Combined control method and system for multiple units of photovoltaic direct-driven air source heat pump

Abstract

The invention relates to the technical field of air source heat pump control, in particular to a combined control method and system for multiple units of a photovoltaic direct-driven air source heat pump, and the method comprises the steps: calculating the heat supply precision of an affected area of each air source heat pump unit in the combined control; under energy constraint, target control parameters of all the air source heat pump units are solved with the minimum target function value as an optimization target; and according to a temperature difference curve of the water inlet temperature and the water return temperature between the starting moment of the combined control and the starting moment of the next combined control, the heat supply precision of each influence area is adjusted for the next combined control. According to the technical scheme, the control parameters of all the air source heat pump units can be obtained, and air source heat pump multi-unit combined control is accurately achieved.

Description

Technical Field

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

[0002] An air source heat pump uses electricity as the driving force, takes the outdoor air as low-grade heat energy, drives the compressor to operate through a small amount of electric energy, completes the process of making hot water, and circulates the hot water in the indoor heating system, so that the hot water exchanges heat with the indoor environment to achieve the heating effect. Compared with the three traditional hot water preparation methods of electric heating, gas heating, and coal burning, the air source heat pump has greater advantages in terms of economy and environmental protection.

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

[0004] The above method takes the minimum power consumption demand proposed by the target scenic area to the power distribution network as the optimization goal, and obtains the target operation state parameters of all air source heat pump units in the target scenic area. However, the indoor areas of scenic area buildings corresponding to different air source heat pump units in the target scenic area are different, 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 each scenic area building, resulting in inaccurate combined control of multiple air source heat pump units in the case of limited electric energy. Summary of the Invention

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

[0006] In the first aspect of the present application, a combined control method for a photovoltaic direct-drive air source heat pump multi-unit is provided. The control method includes: calculating the heating accuracy of the influence area of each air source heat pump unit in this combined control, and the heating accuracy is positively correlated with the personnel activity frequency; under the energy constraint, with the minimum value of the objective function value as the optimization goal, solving the target control parameters of each air source heat pump unit; adjusting the heating accuracy of each influence area according to the volatility 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; 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 weighted summing the first deviations of each influence area according to the normalized heating accuracy to obtain the first objective value; calculating the second deviation of the predicted temperature between any two influence areas, and weighted summing each second deviation according to the adjacency coefficient of any two influence areas to obtain the second objective 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 generation of photovoltaic power generation.

[0007] During each combined control, determine the heating accuracy of each influence area in this combined control according to the personnel activity frequency of each influence area and the volatility of the temperature difference curve during the previous combined control. Priority should be given to ensuring the heating effect of the influence area with a larger heating accuracy; on the premise that the real-time energy consumption of each air source heat pump unit is not greater than the real-time power generation of photovoltaic power generation, calculate the objective function value. The objective function value includes two parts, the first objective value and the second objective value. The first objective value ensures the heating effect of each influence area, and the greater the heating accuracy, the greater the influence of the heating effect of the corresponding influence area on the first objective value; the second objective value ensures that the heating temperature areas between the influence areas with personnel flow are consistent, avoiding the situation of sudden cold and sudden heat when there is personnel flow, and ensuring the user experience within the heating area; with the minimum value of the objective function value as the optimization goal, obtain the target control parameters of each air source heat pump unit to accurately achieve the combined control of the air source heat pump multi-units.

[0008] Preferably, in this combined control, the air source heat pump unit The heating accuracy of the influence area is: ; is the number of people in the influence area of the air source heat pump unit ; is the time of this combined control, is the time of the previous combined control, is the time interval between this combined control and the previous combined control; is the time The air source heat pump unit The number of people in the influence area, is the number threshold, is the time interval the total duration during which the number of people in the affected area of the air source heat pump unit is greater than the number threshold

[0009] Precisely quantify the heating accuracy of the affected area based on the activity frequency of personnel in each affected area, providing a data basis for this joint control. It can ensure that the affected area with a larger heating accuracy can achieve a better heating effect under the condition of limited electric energy

[0010] Preferably, the predicted temperature is obtained by a prediction model. The input of the predicted temperature 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 construction method of 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 this historical heating process as the temperature label; inputting the training samples into the prediction model to obtain the output result, and updating the prediction model according to the mean square error loss between 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, then the construction of the prediction model is completed

[0012] Train the prediction model through the mean square error loss between the output result and the temperature label to ensure that the prediction model can output an accurate predicted temperature

[0013] Preferably, in response to no personnel flow between any two affected areas, the adjacency coefficient is 0; otherwise, the adjacency coefficient is 1

[0014] If there is no personnel flow between two affected areas, it means that there is no need to constrain the predicted temperatures between the two affected areas to be consistent. Directly set the adjacency coefficients of these two affected areas to 0, so that the second target value can accurately reflect the difference in predicted temperatures between the affected areas with personnel flow

[0015] Preferably, the solution for 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 the 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 are large fluctuations in the temperature difference curve, it indicates 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. 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 increased, 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 amount of the real-time power of photovoltaic power generation, and recording the time when the power change amount is greater than the change threshold as the first time; taking the starting time of this joint control as the starting point, and recording the time after a preset control period as the second time; taking the earliest time among the first time and the second time as the starting time of the next joint control.

