[0089] Step S1: the participant calculates the training gradient of the local model based on its own data, encrypts the gradient information through homomorphic encryption, differential privacy or secret sharing technology, and uploads the encrypted result to the cloud;

[0090] ​​Step S2: The cloud server securely aggregates the encryption results of each participant and updates the federated model parameters based on the aggregated gradient;

[0091] Step S3: The cloud endows the new parameters of the federated model to each participant;

[0092] Step S4: The participant accepts the new parameters and updates the local model. The federated model training process repeatedly repeats the above four steps until the parameters of the federated model converge. This training process is applicable to various machine learning models (LR, BPNN, DNN, etc.), and all participants share the final federated model.

[0093] The air conditioner power consumption data of different manufacturers may be stored on different servers, causing data island problems due to data security considerations. Using federated learning can solve the data island problem under privacy protection and build a migration network for all participants (all different air conditioner manufacturers).

[0094] Demand response regulation generally refers to issuing a requirement to reduce the power load in a certain area at a certain time. Through optimization of economic subsidy means, forced power supply cutoff, etc., federated learning is used to build air conditioner power consumption models of multiple manufacturers, which can effectively evaluate the air conditioner loads of different manufacturers at the same time under relevant measures to reduce air conditioner load, meet the demand response regulation requirements, and reduce the economic loss of the power wholesale market on the basis of meeting human comfort as much as possible.

[0095] Similar condition manufacturer air conditioner aims to select air conditioners installed in the same climate zone. Feature selection aims to select appropriate features as inputs for the prediction model. Federated model training aims to safely use the data of similar condition manufacturer air conditioners to train a transferable federated model. Air conditioner power consumption model aims to regulate demand response.

[0096] 1) Similar condition manufacturer air conditioner: air conditioners installed in different climate zones have significantly different air conditioner loads due to differences in building envelope, climate temperature and humidity, etc. When building a migration network for different manufacturer air conditioners, the operation data of similar power consumption patterns are more beneficial to federated model training. By selecting air conditioner power consumption data in the same climate zone or the same area, it can be considered that the user's building envelope is the same and the climate temperature and humidity are similar.

[0097] 2) Feature selection: Feature selection aims to select features related to air conditioner power consumption prediction as inputs for the prediction model. These include set temperature, air conditioner matching number (different matching numbers correspond to different power), room area, building envelope, outdoor temperature, outdoor humidity, return air temperature, running time, running compressor frequency, measurement point temperature (user activity range center point), etc. Data is obtained every n time.

[0098] Where, the building envelope converges in the same region, so this feature can be ignored. Room area, match number can be obtained from the manufacturer; outdoor temperature and humidity can be obtained from the online data or measured by using temperature and humidity sensor; compressor frequency can be measured by using multimeter; other temperatures except outdoor can be measured by using temperature sensor, and air conditioner power consumption can be measured by meter.

[0099] 3) Federal learning training and optimization: according to Figure 5 Federal learning training process, all manufacturers' air conditioner data in the network cooperate to train a federal model. The model is used for power consumption prediction of all manufacturers' air conditioners in the region.

[0100] 4) Predicting photovoltaic system power generation: according to the federal learning model, the power consumption of each manufacturer's air conditioner in the same region can be predicted at the same time, which can efficiently guide the demand response adjustment of air conditioners in the same region.

[0101] The embodiment of the present application also provides a multi-air-conditioning power regulating device. It should be noted that the multi-air-conditioning power regulating device of the embodiment of the present application can be used to execute the multi-air-conditioning power regulating method provided by the embodiment of the present application. The device is used to realize the above-mentioned embodiment and preferred embodiment, and details are not repeated. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiment is preferably realized in software, hardware, or a combination of software and hardware is also possible and is conceived.

[0102] The multi-air-conditioning power regulating device provided by the embodiment of the present application is introduced below.

[0103] Figure 6 is a structural block diagram of the multi-air-conditioning power regulating device according to the embodiment of the present application. As Figure 6 shown, the device includes:

[0104] The acquisition unit 10 is configured to acquire the current return air temperature and the set temperature of each air conditioner. The return air temperature is the current air temperature of the return air outlet of the air conditioner.

[0105] Specifically, when the current return air temperature does not reach the set temperature, the air conditioner can be stopped to reduce the temperature to the energy-saving temperature above the set temperature to save energy. When the current return air temperature has reached the set temperature, this method cannot be used to save energy. Therefore, the current return air temperature and the set temperature of each air conditioner are acquired to determine the first target air conditioner that can use this energy-saving method.

[0106] The first determination unit 20 is configured to determine at least one first predicted energy-saving degree according to the set temperature and the temperature difference of each first target air conditioner when the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature is the air temperature at any point in the user activity area, the first predicted energy-saving degree is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, and the second power consumption is the power consumption for adjusting the current return air temperature to the energy-saving temperature and maintaining the energy-saving temperature within the predetermined time, and the energy-saving temperature is the sum of the set temperature and the temperature difference.

