A joint control method and system for multiple photovoltaic direct-driven air source heat pump units

Abstract

The present application relates to the field of air source heat pump control technology, and in particular to a method and system for joint control of multiple photovoltaic direct-drive air source heat pump units. The method comprises: calculating the heating accuracy of the affected area of each air source heat pump unit in this joint control; solving the target control parameters of each air source heat pump unit with the minimum value of the objective function as the optimization goal under energy constraints; adjusting the heating accuracy of each affected area based on the temperature difference curve between the inlet water temperature and the return water temperature between the start time of this joint control and the start time of the next joint control, for use in the next joint control. Through the technical solution of the present application, the control parameters of each air source heat pump unit can be obtained, and the joint control of multiple air source heat pump units can be accurately achieved.

Description

Technical Field

[0001] The present application relates to the technical field of air source heat pump control, and in particular to a joint control method and system for multiple photovoltaic direct-driven air source heat pump units. Background Art

[0002] Air-source heat pumps are powered by electricity, using low-grade heat from outdoor air. This small amount of electricity drives the compressor, producing hot water. This hot water is then circulated through the indoor heating system, exchanging heat with the indoor air to achieve the desired heating effect. Compared to traditional hot water production methods—electric heating, gas heating, and coal heating—air-source heat pumps offer significant economic and environmental advantages.

[0003] At present, the patent application document with application publication number CN119150438A discloses an operation scheduling method and device for air source heat pump units in a scenic area building complex, wherein the method includes: obtaining air source heat pump unit information of the target scenic area, information of the building complex and environmental information of the target scenic area; wherein the target scenic area is equipped with a photovoltaic power generation system; the environmental information includes solar radiation intensity; the information of the building complex includes structural information and energy consumption information; according to the solar radiation intensity and a predetermined photoelectric conversion coefficient, generating output power information of the photovoltaic power generation system; based on the air source heat pump unit information of the target scenic area, information of the building complex, environmental information of the target scenic area and the output power information, using a target energy center model, a target operation scheduling model and a target thermodynamic model to calculate the target operating status parameters of each device; and scheduling each of the devices to operate with the target operating status parameters, so that the power demand put forward by the target scenic area to the distribution network is minimized while suppressing the cold island effect between the devices.

[0004] The above method takes the minimum electricity demand submitted by the target scenic area to the distribution network as the optimization goal, and obtains the target operating state parameters of all air source heat pump units in the target scenic area. However, different air source heat pump units in the target scenic area correspond to different indoor areas of scenic area buildings, and the heating requirements of different indoor areas of scenic area buildings are different. The above method ignores the differences in heating requirements between the indoor areas of different scenic area buildings, resulting in inaccurate joint control of multiple air source heat pump units under limited electricity conditions. Summary of the Invention

[0005] In order to solve the technical problem of inaccurate joint control of multiple air source heat pump units, the present application provides a joint control method and system for multiple photovoltaic direct-driven air source heat pump units, which can obtain the control parameters of each air source heat pump unit and accurately realize the joint control of multiple air source heat pump units.

[0006] In a first aspect, the present application provides a joint control method for multiple photovoltaic direct-drive air source heat pump units, the control method comprising: calculating the heating accuracy of the influence area of each air source heat pump unit in this joint control, the heating accuracy being positively correlated with the frequency of personnel activities; solving the target control parameters of each air source heat pump unit with the minimum objective function value as the optimization goal under energy constraints; adjusting the heating accuracy of each influence area according to the volatility of the temperature difference curve of the inlet water temperature and the return water temperature between the start time of this joint control and the start time of the next joint control for the next joint control; the objective function value is the sum of the first target value and the second target value; obtaining the first deviation of the predicted temperature and the target temperature under the control parameters of any air source heat pump unit, weightedly summing the first deviations of each influence area according to the normalized heating accuracy, and obtaining the first target value; calculating the second deviation of the predicted temperature between any two influence areas, weightedly summing the second deviations according to the adjacency coefficient of any two influence areas, and obtaining the second target value; the energy constraint is that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power of photovoltaic power generation.

