Solar energy intelligent hot water system heat supply method with variable frequency circulating pump

Abstract

The application discloses a solar intelligent water heating system heat supply method with a variable frequency circulating pump, and comprises the following steps: constructing a water use behavior identification model with the water outlet log data of a heat preservation water tank in an intelligent solar water heating system, and learning and training the optimal operation parameter sequence of the variable frequency circulating pump at each water use behavior corresponding to the water outlet log data in the water use behavior identification model to obtain a behavior adaptive control model. The application realizes the optimal operation effect of the variable frequency circulating pump for each water use behavior to ensure the stability of hot water supply, constructs the water use behavior identification model and the behavior adaptive control model, realizes the adaptive operation of the variable frequency circulating pump according to the water use behavior of a user to ensure the stability of hot water supply, and maintains the stability of the user experience under different user behaviors.

Description

A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump. Technical Field

[0001] This invention relates to the field of solar water heating control technology, specifically to a method for supplying hot water in a solar intelligent water heating system with a variable frequency circulating pump. Background Technology

[0002] The solar water heating system uses a temperature difference circulation method. Temperature sensors are installed in both the collector and the insulated water tank. The sensors send the sensed temperature signals to the control system. When the temperature difference between the collector and the insulated water tank is greater than the set difference, the control system controls the circulation pump to start, thereby circulating the cold water in the insulated water tank to the collector and the hot water in the collector to the insulated water tank, completing one cycle and gradually raising the temperature of the water in the insulated water tank.

[0003] Currently, the use of temperature difference control circulation pumps to maintain hot water supply relies solely on temperature difference control. While this can achieve stable heating, the stability maintained by this temperature difference circulation is a fixed setting and is unrelated to the user's behavior. Therefore, it cannot adapt to the user's actual needs for stable hot water supply, resulting in an inability to maintain a stable user experience under different user behavior conditions. Summary of the Invention

[0004] The purpose of this invention is to provide a method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump, so as to solve the technical problems in the prior art.

[0005] To solve the above-mentioned technical problems, the present invention specifically provides the following technical solution:

[0006] A solar-powered intelligent hot water supply method with a variable frequency circulating pump includes the following steps:

[0007] Step S1: Construct a water usage behavior recognition model in the intelligent solar water heating system using the water outlet log data of the insulated water tank. The water outlet log data is log data reflecting the user's use of solar water heating, and is obtained by the water outlet monitoring component installed at the outlet of the insulated water tank in the intelligent solar water heating system. The water usage behavior recognition model is used to identify the user's water usage behavior based on the water outlet data of the insulated water tank.

[0008] Step S2: Extract the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system, and perform optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior, so as to achieve the optimal operating effect of the variable frequency circulating pump to ensure the stable supply of hot water for each water usage behavior. The control log data is the log data reflecting the control status of the variable frequency circulating pump, and is obtained by the operation monitoring component set at the variable frequency circulating pump in the intelligent solar water heating system to monitor the operating parameters of the variable frequency circulating pump in a time sequence.

[0009] Step S3: In the intelligent solar water heating system, the water outflow log data corresponding to each water use behavior in the water use behavior recognition model and the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior are used to learn and train to obtain the behavior adaptation control model.

[0010] Step S4: The intelligent solar water heating system monitors real-time water output data at the outlet of the insulated water tank. The real-time water output data is used by the behavioral adaptive control model to obtain the real-time operating parameter sequence of the variable frequency circulating pump. The intelligent solar water heating system controls the operation of the variable frequency circulating pump according to the real-time operating parameter sequence to ensure the stability of hot water supply by enabling the variable frequency circulating pump to operate adaptively according to the user's water usage behavior.

[0011] As a preferred embodiment of the present invention, the step of constructing a water usage behavior recognition model based on the water outlet log data of the insulated water tank in the intelligent solar water heating system includes:

[0012] Each water consumption log entry is tagged with water usage behavior.

[0013] The water discharge log data is used as the input to the CNN neural network, and the water usage behavior corresponding to the water discharge log data is used as the output of the CNN neural network.

[0014] The water use behavior recognition model is obtained by training the input and output terms of the CNN neural network.