[0107] Specifically, using the trained federated learning model, the energy-saving potential of all air conditioning equipment in the region for m time is obtained, that is, the energy-saving degree n1. Because generally, the variable frequency air conditioner enters high frequency operation for 10-20 minutes to reach the set temperature, and m is generally greater than 20 minutes, therefore, the corresponding predicted features after m time: outdoor temperature and humidity can be obtained from the network, the return air temperature = the set temperature + the temperature difference, the measurement point temperature = the set temperature, and the running compressor frequency is obtained from the built-in compressor frequency program (which is the corresponding compressor frequency when the return air temperature = the set temperature in the original program).

[0108] The first generation unit 30 is configured to generate a first control strategy when the cumulative value of all the first predicted energy-saving degrees is greater than or equal to the control power, the first control strategy is used to control all the first target air conditioners to adjust the current return air temperature to the energy-saving temperature and maintain the energy-saving temperature within the predetermined time, and the control power is the power consumption that all the air conditioners need to reduce within the predetermined time.

[0109] Specifically, the process ends, and the server issues relevant energy-saving instructions to all air conditioners in the region, that is, issues the temperature and humidity compensation instructions. The issuance of the temperature and humidity compensation instructions is to perform compressor frequency reduction according to the built-in compressor program in advance; in this way, the demand response requirement is met on the basis of not affecting the user experience and economic loss, that is, the power consumption is reduced to the control power.

[0110] The control device for the multi-air-conditioning system, the acquisition unit acquires the current return air temperature and the set temperature of each air conditioner, the return air temperature is the current air temperature of the return air outlet of the air conditioner; the first determination unit determines at least one first predicted energy-saving degree according to the set temperature and the temperature difference of each first target air conditioner when the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature is the air temperature at any point in the user activity area, the first predicted energy-saving degree is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption is the power consumption for adjusting the current return air temperature to the energy-saving temperature and maintaining the energy-saving temperature within the predetermined time, the energy-saving temperature is the sum of the set temperature and the temperature difference; the first generation unit generates a first control strategy when the cumulative value of all the first predicted energy-saving degrees is greater than or equal to the control power, the first control strategy is used to control all the first target air conditioners to adjust the current return air temperature to the energy-saving temperature and maintain the energy-saving temperature within the predetermined time, and the control power is the power consumption that all the air conditioners need to reduce within the predetermined time. Since the return air temperature sensor of the air conditioner wall-mounted machine is generally installed at the return air outlet of the air conditioner, it is located higher from the ground and farther from the user activity area. Since the air conditioner outlet temperature is low and the cold air sinks, there is a certain deviation between the return air temperature and the temperature at the user's actual activity position, that is, the return air temperature is higher than the measurement point temperature, which leads to poor temperature control effect. The device stops cooling when the return air temperature of the air conditioner drops to the energy-saving temperature above the set temperature, that is, the measurement point temperature reaches the set temperature. The first predicted energy-saving degree corresponding to each air conditioner is calculated, and the first target air conditioner is controlled to operate in this energy-saving mode when the current return air temperature of the first target air conditioner is greater than the corresponding set temperature. The cumulative value of all the first predicted energy-saving degrees is greater than or equal to the control power, that is, all the air conditioners operating in this energy-saving mode can reduce the power consumption to achieve the control power, thereby solving the problem of inconvenience in power consumption caused by cutting off part of the power supply to achieve the control power in the prior art.

[0111] To ensure that the power consumption is reduced to achieve the control power, in an optional solution, the device further comprises:

[0112] The second determining unit is configured to determine whether the set temperature of each air conditioner is within an optimal set temperature range in a case where a first condition or a second condition is met after the current return air temperature and the set temperature of each air conditioner are obtained, the first condition is that all the current return air temperatures are less than or equal to the corresponding set temperature, the second condition is that the cumulative value of all the predicted energy-saving degrees is less than the regulated power consumption, and the optimal set temperature range is a range of set temperatures in which user comfort is optimal.

[0113] The third determining unit is configured to determine the number of air conditioners to be turned off according to the set temperature of each air conditioner in a case where the set temperature of each air conditioner is within the optimal set temperature range, the number of air conditioners to be turned off is a number of air conditioners that are turned off to cause the reduced power consumption to be greater than or equal to the regulated power consumption.

[0114] The second generating unit is configured to generate a second regulation strategy according to the number of air conditioners to be turned off, and the second regulation strategy is used to control the air conditioners to be turned off.