[0019] When the real-time power of photovoltaic power generation changes, it indicates 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 does not change 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 achieve precise control of multiple air source heat pump units.

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

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

[0022] The technical solution of the present application has the following beneficial technical effects: During each joint control, determine the heating accuracy of each affected area during the current joint control according to the personnel activity frequency 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 a larger heating accuracy; on 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, calculate the objective function value, which includes two parts: the first objective value and the second objective value. The first objective 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 objective value; the second objective value ensures that the heating temperature areas between the affected areas with personnel flow are consistent, avoiding the situation of sudden cold and sudden heat when there is personnel flow, and ensuring the user experience within the heating area; taking the minimum of the objective function value as the optimization goal, obtain the target control parameters of each air source heat pump unit to accurately achieve the joint control of multiple air source heat pump units. Description of the Drawings

[0023] Figure 1 It is a flowchart of a joint control method for multiple units of a photovoltaic direct-drive air source heat pump according to an embodiment of the present application.

[0024] Figure 2 It is a structural block diagram of a joint control system for multiple units of a photovoltaic direct-drive air source heat pump according to an embodiment of the present application. Detailed Embodiments

[0025] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the protection scope of the present application.

[0026] According to the first aspect of the present application, the present application provides a joint control method for multiple units of a photovoltaic direct-drive air source heat pump. Figure 1 It is a flowchart of a joint control method for multiple units of a photovoltaic direct-drive air source heat pump according to an embodiment of the present application. As Figure 1 shown, the joint control method for multiple units of the photovoltaic direct-drive air source heat pump includes steps S101 to S103, which are described in detail below.

[0027] S101, calculate the heating accuracy of the affected areas of each air source heat pump unit during the current joint control, and the heating accuracy is positively correlated with the personnel activity frequency.

[0028] In one embodiment, multiple air source heat pump units are deployed within 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 directly driven by photovoltaic power, that is, the electric energy consumed by the multiple air source heat pump units is provided by a photovoltaic power generation system.

[0029] Exemplarily, the heating area is a smart building, and the influence area can 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 electric energy for all air source heat pump units.

[0030] When people move within the heating area, the activity frequencies in different influence areas are different. The purpose of the multiple air source heat pump units to heat the heating area is to enable people to move within a comfortable temperature range. Therefore, during this joint control process, heating precision is allocated to each influence area according to the personnel activity frequency of each influence area. If the personnel activity frequency in an influence area is low, it means that the influence area is an area with less personnel activity, and a smaller heating precision should be allocated to this influence area. That is, when the electric energy is limited, a larger deviation in the heating effect of this influence area can be allowed.

[0031] Specifically, the number of people entering and leaving each room is counted based on the infrared sensors deployed at the door of each room, and then the number of people in the room at any time can be judged; in this joint control, the air source heat pump unit Heating precision of the influence area is: ; is the number of people in the influence area of the air source heat pump unit ; is the moment of this joint control, is the moment of the previous joint control, is the time interval between this joint control and the previous joint control; is the moment the number of people in the influence area of the air source heat pump unit ; is the number threshold, is the time interval the total duration during which the number of people in the influence area of the air source heat pump unit is greater than the number threshold within

[0032] Among them, the value of the number threshold is 0, and the proportion of the time when the number of people in the influence area within the time interval is greater than 0 can reflect the personnel activity frequency of this influence area, and directly use the personnel activity frequency as the heating precision of the influence area of the air source heat pump unit ;

[0033] It should be noted that a method based on image processing can also be used to determine the number of people in the room at any time. The image information in the room is input into the target detection network to identify the number of people in the room, which will not be elaborated here.

[0034] In this way, the heating accuracy of the influence area is accurately quantified according to the activity frequency of personnel in each influence area, providing a data basis for the joint control this time. It can preferentially ensure that the influence area with a larger heating accuracy can achieve a better heating effect under the condition of limited electric energy.

[0035] S102, under the energy constraint, with the minimum value of the objective function as the optimization goal, solve the target control parameters of each air source heat pump unit.

[0036] In one embodiment, due to the large influence of environmental factors such as solar radiation and light occlusion on photovoltaic power generation, the real-time power of photovoltaic power generation changes continuously, resulting in different amounts of electric energy available for each air source heat pump unit at different times.