[0015] The model expression for the water usage identification model is:

[0016] Type = CNN(T_data);

[0017] In the formula, Type represents water usage behavior, T_data represents water discharge log data, and CNN represents a CNN neural network.

[0018] As a preferred embodiment of the present invention, the water use behavior includes instantaneous water use behavior, short-term water use behavior, and long-term water use behavior.

[0019] As a preferred embodiment of the present invention, the step of extracting the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system includes:

[0020] Extract the monitoring time sequence of the water outlet log data of the insulated water tank, and the water usage behavior corresponding to the water outlet log data of the insulated water tank;

[0021] Extract the operating parameters of the variable frequency circulating pump located at the end of the monitoring time sequence of the effluent log data;

[0022] The operating parameters of the variable frequency circulating pump at the post-time sequence are used as the control log data of the variable frequency circulating pump for the water usage behavior.

[0023] As a preferred embodiment of the present invention, the step of performing optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior includes:

[0024] With the goal of maximizing adaptability, the control log data of each variable frequency circulating pump corresponding to each water usage behavior is adaptively optimized. The adaptive optimization function is as follows:

[0025]

[0026] In the formula, K i For the fitness of the optimal operating parameter sequence corresponding to the i-th water use behavior, max is the maximization operator, E i S represents the optimal operating parameter sequence for the variable frequency circulating pump corresponding to the i-th water usage behavior. i,j This represents the control log data of the j-th variable frequency circulating pump corresponding to the i-th water usage behavior, where i and j are counting variables, and m is the total number of control log data entries of the variable frequency circulating pump corresponding to the i-th water usage behavior.

[0027] With the goal of minimizing volatility, the control log data of each variable frequency circulating pump corresponding to each water usage behavior is optimized for volatility. The volatility optimization function is as follows:

[0028]

[0029] In the formula, L i S represents the volatility of the optimal operating parameter sequence corresponding to the i-th water use behavior, where min is the minimization operator. i,j,0 S represents the operating parameters of the variable frequency circulating pump located at the adjacent preceding time step of the control log data of the j-th variable frequency circulating pump in the i-th water usage behavior. i,j,k+1E represents the operating parameters of the variable frequency circulating pump located at the adjacent time sequence of the control log data of the j-th variable frequency circulating pump in the i-th water usage behavior. i,1 ,…,E i,k Let i, j, and k be the operating parameters from the first time series to the kth time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, where k is the total number of time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, and i, j, and k are counting variables.

[0030] S i,j,0 Use X i,j,0 It means that E i,1 ,…,E i,k Use X i,j,1 …,X i,j,k It means that S i,j,k+1 Use X i,j,k+1 This indicates that character standardization is being performed, where X i,j,0 With S i,j,0 Same meaning, X i,j,k+1 With S i,j,k+1 Same meaning, X i,j,1 …,X i,j,k respectively with E i,1 ,…,E i,k Same meaning;

[0031] The adjustment range of the operating parameters of the variable frequency circulating pump is used as a constraint. The fluctuation optimization function and the adaptive optimization function are solved within the constraint to obtain the optimal operating parameter sequence corresponding to each water use behavior.

[0032] As a preferred embodiment of the present invention, the step of learning and training a behavior adaptation control model in the intelligent solar energy system using the water consumption behavior recognition model corresponding to each water consumption behavior and the optimal operating parameter sequence of the variable frequency circulating pump at each water consumption behavior includes:

[0033] The water log data corresponding to each water use behavior is used as the input of the BP neural network, and the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior is used as the output of the BP neural network.

[0034] The behavior adaptation control model is obtained by training the input and output terms of the BP neural network using a BP neural network.

[0035] The model expression for the behavioral adaptation control model is:

[0036] E = BP(T_data);

[0037] In the formula, E is the optimal operating parameter sequence, T_data is the effluent log data, and BP is the BP neural network.

[0038] As a preferred embodiment of the present invention, the effluent log data and the control log data of the variable frequency circulating pump are normalized before network training.

[0039] As a preferred embodiment of the present invention, both the CNN neural network and the BP neural network contain at least three network layers.

[0040] As a preferred embodiment of the present invention, the operating parameters of the variable frequency circulating pump include variable frequency current, variable frequency voltage, and variable frequency power.

[0041] In a preferred embodiment of the present invention, the sequence of operating parameters is formed by arranging the operating parameters in a time sequence.