[0115] Specifically, all the current return air temperatures are less than or equal to the corresponding set temperature, so that energy saving cannot be achieved by increasing the target return air temperature, and the cumulative energy-saving degree n1 of this energy-saving mode is less than the regulated power consumption, and the target of reducing power consumption is not achieved, and then it is determined whether the set temperature of each air conditioner is within the optimal set temperature range of 26 to 28 degrees, if all the set temperatures are within the optimal set temperature range, there is no space for energy saving, and the number of air conditioners to be turned off is directly determined to achieve the regulated power consumption by turning off the air conditioners. The set temperature of the air conditioner should not be too high or too low. The temperature of the general air conditioner is preferably recommended to be 26 to 28 degrees. In a refrigeration environment, the ideal set temperature of the air conditioner is 26 degrees, and the power consumption is saved by about 7% to 10% for each increase of 1 degree of the household air conditioner.

[0116] Of course, the air conditioner needs to be turned off to give economic compensation for regulation. The federal learning model is trained to obtain the energy-saving potential of a single air conditioner in the region, i.e., the energy-saving degree n3, corresponding to the feature data in the m time length, the outdoor temperature and humidity are crawled on the network, the return air temperature is the set temperature, the measurement point temperature is the set temperature minus the temperature difference, the running compressor frequency is obtained in the built-in compressor frequency program, and then the number x of air conditioners to be turned off is determined.

[0117] To ensure that the reduced power consumption reaches the regulated power consumption, in an optional solution, the device further comprises:

[0118] the fourth determining unit is configured to, after determining whether the set temperature of each air conditioner is within the optimal set temperature range, determine at least one second predicted energy saving degree number according to the set temperature and a first adjusted set temperature in a case where the third condition and the fourth condition are simultaneously satisfied or the third condition and the fifth condition are simultaneously satisfied, the first adjusted set temperature being a temperature in the optimal set temperature range with a minimum absolute value of a difference from the set temperature, the second predicted energy saving degree number being an amount of power consumption reduced by adjusting a target temperature of a second target air conditioner from the set temperature to the first adjusted set temperature, the first target air conditioner being one or more of the air conditioners, the third condition being that the set temperature of the second target air conditioner is not within the optimal set temperature range, the fourth condition being that a difference between the set temperature of the second target air conditioner and a maximum value of the optimal set temperature range is greater than 0 and less than a predetermined threshold, and the fifth condition being that a difference between a minimum value of the optimal set temperature range of the second target air conditioner and the set temperature is greater than 0 and less than the predetermined threshold;

[0119] the third generating unit is configured to generate a third control strategy in a case where a cumulative value of all the first predicted energy saving degree numbers and all the second predicted energy saving degree numbers is greater than or equal to the control power, the third control strategy being used to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature.

[0120] Specifically, it is determined whether the set temperature is 25 degrees or 29 degrees, and if so, the set temperature is increased by 1 degree or decreased by 1 degree, which has little effect on the user and does not affect the comfort. Specifically, a trained federated learning model is used to obtain the energy saving potential of all air conditioning equipment in the region, i.e., the energy saving degree number n2, under the m time length and corresponding feature data: outdoor temperature and humidity are crawled from the Internet, return air temperature = set temperature, measurement point temperature = set temperature-temperature difference, and running compressor frequency is obtained in the built-in compressor frequency program. It is determined whether the demand response control requirement is met, i.e., whether n1+n2 or n2 is greater than or equal to n, and if so, a third control strategy is generated to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature, so as to ensure that the power consumption is reduced to the control power.

[0121] To ensure that the power consumption is reduced to the control power, in an optional solution, the device further comprises:

[0122] The fifth determining unit is configured to, after determining whether the set temperature of each air conditioner is within the optimal set temperature range, determine at least one third predicted energy saving degree according to the set temperature and a second adjusted set temperature in a case where the third condition and the sixth condition are simultaneously satisfied or the third condition and the seventh condition are simultaneously satisfied, the second adjusted set temperature being a temperature within the optimal set temperature range and having a minimum absolute value of a difference from the set temperature, the third predicted energy saving degree being an amount of power consumption reduced when a target temperature of a third target air conditioner is adjusted from the set temperature to the second adjusted set temperature, the third target air conditioner being one or more of the air conditioners, the third condition being that the set temperature of the third target air conditioner is not within the optimal set temperature range, the sixth condition being that a difference between the set temperature of the third target air conditioner and a maximum value of the optimal set temperature range is greater than or equal to a predetermined threshold value, and the seventh condition being that a difference between a minimum value of the optimal set temperature range of the third target air conditioner and the set temperature is greater than or equal to the predetermined threshold value;

[0123] The fourth generating unit is configured to generate a fourth control strategy in a case where a cumulative value of all the first predicted energy saving degrees and all the third predicted energy saving degrees is greater than or equal to the control power, the fourth control strategy being used to control all the third target air conditioners to adjust the target temperature from the set temperature to the second adjusted set temperature.