[0007] During each joint control, the heating accuracy of each affected area during this joint control is determined according to the frequency of personnel activities in each affected area and the volatility of the temperature difference curve during the previous joint control. Priority should be given to ensuring the heating effect of the affected area with greater heating accuracy; under the premise that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power of photovoltaic power generation, the objective function value is calculated. The objective function value includes two parts: the first target value and the second target value. The first target value ensures the heating effect of each affected area, and the greater the heating accuracy, the greater the impact of the heating effect of the corresponding affected area on the first target value; the second target value ensures that the heating temperature areas between the affected areas with personnel flow are consistent, avoiding the situation of fluctuating temperatures when personnel flow, and ensuring the user experience in the heating area; with the minimum objective function value as the optimization goal, the target control parameters of each air source heat pump unit are obtained, and the joint control of multiple air source heat pump units is accurately realized.

[0008] Preferably, the air source heat pump unit in this joint control Heating accuracy in affected areas for: ; Air source heat pump unit Number of people in the affected area; For this joint control moment, The moment of last joint control, is the time interval between this joint control and the previous joint control; For the moment Air source heat pump unit Number of people in the affected area, is the number of people threshold, For time interval Internal air source heat pump unit The total duration that the number of people in the affected area exceeds the threshold.

[0009] The heating accuracy of the affected areas is accurately quantified based on the frequency of human activities in each affected area, providing a data basis for this joint control. When electricity is limited, it can give priority to ensuring that the affected areas with greater heating accuracy can achieve better heating effects.

[0010] Preferably, the predicted temperature is obtained by a prediction model, the predicted temperature input is the outdoor temperature, the initial indoor temperature and the control parameters of the air source heat pump unit, and the output is the predicted temperature.

[0011] Preferably, the method for constructing the prediction model includes: taking the outdoor temperature, initial indoor temperature and control parameters of the air source heat pump unit in the historical heating process as training samples, and taking the indoor temperature that reaches a stable state in the historical heating process as a temperature label; inputting the training samples into the prediction model to obtain the output result, and updating the prediction model based on the output result and the mean square error loss of the temperature label until the mean square error loss is less than the loss threshold or the number of updates reaches a preset number, thereby completing the construction of the prediction model.

[0012] The prediction model is trained using the mean square error loss of the output results and temperature labels to ensure that the prediction model can output accurate predicted temperatures.

[0013] Preferably, in response to the absence of personnel flow between any two impact areas, the adjacency coefficient is 0, otherwise, the adjacency coefficient is 1.

[0014] If there is no flow of people between the two impact areas, it means that there is no need to constrain the predicted temperatures between the two impact areas to remain consistent. The adjacency coefficient of the two impact areas is directly set to 0, so that the second target value can accurately reflect the difference in predicted temperatures between the impact areas with the flow of people.

[0015] Preferably, the solution of the target control parameters of each air source heat pump unit includes: continuously updating the control parameters of each air source heat pump unit within the allowable value range of the control parameters, and using an optimization algorithm to obtain the control parameters of each air source heat pump unit when the objective function value takes the minimum value, as the target control parameters of the corresponding air source heat pump unit.

[0016] Preferably, the adjustment of the heating accuracy of each affected area includes: taking the variance of the temperature difference curve in each affected area as volatility; taking the product of the normalized volatility of any affected area and the heating accuracy of the affected area in this joint control as the heating accuracy of the affected area in the next joint control.

[0017] If there is a large fluctuation in the temperature difference curve, it means that there is frequent heat exchange between the affected area and the heat exchange medium. At this time, the temperature fluctuation in the affected area is large and the heating effect is poor. Therefore, the volatility of the temperature difference curve can reflect the heating effect. According to the volatility of the temperature difference curve, the heating accuracy of each affected area in the next joint control is adjusted, so that the heating accuracy of the affected area with poor heating effect in the next joint control is improved, ensuring that each affected area can achieve a good heating effect.

[0018] Preferably, the method for obtaining the starting time of the next joint control includes: monitoring the power change of the real-time power of photovoltaic power generation, and recording the moment when the power change is greater than the change threshold as the first moment; taking the starting time of this joint control as the starting point, recording the moment after the preset control cycle as the second moment; and taking the earliest moment between the first moment and the second moment as the starting time of the next joint control.