[0037] The value of the objective function is the sum of the first objective value and the second objective value; obtain the first deviation between the predicted temperature and the target temperature under the control parameters of any air source heat pump unit, and weighted sum the first deviations of each influence area according to the normalized heating accuracy to obtain the first objective value; calculate the second deviation of the predicted temperature between any two influence areas, and weighted sum each second deviation according to the adjacency coefficient between any two influence areas to obtain the second objective value; the energy constraint is that the real-time energy consumption of each air source heat pump unit does not exceed the real-time power of photovoltaic power generation.

[0038] Among them, the predicted temperature is obtained by a prediction model. The input of the predicted temperature 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. 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 construction method of 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 this historical heating process as the temperature label; inputting the training samples into the prediction model to obtain the output result, and updating the prediction model according to the mean square error loss between 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 of times, then the construction of the prediction model is completed. Among them, the loss threshold is 0.01; the preset number of times is 100.

[0039] Among them, in response to the absence of personnel flow between any two influence areas, the adjacency coefficient is 0; conversely, the adjacency coefficient is 1. It should be noted that the adjacency coefficient between any two influence areas can be set artificially. If there is no personnel flow between any two influence areas, the adjacency coefficient between these two influence areas is directly set to 0.

[0040] Specifically, the objective function value satisfies the relational expression: ; is the number of air source heat pump units, is the air source heat pump unit the heating accuracy of the influence area, is the sum of the heating accuracies of each influence area, and are respectively the air source heat pump unit and the air source heat pump unit the predicted temperature of the influence area, is the air source heat pump unit the target temperature of the influence area, is the air source heat pump unit and the air source heat pump unit the adjacency coefficient of the influence area, and the value of the adjacency coefficient is 0 or 1; is the adjustment coefficient. Among them, the value of the adjustment coefficient is 0.5.

[0041] It can be understood that is used to constrain the predicted temperature of each influence area to be equal to the target temperature. When the value tends to 0, it means that the heating effect of each influence area reaches the best. The predicted temperature is the temperature in the influence area after the air source heat pump unit operates under the control parameters. is used to constrain the predicted temperatures between the influence areas with personnel flow to tend to be consistent. The predicted temperature is the heating temperature after heating, avoiding too large a difference in the heating temperatures between the influence areas when personnel flow between different influence areas, resulting in the situation of people feeling alternately cold and hot, and improving the user experience in the heating area.

[0042] The energy constraint is: ; among them, is the number of air source heat pump units, is the air source heat pump unit the real-time energy consumption, and the real-time energy consumption is related to the control parameters of the air source heat pump unit ; is the real-time power of photovoltaic power generation.

[0043] 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 of the air source heat pump unit is less than or equal to the real-time power generation of the photovoltaic panel corresponding to the air source heat pump unit .

[0044] It can be understood that after determining the control parameters of the air source heat pump unit , the real-time operating power of the air source heat pump unit under the control parameters can be obtained according to the mapping relationship between the control parameters and the actual operating power. The actual operating power corresponds to the real-time energy consumption of the air source heat pump unit .

[0045] In one embodiment, the method for solving 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

[0046] Among them, the optimization algorithm is the gradient descent method, the genetic algorithm or the hill climbing algorithm

[0047] In this way, with the optimization goal that the heating effect of each affected area reaches the best and the heating temperatures between the affected areas with personnel flow are basically the same, under the premise of meeting the energy constraint, 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

[0048] S103. Adjust the heating accuracy of each affected area according to the volatility 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 for the next joint control

[0049] In one embodiment, after controlling each air source heat pump unit according to the target control parameters, monitor the temperature difference curve between the inlet water temperature and the return water temperature of each affected area. The inlet water temperature is the temperature of the heat exchange medium before entering the heating system for circulation; the return water temperature is the temperature of the heat exchange medium after circulating in the heating system of 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 change of the heat load of each affected area

[0050] ​For any affected area, if the temperature difference curve tends to be flat, it indicates that the heat exchange between the affected area and the heat exchange medium reaches an equilibrium state. At this time, the temperature within the affected area is close to the target temperature, and the heating effect is good. If the temperature difference curve fluctuates greatly, it indicates that frequent heat exchange occurs between the affected area and the heat exchange medium. At this time, the temperature within 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, adjust the heating accuracy of each affected area according to the volatility of the temperature difference curve between this joint control and the next joint control, so that in the next joint control, improve the heating accuracy of the affected area with a poor heating effect, that is, improve the heating accuracy of the affected area with a large volatility of the temperature difference curve, and ensure that each affected area can achieve a good heating effect.

[0051] Specifically, the adjustment of the heating accuracy of each affected area includes: taking the variance of the temperature difference curve within each affected area as the 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.

[0052] In one embodiment, the method for obtaining the starting moment of the next joint control includes: monitoring the power change amount of the real-time power of photovoltaic power generation, and recording the moment when the power change amount is greater than the change threshold as the first moment; taking the starting moment of this joint control as the starting point, and recording the moment after a preset control period as the second moment; taking the earliest moment among the first moment and the second moment as the starting moment of the next joint control.