[0124] Specifically, the set temperature is far away from the optimal set temperature range, and the set temperature is increased or decreased by n degrees (the set temperature is at most 30 degrees), which has a relatively obvious influence on the user, and economic compensation is given for control. Specifically, a trained federated learning model is used to obtain, in m time periods, corresponding feature data: outdoor temperature and humidity crawled from the Internet, return air temperature = set temperature, measurement point temperature = set temperature - temperature difference, compressor frequency = built-in compressor frequency program, and energy saving potential of all air conditioning equipment in the region, i.e., energy saving degree n2; it is determined whether the demand response control demand is met, i.e., whether n1+n2 or n2 is greater than or equal to n, and if so, a third control strategy is generated to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature, so as to ensure that the amount of power consumption is reduced to reach the control power.

[0125] To ensure that the amount of power consumption is reduced to reach the control power, in an optional solution, the first determining unit includes:

[0126] The first determining sub-module is configured to determine the set temperature as a target measuring point temperature, and calculate a sum of the set temperature and the temperature difference to obtain a target return air temperature, wherein the target measuring point temperature is a temperature at which the user activity area reaches the set temperature, and the target return air temperature is the return air temperature at which the user activity area reaches the set temperature;

[0127] The first analysis sub-module is configured to input the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, the outdoor temperature and humidity, and the compressor frequency of each first target air conditioner into an energy saving model to obtain at least one first predicted energy saving degree, wherein the energy saving model is trained by using a plurality of sets of training data, and each set of training data in the plurality of sets of training data includes the return air temperature, the corresponding target return air temperature, the corresponding measuring point temperature, the corresponding target measuring point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding first predicted energy saving degree at a historical time.

[0128] Specifically, the energy saving is analyzed by using machine learning, a trained federated learning model is used as the energy saving model, the energy saving potential of all air conditioner devices in the region is obtained in m time, that is, the energy saving degree n1, that is, the first predicted energy saving degree, and the corresponding predicted features after m time, that is, the outdoor temperature and humidity, the return air temperature = set temperature + temperature difference, the measuring point temperature = set temperature, and the running compressor frequency are obtained from the built-in compressor frequency program (which is the corresponding compressor frequency when the return air temperature = set temperature in the original program).

[0129] To ensure that the power consumption is reduced to regulate the power, in an optional solution, the fourth determining unit includes:

[0130] The second determining sub-module is configured to calculate a difference between the first adjusted set temperature and the temperature difference to obtain a target measuring point temperature, and determine the first adjusted set temperature as a target return air temperature, wherein the target measuring point temperature is a temperature of the user activity area when the return air temperature reaches the first adjusted set temperature, and the target return air temperature is a temperature at which the return air temperature reaches the first adjusted set temperature.

[0131] The second analysis submodule is configured to input the return air temperature, the measurement point temperature, the target return air temperature, the target measurement point temperature, the outdoor temperature and humidity, and the compressor frequency of each of the second target air conditioner into an energy saving model to obtain at least one second predicted energy saving number, wherein the energy saving model is trained by using a plurality of sets of training data, and each set of training data in the plurality of sets of training data includes the return air temperature, the corresponding target return air temperature, the corresponding measurement point temperature, the corresponding target measurement point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding second predicted energy saving number at a historical time.

[0132] Specifically, the energy saving is analyzed by using machine learning, a trained federated learning model is used as the energy saving model, the trained federated learning model is used to obtain corresponding feature data under m time length, the outdoor temperature and humidity is obtained by web crawling, the return air temperature is equal to the set temperature, the measurement point temperature is equal to the set temperature minus the temperature difference, the running compressor frequency is obtained in the built-in compressor frequency program, and the energy saving potential of all air conditioner devices in the region, i.e., the energy saving number n2, i.e., the second predicted energy saving number, is obtained.

[0133] To ensure that the power consumption is reduced to regulate the power, in an optional solution, the fourth determination unit includes:

[0134] The second determination submodule is configured to calculate the difference between the second adjusted set temperature and the temperature difference to obtain a target measurement point temperature, and determine the second adjusted set temperature as a target return air temperature, wherein the target measurement point temperature is the temperature of the user activity area when the return air temperature reaches the second adjusted set temperature, and the target return air temperature is the temperature when the return air temperature reaches the second adjusted set temperature.

[0135] The third analysis submodule is configured to input the return air temperature, the measurement point temperature, the target return air temperature, the target measurement point temperature, the outdoor temperature and humidity, and the compressor frequency of each of the third target air conditioner into an energy saving model to obtain at least one third predicted energy saving number, wherein the energy saving model is trained by using a plurality of sets of training data, and each set of training data in the plurality of sets of training data includes the return air temperature, the corresponding target return air temperature, the corresponding measurement point temperature, the corresponding target measurement point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding third predicted energy saving number at a historical time.