[0019] When the real-time power of photovoltaic power generation changes, it means that the energy constraint has changed. At this time, it is necessary to solve the target control parameters of each air source heat pump unit again; if the real-time power of photovoltaic power generation has not changed within the preset control period, in order to ensure that each affected area can achieve a good heating effect, it is still necessary to solve the target control parameters of each air source heat pump unit again to realize the precise control of multiple air source heat pump units.

[0020] Preferably, the control parameters include compressor frequency, water pump frequency and water outlet temperature.

[0021] In the second aspect of the present application, a joint control system for multiple photovoltaic direct-driven air source heat pump units is provided, comprising a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, a joint control method for multiple photovoltaic direct-driven air source heat pump units according to the first aspect of the present application is implemented.

[0022] The technical solution of this application has the following beneficial technical effects:

[0023] During each joint control, the heating accuracy of each affected area during this joint control is determined according to the frequency of personnel activities in each affected area and the volatility of the temperature difference curve during the previous joint control. Priority should be given to ensuring the heating effect of the affected area with greater heating accuracy; under the premise that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power of photovoltaic power generation, the objective function value is calculated. The objective function value includes two parts: the first target value and the second target value. The first target value ensures the heating effect of each affected area, and the greater the heating accuracy, the greater the impact of the heating effect of the corresponding affected area on the first target value; the second target value ensures that the heating temperature areas between the affected areas with personnel flow are consistent, avoiding the situation of fluctuating temperatures when personnel flow, and ensuring the user experience in the heating area; with the minimum objective function value as the optimization goal, the target control parameters of each air source heat pump unit are obtained, and the joint control of multiple air source heat pump units is accurately realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of a joint control method for multiple photovoltaic direct-driven air source heat pump units according to an embodiment of the present application.

[0025] Figure 2 This is a structural block diagram of a joint control system for multiple photovoltaic direct-driven air source heat pump units according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0027] According to the first aspect of the present application, the present application provides a joint control method for multiple photovoltaic direct-driven air source heat pump units. Figure 1 This is a flow chart of a joint control method for multiple photovoltaic direct-driven air source heat pump units according to an embodiment of the present application. Figure 1 As shown, the joint control method of the photovoltaic direct-driven air source heat pump multi-unit includes steps S101 to S103, which are described in detail below.

[0028] S101, calculating the heating accuracy of the area affected by each air source heat pump unit in this joint control, where the heating accuracy is positively correlated with the frequency of human activities.

[0029] In one embodiment, multiple air source heat pump units are deployed in the heating area, one air source heat pump unit corresponds to one influence area, and the union of all influence areas can cover the entire heating area. The multiple air source heat pump units are photovoltaic direct drive, that is, the electric energy consumed by the multiple air source heat pump units is provided by the photovoltaic power generation system.

[0030] Exemplarily, the heating area is a smart building, and the affected area may be one or more rooms in the smart building, that is, one air source heat pump unit can affect one or more rooms; the photovoltaic power generation system provides electricity for all air source heat pump units.

[0031] When people are active in the heating area, the frequency of their activities in different affected areas is different. The purpose of the air source heat pump multi-unit heating the heating area is to enable people to move within a comfortable temperature range. Therefore, in the process of this joint control, heating accuracy is allocated to each affected area according to the frequency of people's activities in each affected area. If the frequency of people's activities in an affected area is low, it means that the affected area is an area with less people's activities, and a smaller heating accuracy should be allocated to the affected area. That is, when electricity is limited, a larger deviation in the heating effect of the affected area can be allowed.

[0032] Specifically, the number of people entering and leaving each room is counted by the infrared sensors deployed at the door of each room, and the number of people in the room at any time can be determined; the air source heat pump unit in this joint control Heating accuracy of the affected area for: ; Air source heat pump unit Number of people in the affected area; For the moment of this joint control, The moment of last joint control, is the time interval between this joint control and the previous joint control; For the moment Air source heat pump unit Number of people in the affected area, is the number of people threshold, For time interval Internal air source heat pump unit The total duration that the number of people in the affected area exceeds the threshold.

[0033] The number of people threshold is 0, and the time interval is The proportion of time when the number of people in the affected area is greater than 0 can reflect the frequency of personnel activities in the affected area, and the frequency of personnel activities can be directly used as the frequency of air source heat pump unit Affects the heating accuracy of the area.

