Distributed air conditioning equipment, air conditioning equipment control method, terminal and medium

Abstract

The present application discloses a distributed air-conditioning device, an air-conditioning device control method, a terminal and a medium. The distributed air-conditioning device includes an air-conditioning controller, an air-conditioning host, a power grid state sensing unit, a comfort monitoring unit, a power wireless communication module, a current sensor and a voltage sensor. The air-conditioning controller adaptively adjusts the load power in combination with the power grid state, comfort requirements and air-conditioning working state, prompting the air-conditioning device to be transformed from a traditional single "passive energy consumption" device to an "active control" device. By communicating with the terminal device through the power wireless communication module, the air-conditioning device has both "active control" and "passive control" capabilities. It can not only improve the flexibility of the air-conditioning equipment in participating in the load control scheme, but also significantly reduce the pressure of the power grid to centrally control massive loads.

Description

Technical Field

[0001] The present application relates to the technical field of demand-side response load regulation in power systems, and in particular to a distributed air-conditioning device, an air-conditioning device control method, a terminal and a medium. Background Art

[0002] In recent years, due to the frequent occurrence of extremely high temperatures in summer, air conditioning loads are affected by meteorological factors. In many first-tier and second-tier cities, air conditioning loads have become the main component of the total summer load, accounting for more than 50%. Excessive air conditioning loads have become the main reason for the widening of the peak-to-valley difference of the power grid and the prominence of peak loads, which has seriously reduced the stability of power grid operation and brought huge pressure to ensure the power supply for people's livelihood. Therefore, there is an urgent need for effective and flexible control of air conditioning loads.

[0003] At present, load control of air-conditioning load stock equipment is usually achieved by installing additional equipment such as load control terminals and energy management units. In addition, as a typical energy-consuming load, traditional air-conditioning equipment usually does not have the ability to perceive the operation status of the power grid, that is, it cannot actively monitor the operation status of the power grid and adjust the control strategy of the air-conditioning host. Summary of the invention

[0004] The present application provides a distributed air-conditioning device, an air-conditioning device control method, a terminal and a medium, which have the advantages of having the ability to self-sense the power grid status and control the air-conditioning according to the power grid status, thereby improving its autonomous control capability, optimizing its operating status, and achieving the purpose of energy saving and consumption reduction.

[0005] The technical solution of this application is as follows:

[0006] In one aspect, the present application provides an air conditioning equipment control method, comprising the following steps:

[0007] S1: Obtain the grid status information of the common point where the air-conditioning equipment is connected to the grid;

[0008] Get the current air conditioning load power;

[0009] Get the working status of the air conditioner host at the current moment;

[0010] Get the comfort information of the air conditioning usage scenario at the current moment;

[0011] S2: Establish a fitting function between the sum of air-conditioning load power and comfort level and the grid status information, air-conditioning load power, air-conditioning host working status and comfort level information;

[0012] Establish a fitting function between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information;

[0013] S3: Construct the objective function and its constraints by minimizing the sum of the expected air conditioning load power and comfort level and maximizing the air conditioning energy efficiency ratio;

[0014] S4: Solve the objective function and obtain the air conditioning temperature and humidity control instructions at the current moment.

[0015] Furthermore, the grid status information includes a power supply voltage deviation and a frequency deviation, and obtaining the grid status information of the common point where the air-conditioning equipment is connected to the grid includes the following steps:

[0016] The real-time voltage and current signals of the common point where the air-conditioning equipment is connected to the power grid are obtained, and the power supply voltage deviation and frequency deviation are calculated based on the real-time voltage and current signals.

[0017] Furthermore, obtaining the comfort information of the air conditioning usage scenario at the current moment includes the following steps:

[0018] Obtain real-time temperature and humidity information inside and outside the air-conditioning usage scenario, and calculate the real-time comfort level;

[0019] The real-time comfort level is defined as C t =λ1S T +λ2S h , where S T , S h are the normalized temperature and humidity indicators respectively, and λ1 and λ2 are adjustable coefficients respectively.