[0136] Specifically, corresponding feature data under m time length is obtained, the outdoor temperature and humidity is obtained by web crawling, the return air temperature is equal to the set temperature, the measurement point temperature is equal to the set temperature minus the temperature difference, the running compressor frequency is obtained in the built-in compressor frequency program, and the energy saving potential of all air conditioner devices in the region, i.e., the energy saving number n2, i.e., the third predicted energy saving number, is obtained.

[0137] To ensure that the power consumption is reduced to regulate the power, in an optional solution, the device further comprises:

[0138] A control unit is configured to control the operation of the air conditioner until the return air temperature of the air conditioner reaches the set temperature.

[0139] A collection unit is configured to obtain the return air temperature and the measurement point temperature at a predetermined time interval during the operation of the air conditioner, thereby obtaining a plurality of return air temperatures and a plurality of corresponding measurement point temperatures.

[0140] A calculation unit is configured to calculate the average value of the difference between each return air temperature and the corresponding measurement point temperature, thereby obtaining the temperature difference.

[0141] Specifically, the set temperature, operation time, return air temperature, and measurement point temperature of a certain air conditioning device are selected, the difference (temperature difference) between the return air temperature and the measurement point temperature is calculated every n time, and when the return air temperature = set temperature, the timing and calculation are stopped. The average value of the temperature difference in this period is obtained as the return air temperature compensation value; that is, instead of return air temperature = set temperature, the compressor is reduced in frequency to return air temperature - temperature difference = set temperature, and the compressor is reduced in frequency, thereby achieving the effect of energy saving.

[0142] The power regulation device for multiple air conditioners includes a processor and a memory, and the acquisition unit, the first determination unit, and the first generation unit are all stored in the memory as program units. The corresponding functions are realized by the processor executing the program units stored in the memory. The modules are all located in the same processor, or the modules are located in different processors in any combination.

[0143] The processor includes a core, and the core retrieves the corresponding program unit from the memory. The core can be set to one or more, and the problem of inconvenience in use caused by cutting off part of the power supply to reduce the power consumption to regulate the power in the prior art can be solved by adjusting the core parameters.

[0144] The memory can include a non-permanent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory includes at least one memory chip.

[0145] The embodiment of the application provides a computer readable storage medium, and the computer readable storage medium includes a stored program, wherein when the program runs, the device where the computer readable storage medium is located executes the power regulation method for multiple air conditioners.

[0146] Specifically, the power regulation method for multiple air conditioners includes:

[0147] Step S201, obtaining current return air temperature and set temperature of each air conditioner, the return air temperature being current air temperature of a return air outlet of the air conditioner;

[0148] Step S202, in a case where the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, determining at least one first predicted energy-saving degree number according to the set temperature and temperature difference of each first target air conditioner, the first target air conditioner being one or more of the air conditioners, the temperature difference being a difference between the current return air temperature and a measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature being air temperature at any point in a user activity area, the first predicted energy-saving degree number being a difference between a first power consumption and a second power consumption, the first power consumption being power consumption for adjusting the current return air temperature to the set temperature and maintaining the current return air temperature at the set temperature within a predetermined time, the second power consumption being power consumption for adjusting the current return air temperature to an energy-saving temperature and maintaining the current return air temperature at the energy-saving temperature within the predetermined time, the energy-saving temperature being a sum of the set temperature and the temperature difference;

[0149] Step S203, in a case where a cumulative value of all the first predicted energy-saving degree numbers is greater than or equal to a control power, generating a first control strategy, the first control strategy being used to control all the first target air conditioners to adjust the current return air temperature to the energy-saving temperature and maintain the current return air temperature at the energy-saving temperature within the predetermined time, the control power being power consumption required to be reduced by all the air conditioners within the predetermined time. An embodiment of the present application provides a processor, the processor being used to run a program, wherein the program performs the multi-air-conditioner power control method when running.

[0150] Specifically, the multi-air-conditioner power control method comprises:

[0151] Step S201, obtaining current return air temperature and set temperature of each air conditioner, the return air temperature being current air temperature of a return air outlet of the air conditioner;

[0152] Step S202, in the case that the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, at least one first predicted energy saving degree is determined according to the set temperature and the temperature difference of each first target air conditioner, the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature is the air temperature at any point in the user activity area, the first predicted energy saving degree is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption is the power consumption for adjusting the current return air temperature to the energy saving temperature and maintaining the energy saving temperature within the predetermined time, and the energy saving temperature is the sum of the set temperature and the temperature difference.

