Control method of household multi-water-tank adjustable fluorine path and adjustable water path heat pump system

Abstract

The invention discloses a control method of a household multi-water-tank adjustable fluorine path and adjustable water path heat pump system, and belongs to the technical field of heat pump water heaters. The method comprises the steps of data collection and processing, data analysis, prediction model establishment, real-time adjustment and real-time monitoring and maintenance. Water consumption data of a user in the first n days are collected, processed and analyzed, water consumption habits of the user are recognized through a clustering analysis method, and then a refrigerant flow model and a water flow model of the heat pump system are established. On the basis of the models, an MPC prediction model is constructed, and rolling prediction and optimization are conducted on the model in combination with a prediction result of future water consumption demands so as to predict temperature changes of the water tank within a certain time in the future and optimize distribution of refrigerant flow and water flow; the fluorine path flow and the water path flow are dynamically adjusted by adjusting the water pump and the valve in real time, efficient operation of the heat pump system is achieved, meanwhile, the system state is monitored and maintained in real time, and stability and reliability of the heat pump system are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of heat pump water heaters, and in particular to a control method for a household multi-water tank adjustable fluorine path and adjustable water path heat pump system. Background Art

[0002] With the increasing awareness of energy conservation and environmental protection, household heat pump systems have gradually become a popular choice to replace traditional gas water heaters and boilers. However, the current household heat pump water heater systems are mostly limited to a single water tank design. Its fixed fluorine circuit and water circuit configurations are difficult to meet the needs of users in diverse usage scenarios, and cannot be flexibly adjusted according to different user needs, resulting in low energy efficiency and poor user experience. With the improvement of the quality of life, the demand for hot water in households is becoming increasingly diversified, such as the need for hot water supply, heating, and special water tank heating. Traditional systems are inefficient in the face of multiple demand scenarios, energy distribution is uneven, and cannot meet personalized needs. In addition, the application scenarios of several water tanks often require different water temperatures and water qualities, and the existing technology is difficult to achieve independent control of these needs, which seriously affects the user experience and system efficiency. Therefore, there is an urgent need for a heat pump linkage control method that can intelligently and efficiently allocate energy while meeting the needs of different scenarios. Summary of the invention

[0003] The present invention aims to provide a control method for a household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system, which solves the problem that the water heater in the above-mentioned background technology cannot meet the user's diverse hot water needs and efficiently distribute energy by accurately adjusting the fluorine circuit and the water circuit.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] 1. A control method for a household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system, comprising the following steps:

[0006] S1. Data collection and processing

[0007] Use the water metering module to accurately measure and record the water usage data of several water tanks in the heat pump system of the user in the previous n days, and the water usage data includes the water volume W, water temperature T and water usage time t of several water tanks;

[0008] The heat pump system includes a heat pump host, several water tanks for different purposes, a fluorine circuit regulating device, a water circuit distribution device and a control unit; the heat pump host is connected to the several water tanks through the fluorine circuit regulating device and the water circuit distribution device, and transmits heat to the several water tanks through the fluorine circuit; the water metering module is provided at the water outlet of the several water tanks, and the first temperature sensor is installed inside the several water tanks, and the first temperature sensor is electrically connected to the control unit; the fluorine circuit regulating device includes several solenoid valves and flow control valves; the water circuit distribution device includes multiple water pumps, a second temperature sensor, a flow sensor and a water circuit switching valve; the control The unit includes a main controller and several sub-controllers; the main controller is responsible for receiving the hot water demand and scene usage information of the several water tanks, dynamically adjusting the fluorine circuit flow and the temperature and flow of the water circuit according to the information, and calculating the adjustment parameters of the several sub-controllers through linkage control logic; the several sub-controllers are electrically connected to the main controller and receive the adjustment parameters of the main controller; the several sub-controllers correspond to the several water tanks one by one and control the water circuits corresponding to the several water tanks; receive the signals of the first temperature sensor and the flow sensor, and automatically control the water pump and the water circuit switching valve of the water circuit distribution device according to the preset control algorithm and user needs;

[0009] The collected water usage data is automatically uploaded and stored in the control unit after pre-processing;