[0020] Furthermore, in step S3, the objective function is:

[0021]

[0022] Where V b is the real-time voltage deviation ratio, f b is the real-time frequency deviation ratio, P l is the air conditioning load power, s t is the working status of the air conditioner host at the current moment, C t is the comfort information at the current moment; T, h are the temperature and humidity control instructions to be solved; minP a is the minimum value of the expected air conditioning load power under the temperature and humidity control command; min C a is the minimum comfort requirement under the temperature and humidity control command; maxcop is the maximum value of the air conditioning energy efficiency ratio; functions F1 and F2 are fitting functions, which are obtained by fitting the measured values ​​of the independent variables and dependent variables of the optimization function under experimental conditions;

[0023] The constraints for solving the above multi-objective optimization function include:

[0024] (1) Voltage deviation ratio upper and lower limit constraints:

[0025]

[0026] In the formula, is the lower limit of the voltage deviation ratio, is the upper limit of voltage deviation ratio;

[0027] (2) Frequency deviation ratio upper and lower limit constraints:

[0028]

[0029] In the formula, is the lower limit of the frequency deviation ratio, is the upper limit of frequency deviation ratio;

[0030] (3) Working status constraints:

[0031]

[0032] (4) Comfort level upper and lower limits:

[0033]

[0034] In the formula, is the lower limit of comfort, The upper limit of comfort level;

[0035] (5) Upper and lower limit constraints of temperature control instructions:

[0036] T min ≤T≤T max

[0037] Where, T min is the lower limit of temperature control instruction, T max It is the upper limit of temperature control instruction;

[0038] (6) Humidity control command upper and lower limit constraints:

[0039] h min ≤h≤h max

[0040] In the formula, h min is the lower limit of humidity control instruction, h max It is the upper limit of humidity control instruction.

[0041] In another aspect, the present application provides a distributed air conditioning device with self-sensing power grid status, comprising:

[0042] Air conditioning host;

[0043] Air conditioning controller;

[0044] A power grid status sensing unit, used to obtain power grid status information of the air-conditioning equipment connected to the power grid common point;

[0045] and a comfort detection unit for obtaining comfort information of the air-conditioning usage scenario at the current moment;

[0046] The air conditioning controller is configured with at least one optional control mode, which is an automatic control mode. In this control mode:

[0047] Establish a fitting function between the sum of air-conditioning load power and comfort level and grid status information, air-conditioning load power, air-conditioning host working status and comfort level information;

[0048] Establish a fitting function between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information;

[0049] The objective function and its constraints are constructed by minimizing the sum of the expected air conditioning load power and comfort level and maximizing the air conditioning energy efficiency ratio;

[0050] Solve the objective function, obtain the current air conditioning temperature and humidity control instructions and control the air conditioning host.

[0051] Furthermore, the air conditioning controller is also configured with optional user control mode and load regulation mode;

[0052] In user control mode, the temperature and humidity control commands are sent by the user to the air conditioner controller to control the operation of the air conditioner host;

[0053] In the load control mode, the air conditioner controller receives the load control command input from the outside to control the operation of the air conditioner host. When the air conditioner controller receives the flexible control command, its control method is as follows:

[0054] The air conditioning temperature and humidity control instructions are obtained by solving the multi-objective optimization function:

[0055]

[0056] In the formula, F3 is the characterization of P l 、s t , C t With P a , C a The fitting function of the mathematical mapping relationship.

[0057] Solving the above multi-objective optimization function requires satisfying working state constraints, upper and lower limits of comfort, upper and lower limits of temperature control instructions, and upper and lower limits of humidity control instructions;

[0058] When the air-conditioning controller receives the rigid control instruction, it directly gives a control instruction to shut down the air-conditioning host within the required time range.

[0059] Furthermore, the distributed air-conditioning equipment with self-sensing grid status also includes a current sensor and a voltage sensor, which are used to detect the real-time voltage and current signals of the air-conditioning host connected to the common point of the grid and send them to the grid status sensing unit.

[0060] Furthermore, the distributed air-conditioning equipment with self-sensing grid status also includes a power wireless communication module, which is connected to an external load control terminal or an energy management unit and is used to exchange air-conditioning load control demand information with the air-conditioning controller.

[0061] On the other hand, the present application provides an air conditioning equipment control terminal, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the air conditioning equipment control method as described above is implemented.

[0062] On the other hand, the present application provides a computer-readable medium, wherein the computer-readable medium stores a computer program, and when the computer program is called and executed by a computer, the air-conditioning equipment control method as described above is implemented.