[0153] Step S203, in the case that the cumulative value of all the first predicted energy saving degrees is greater than or equal to the control power, a first control strategy is generated, the first control strategy is used to control all the first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the energy saving temperature within the predetermined time, and the control power is the power consumption that all the air conditioners need to reduce within the predetermined time. The embodiment of the present application provides a multi-air-conditioner control system, which comprises a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, at least the following steps are implemented:

[0154] Step S201, the current return air temperature and the set temperature of each air conditioner are obtained, and the return air temperature is the current air temperature at the return air outlet of the air conditioner.

[0155] Step S202, in the case that the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, at least one first predicted energy saving degree is determined according to the set temperature and the temperature difference of each first target air conditioner, the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature is the air temperature at any point in the user activity area, the first predicted energy saving degree is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption is the power consumption for adjusting the current return air temperature to the energy saving temperature and maintaining the energy saving temperature within the predetermined time, and the energy saving temperature is the sum of the set temperature and the temperature difference.

[0156] Step S203, in the case that the cumulative value of all the above first predicted energy saving degrees is greater than or equal to the regulation power, a first regulation strategy is generated, the first regulation strategy is used to control all the above first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the power consumption at the energy saving temperature within the predetermined time, and the regulation power is the power consumption that all the above air conditioners need to reduce within the predetermined time. Specifically, the flow ends, the server issues the relevant energy saving instructions to all the air conditioners in the region, that is, the temperature and humidity compensation instructions are issued. The issuance of the temperature and humidity compensation instructions is to perform the compressor frequency reduction processing in advance according to the built-in compressor program; in this way, the requirement of demand response is met, that is, the power consumption is reduced to the regulation power, without affecting the user experience and economic loss.

[0157] The application also provides a computer program product adapted to execute a program that initializes at least the following method steps when executed on a data processing device:

[0158] Step S201, the current return air temperature and the set temperature of each air conditioner are obtained, the return air temperature is the current air temperature of the return air outlet of the air conditioner;

[0159] Step S202, in the case that the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, at least one first predicted energy saving degree is determined according to the set temperature and the temperature difference of each first target air conditioner, the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the air temperature at any point in the user activity area when the current return air temperature reaches the corresponding set temperature, the first predicted energy saving degree is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the power consumption at the set temperature within a predetermined time, and the second power consumption is the power consumption for adjusting the current return air temperature to the energy saving temperature and maintaining the power consumption at the energy saving temperature within the predetermined time, and the energy saving temperature is the sum of the set temperature and the temperature difference;

[0160] Step S203, in the case that the cumulative value of all the above first predicted energy saving degrees is greater than or equal to the regulation power, a first regulation strategy is generated, the first regulation strategy is used to control all the above first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the power consumption at the energy saving temperature within the predetermined time, and the regulation power is the power consumption that all the above air conditioners need to reduce within the predetermined time.

[0161] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0162] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0163] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0164] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0165] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process.Figure 1 one or more processes and / or functions specified in one or more blocks Figure 1 one or more processes and / or functions specified in one or more blocks

[0166] In one typical arrangement, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0167] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory, etc. The memory is an example of computer readable media.

[0168] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0169] It should also be noted that the terms "comprising", "containing", or any other variant thereof, are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices that include a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device that includes the element.

[0170] From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects:

[0171] The technical scheme of the present application, since the return air temperature sensing bag of the air conditioner wall-mounted machine is generally installed at the air return position of the air conditioner, is higher from the ground position, and is also far from the user activity area. Since the air outlet temperature of the air conditioner is low, the cold air sinks, and thus there is a certain deviation between the return air temperature and the temperature of the actual activity position of the user, that is, the return air temperature is higher than the measuring point temperature, which leads to that the temperature control effect cannot be good. The method can stop the temperature reduction when the return air temperature of the air conditioner is reduced to the energy-saving temperature above the set temperature, that is, the measuring point temperature can reach the set temperature. The first predicted energy-saving degree corresponding to each air conditioner is calculated. As long as the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, the first target air conditioner can be controlled to run in such an energy-saving mode. The cumulative value of all the first predicted energy-saving degrees is greater than or equal to the regulated power, so that all the air conditioners running in such an energy-saving mode can reduce the power consumption to reach the regulated power, thereby solving the problem of inconvenience in use caused by cutting off part of the power supply to reduce the power consumption to reach the regulated power in the prior art.