[0042] Compared with the prior art, the present invention has the following advantages:

[0043] This invention performs optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior. This achieves the optimal operating effect of the variable frequency circulating pump to ensure a stable supply of hot water for each water usage behavior. A water usage behavior identification model and a behavior adaptation control model are constructed to enable the variable frequency circulating pump to adapt to the user's water usage behavior to ensure the stability of the hot water supply and maintain a stable user experience under different user behavior conditions. Attached Figure Description

[0044] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0045] Figure 1 is a flowchart of the solar-powered intelligent hot water supply method provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Currently, hot water supply is maintained by circulating pumps controlled by temperature differences. While this achieves stable heating, the stability is a fixed setting, independent of the user's actual behavior. Therefore, it cannot adapt to the user's actual needs, resulting in inconsistent user experience under varying user behavior. This invention provides a solar-powered intelligent hot water supply method with a variable frequency circulating pump. This method identifies user water usage behavior and controls the circulation accordingly to maintain stable heating and improve user experience.

[0048] As shown in Figure 1, the present invention provides a solar-powered intelligent hot water supply method with a variable frequency circulating pump, comprising the following steps:

[0049] Step S1: Construct a water usage behavior recognition model in the smart solar water heating system using the water outlet log data of the insulated water tank. The water outlet log data is log data reflecting the user's use of solar water heating. It is obtained by the water outlet monitoring component set at the water outlet of the insulated water tank in the smart solar water heating system. The water usage behavior recognition model is used to identify the user's water usage behavior based on the water outlet data of the insulated water tank.

[0050] Step S2: Extract the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system, and perform optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior, so as to achieve the optimal operating effect of the variable frequency circulating pump to ensure the stable supply of hot water for each water usage behavior. The control log data is the log data reflecting the control status of the variable frequency circulating pump, and is obtained by the operation monitoring component set at the variable frequency circulating pump in the intelligent solar water heating system to monitor the operating parameters of the variable frequency circulating pump in a time sequence.

[0051] Step S3: In the intelligent solar water heating system, the water outflow log data corresponding to each water use behavior in the water use behavior recognition model and the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior are used to learn and train to obtain the behavior adaptation control model.

[0052] Step S4: The intelligent solar water heating system monitors real-time water output data at the outlet of the insulated water tank. The real-time water output data is used by the behavioral adaptive control model to obtain the real-time operating parameter sequence of the variable frequency circulating pump. The intelligent solar water heating system controls the operation of the variable frequency circulating pump according to the real-time operating parameter sequence to ensure the stability of hot water supply by enabling the variable frequency circulating pump to operate adaptively according to the user's water usage behavior.

[0053] Users' solar water heating usage behaviors are diverse, including instantaneous, short-term, and long-term usage. Instantaneous usage refers to the need for hot water only for a brief period, short-term usage refers to the need for hot water over a long period, and long-term usage refers to the need for hot water over an extended period. Currently, solar water heating systems using temperature difference circulation control do not differentiate between user behaviors. They only monitor the temperature difference between the collector and the insulated water tank after a user's water usage occurs. If the temperature difference exceeds a set threshold, circulation is initiated to maintain a stable hot water supply. Therefore, the variable frequency circulation pump's operating state is determined by the temperature difference. Although the generation of temperature difference reflects user behavior or demand, the variable frequency circulation pump, determined by temperature difference, adapts to user behavior or demand. While current variable frequency circulating pumps adapt to user behavior, their operation lags behind the generation of temperature differences, which in turn lags behind user behavior or demand. This results in poor timeliness and adaptability of temperature difference-controlled variable frequency circulating pumps to user water usage. Therefore, this invention constructs a behavior-adaptive control model that directly obtains the operating parameters of the variable frequency circulating pump through the water output data from the insulated water tank, reflecting user behavior. Essentially, it uses the water output data from the insulated water tank to understand user water usage behavior or demand, and controls and matches this behavior to ensure a stable supply of solar hot water. This eliminates the need for temperature difference monitoring, allowing the variable frequency circulating pump to immediately respond to user behavior or demand in one step, improving the timeliness and adaptability of the variable frequency circulating pump to user water usage and enhancing the user experience.

