Hot water supply optimization method, device and equipment for residential building and storage medium

Abstract

The invention discloses a hot water supply optimization method, device and equipment of a residential building and a storage medium, and relates to the technical field of heat supply, the method analyzes the relation between water temperature and water use habits of residents and the relation between water pressure and the water use habits of the residents, and the two are from the same hot water supply system; according to the method, the two pieces of data are respectively subjected to linear regression, but the two pieces of linear regression have relevance, so that the two pieces of data obtained by subsequent prediction are correlated with each other without data deviation, and the linear regression coefficient obtained by analysis visually reflects the water use habit of each resident of the residential building; according to the method and the system, the result of the prediction data also has strong relevance, the prediction data is accurate, and finally, a corresponding supply plan is formulated according to the performance of the prediction data, so that each resident can stably and efficiently use hot water.

Description

Technical Field

[0001] This application relates to the technical field of heating, and particularly to an optimization method, device, equipment and storage medium for hot water supply in residential buildings. Background Art

[0002] A hot water supply system is a water supply system that ensures users can obtain hot water with the water volume, water temperature, water pressure and water quality meeting the design requirements on time. Hot water supply can meet the basic living needs of residents such as daily bathing, laundry, cooking, etc., improving the living quality and comfort of residents. Hot water supply helps to improve public health conditions, reduce the occurrence of various diseases caused by poor water quality, and ensure the normal activities of society. In addition, hot water supply can also be used for flushing, dilution, sprinkling and washing, etc., to maintain the sanitary environment of towns.

[0003] In a system that conventionally uses a pressurized water supply pump for hot water supply and return water circulation, the start and stop control of the pressurized water supply pump adopts dual control of pressure and temperature. A temperature probe is set on the hot water return main pipe near the hot water machine room, and the pressurized water supply pump is equipped with a pressure device. When the temperature probe monitors that the water temperature is lower than the set value or the pressure device monitors that the water pressure in the pipe network is lower than the set value, the pressurized water supply pump is started. When the temperature probe monitors that the water temperature reaches the set value and the pressure device monitors that the water pressure in the pipe network reaches the set value, the pressurized water supply pump stops.

[0004] Currently, in a system that conventionally uses a pressurized water supply pump for hot water supply and return water circulation, the water supply to each water usage point cannot be accurately controlled. When the water supply range is large, the hot water temperature in the pipe network at some end water usage points has become relatively low due to heat loss, but at this time, the water temperature in the hot water return main pipe near the hot water machine room is still relatively high, resulting in the situation that the pressurized water supply pump is not started. At this time, some end water usage points cannot provide hot water with sufficient temperature in time, resulting in poor water usage comfort. Moreover, the hot water consumption at some end water usage points is small or the hot water has not been used for a long time, but when the pressurized water supply pump is running, the hot water still circulates in the entire pipe network, resulting in considerable ineffective heat loss and energy consumption of the pressurized water supply pump. Summary of the Invention

[0005] The main purpose of this application is to provide an optimization method, device, equipment and storage medium for hot water supply in residential buildings, so as to solve the problem in the prior art that for the hot water supply in residential buildings, the hot water temperature in the pipe network at some end water usage points has become relatively low due to heat loss, but at this time, the water temperature in the hot water return main pipe near the hot water machine room is still relatively high, resulting in the situation that the pressurized water supply pump is not started. At this time, some end water usage points cannot provide hot water with sufficient temperature in time, resulting in poor water usage comfort. Moreover, the hot water consumption at some end water usage points is small or the hot water has not been used for a long time, but when the pressurized water supply pump is running, the hot water still circulates in the entire pipe network, resulting in considerable ineffective heat loss and energy consumption of the pressurized water supply pump.

[0006] To achieve the above object, the present application provides the following technical solutions:

[0007] A method for optimizing the hot water supply of a residential building, the residential building having at least two floors, each floor having a water supply pipe and a water return pipe communicating with each other, each water supply pipe having at least two hot water usage ends, all water supply pipes being connected to a hot water supply end outside the residential building, all water return pipes being connected to a hot water return end outside the residential building, and hot water monitoring components being installed at all hot water usage ends, the hot water supply end, and the hot water return end. The hot water supply optimization method includes:

[0008] Step S1, obtaining the water usage data of each hot water usage end respectively through the hot water monitoring component based on a plurality of preset time periods;

[0009] Step S2, obtaining the water supply data of the hot water supply end and the water return data of the hot water return end through the hot water monitoring component based on a plurality of the preset time periods;

[0010] Step S3, obtaining the temperature difference and the pressure difference between the water supply data and the water return data based on the same preset time period;