[0172] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for controlling the power consumption of multiple air conditioners, characterized in that, The method comprises: obtaining current return air temperature and set temperature of each air conditioner, wherein the return air temperature is the current air temperature of the return air outlet of the air conditioner; in the case that the current return air temperature of the first target air conditioner is greater than the corresponding set temperature, determining at least one first predicted energy saving degree number according to the set temperature and temperature difference of each first target air conditioner, wherein the first target air conditioner is one or more of the air conditioners, the temperature difference is the difference between the current return air temperature and the measurement point temperature when the current return air temperature reaches the corresponding set temperature, the measurement point temperature is the air temperature at any point in the user activity area, the first predicted energy saving degree number is the difference between the first power consumption and the second power consumption, the first power consumption is the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, and the second power consumption is the power consumption for adjusting the current return air temperature to the energy saving temperature and maintaining the energy saving temperature within the predetermined time, and the energy saving temperature is the sum of the set temperature and the temperature difference; in the case that the cumulative value of all the first predicted energy saving degree numbers is greater than or equal to the regulation power, generating a first regulation strategy, wherein the first regulation strategy is used to control all the first target air conditioners to adjust the current return air temperature to the energy saving temperature and maintain the energy saving temperature within the predetermined time, and the regulation power is the power required to be reduced by the user side within the predetermined time.

2. The method of claim 1, wherein, After obtaining the current return air temperature and the set temperature of each air conditioner, the method further comprises: in the case that the first condition or the second condition is met, determining whether the set temperature of each air conditioner is within an optimal set temperature range, wherein the first condition is that all the current return air temperatures are less than or equal to the corresponding set temperature, the second condition is that the cumulative value of all the predicted energy saving degree numbers is less than the regulation power, and the optimal set temperature range is the range of the set temperature in which the user comfort is optimal; in the case that the set temperature of all the air conditioners is within the optimal set temperature range, determining the number of air conditioners to be turned off according to the set temperature of each air conditioner, wherein the number of air conditioners to be turned off is the number of air conditioners that are turned off to cause the reduced power consumption to be greater than or equal to the regulation power; generating a second regulation strategy according to the number of air conditioners to be turned off, wherein the second regulation strategy is used to control the air conditioners to be turned off.

3. The method of claim 2, wherein, After determining whether the set temperature of each air conditioner is within the optimal set temperature range, the method further comprises: In a case that the third condition and the fourth condition are satisfied simultaneously or the third condition and the fifth condition are satisfied simultaneously, at least one second predicted energy saving degree number is determined according to the set temperature and a first adjusted set temperature, the first adjusted set temperature is a temperature in the optimal set temperature range with a minimum absolute value of a difference from the set temperature, the second predicted energy saving degree number is a power consumption amount of a target temperature of a second target air conditioner being adjusted from the set temperature to the first adjusted set temperature, the first target air conditioner is one or more of the air conditioners, the third condition is that the set temperature of the second target air conditioner is not in the optimal set temperature range, the fourth condition is that a difference between the set temperature of the second target air conditioner and a maximum value of the optimal set temperature range is greater than 0 and less than a predetermined threshold, and the fifth condition is that a difference between a minimum value of the optimal set temperature range of the second target air conditioner and the set temperature is greater than 0 and less than the predetermined threshold; In a case that a cumulative value of all the first predicted energy saving degree numbers and all the second predicted energy saving degree numbers is greater than or equal to the regulation power amount, a third regulation strategy is generated, the third regulation strategy is used to control all the second target air conditioners to adjust the target temperature from the set temperature to the first adjusted set temperature.

4. The method of claim 2, wherein, After determining whether the set temperature of each air conditioner is in the optimal set temperature range, the method further comprises: In a case that the third condition and the sixth condition are satisfied simultaneously or the third condition and the seventh condition are satisfied simultaneously, at least one third predicted energy saving degree number is determined according to the set temperature and a second adjusted set temperature, the second adjusted set temperature is a temperature in the optimal set temperature range with a minimum absolute value of a difference from the set temperature, the third predicted energy saving degree number is a power consumption amount of a target temperature of a third target air conditioner being adjusted from the set temperature to the second adjusted set temperature, the third target air conditioner is one or more of the air conditioners, the third condition is that the set temperature of the third target air conditioner is not in the optimal set temperature range, the sixth condition is that a difference between the set temperature of the third target air conditioner and a maximum value of the optimal set temperature range is greater than or equal to a predetermined threshold, and the seventh condition is that a difference between a minimum value of the optimal set temperature range of the third target air conditioner and the set temperature is greater than or equal to the predetermined threshold; In a case that a cumulative value of all the first predicted energy saving degree numbers and all the third predicted energy saving degree numbers is greater than or equal to the regulation power amount, a fourth regulation strategy is generated, the fourth regulation strategy is used to control all the third target air conditioners to adjust the target temperature from the set temperature to the second adjusted set temperature.