[0010] S2. Data Analysis

[0011] Use cluster analysis to analyze the user's water consumption data from several water tanks in the previous n days, identify peak and low water consumption periods and the user's fixed water consumption habits, and draw a water consumption pattern curve for the user on that day;

[0012] According to the water consumption pattern curve of the user on that day, combined with the working principle, physical effects and historical operation data of the heat pump system, a refrigerant flow model and a water flow model of the heat pump system are established;

[0013] The refrigerant flow model calculates the refrigerant flow Fm required by the heat pump system according to the user's water demand, the water tank temperature and the ambient temperature, so as to achieve efficient operation of the heat pump system. For example, during peak water consumption, the refrigerant flow is adjusted in time to maintain a suitable water temperature according to the large water consumption and water temperature changes;

[0014] The calculation formula is:

[0015] Among them, Fm is the refrigerant flow rate required by the heat pump system (m3 / h), a and b are coefficients determined according to the characteristics of the heat pump system. is the temperature drop rate of the water tank corresponding to different time periods, W is the water consumption in this period (L), and t is the duration of water use by the user (h);

[0016] The water flow model calculates the water flow Fw required by the heat pump system according to the water use frequency, water consumption and water tank temperature changes; the water flow model can reasonably adjust the water flow according to the user's water use habits and temperature requirements to ensure that the water temperature in the water tank can meet the user's needs while avoiding the waste of water resources and energy;

[0017] The water flow calculation formula is:

[0018] Where Fw is the water flow rate required by the heat pump system (m3 / h), W is the water consumption (L), T1 is the target temperature of the water tank (℃), T0 is the initial temperature of the water tank (℃), c is the specific heat capacity of water (J / (kg.℃)), t is the duration of user water use (h), ρ is the density of water (kg / m3), q is the heat provided by the heat pump to the hot water system (J), and η is the system efficiency factor;

[0019] S3. Build a prediction model

[0020] Based on the refrigeration process of the heat pump system, an MPC prediction model including a refrigerant flow model and a water flow model is constructed. The MPC prediction model uses the prediction result of future water demand as an important input parameter of the MPC model. The MPC prediction model is combined with the current water tank temperature, refrigerant flow and water flow system status information to perform rolling prediction and optimization, so as to predict the target refrigerant flow, target water flow and target temperature of the several water tanks within a certain period of time in the future; and based on these predictions, the optimal control strategy is found by optimizing the cost function; the MPC cost function is set as:

[0021]

[0022] Among them, N is the prediction range, M is the number of water tanks, α, β, γ, δ are weight coefficients, and T i (k) is the temperature of the water tank at the kth moment, T set,i is the set temperature, m w,i (k) is the water flow rate of the water tank at the kth moment, m r,i (k) is the refrigerant flow rate of the water tank at the kth moment, D k+1 is the predicted water demand at the k+1th moment, S k+1 is the amount of water that the system can provide at the k+1th moment;

[0023] S4, real-time adjustment

[0024] According to the target refrigerant flow, target water flow and target temperature obtained by the MPC prediction model, the control unit monitors the water volume and temperature of the plurality of water tanks in real time according to the control logic, and dynamically adjusts the fluorine circuit flow and the water circuit flow;

[0025] The flow rate of the fluorine circuit is dynamically adjusted by comparing the current water temperature Tc of the heat pump system with the target temperature Tt to adjust the opening degree of the flow control valve;

[0026] a1. When Tc < Tt, reduce the opening degree of the flow control valve to reduce the refrigerant flow rate;

[0027] a2. When Tc > Tt, increase the opening degree of the flow control valve to increase the refrigerant flow rate;

[0028] The flow rate of the water circuit is dynamically adjusted by comparing the current flow rate Fc of the heat pump system with the target flow rate Ft to adjust the rotational speed of the water pump;

[0029] b1. When Fc < Ft, increase the rotational speed of the water pump to increase the flow rate;

[0030] b2. When Fc > Ft, reduce the rotational speed of the water pump to reduce the flow rate;

[0031] S5. Real-time monitoring and maintenance

[0032] The MPC model continuously compares the prediction results under different control strategies and adjusts the set values of the refrigerant flow rate and the water flow rate in real time; at the same time, the heat pump system conducts self-checks regularly, monitors the water tank status and the system efficiency in real time, and discovers and processes potential problems in a timely manner.