[0054] A water usage behavior recognition model is constructed using the water outlet log data from the insulated water tank in an intelligent solar water heating system, including:

[0055] Each water consumption log entry is tagged with water usage behavior.

[0056] The water discharge log data is used as the input to the CNN neural network, and the water usage behavior corresponding to the water discharge log data is used as the output of the CNN neural network.

[0057] A water use behavior recognition model is obtained by training the input and output terms of a CNN neural network.

[0058] The model expression for the water identification model is:

[0059] Type = CNN(T_data);

[0060] In the formula, Type represents water usage behavior, T_data represents water discharge log data, and CNN represents a CNN neural network.

[0061] Water use behavior includes instantaneous water use behavior, short-term water use behavior, and long-term water use behavior.

[0062] The responsiveness of a variable frequency (VFD) circulating pump to user behavior is related to its operating parameters. To ensure optimal responsiveness, this invention provides an optimization method. This method sets optimal operating parameters for the VFD circulating pump for each user's water usage behavior, achieving the optimal operating effect of the VFD circulating pump while ensuring a stable supply of hot water for each water usage behavior. Optimal responsiveness further enhances the user experience. The specific process is as follows:

[0063] Extract the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system, including:

[0064] Extract the monitoring time sequence of the water outlet log data of the insulated water tank, and the water usage behavior corresponding to the water outlet log data of the insulated water tank;

[0065] Extract the operating parameters of the variable frequency circulating pump located at the end of the monitoring time sequence of the effluent log data;

[0066] The operating parameters of the variable frequency circulating pump at the post-time sequence are used as the control log data of the variable frequency circulating pump for water usage behavior.

[0067] An optimization analysis was performed on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump for each water usage behavior, including:

[0068] With the goal of maximizing adaptability, the control log data of each variable frequency circulating pump corresponding to each water usage behavior is adaptively optimized. The adaptive optimization function is as follows:

[0069]

[0070] In the formula, K i For the fitness of the optimal operating parameter sequence corresponding to the i-th water use behavior, max is the maximization operator, E i S represents the optimal operating parameter sequence for the variable frequency circulating pump corresponding to the i-th water usage behavior. i,j This represents the control log data of the j-th variable frequency circulating pump corresponding to the i-th water usage behavior, where i and j are counting variables, and m is the total number of control log data entries of the variable frequency circulating pump corresponding to the i-th water usage behavior.

[0071] With the goal of minimizing volatility, the control log data of each variable frequency circulating pump corresponding to each water usage behavior is optimized for volatility. The volatility optimization function is as follows:

[0072]

[0073] In the formula, L i S represents the volatility of the optimal operating parameter sequence corresponding to the i-th water use behavior, where min is the minimization operator. i,j,0 S represents the operating parameters of the variable frequency circulating pump located at the adjacent preceding time step of the control log data of the j-th variable frequency circulating pump in the i-th water usage behavior. i,j,k+1 E represents the operating parameters of the variable frequency circulating pump located at the adjacent time sequence of the control log data of the j-th variable frequency circulating pump in the i-th water usage behavior. i,1 ,…,E i,k Let i, j, and k be the operating parameters from the first time series to the kth time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, where k is the total number of time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, and i, j, and k are counting variables.

[0074] S i,j,0 Use X i,j,0 It means that E i,1 ,…,E i,k Use X i,j,1 …,X i,j,k It means that S i,j,k+1 Use X i,j,k+1 This indicates that character standardization is being performed, where X i,j,0 With S i,j,0 Same meaning, X i,j,k+1 With S i,j,k+1 Same meaning, X i,j,1 …,X i,j,k respectively with E i,1 ,…,E i,k Same meaning;

[0075] The adjustment range of the operating parameters of the variable frequency circulating pump is used as a constraint. The fluctuation optimization function and the adaptive optimization function are solved within the constraint to obtain the optimal operating parameter sequence corresponding to each water use behavior.

[0076] Maximizing adaptability means that the optimal operating parameter sequence of the variable frequency circulating pump can adapt to the water use behavior in various systems, has a wide range of applications, and is robust and portable. Minimizing volatility means that the optimal operating parameter sequence of the variable frequency circulating pump can maintain high stability of the system before and after the adjustment when the variable frequency circulating pump is adjusted to adapt to the water use behavior.