[0063] In summary, the beneficial effects of the present application are as follows: The patent scheme of the present invention adds a grid state sensing unit to the traditional air-conditioning equipment, designs a method for adaptively controlling the air-conditioning equipment according to the changes in the grid state, and promotes the transformation of the air-conditioning equipment from a traditional single "passive energy consumption" device to an "active regulation" device. In addition, considering the actual needs of the existing demand-side response load control, an electric power wireless communication module is designed, so that the air-conditioning equipment has both "active regulation" and "passive regulation" capabilities. This technical solution not only improves the flexibility of air-conditioning equipment in participating in the load control scheme, but also can significantly reduce the pressure of the power grid to centrally control massive loads. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic diagram of the composition of a distributed air conditioning device in a specific embodiment of the present application;

[0065] Figure 2 is a schematic diagram of a control mode of a distributed air conditioning device in a specific embodiment of the present application;

[0066] Figure 3 It is a schematic diagram of the control flow of a distributed air-conditioning device in a specific embodiment of the present application. DETAILED DESCRIPTION

[0067] The specific implementation of the present application is described in detail below with reference to the accompanying drawings.

[0068] Embodiment 1: A method for controlling an air conditioning device, comprising the following steps:

[0069] S1: Obtain the grid status information of the common point where the air-conditioning equipment is connected to the grid;

[0070] Get the current air conditioning load power;

[0071] Get the working status of the air conditioner host at the current moment;

[0072] Get the comfort information of the air conditioning usage scenario at the current moment.

[0073] The grid status information includes the supply voltage deviation and the frequency deviation, and the obtaining of the grid status information of the common point where the air-conditioning equipment is connected to the grid includes the following steps:

[0074] The real-time voltage and current signals of the common point where the air-conditioning equipment is connected to the power grid are obtained, and the power supply voltage deviation and frequency deviation are calculated based on the real-time voltage and current signals.

[0075] Obtaining the comfort information of the air conditioning usage scenario at the current moment includes the following steps:

[0076] Obtain real-time temperature and humidity information inside and outside the air-conditioning usage scenario, and calculate the real-time comfort level;

[0077] The real-time comfort level is defined as C t =λ1S T +λ2S h , where S T , S h are the normalized temperature and humidity indicators respectively, and λ1 and λ2 are adjustable coefficients respectively.

[0078] S2: Establish a fitting function between the sum of air-conditioning load power and comfort level and the grid status information, air-conditioning load power, air-conditioning host working status and comfort level information;

[0079] A fitting function is established between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information.

[0080] S3: Construct the objective function and its constraints by minimizing the sum of the expected air conditioning load power and comfort level and maximizing the air conditioning energy efficiency ratio.

[0081] The objective function is:

[0082]

[0083] Where V b is the real-time voltage deviation ratio, f b is the real-time frequency deviation ratio, P l is the air conditioning load power, s t is the working status of the air conditioner host at the current moment, C tis the comfort information at the current moment; T, h are the temperature and humidity control instructions to be solved; minP a is the minimum value of the expected air conditioning load power under the temperature and humidity control command; min C a is the minimum comfort requirement under the temperature and humidity control command; maxcop is the maximum value of the air conditioning energy efficiency ratio; functions F1 and F2 are fitting functions, which are obtained by fitting the measured values ​​of the independent variables and dependent variables of the optimization function under experimental conditions;

[0084] The constraints for solving the above multi-objective optimization function include:

[0085] (1) Voltage deviation ratio upper and lower limit constraints:

[0086]

[0087] In the formula, is the lower limit of the voltage deviation ratio, is the upper limit of voltage deviation ratio;

[0088] (2) Frequency deviation ratio upper and lower limit constraints:

[0089]

[0090] In the formula, is the lower limit of the frequency deviation ratio, is the upper limit of frequency deviation ratio;

[0091] (3) Working status constraints:

[0092]

[0093] (4) Comfort level upper and lower limits:

[0094]

[0095] In the formula, is the lower limit of comfort, The upper limit of comfort level;

[0096] (5) Upper and lower limit constraints of temperature control instructions:

[0097] T min ≤T≤T max

[0098] Where, T min is the lower limit of temperature control instruction, T max It is the upper limit of temperature control instruction;

[0099] (6) Humidity control command upper and lower limit constraints:

[0100] h min ≤h≤hmax

[0101] In the formula, h min is the lower limit of humidity control instruction, h max It is the upper limit of humidity control instruction.