[0033] Specifically, in step S3, the initial input value of the MPC prediction model wherein, is the average value of the water consumption in each time period, and k is a correction coefficient;

[0034] Furthermore, the method for determining the initial input value of the MPC prediction model is as follows:

[0035] c1. Statistically analyze the water consumption in the same time period of the previous n days; assume that the water consumption in the same time period of the previous n days is W1, W2.....Wn respectively, and calculate the average value of the water consumption in this time period

[0036] c2. Make corrections according to the water consumption that has occurred on the current day; in order to make the prediction more in line with the actual water consumption trend of the current day, assume that the water consumption that has occurred on the current day is Wd, and the correction coefficient wherein, when Wd is small, a lower limit value can be set according to historical data to avoid abnormal corrections;

[0037] c3. During the operation of the system, as new water consumption data is continuously generated, recalculate regularly and k, thereby updating and optimizing the forecast model input and results of future water demand, ensuring that the forecast results of future water demand are always based on the latest data, thereby improving the accuracy of the forecast.

[0038] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. By collecting and analyzing users’ water usage data and using cluster analysis methods to identify users’ water usage habits, accurate refrigerant flow models and water flow models were established. Combined with the MPC prediction model, accurate predictions of future water demand were achieved, and the fluorine circuit flow and water circuit flow were dynamically adjusted according to the prediction results, thereby ensuring the efficient operation of the heat pump system and improving energy utilization.

[0040] 2. The control unit dynamically adjusts the opening of the water pump and valve to adjust the water flow and fluorine flow according to the real-time monitoring data, ensuring that the heat pump heating is started before the predicted peak water usage period to meet user needs. At the same time, the adaptive control of the water flow and fluorine flow ensures the efficient and stable operation of the system under various conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the control method of the household multi-water tank adjustable fluorine circuit and adjustable water circuit of the present invention;

[0042] Figure 2 This is a structural block diagram of the household multi-water tank adjustable fluorine circuit and adjustable water circuit heat pump system of the present invention. DETAILED DESCRIPTION

[0043] The specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments given here are only used to illustrate and explain the present invention, and cannot be used to limit the present invention.

[0044] It should be noted that many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention may also have other implementation modes. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0045] Combined with Figure 1-2 It can be seen that a control method for a household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system includes the following steps:

[0046] S1. Data collection and processing

[0047] Use the water metering module to accurately measure and record the water usage data of several water tanks in the heat pump system of the user in the previous n days, and the water usage data includes the water volume W, water temperature T and water usage time t of several water tanks;

[0048] The heat pump system includes a heat pump host, several water tanks for different purposes, a fluorine circuit regulating device, a water circuit distribution device and a control unit; the heat pump host is connected to the several water tanks through the fluorine circuit regulating device and the water circuit distribution device, and transmits heat to the several water tanks through the fluorine circuit; the water metering module is provided at the water outlet of the several water tanks, and the first temperature sensor is installed inside the several water tanks, and the first temperature sensor is electrically connected to the control unit; the fluorine circuit regulating device includes several solenoid valves and flow control valves; the water circuit distribution device includes multiple water pumps, a second temperature sensor, a flow sensor and a water circuit switching valve; the control The unit includes a main controller and several sub-controllers; the main controller is responsible for receiving the hot water demand and scene usage information of the several water tanks, dynamically adjusting the fluorine circuit flow and the temperature and flow of the water circuit according to the information, and calculating the adjustment parameters of the several sub-controllers through linkage control logic; the several sub-controllers are electrically connected to the main controller and receive the adjustment parameters of the main controller; the several sub-controllers correspond to the several water tanks one by one and control the water circuits corresponding to the several water tanks; receive the signals of the first temperature sensor and the flow sensor, and automatically control the water pump and the water circuit switching valve of the water circuit distribution device according to the preset control algorithm and user needs;

[0049] In this specific embodiment, the several water tanks are hot water tanks, heating water tanks, and bathing water tanks;

[0050] The collected water usage data is automatically uploaded and stored in the control unit after pre-processing;