[0077] In a smart solar energy system, a behavior-adaptive control model is obtained by learning and training the water discharge log data corresponding to each water use behavior in the water use behavior recognition model and the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior. This model includes:

[0078] The water log data corresponding to each water use behavior is used as the input of the BP neural network, and the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior is used as the output of the BP neural network.

[0079] A behavioral adaptive control model is obtained by training the input and output terms of a BP neural network.

[0080] The model expression for the behavioral adaptation control model is:

[0081] E = BP(T_data);

[0082] In the formula, E is the optimal operating parameter sequence, T_data is the effluent log data, and BP is the BP neural network.

[0083] The intelligent solar water heating system monitors real-time water output data at the outlet of the insulated water tank. The real-time water output data is used by a behavioral adaptive control model to obtain the real-time operating parameter sequence of the variable frequency circulating pump. The intelligent solar water heating system controls the operation of the variable frequency circulating pump according to the real-time operating parameter sequence, so as to realize the adaptive operation of the variable frequency circulating pump according to the user's water usage behavior to ensure the stability of hot water supply.

[0084] By constructing a behavioral adaptation control model and establishing a mapping relationship between optimal operating parameters and effluent data, a correlation mapping relationship is essentially established between the operating status of the variable frequency circulating pump and the user's water usage behavior or water demand. This enables the direct acquisition of the variable frequency circulating pump's operating parameter sequence through effluent data, allowing for operation control of the variable frequency circulating pump and achieving matching between the operation of the variable frequency circulating pump and the user's water usage behavior or water demand.

[0085] The effluent log data and the control log data of the variable frequency circulating pump are normalized before network training.

[0086] Both CNN neural networks and BP neural networks contain at least three network layers.

[0087] The operating parameters of a variable frequency circulating pump include variable frequency current, variable frequency voltage, and variable frequency power.

[0088] The sequence of operating parameters is formed by arranging the operating parameters in a time sequence.

[0089] This invention performs optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior. This achieves the optimal operating effect of the variable frequency circulating pump to ensure a stable supply of hot water for each water usage behavior. A water usage behavior identification model and a behavior adaptation control model are constructed to enable the variable frequency circulating pump to adapt to the user's water usage behavior to ensure the stability of the hot water supply and maintain a stable user experience under different user behavior conditions.

[0090] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump, characterized in that, Includes the following steps: Step S1: Construct a water usage behavior recognition model in the intelligent solar water heating system using the water outlet log data from the insulated water tank. The water outlet log data reflects the user's solar water heating usage and is obtained by a water outlet monitoring component installed at the outlet of the insulated water tank in the intelligent solar water heating system. The water usage behavior recognition model is used to identify the user's water usage behavior based on the water outlet data from the insulated water tank. Step S2: Extract the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system. Perform optimization analysis on the control log data of the variable frequency circulating pump corresponding to each water usage behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water usage behavior. This achieves the optimal operating effect of the variable frequency circulating pump to ensure a stable supply of hot water for each water usage behavior. The control log data reflects the control status of the variable frequency circulating pump and is obtained by a time-series monitoring component installed at the variable frequency circulating pump in the intelligent solar water heating system. Step S3: In the intelligent solar water heating system, the water consumption log data corresponding to each water consumption behavior in the water consumption behavior recognition model is used to learn and train the optimal operating parameter sequence of the variable frequency circulating pump at each water consumption behavior to obtain a behavior adaptive control model; Step S4: The intelligent solar water heating system monitors real-time water consumption data at the outlet of the insulated water tank, and uses the behavior adaptive control model to obtain the real-time operating parameter sequence of the variable frequency circulating pump. The intelligent solar water heating system controls the operation of the variable frequency circulating pump according to the real-time operating parameter sequence to achieve adaptive operation of the variable frequency circulating pump according to the user's water consumption behavior to ensure the stability of hot water supply; Each water consumption log data is labeled with water consumption behavior; The water consumption log data is used as the input of the CNN neural network, and the water consumption behavior corresponding to the water consumption log data is used as the output of the CNN neural network; Water consumption behavior includes instantaneous water consumption behavior, short-term water consumption behavior, and long-term water consumption behavior; The water consumption log data corresponding to each water consumption behavior is used as the input of the BP neural network, and the optimal operating parameter sequence of the variable frequency circulating pump at each water consumption behavior is used as the output of the BP neural network.