[0034] It should be noted that an image processing-based method can also be used to determine the number of people in the room at any time, and the image information in the room is input into the target detection network to identify the number of people in the room. This will not be elaborated here.

[0035] In this way, the heating accuracy of the affected areas can be accurately quantified according to the frequency of human activities in each affected area, providing a data basis for this joint control. When electricity is limited, it can give priority to ensuring that the affected areas with greater heating accuracy can achieve better heating effects.

[0036] S102, under energy constraints, with the minimum objective function value as the optimization goal, solve the target control parameters of each air source heat pump unit.

[0037] In one embodiment, photovoltaic power generation is greatly affected by environmental factors such as solar radiation and light blocking, resulting in a constant change in the real-time power of photovoltaic power generation, which in turn results in different amounts of electricity available to each air source heat pump unit at different times.

[0038] The objective function value is the sum of the first target value and the second target value; the first deviation of the predicted temperature and the target temperature under the control parameters of any air source heat pump unit is obtained, and the first deviation of each influence area is weighted and summed according to the normalized heating accuracy to obtain the first target value; the second deviation of the predicted temperature between any two influence areas is calculated, and the second target value is obtained by weighted summation of each second deviation according to the adjacency coefficient of any two influence areas; the energy constraint is that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power of photovoltaic power generation.

[0039] Wherein, the predicted temperature is obtained by a prediction model, and the predicted temperature input is the outdoor temperature, the initial indoor temperature and the control parameters of the air source heat pump unit, and the output is the predicted temperature, and the control parameters include the compressor frequency, the water pump frequency and the outlet water temperature. The predicted temperature can be a neural network or a polynomial regression model. The method for constructing the prediction model includes: using the outdoor temperature, the initial indoor temperature and the control parameters of the air source heat pump unit in the historical heating process as training samples, and using the indoor temperature that reaches a stable state in the historical heating process as a temperature label; inputting the training sample into the prediction model to obtain the output result, and updating the prediction model based on the mean square error loss of the output result and the temperature label until the mean square error loss is less than the loss threshold or the number of updates reaches the preset number, and the construction of the prediction model is completed. Wherein, the loss threshold is 0.01; the preset number of times is 100.

[0040] In response to the absence of personnel flow between any two impact areas, the adjacency coefficient is 0, otherwise, the adjacency coefficient is 1. It should be noted that the adjacency coefficient between any two impact areas can be set manually. If there is no personnel flow between any two impact areas, the adjacency coefficient between the two impact areas is directly set to 0.

[0041] Specifically, the objective function value Satisfies the relationship:

[0042] ; is the number of air source heat pump units, Air source heat pump unit Affects the heating accuracy of the area, is the sum of the heating accuracy of each affected area, and Air source heat pump units and air source heat pump units The predicted temperature of the affected area, Air source heat pump unit target temperature of the affected area, Air source heat pump unit and air source heat pump units The adjacency coefficient of the affected area, where the value of the adjacency coefficient is 0 or 1; is the adjustment coefficient, where the value of the adjustment coefficient is 0.5.

[0043] Understandably, It is used to constrain the predicted temperature of each affected area to be equal to the target temperature. When the value approaches 0, it means that the heating effect of each affected area has reached the best. The predicted temperature is the temperature in the affected area after the air source heat pump unit is operated under the control parameters. It is used to constrain the predicted temperatures between affected areas where there is personnel flow to be consistent. The predicted temperature is the heating temperature after heating. This avoids excessive differences in heating temperatures between affected areas when personnel flow between different affected areas, resulting in people experiencing alternating hot and cold temperatures, and improves the user experience within the heating area.

[0044] The energy constraint is: ;in, is the number of air source heat pump units, Air source heat pump unit The real-time energy consumption of the air source heat pump unit The control parameters are related to is the real-time power of photovoltaic power generation.

[0045] It should be noted that in other embodiments, one air source heat pump unit corresponds to one photovoltaic panel, and the energy constraint at this time is: The real-time energy consumption is less than or equal to the air source heat pump unit Corresponding to the real-time power of photovoltaic power generation by photovoltaic panels.