[0011] Step S4, defining all the water usage data of the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable;

[0012] Step S5, analyzing the first linear regression relationship between the first dependent variable and all the independent variables of all the preset time periods through multiple linear regression;

[0013] Step S6, analyzing the second linear regression relationship between the second dependent variable and all the independent variables of all the preset time periods through the multiple linear regression;

[0014] Step S7, predicting a plurality of future temperature differences through the first linear regression relationship and predicting a plurality of future pressure differences through the second linear regression relationship based on a plurality of preset prediction steps;

[0015] Step S8, obtaining the first future timestamp when all the future temperature differences are greater than or equal to a preset temperature threshold, and the second future timestamp when all the future pressure differences are greater than or equal to a preset pressure threshold;

[0016] Step S9, turning on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turning on the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp.

[0017] As a further improvement of the present application, in step S9, the heating function of the hot water supply end is turned on on time or in advance by a preset duration based on the first future timestamp, and the pressurization function of the hot water supply end is turned on on time or in advance by the preset duration based on the second future timestamp. After that, the following steps are further included:

[0018] Step S10, after the heating function is turned on, obtain the real-time temperature difference between the hot water supply end and the hot water return end through the hot water monitoring component at intervals of the preset time period;

[0019] Step S20, based on each monitoring, determine whether the real-time temperature difference is less than the preset temperature threshold. If so, execute step S30;

[0020] Step S30, turn off the heating function and return to step S1.

[0021] As a further improvement of the present application, in step S9, the heating function of the hot water supply end is turned on on time or in advance by a preset duration based on the first future timestamp, and the pressurization function of the hot water supply end is turned on on time or in advance by the preset duration based on the second future timestamp. After that, the following steps are further included:

[0022] Step S100, after the pressurization function is turned on, obtain the real-time pressure difference between the hot water supply end and the hot water return end through the hot water monitoring component at intervals of the preset time period;

[0023] Step S200, based on each monitoring, determine whether the real-time pressure difference is less than the preset pressure threshold. If so, go to step S300;

[0024] Step S300, turn off the pressurization function and return to step S1.

[0025] As a further improvement of the present application, in step S9, the heating function of the hot water supply end is turned on on time or in advance by a preset duration based on the first future timestamp, and the pressurization function of the hot water supply end is turned on on time or in advance by the preset duration based on the second future timestamp. After that, the following steps are further included:

[0026] Step S1000, obtain the digital model of the residential building;

[0027] Step S2000, obtain the visualization styles of all water supply pipes, all water return pipes, all hot water usage ends, the hot water supply end, and the hot water return end and input them into the digital model;

[0028] Step S3000, obtain the temperature difference and pressure difference at the current moment and input them into the digital model;

[0029] Step S4000, input the first future timestamp and the second future timestamp into the digital model in a countdown style respectively;

[0030] Step S5000, send the digital model to an external visual monitoring terminal.

[0031] As a further improvement of this application, in step S5000, after sending the digital model to the external visual monitoring terminal, it further includes:

[0032] Step S10000, when the countdown of the first future timestamp reaches zero, generate a heating function activation instruction;

[0033] Step S20000, send the heating function activation instruction to an external hot water supply terminal;

[0034] Step S30000, when the countdown of the second future timestamp reaches zero, generate a pressurization function activation instruction;

[0035] Step S40000, send the pressurization function activation instruction to the external hot water supply terminal.

[0036] To achieve the above object, this application also provides the following technical solutions:

[0037] A hot water supply optimization device for a residential building, the hot water supply optimization device is applied to the hot water supply optimization method as described above, and the hot water supply optimization device includes:

[0038] A water usage data acquisition module, configured to acquire the water usage data of each hot water usage terminal respectively through the hot water monitoring component based on a plurality of the preset time periods;

[0039] A supply and return water data acquisition module, configured to acquire the supply water data of the hot water supply terminal and the return water data of the hot water return terminal through the hot water monitoring component based on a plurality of the preset time periods;

[0040] A temperature difference and pressure difference data acquisition module, configured to acquire the temperature difference and pressure difference between the supply water data and the return water data based on the same preset time period;

[0041] A data variable definition module, configured to define all the water usage data of the same preset time period as a set of independent variables, define the temperature difference as the first dependent variable, and define the pressure difference as the second dependent variable;

[0042] A temperature difference data variable analysis module, configured to analyze the first linear regression relationship between the first dependent variable and all the independent variables of all the preset time periods through multiple linear regression;

[0043] Differential pressure data variable analysis module, configured to analyze the second linear regression relationship between the second dependent variable and all independent variables for all preset time periods through the multiple linear regression;

[0044] Temperature differential pressure data prediction module, configured to predict a plurality of future temperature differences through the first linear regression relationship and predict a plurality of future pressure differences through the second linear regression relationship based on a plurality of preset prediction steps;

[0045] Future temperature differential pressure timestamp acquisition module, configured to acquire a first future timestamp when all future temperature differences are greater than or equal to a preset temperature threshold, and a second future timestamp when all future pressure differences are greater than or equal to a preset pressure threshold;

[0046] Hot water supply end function activation module, configured to activate the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and activate the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp.