[0102] S4: Solve the objective function, obtain the air conditioning temperature and humidity control instructions at the current moment and use them to control the air conditioning.

[0103] Embodiment 2: A distributed air conditioning device with self-sensing power grid status, such as Figure 1 As shown, it includes an air-conditioning controller, an air-conditioning host, a power grid status sensing unit, a comfort monitoring unit, a power wireless communication module, a current sensor, and a voltage sensor.

[0104] The current sensor and the voltage sensor are used to detect the real-time voltage and current signals of the air conditioner host connected to the common point of the power grid and send them to the power grid state sensing unit. The power grid state sensing unit is used to obtain the power grid state information of the air conditioner connected to the common point of the power grid.

[0105] The grid state information includes power supply voltage deviation and frequency deviation, which are calculated based on real-time voltage and current signals.

[0106] The comfort detection unit is used to obtain the comfort information of the air-conditioning use scene at the current moment; obtaining the comfort information of the air-conditioning use scene at the current moment includes the following steps: obtaining the real-time temperature and humidity information inside and outside the air-conditioning use scene, calculating the real-time comfort

[0107] The wireless communication module is connected to an external load control terminal or an energy management unit, and is used to exchange air conditioning load control demand information with the air conditioning controller. The power wireless communication module refers to a module adapted to the power wireless communication interface and protocol, and the power wireless communication module exchanges information with professional equipment such as the load control terminal or the energy management unit. Considering that the load control terminal or the energy management unit adopts a wireless virtual private network, the communication interface of the power wireless communication module should support at least LoRa and ZigBee, and the communication protocol should support DL / T 634.5104, MQTT, DL / T 634.5 101 and DL / T698.45 protocols, etc.

[0108] like Figure 2 As shown, the air conditioning controller is configured with three optional control modes, namely user control mode, automatic control mode and load regulation mode, and the distributed air conditioning equipment operates in the above three modes.

[0109] When the distributed air-conditioning equipment works in user control mode, the temperature and humidity control commands are sent by the user to the air-conditioning controller to control the operation of the air-conditioning host. At this time, the air-conditioning operation control does not require the participation of grid status information and air-conditioning load regulation demand information.

[0110] When the distributed air-conditioning equipment works in automatic control mode, the air-conditioning controller sends control instructions to the air-conditioning host based on the grid status, comfort level, air-conditioning load power and air-conditioning host working status information, thereby controlling the operation of the air-conditioning host. At this time, the air-conditioning operation control does not require the participation of air-conditioning load regulation information, and the air-conditioning controller receives the temperature and humidity control commands sent by the user. When the grid supply voltage is low or the grid supply voltage frequency is low, the distributed air-conditioning equipment should automatically reduce part of the load capacity, but should meet the local minimum comfort requirements; when the grid supply voltage deviation or frequency deviation does not meet the power supply requirements, the distributed air-conditioning equipment should automatically shut down. The specific reduction capacity is automatically calculated by the pre-configured intelligent algorithm.

[0111] In the automatic control mode, a fitting function is established between the sum of the air conditioning load power and comfort and the grid status information, air conditioning load power, air conditioning host working status and comfort information; a fitting function is established between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information; the objective function and its constraints are constructed by minimizing the expected sum of the air conditioning load power and comfort and maximizing the air conditioning energy efficiency ratio; the objective function is

[0112]

[0113] Where V b is the real-time voltage deviation ratio calculated by the grid state sensing unit, f b is the real-time frequency deviation ratio calculated by the grid state sensing unit, P l is the air conditioning load power, s t is the working status of the air conditioner host at the current moment, C t is the comfort information at the current moment. T,h are the temperature and humidity control instructions to be solved. min P a It is the minimum value of the expected air conditioning load power under the temperature and humidity control command. minC a is the minimum comfort requirement under the temperature and humidity control command. maxcop is the maximum value of the air conditioning energy efficiency ratio. Functions F1 and F2 are fitting functions, which can be obtained by fitting the measured values ​​of the independent variables and dependent variables of the optimization function under experimental conditions.