[0046] Understandably, determining the air source heat pump unit After the control parameters are obtained, the air source heat pump unit can be obtained according to the mapping relationship between the control parameters and the actual operating power. The actual operating power under the control parameters corresponds to the actual operating power of the air source heat pump unit. Real-time energy consumption.

[0047] In one embodiment, the solution of the target control parameters of each air source heat pump unit includes: continuously updating the control parameters of each air source heat pump unit within the allowable value range of the control parameters, and using an optimization algorithm to obtain the control parameters of each air source heat pump unit when the objective function value takes the minimum value as the target control parameters of the corresponding air source heat pump unit.

[0048] Wherein, the optimization algorithm is a gradient descent method, a genetic algorithm or a hill climbing algorithm.

[0049] In this way, the optimization goal is to achieve the best heating effect in each affected area and keep the heating temperature basically consistent between the affected areas with personnel flow. Under the premise of meeting the energy constraints, the target control parameters of each air source heat pump unit are determined, and each air source heat pump unit is controlled according to the target control parameters.

[0050] S103, adjusting the heating accuracy of each affected area according to the fluctuation of the temperature difference curve between the inlet water temperature and the return water temperature between the start time of this combined control and the start time of the next combined control, for the next combined control.

[0051] In one embodiment, after controlling each air source heat pump unit according to the target control parameters, the temperature difference curve between the inlet water temperature and the return water temperature of each affected area is monitored. The inlet water temperature is the temperature of the heat exchange medium before it is sent into the heating system for circulation; the return water temperature is the temperature of the heat exchange medium after it circulates in the heating system within the affected area; the temperature difference between the inlet water temperature and the return water temperature can reflect the heat exchange between the heat exchange medium and the affected area, and thus characterize the heat load changes in each affected area.

[0052] For any affected area, if the temperature difference curve tends to be flat, it means that the heat exchange between the affected area and the heat exchange medium has reached a state of equilibrium. At this time, the temperature in the affected area is close to the target temperature, and the heating effect is good. If the temperature difference curve has large fluctuations, it means that there is frequent heat exchange between the affected area and the heat exchange medium. At this time, the temperature in the affected area fluctuates greatly, and the heating effect is poor. Therefore, the volatility of the temperature difference curve can reflect the heating effect. In the next joint control, the heating accuracy of each affected area is adjusted based on the volatility of the temperature difference curve between this joint control and the next joint control. In this way, in the next joint control, the heating accuracy of the affected area with poor heating effect is improved, that is, the heating accuracy of the affected area with large temperature difference curve fluctuations is improved, ensuring that each affected area can achieve a good heating effect.

[0053] Specifically, the adjustment of the heating accuracy of each affected area includes: taking the variance of the temperature difference curve in each affected area as volatility; taking the product of the normalized volatility of any affected area and the heating accuracy of the affected area in this joint control as the heating accuracy of the affected area in the next joint control.

[0054] In one embodiment, the method for obtaining the starting time of the next joint control includes: monitoring the power change of the real-time power of photovoltaic power generation, and recording the moment when the power change is greater than the change threshold as the first moment; taking the starting time of this joint control as the starting point, recording the moment after the preset control cycle as the second moment; and taking the earliest moment between the first moment and the second moment as the starting time of the next joint control.

[0055] Understandably, in the present embodiment, the preset control period is 15 minutes. When the real-time power of photovoltaic power generation changes, indicating a change in the energy constraint, the target control parameters of each air-source heat pump unit need to be re-solved. If the real-time power of photovoltaic power generation does not change within the preset control period, the target control parameters of each air-source heat pump unit need to be re-solved to ensure that each affected area can achieve a good heating effect.

[0056] In this way, multiple joint controls are performed on multiple air source heat pump units to ensure that each affected area can achieve a good heating effect.

[0057] According to the second aspect of the present application, the present application also provides a joint control system for multiple photovoltaic direct-driven air source heat pump units. Figure 2 This is a structural block diagram of a joint control system for a photovoltaic direct-driven air source heat pump multi-unit according to an embodiment of the present application. Figure 2As shown, the system 50 includes a processor and a memory. The memory stores computer program instructions. When the computer program instructions are executed by the processor, the method for controlling multiple photovoltaic direct-drive air-source heat pump units according to the first aspect of the present application is implemented. The system also includes other components familiar to those skilled in the art, such as a communication bus and a communication interface. The configuration and functions of these components are well known in the art and are not further described here.