[0047] To achieve the above object, the present application also provides the following technical solutions:

[0048] An electronic device, comprising a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, the hot water supply optimization method as described above is implemented.

[0049] To achieve the above object, the present application also provides the following technical solutions:

[0050] A storage medium, the storage medium storing program instructions, and when the program instructions are executed by a processor, the hot water supply optimization method as described above can be implemented.

[0051] This application obtains the water usage data of each hot water usage end through a hot water monitor based on several preset time periods; obtains the water supply data of the hot water supply end and the return water data of the hot water return end through the hot water monitor based on several preset time periods; obtains the temperature difference and pressure difference between the water supply data and the return water data based on the same preset time period; defines all the water usage data in the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable; analyzes the first linear regression relationship between the first dependent variable and all independent variables in all preset time periods through multiple linear regression; analyzes the second linear regression relationship between the second dependent variable and all independent variables in all preset time periods through multiple linear regression; predicts several future temperature differences based on the first linear regression relationship and several future pressure differences based on the second linear regression relationship for several preset prediction steps; obtains the first future timestamp when all future temperature differences are greater than or equal to a preset temperature threshold, and the second future timestamp when all future pressure differences are greater than or equal to a preset pressure threshold; turns on the heating function of the hot water supply end on time or in advance of a preset duration based on the first future timestamp, and turns on the pressurization function of the hot water supply end on time or in advance of a preset duration based on the second future timestamp. This application analyzes the relationship between the water temperature and the water usage habits of the residents, and the relationship between the water pressure and the water usage habits of the residents respectively. Both are from the same hot water supply system, so that although the two sets of data are linearly regressed separately, there is a correlation between the two linear regressions, making the two types of data obtained by subsequent predictions related to each other, without data deviation. Moreover, the obtained linear regression coefficients intuitively reflect the water usage habits of each household in this residential building, making the results of the predicted data also strongly correlated, making the predicted data accurate. Finally, a corresponding supply plan is formulated according to the performance of the predicted data, so that each household can use hot water smoothly and efficiently. The whole process of this application is automatically calculated by the computer without manual participation, avoiding the empirical error of subjective adjustment. Moreover, this application realizes the prediction functions of heating and pressurization, making the adjustment of hot water supply have foresight. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic flowchart of the steps of an embodiment of the hot water supply optimization method for a residential building in this application;

[0053] Figure 2 It is a schematic diagram of the functional modules of an embodiment of the hot water supply optimization device for a residential building in this application;

[0054] Figure 3 It is a schematic diagram of the preferred device setting method for the actual application of an embodiment of the hot water supply optimization device for a residential building in this application;

[0055] Figure 4 It is a schematic diagram of the structure of an embodiment of an electronic device in this application;

[0056] Figure 5 This is a schematic structural diagram of an embodiment of the storage medium of the present application. Specific embodiments

[0057] 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 only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0058] The terms "first", "second", and "third" in the present application are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", and "third" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of the present application are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0059] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in connection with the embodiments may be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0060] Such as Figure 1As shown in the figure, this embodiment provides an embodiment of an optimization method for hot water supply in residential buildings. In this embodiment, the residential building has at least two floors, and each floor has a water supply pipe and a return water pipe that are interconnected. Each water supply pipe has at least two hot water usage ends. All water supply pipes are connected to the hot water supply end outside the residential building, and all return water pipes are connected to the hot water return end outside the residential building. Hot water monitoring components are installed at all hot water usage ends, hot water supply ends, and hot water return ends.

[0061] Preferably, in practical applications, since the hot water monitoring component can monitor the water temperature and water pressure simultaneously at the same monitoring position, the hot water monitoring component can be set as a water temperature sensor and a pressure gauge at the same position, or a water temperature and water pressure combined meter can also be used. The acquisition of water temperature and water pressure is a mature existing technology. The acquisition of water temperature and water pressure in this embodiment is a conventional application, and the detailed structures and models of the above instruments will not be elaborated in this embodiment.