[0114] The constraints for solving the above multi-objective optimization function include upper and lower limit constraints on voltage deviation ratio, upper and lower limit constraints on frequency deviation ratio, working state constraints, upper and lower limit constraints on comfort, upper and lower limit constraints on temperature control instructions, and upper and lower limit constraints on humidity control instructions. It should be noted that the values ​​of the set constraint range should take into account the power grid specifications, the actual working state of the air conditioner, and the environmental requirements of the energy consumption scenario, so as to make a reasonable selection.

[0115] Solve the objective function, obtain the current air conditioning temperature and humidity control instructions and control the air conditioning host.

[0116] When the distributed air-conditioning equipment works in load control mode, the air-conditioning controller receives the load control command through the power wireless communication module to control the operation of the air-conditioning host. At this time, the air-conditioning operation control does not require the participation of the grid status information. Load control commands are divided into flexible control commands and rigid control commands. Among them, flexible control commands allow distributed air-conditioning equipment to formulate control strategies based on the current working status of the air-conditioning and the comfort requirements on site; rigid control commands mainly refer to forced shutdown commands and shutdown time ranges.

[0117] When the air conditioning controller receives the flexible control command, its control method is:

[0118] The air conditioning temperature and humidity control instructions are obtained by solving the multi-objective optimization function:

[0119]

[0120] In the formula, F3 is the characterization of P l 、s t , C t With P a , C a The fitting function of the mathematical mapping relationship.

[0121] Solving the above multi-objective optimization function requires satisfying working state constraints, upper and lower limit constraints of comfort, upper and lower limit constraints of temperature control instructions, and upper and lower limit constraints of humidity control instructions.

[0122] When the air-conditioning controller receives the rigid control instruction, it directly gives a control instruction to shut down the air-conditioning host within the required time range.

[0123] As an example, in a specific embodiment, the priority of user control is ranked first by default, the automatic control is ranked second, and the priority of the load control mode is ranked third. The control process of the distributed air conditioning equipment is as follows: Figure 3 It is worth noting that the priority can be optimized and adjusted according to site needs.

[0124] The distributed air conditioning equipment and the control method thereof are applicable to single small-capacity air conditioners, multi-split air conditioning systems and central air conditioning systems.

[0125] Embodiment 3: An air conditioning equipment control terminal comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the air conditioning equipment control method as described in Embodiment 1 is implemented.

[0126] Embodiment 4: A computer-readable medium stores a computer program, and when the computer program is called and executed by a computer, the air conditioning equipment control method as described in Embodiment 1 is implemented.

[0127] The above is only a preferred implementation of the present application. It should be pointed out that a person skilled in the art can make several modifications and improvements without departing from the inventive concept of the present application, and these all fall within the scope of protection of the present application.

Claims

1. A method for controlling an air conditioning device, characterized in that: The following steps are involved: S1: Obtain the grid status information of the common point where the air-conditioning equipment is connected to the grid; Get the current air conditioning load power; Get the working status of the air conditioner host at the current moment; Get the comfort information of the air conditioning usage scenario at the current moment; S2: Establish a fitting function between the sum of air-conditioning load power and comfort level and the grid status information, air-conditioning load power, air-conditioning host working status and comfort level information; Establish a fitting function between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information; S3: Construct the objective function and its constraints by minimizing the sum of the expected air conditioning load power and comfort level and maximizing the air conditioning energy efficiency ratio; S4: Solve the objective function to obtain the air conditioning temperature and humidity control instructions at the current moment; The grid status information includes the supply voltage deviation and the frequency deviation, and the obtaining of the grid status information of the common point where the air-conditioning equipment is connected to the grid includes the following steps: Obtain the real-time voltage and current signals of the public point where the air-conditioning equipment is connected to the power grid, and calculate the power supply voltage deviation and frequency deviation based on the real-time voltage and current signals; Obtaining the comfort information of the air conditioning usage scenario at the current moment includes the following steps: Obtain real-time temperature and humidity information in air-conditioning usage scenarios and calculate real-time comfort; The real-time comfort level is defined as C t =λ1S T +λ2S h , where S T , S h are normalized temperature and humidity indicators, respectively, λ1 and λ2 are adjustable coefficients; In step S3, the objective function is: Where V b is the real-time voltage deviation ratio, f b is the real-time frequency deviation ratio, P l is the air conditioning load power, s t is the working status of the air conditioner host at the current moment, C t is the comfort information at the current moment; T, h are the temperature and humidity control instructions to be solved; minP a is the minimum value of the expected air conditioning load power under the temperature and humidity control command; min C a is the minimum comfort requirement under the temperature and humidity control command; maxcop is the maximum value of the air conditioning energy efficiency ratio; functions F1 and F2 are fitting functions, which are obtained by fitting the measured values ​​of the independent variables and dependent variables of the optimization function under experimental conditions; The constraints for solving the above objective function include: (1) Voltage deviation ratio upper and lower limit constraints: In the formula, is the lower limit of the voltage deviation ratio, is the upper limit of voltage deviation ratio; (2) Frequency deviation ratio upper and lower limit constraints: In the formula, is the lower limit of the frequency deviation ratio, is the upper limit of frequency deviation ratio; (3) Working status constraints: (4) Comfort level upper and lower limits: In the formula, is the lower limit of comfort, The upper limit of comfort level; (5) Upper and lower limit constraints of temperature control instructions: T min ≤T≤T max Where, T min is the lower limit of temperature control instruction, T max It is the upper limit of temperature control instruction; (6) Humidity control command upper and lower limit constraints: h min ≤h≤h max In the formula, h min is the lower limit of humidity control instruction, h max It is the upper limit of humidity control instruction.