[0051] S2. Data Analysis

[0052] Use cluster analysis to analyze the user's water consumption data from several water tanks in the previous n days, identify peak and low water consumption periods and the user's fixed water consumption habits, and draw a water consumption pattern curve for the user on that day;

[0053] According to the water consumption pattern curve of the user on that day, combined with the working principle, physical effects and historical operation data of the heat pump system, a refrigerant flow model and a water flow model of the heat pump system are established;

[0054] The refrigerant flow model calculates the refrigerant flow Fm required by the heat pump system according to the user's water demand, the water tank temperature and the ambient temperature, so as to achieve efficient operation of the heat pump system. For example, during peak water consumption, the refrigerant flow is adjusted in time to maintain a suitable water temperature according to the large water consumption and water temperature changes;

[0055] The calculation formula is:

[0056] Among them, Fm is the refrigerant flow rate required by the heat pump system (m3 / h), a and b are coefficients determined according to the characteristics of the heat pump system. is the temperature drop rate of the water tank corresponding to different time periods, W is the water consumption in this period (L), and t is the duration of water use by the user (h);

[0057] The water flow model calculates the water flow Fw required by the heat pump system according to the water use frequency, water consumption and water tank temperature changes; the water flow model can reasonably adjust the water flow according to the user's water use habits and temperature requirements to ensure that the water temperature in the water tank can meet the user's needs while avoiding the waste of water resources and energy;

[0058] The water flow calculation formula is:

[0059] Where Fw is the water flow rate required by the heat pump system (m3 / h), W is the water consumption (L), T1 is the target temperature of the water tank (℃), T0 is the initial temperature of the water tank (℃), c is the specific heat capacity of water (J / (kg.℃)), t is the duration of user water use (h), ρ is the density of water (kg / m3), q is the heat provided by the heat pump to the hot water system (J), and η is the system efficiency factor;

[0060] S3. Build a prediction model

[0061] Based on the refrigeration process of the heat pump system, an MPC prediction model including a refrigerant flow model and a water flow model is constructed. The MPC prediction model uses the prediction result of future water demand as an important input parameter of the MPC model. The MPC prediction model is combined with the current water tank temperature, refrigerant flow and water flow system status information to perform rolling prediction and optimization, so as to predict the target refrigerant flow, target water flow and target temperature of the several water tanks within a certain period of time in the future; and based on these predictions, the optimal control strategy is found by optimizing the cost function; the MPC cost function is set as:

[0062]

[0063] Among them, N is the prediction range, M is the number of water tanks, α, β, γ, δ are weight coefficients, and T i (k) is the temperature of the water tank at the kth moment, T set,i is the set temperature, m w,i (k) is the water flow rate of the water tank at the kth moment, m r,i (k) is the refrigerant flow rate of the water tank at the kth moment, D k+1 is the predicted water demand at the k+1th moment, S k+1 is the amount of water that the system can provide at the k+1th moment;

[0064] S4, real-time adjustment

[0065] The target refrigerant flow rate, target water flow rate, and target temperature obtained according to the MPC prediction model. The control unit monitors the water volume and temperature of the several water tanks in real time according to the control logic, and dynamically adjusts the refrigerant flow rate and water flow rate;

[0066] The refrigerant flow rate dynamically adjusts the opening degree of the flow control valve by comparing the current water temperature Tc of the heat pump system with the target temperature Tt;

[0067] a1. When Tc < Tt, reduce the opening degree of the flow control valve to reduce the refrigerant flow rate;

[0068] a2. When Tc > Tt, increase the opening degree of the flow control valve to increase the refrigerant flow rate;

[0069] The water flow rate dynamically adjusts the rotational speed of the water pump by comparing the current flow rate Fc of the heat pump system with the target flow rate Ft;

[0070] b1. When Fc < Ft, increase the rotational speed of the water pump to increase the flow rate;

[0071] b2. When Fc > Ft, reduce the rotational speed of the water pump to reduce the flow rate;

[0072] S5. Real-time monitoring and maintenance

[0073] The MPC model continuously compares the prediction results under different control strategies, and adjusts the set values of the refrigerant flow rate and water flow rate in real time; at the same time, the heat pump system conducts self-checks regularly, monitors the water tank status and system efficiency in real time, and discovers and processes potential problems in a timely manner.