[0062] Specifically, the hot water supply optimization method includes the following steps:

[0063] Step S1, obtain the water usage data of each hot water usage end through the hot water monitoring component based on a number of preset time periods.

[0064] Preferably, since water usage behaviors such as washing hands and getting wet are short-term behaviors, which are basically from a few seconds to dozens of seconds, and long-term behaviors such as doing laundry and taking a bath are basically from dozens of minutes to one hour, and water usage behaviors have the random characteristic of multi-user superposition. In order to make the prediction results of this embodiment accurate, more short-term preset time periods and preset prediction steps can be appropriately selected, such as 3 seconds, 5 seconds, and 10 seconds.

[0065] Step S2, obtain the water supply data of the hot water supply end and the return water data of the hot water return end through the hot water monitoring component based on a number of preset time periods.

[0066] Preferably, this embodiment makes predictions based on the temperature difference and pressure difference. Therefore, the water supply data and the return water data can both include the water supply temperature, water supply pressure, return water temperature, and return water pressure. Moreover, the higher the water consumption per unit time, the greater the temperature difference and pressure difference. The two differences have a positive linear relationship with the water consumption, providing a basis for subsequent relationship analysis and prediction in the embodiment.

[0067] Step S3, obtain the temperature difference and pressure difference between the water supply data and the return water data based on the same preset time period.

[0068] Preferably, the temperature difference should be obtained based on two temperature values with the same measurement unit, and the same applies to the pressure difference.

[0069] Step S4: Define all the water usage data within the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable.

[0070] Step S5: Analyze the first linear regression relationship between the first dependent variable and all independent variables for all preset time periods through multiple linear regression.

[0071] Preferably, in this embodiment, LASSO linear regression is preferred.

[0072] Step S6: Analyze the second linear regression relationship between the second dependent variable and all independent variables for all preset time periods through multiple linear regression.

[0073] Step S7: Predict a number of future temperature differences through the first linear regression relationship and a number of future pressure differences through the second linear regression relationship based on a number of preset prediction steps.

[0074] Step S8: Obtain the first future timestamp when all future temperature differences are greater than or equal to the preset temperature threshold, and the second future timestamp when all future pressure differences are greater than or equal to the preset pressure threshold.

[0075] Preferably, the preset temperature threshold can be set to half of the maximum temperature. For example, if the supply water temperature is 80 degrees Celsius, then the preset temperature threshold is 40 degrees Celsius. That is, when the return water temperature is 80 - 40 = 40 degrees Celsius, it indicates that the hot water usage in the residential building is large, and the heating function is turned on.

[0076] Preferably, the preset pressure threshold can be set to half of the maximum pressure. For example, if the supply water pressure is 0.8 MPa, then the preset pressure threshold is 0.4 MPa. That is, when the return water pressure is 0.8 - 0.4 = 0.4 MPa, it indicates that the hot water usage in the residential building is large, and the pressurization function is turned on.

[0077] Step S9: Turn on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turn on the pressurization function of the hot water supply end on time or in advance by a preset duration based on the second future timestamp.

[0078] Preferably, the preset duration can be set according to actual needs. Since it takes a certain amount of time to heat water, the heating function can be turned on 15 to 30 minutes in advance, while pressurization has an instantaneous characteristic, so pressurization can be done 1 minute in advance.

[0079] Furthermore, in step S9, after turning on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turning on the pressurization function of the hot water supply end on time or in advance by a preset duration based on the second future timestamp, the following steps are further included:

[0080] Step S10, after the heating function is turned on, obtain the real-time temperature difference between the hot water supply end and the hot water return end at preset time intervals through the hot water monitoring component.

[0081] Step S20, based on each monitoring, determine whether the real-time temperature difference is less than the preset temperature threshold. If so, execute Step S30.

[0082] Step S30, turn off the heating function and return to Step S1.

[0083] Preferably, the threshold settings in Steps S10 to S30 can be the same as the above-mentioned threshold settings.

[0084] Further, in Step S9, turn on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turn on the pressurization function of the hot water supply end on time or in advance by a preset duration based on the second future timestamp. After that, the following steps are further included:

[0085] Step S100, after the pressurization function is turned on, obtain the real-time pressure difference between the hot water supply end and the hot water return end at preset time intervals through the hot water monitoring component.

[0086] Step S200, based on each monitoring, determine whether the real-time pressure difference is less than the preset pressure threshold. If so, go to Step S300.

[0087] Step S300, turn off the pressurization function and return to Step S1.