2. The method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 1, characterized in that: The step of constructing a water usage behavior recognition model based on the water outlet log data of the insulated water tank in the intelligent solar water heating system includes: training the input and output terms of the CNN neural network to obtain the water usage behavior recognition model; the model expression of the water usage behavior recognition model is: Type=CNN(T_data); where Type is the water usage behavior, T_data is the water outlet log data, and CNN is the CNN neural network.

3. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 2, characterized in that: The step of extracting the control log data of the variable frequency circulating pump corresponding to each water usage behavior in the intelligent solar water heating system includes: extracting the monitoring time sequence of the water outlet log data of the insulated water tank, and the water usage behavior corresponding to the water outlet log data of the insulated water tank; extracting the operating parameters of the variable frequency circulating pump located at the later time sequence of the monitoring time sequence of the water outlet log data; and using the operating parameters of the variable frequency circulating pump at the later time sequence as the control log data of the variable frequency circulating pump for the water usage behavior.

4. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 3, characterized in that: The optimization analysis of the control log data of the variable frequency circulating pump corresponding to each water use behavior to obtain the optimal operating parameter sequence of the variable frequency circulating pump at each water use behavior includes: adaptively optimizing the control log data of each variable frequency circulating pump corresponding to each water use behavior with the goal of maximizing adaptability, wherein the adaptive optimization function is: In the formula, Let max be the fitness of the optimal operating parameter sequence corresponding to the i-th water usage behavior, where max is the maximization operator. This is the optimal operating parameter sequence for the variable frequency circulating pump corresponding to the i-th water usage behavior. Let m be the control log data of the j-th variable frequency circulating pump corresponding to the i-th water usage behavior, where i and j are counting variables, and m is the total number of control log data entries for the variable frequency circulating pump corresponding to the i-th water usage behavior. With the goal of minimizing volatility, the control log data of each variable frequency circulating pump corresponding to each water usage behavior is optimized for volatility. The volatility optimization function is: In the formula, Let represent the volatility of the optimal operating parameter sequence corresponding to the i-th water usage behavior, where min is the minimization operator. The operating parameters of the variable frequency circulating pump located at the adjacent preceding time sequence of the control log data of the j-th variable frequency circulating pump in the i-th water usage behavior are... The operating parameters of the variable frequency circulating pump located at the adjacent time sequence of the control log data of the j-th variable frequency circulating pump in the i-th water use behavior are... Let i, j, and k be the operating parameters from the first time series to the kth time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, where k is the total number of time series in the optimal operating parameter sequence corresponding to the i-th water use behavior, and i, j, and k are count variables. use It means that it will use It means that it will use This indicates that character standardization is being implemented, where... and Same meaning and Same meaning respectively with The meaning is the same; the adjustment range of the operating parameters of the variable frequency circulating pump is used as a constraint condition, and the fluctuation optimization function and the adaptive optimization function are solved in the constraint condition to obtain the optimal operating parameter sequence corresponding to each water use behavior.

5. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 4, characterized in that: The method of learning and training a behavior adaptive control model in an intelligent hot water system using the water consumption behavior recognition model to obtain the water consumption log data corresponding to each water consumption behavior and the optimal operating parameter sequence of the variable frequency circulating pump at each water consumption behavior includes: using a BP neural network to train the input and output terms of the BP neural network to obtain the behavior adaptive control model; the model expression of the behavior adaptive control model is: E=BP(T_data); where E is the optimal operating parameter sequence, T_data is the water consumption log data, and BP is the BP neural network.

6. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 5, characterized in that: The effluent log data and the control log data of the variable frequency circulating pump are normalized before network training.

7. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 5, characterized in that, Both the CNN neural network and the BP neural network contain at least three network layers.

8. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 1, characterized in that, The operating parameters of the variable frequency circulating pump include variable frequency current, variable frequency voltage, and variable frequency power.

9. A method for supplying hot water in a solar-powered intelligent hot water system with a variable frequency circulating pump according to claim 1, characterized in that, The sequence of operating parameters is formed by arranging the operating parameters in chronological order.

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