[0074] Specifically, in step S3, the initial input value of the MPC prediction model wherein, is the average value of the water consumption in each period, and k is a correction coefficient;

[0075] Furthermore, the method for determining the initial input value of the MPC prediction model is as follows:

[0076] c1. Statistically analyze the water consumption in the same period of the previous n days; assume that the water consumption in the same period of the previous n days is W1, W2.....Wn respectively, and calculate the average value of the water consumption in this period

[0077] c2. Correct according to the water consumption that has occurred on the current day; in order to make the prediction more in line with the actual water consumption trend of the current day, assume that the water consumption that has occurred on the current day is Wd, and the correction coefficient k = Wd / W; wherein, when Wd is small, a lower limit value can be set according to historical data to avoid abnormal correction;

[0078] c3. During the operation of the system, as new water usage data is continuously generated, W and k are recalculated regularly to update the input value of the future water demand forecast result.

[0079] In this specific embodiment, the water metering module first records the water consumption, temperature and time of each water tank of the user within one month, and uses cluster analysis to obtain the peak and valley periods of water consumption of the user. Subsequently, a refrigerant flow model is established based on these data, and the required refrigerant flow is calculated according to the water consumption, water tank temperature and ambient temperature; at the same time, a water flow model is established to calculate the required water flow according to the water frequency, water consumption and water tank temperature changes; then, an MPC prediction model is constructed, and the future water demand forecast is used as input, combined with the current water tank temperature, refrigerant and water flow status, to predict the target flow and temperature in the future period, and find the optimal control strategy by optimizing the cost function; in the real-time adjustment stage, the system dynamically adjusts the flow control valve and the water pump speed according to the MPC prediction results to ensure that the water temperature meets the demand and the resources are used efficiently; in addition, the system recalculates and updates the water demand forecast value every three hours, and performs self-inspection and monitoring regularly to ensure stable operation; when it is at the peak of heating in winter, the system can automatically increase the refrigerant flow, increase the temperature of the heating water tank, and reduce the refrigerant supply of the bathing water tank to achieve intelligent energy saving.

[0080] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions and variations of these embodiments are made without departing from the principles and spirit of the present invention, and still fall within the scope of protection of the present invention.