[0053] It can be understood that in the embodiment of the present application, the preset control period is 15 minutes. When the real-time power of photovoltaic power generation changes, it indicates 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 does not change 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.

[0054] In this way, perform multiple joint controls on the multi-unit air source heat pump to ensure that each affected area can achieve a good heating effect.

[0055] According to the second aspect of the present application, the present application also provides a joint control system for a photovoltaic direct-drive multi-unit air source heat pump. Figure 2 It is a structural block diagram of a joint control system for a photovoltaic direct-drive multi-unit air source heat pump according to an embodiment of the present application. As Figure 2As shown, the system 50 includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a joint control method for a photovoltaic direct-drive air source heat pump multi-unit according to the first aspect of the present application. The system also includes a communication bus, a communication interface, and other components well-known to those skilled in the art. Their settings and functions are known in the art and will not be elaborated herein.

[0056] It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can be made, and these all fall within the protection scope of the present application.

Claims

1. A combined control method for a photovoltaic direct-drive air source heat pump with multiple units, characterized in that, The control method includes: calculating the heating accuracy of the influence area of each air source heat pump unit in the current combined control, and the heating accuracy is positively correlated with the personnel activity frequency; Under the energy constraint, with the minimum value of the objective function value as the optimization goal, solving the target control parameters of each air source heat pump unit; Adjusting the heating accuracy of each influence area according to the volatility of the temperature difference curve between the inlet water temperature and the return water temperature between the start time of the current combined control and the start time of the next combined control for the next combined 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 weighted summing the first deviations of each influence area according to the normalized heating accuracy to obtain the first objective value; calculating the second deviation of the predicted temperature between any two influence areas, and weighted summing the second deviations according to the adjacency coefficient of any two influence areas to obtain the second objective 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 generation of photovoltaic power generation.

2. The combined control method of a photovoltaic direct-drive air source heat pump multi-unit according to claim 1, characterized in that The air source heat pump unit in this joint control The heating accuracy of the affected area is: ; is the number of people in the area affected by the air source heat pump unit ; is the moment of this joint control, is the moment of the previous joint control, is the time interval between this joint control and the previous joint control; is the moment The number of people in the area affected by the air source heat pump unit ; is the number threshold, is the time interval The total duration during which the number of people in the area affected by the air source heat pump unit is greater than the number threshold within the time interval 3. The combined control method of a photovoltaic direct-drive air-source heat pump multi-unit according to claim 1, characterized in that, The predicted temperature is obtained by a prediction model, and the input of the predicted temperature 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.

4. The combined control method of a photovoltaic direct-drive air source heat pump multi-unit according to claim 3, characterized in that, The construction method of the prediction model includes: Taking 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 taking the indoor temperature reaching a steady state in the historical heating process as the temperature label; Inputting the training samples into the prediction model to obtain the output result, and updating the prediction model according to the mean square error loss between 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 of times, and completing the construction of the prediction model.

5. The combined control method of a photovoltaic direct-drive air source heat pump multi-unit according to claim 1, characterized in that, In response to no personnel flow between any two influence areas, the adjacency coefficient is 0, otherwise, the adjacency coefficient is 1.

6. The combined control method of a photovoltaic direct-drive air source heat pump multi-unit according to claim 1, characterized in that, The solving 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 the 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.

7. The combined control method of a photovoltaic direct-drive air-source heat pump multi-unit according to claim 1, characterized in that The adjustment of the heating accuracy of each influence area includes: Taking the variance of the temperature difference curve in each influence area as the volatility; Taking the product of the normalized volatility of any influence area and the heating accuracy of the influence area in the current combined control as the heating accuracy of the influence area in the next combined control.

8. The combined control method of a photovoltaic direct-drive air-source heat pump multi-unit according to claim 1, characterized in that The obtaining method of the start time of the next combined control includes: Monitoring the power change amount of the real-time power generation of photovoltaic power generation, and recording the moment when the power change amount is greater than the change threshold as the first moment; Taking the start time of the current combined control as the starting point, and recording the moment after the preset control period as the second moment; taking the earliest moment among the first moment and the second moment as the start time of the next combined control.

9. The combined control method of a photovoltaic direct-drive air-source heat pump multi-unit according to claim 1, characterized in that The control parameters include the compressor frequency, the water pump frequency and the outlet water temperature.

10. A combined control system for a photovoltaic direct-drive air source heat pump with multiple units, characterized in that, It includes a processor and a memory, and the memory stores computer program instructions. When the computer program instructions are executed by the processor, a combined control method for a photovoltaic direct-drive air source heat pump multi-unit according to any one of claims 1 to 9 is implemented.

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