[0058] It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all fall within the scope of protection of the present application.

Claims

1. A joint control method for multiple photovoltaic direct-driven air source heat pump units, characterized in that: The control method includes: calculating the heating accuracy of the area affected by each air source heat pump unit in this joint control, wherein the heating accuracy is positively correlated with the frequency of personnel activities; Under energy constraints, the target control parameters of each air source heat pump unit are solved with the minimum value of the objective function as the optimization goal; Adjust the heating accuracy of each affected area according to the fluctuation of the temperature difference curve between the inlet water temperature and the return water temperature between the start time of this joint control and the start time of the next joint control, so as to be used for the next joint control; The objective function value is the sum of the first objective value and the second objective value; obtaining the first deviation between the predicted temperature and the target temperature under the control parameters of any air source heat pump unit, and weightedly summing the first deviations of each affected area according to the normalized heating accuracy to obtain the first target value; calculating the second deviation of the predicted temperature between any two affected areas, and weightedly summing the second deviations according to the adjacency coefficient of any two affected areas to obtain the second target value; the energy constraint is that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power of photovoltaic power generation; Air source heat pump unit in this joint control Heating accuracy of the affected area for: ; Air source heat pump unit Number of people in the affected area; For the moment of this joint control, The moment of last joint control, is the time interval between this joint control and the previous joint control; For the moment Air source heat pump unit Number of people in the affected area, is the number of people threshold, For time interval Internal air source heat pump unit The total duration that the number of people in the affected area exceeds the threshold; In response to the absence of personnel flow between any two impact areas, the adjacency coefficient is 0, otherwise, the adjacency coefficient is 1.

2. A joint control method for multiple photovoltaic direct-driven air source heat pump units according to claim 1, characterized in that: The predicted temperature is obtained by a prediction model, the predicted temperature input is the outdoor temperature, the initial indoor temperature and the control parameters of the air source heat pump unit, and the output is the predicted temperature.

3. The method for joint control of multiple photovoltaic direct-driven air source heat pump units according to claim 2, characterized in that: The method for constructing the prediction model includes: The outdoor temperature, initial indoor temperature and control parameters of the air source heat pump unit in the historical heating process are used as training samples, and the indoor temperature that reaches a stable state in the historical heating process is used as the temperature label; The training samples are input into the prediction model to obtain the output results. The prediction model is updated based on the output results and the mean square error loss of the temperature label until the mean square error loss is less than the loss threshold or the number of updates reaches the preset number, completing the construction of the prediction model.

4. The method for joint control of multiple photovoltaic direct-driven air source heat pump units according to claim 1, characterized in that: The target control parameters of each air source heat pump unit are solved as follows: The control parameters of each air source heat pump unit are continuously updated within the allowable value range of the control parameters, and the control parameters of each air source heat pump unit when the objective function value takes the minimum value are obtained using the optimization algorithm as the target control parameters of the corresponding air source heat pump unit.

5. The method for joint control of multiple photovoltaic direct-driven air source heat pump units according to claim 1, characterized in that: The adjustment of the heating accuracy of each affected area includes: The variance of the temperature difference curve in each affected area is regarded as volatility; The product of the normalized volatility of any affected area and the heating accuracy of the affected area in this joint control is used as the heating accuracy of the affected area in the next joint control.

6. The method for joint control of multiple photovoltaic direct-driven air source heat pump units according to claim 1, characterized in that: The method for obtaining the next joint control starting time includes: Monitor the power variation of the real-time power of photovoltaic power generation, and record the moment when the power variation is greater than the variation threshold as the first moment; Taking the start time of this joint control as the starting point, the time after the preset control cycle is recorded as the second time; the earliest time between the first time and the second time is used as the start time of the next joint control.

7. The method for joint control of multiple photovoltaic direct-driven air source heat pump units according to claim 1, characterized in that: The control parameters include compressor frequency, water pump frequency and water outlet temperature.

8. A joint control system for multiple photovoltaic direct-driven air source heat pump units, characterized in that: The invention comprises a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a joint control method for a photovoltaic direct-driven air source heat pump multi-unit is implemented according to any one of claims 1 to 7.

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