Claims

1. A control method for a household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system, characterized in that: The following steps are involved: S1. Data collection and processing Use the water metering module to accurately measure and record the water usage data of several water tanks in the heat pump system of the user in the previous n days, and the water usage data includes the water volume W, water temperature T and water usage time t of several water tanks; The heat pump system includes a heat pump host, several water tanks for different purposes, a fluorine circuit regulating device, a water circuit distribution device and a control unit; the heat pump host is connected to the several water tanks through the fluorine circuit regulating device and the water circuit distribution device, and transmits heat to the several water tanks through the fluorine circuit; the water metering module is provided at the water outlet of the several water tanks, and the first temperature sensor is installed inside the several water tanks, and the first temperature sensor is electrically connected to the control unit; the fluorine circuit regulating device includes several solenoid valves and flow control valves; the water circuit distribution device includes multiple water pumps, a second temperature sensor, a flow sensor and a water circuit switching valve; the control The unit includes a main controller and several sub-controllers; the main controller is responsible for receiving the hot water demand and scene usage information of the several water tanks, dynamically adjusting the fluorine circuit flow and the temperature and flow of the water circuit according to the information, and calculating the adjustment parameters of the several sub-controllers through linkage control logic; the several sub-controllers are electrically connected to the main controller and receive the adjustment parameters of the main controller; the several sub-controllers correspond to the several water tanks one by one and control the water circuits corresponding to the several water tanks; receive the signals of the first temperature sensor and the flow sensor, and automatically control the water pump and the water circuit switching valve of the water circuit distribution device according to the preset control algorithm and user needs; The collected water usage data is automatically uploaded and stored in the control unit after pre-processing; S2. Data Analysis Use cluster analysis to analyze the user's water consumption data from several water tanks in the previous n days, identify peak and low water consumption periods and the user's fixed water consumption habits, and draw a water consumption pattern curve for the user on that day; According to the water consumption pattern curve of the user on that day, combined with the working principle, physical effects and historical operation data of the heat pump system, a refrigerant flow model and a water flow model of the heat pump system are established; The refrigerant flow model calculates the refrigerant flow Fm required by the heat pump system according to the user's water demand, the water tank temperature and the ambient temperature. The calculation formula is: Among them, Fm is the refrigerant flow rate required by the heat pump system (m3 / h), a and b are coefficients determined according to the characteristics of the heat pump system. is the temperature drop rate of the water tank corresponding to different time periods, W is the water consumption in this period (L), and t is the duration of water use by the user (h); The water flow model calculates the water flow Fw required by the heat pump system according to the water use frequency, water consumption and water tank temperature changes; The water flow calculation formula is: Where Fw is the water flow rate required by the heat pump system (m3 / h), W is the water consumption (L), T1 is the target temperature of the water tank (℃), T0 is the initial temperature of the water tank (℃), c is the specific heat capacity of water (J / (kg.℃)), t is the duration of user water use (h), ρ is the density of water (kg / m3), q is the heat provided by the heat pump to the hot water system (J), and η is the system efficiency factor; S3. Build a prediction model Based on the refrigeration process of the heat pump system, an MPC prediction model including a refrigerant flow model and a water flow model is constructed. The MPC prediction model takes the prediction result of the future water demand as an important input parameter of the MPC model. The MPC prediction model is combined with the system state information of the current water tank temperature, refrigerant flow rate and water flow rate to perform rolling prediction and optimization, so as to predict the target refrigerant flow rate, target water flow rate and target temperature of the several water tanks within a certain future time; and based on these predictions, the optimal control strategy is found by optimizing the cost function; the MPC cost function is set as: Among them, N is the prediction range, M is the number of water tanks, α, β, γ, δ are weight coefficients, and T i (k) is the temperature of the water tank at the kth moment, T set,i is the set temperature, m w,i (k) is the water flow rate of the water tank at the kth moment, m r,i (k) is the refrigerant flow rate of the water tank at the kth moment, D k+1 is the predicted water demand at the k+1th moment, S k+1 is the amount of water that the system can provide at the k+1th moment; S4. Real-time adjustment According to the target refrigerant flow rate, target water flow rate and target temperature obtained from the MPC prediction model, the control unit monitors the water volume and temperature of the several water tanks in real time according to the control logic, and dynamically adjusts the refrigerant circuit flow rate and the water circuit flow rate; The refrigerant circuit flow rate dynamically adjusts the opening degree of the flow control valve by comparing the current water temperature Tc of the heat pump system with the target temperature Tt; a1. When Tc < Tt, reduce the opening degree of the flow control valve to reduce the refrigerant flow rate; a2. When Tc > Tt, increase the opening degree of the flow control valve to increase the refrigerant flow rate; The water circuit flow rate dynamically adjusts the rotation speed of the water pump by comparing the current flow rate Fc of the heat pump system with the target flow rate Ft; b1. When Fc < Ft, increase the rotation speed of the water pump to increase the flow rate; b2. When Fc > Ft, reduce the rotation speed of the water pump to reduce the flow rate; S5. Real-time monitoring and maintenance The MPC model continuously compares the prediction results under different control strategies and adjusts the set values of the refrigerant flow rate and the water flow rate in real time; at the same time, the heat pump system performs self-check regularly, monitors the water tank state and system efficiency in real time, and discovers and processes potential problems in time.

2. The control method of the household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system according to claim 1 is characterized in that: In step S3, the initial input value of the MPC prediction model in, is the average water consumption in each period, and k is the correction coefficient.

3. The control method of the household multi-tank adjustable fluorine circuit and adjustable water circuit heat pump system according to claim 2 is characterized in that: The method for determining the initial input value of the MPC prediction model is as follows: c1. Perform statistical analysis on the water consumption in the same period of the previous n days; suppose the water consumption in the same period of the previous n days is W1, W2...Wn, and calculate the average water consumption in this period. c2. Make corrections based on the water consumption that has occurred on that day; assuming that the water consumption that has occurred on that day is Wd, the correction coefficient c3. During the operation of the system, as new water consumption data is continuously generated, the system will be recalculated regularly. and k, thereby updating and optimizing the forecast model inputs and results of future water demand.

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