5. The method of claim 1, wherein, According to determining at least one first predicted energy saving degree number from the set temperature and a temperature difference of each first target air conditioner, comprising: determining the set temperature as a target measuring point temperature, and calculating a sum of the set temperature and the temperature difference to obtain a target return air temperature, the target measuring point temperature being a temperature at which the user activity area reaches the set temperature, and the target return air temperature being the return air temperature at which the user activity area reaches the set temperature; inputting the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, outdoor temperature and humidity, and compressor frequency of each first target air conditioner into an energy saving model to obtain at least one first predicted energy saving degree, the energy saving model being trained by using a plurality of sets of training data, each set of training data including the return air temperature, the target return air temperature, the measuring point temperature, the target measuring point temperature, the outdoor temperature and humidity, the compressor frequency, and the first predicted energy saving degree at a historical time.

6. The method of claim 3, wherein, determining at least one second predicted energy saving degree according to the set temperature and a first adjusted set temperature, including: calculating a difference between the first adjusted set temperature and the temperature difference to obtain a target measuring point temperature, and determining the first adjusted set temperature as a target return air temperature, the target measuring point temperature being a temperature of the user activity area when the return air temperature reaches the first adjusted set temperature, and the target return air temperature being a temperature at which the return air temperature reaches the first adjusted set temperature; inputting the return air temperature, the measuring point temperature, the target return air temperature, the target measuring point temperature, outdoor temperature and humidity, and compressor frequency of each second target air conditioner into an energy saving model to obtain at least one second predicted energy saving degree, the energy saving model being trained by using a plurality of sets of training data, each set of training data including the return air temperature, the target return air temperature, the measuring point temperature, the target measuring point temperature, the outdoor temperature and humidity, the compressor frequency, and the second predicted energy saving degree at a historical time.

7. The method of claim 4, wherein, determining at least one third predicted energy saving degree according to the set temperature and a second adjusted set temperature, including: calculating a difference between the second adjusted set temperature and the temperature difference to obtain a target measuring point temperature, and determining the second adjusted set temperature as a target return air temperature, the target measuring point temperature being a temperature of the user activity area when the return air temperature reaches the second adjusted set temperature, and the target return air temperature being a temperature at which the return air temperature reaches the second adjusted set temperature; inputting the return air temperature, the measured point temperature, the target return air temperature, the target measured point temperature, the outdoor temperature and humidity, and the compressor frequency of each third target air conditioner into an energy saving model to obtain at least one third predicted energy saving degree, the energy saving model being trained by using a plurality of sets of training data, each set of training data including the return air temperature, the corresponding target return air temperature, the corresponding measured point temperature, the corresponding target measured point temperature, the corresponding outdoor temperature and humidity, the corresponding compressor frequency, and the corresponding third predicted energy saving degree at a historical time.

8. The method according to any one of claims 1 to 7, characterized in that, Before determining the at least one first predicted energy saving degree according to the set temperature and the temperature difference of each first target air conditioner, the method further comprises: controlling the air conditioner to operate until the return air temperature of the air conditioner reaches the set temperature; during the operation of the air conditioner, obtaining the return air temperature and the measured point temperature once at a predetermined time interval to obtain a plurality of return air temperatures and a plurality of corresponding measured point temperatures; calculating the average of the difference between each return air temperature and the corresponding measured point temperature to obtain the temperature difference.

9. A regulating device for multi-space calling electric, characterized in that, comprise: an obtaining unit, configured to obtain the current return air temperature and the set temperature of each air conditioner, the return air temperature being the current air temperature at the return air outlet of the air conditioner; a first determining unit, configured to, in a case where the current return air temperature of a first target air conditioner is greater than the corresponding set temperature, determine at least one first predicted energy saving degree according to the set temperature and the temperature difference of each first target air conditioner, the first target air conditioner being one or more of the air conditioners, the temperature difference being the difference between the current return air temperature and the measured point temperature when the current return air temperature reaches the corresponding set temperature, the measured point temperature being the air temperature at any point in the user activity area, the first predicted energy saving degree being the difference between a first power consumption and a second power consumption, the first power consumption being the power consumption for adjusting the current return air temperature to the set temperature and maintaining the set temperature within a predetermined time, the second power consumption being the power consumption for adjusting the current return air temperature to an energy saving temperature and maintaining the energy saving temperature within the predetermined time, the energy saving temperature being the sum of the set temperature and the temperature difference; a first generating unit, configured to, in a case where the cumulative value of all the first predicted energy saving degrees is greater than or equal to a regulation power, generate a first regulation strategy, the first regulation strategy being used to control all the first target air conditioners to adjust the current return air temperature to an energy saving temperature and maintain the energy saving temperature within the predetermined time, the regulation power being the total power required to be reduced by the user side within the predetermined time, and the regulation power being the total power required to be reduced by the user side within the predetermined time and sent to the power supply side to instruct the user side.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to execute the method of any one of claims 1 to 8 when the program is running.

11. A multi-air conditioner control system characterized by comprising: comprise: one or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including programs for performing the method of any one of claims 1 to 8.

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