2. A distributed air conditioning device with self-sensing power grid status using the air conditioning device control method according to claim 1, characterized in that: include: Air conditioning host; Air conditioning controller; A power grid status sensing unit, used to obtain power grid status information of the air-conditioning equipment connected to the power grid common point; and a comfort detection unit for obtaining comfort information of the air-conditioning usage scenario at the current moment; The air conditioning controller is configured with at least one optional control mode, which is an automatic control mode. In this control mode: Establish a fitting function between the sum of air-conditioning load power and comfort level and grid status information, air-conditioning load power, air-conditioning host working status and comfort level information; Establish a fitting function between the air conditioning energy efficiency ratio and the air conditioning temperature and humidity control instructions, air conditioning load power, air conditioning host working status and comfort information; The objective function and its constraints are constructed by minimizing the sum of the expected air conditioning load power and comfort level and maximizing the air conditioning energy efficiency ratio; Solve the objective function, obtain the current air conditioning temperature and humidity control instructions and control the air conditioning host.

3. The distributed air conditioning device with self-sensing power grid status according to claim 2 is characterized in that: The air conditioning controller is also configured with optional user control mode and load regulation mode; In user control mode, the temperature and humidity control commands are sent by the user to the air conditioner controller to control the operation of the air conditioner host; In the load control mode, the air conditioner controller receives the load control command input from the outside to control the operation of the air conditioner host; when the air conditioner controller receives the flexible control command, its control method is as follows: The air conditioning temperature and humidity control instructions are obtained by solving the following multi-objective optimization function: In the formula, F3 is the characterization of P l 、s t , C t With P a , C a Fitting function of mathematical mapping relationship; Solving the above multi-objective optimization function requires satisfying working state constraints, upper and lower limits of comfort, upper and lower limits of temperature control instructions, and upper and lower limits of humidity control instructions; When the air-conditioning controller receives the rigid control instruction, it directly gives a control instruction to shut down the air-conditioning host within the required time range.

4. The distributed air conditioning device with self-sensing power grid status according to claim 2, characterized in that: The distributed air-conditioning equipment with self-sensing grid status also includes a current sensor and a voltage sensor, which are used to detect the real-time voltage and current signals of the air-conditioning host connected to the common point of the grid and send them to the grid status sensing unit.

5. The distributed air conditioning device with self-sensing power grid status according to claim 2, characterized in that: The distributed air-conditioning device with self-sensing grid status also includes a power wireless communication module, which is connected to an external load control terminal or an energy management unit and is used to exchange air-conditioning load control demand information with the air-conditioning controller.

6. An air conditioning equipment control terminal, characterized in that: The system comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the air conditioning equipment control method as claimed in claim 1 is implemented.

7. A computer-readable medium, characterized in that The computer-readable medium stores a computer program, and when the computer program is called and executed by a computer, the air conditioning equipment control method according to claim 1 is implemented.

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