[0088] Preferably, the threshold settings in Steps S100 to S300 can be the same as the above-mentioned threshold settings.

[0089] Further, in Step S9, turn on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turn on the pressurization function of the hot water supply end on time or in advance by a preset duration based on the second future timestamp. After that, it further includes:

[0090] Step S1000, obtain the digital model of the residential building.

[0091] Step S2000, obtain the visualization styles of all water supply pipes, all water return pipes, all hot water usage ends, the hot water supply end, and the hot water return end and input them into the digital model.

[0092] Step S3000, obtain the current temperature difference and pressure difference and input them into the digital model.

[0093] Step S4000, input the first future timestamp and the second future timestamp into the digital model in the form of a countdown respectively.

[0094] Step S5000, send the digital model to an external visual monitoring terminal.

[0095] Further, in step S5000, after sending the digital model to an external visual monitoring terminal, the following steps are also included:

[0096] Step S10000, when the countdown of the first future timestamp reaches zero, generate a heating function activation instruction.

[0097] Step S20000, send the heating function activation instruction to an external hot water supply terminal.

[0098] Step S30000, when the countdown of the second future timestamp reaches zero, generate a pressurization function activation instruction.

[0099] Step S40000, send the pressurization function activation instruction to an external hot water supply terminal.

[0100] In this embodiment, water usage data of each hot water usage end is obtained respectively by a hot water monitor based on a number of preset time periods; water supply data of the hot water supply end and return water data of the hot water return end are obtained by the hot water monitor based on a number of preset time periods; the temperature difference and pressure difference between the water supply data and the return water data are obtained based on the same preset time period; all water usage data in the same preset time period is defined as a set of independent variables, the temperature difference is defined as the first dependent variable, and the pressure difference is defined as the second dependent variable; the first linear regression relationship between the first dependent variable and all independent variables in all preset time periods is analyzed through multiple linear regression; the second linear regression relationship between the second dependent variable and all independent variables in all preset time periods is analyzed through multiple linear regression; a number of future temperature differences are predicted based on the first linear regression relationship and a number of future pressure differences are predicted based on the second linear regression relationship for a number of preset prediction steps; the first future timestamp when all future temperature differences are greater than or equal to a preset temperature threshold and the second future timestamp when all future pressure differences are greater than or equal to a preset pressure threshold are obtained; the heating function of the hot water supply end is turned on on time or in advance by a preset duration based on the first future timestamp, and the pressurization function of the hot water supply end is turned on on time or in advance by a preset duration based on the second future timestamp. This embodiment analyzes the relationship between the water temperature and the water usage habits of the residents, and the relationship between the water pressure and the water usage habits of the residents respectively. Both are from the same hot water supply system, so that although the two sets of data are linearly regressed separately, the two linear regressions are related to each other, making the two types of data obtained by subsequent prediction related to each other and not deviating from the data. Moreover, the obtained linear regression coefficients intuitively reflect the water usage habits of each household in this residential building, making the results of the predicted data also strongly related, making the predicted data accurate. Finally, a corresponding supply plan is formulated according to the performance of the predicted data, so that each household can use hot water smoothly and efficiently. This embodiment is calculated automatically by a computer throughout the process without manual participation, avoiding the empirical error of subjective adjustment. Moreover, this embodiment realizes the prediction functions of heating and pressurization, making the adjustment of hot water supply have foresight.

[0101] As Figure 2 shown, this embodiment provides an embodiment of a hot water supply optimization device for a residential building. In this embodiment, the hot water supply optimization device is applied to the hot water supply optimization method in the above embodiment.

[0102] Specifically, the hot water supply optimization device includes a water usage data acquisition module 100, a water supply and return data acquisition module 200, a temperature and pressure difference data acquisition module 300, a data variable definition module 400, a temperature difference data variable analysis module 500, a pressure difference data variable analysis module 600, a temperature and pressure difference data prediction module 700, a future temperature and pressure difference timestamp acquisition module 800, and a hot water supply end function activation module 900, which are electrically connected in sequence.

[0103] Among them, the water usage data acquisition module 100 is used to acquire the water usage data of each hot water usage end respectively through hot water monitoring components based on a plurality of preset time periods; the supply and return water data acquisition module 200 is used to acquire the supply water data of the hot water supply end and the return water data of the hot water return end through hot water monitoring components based on a plurality of preset time periods; the temperature difference and pressure difference data acquisition module 300 is used to acquire the temperature difference and pressure difference between the supply water data and the return water data based on the same preset time period; the data variable definition module 400 is used to define all the water usage data of the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable; the temperature difference data variable analysis module 500 is used to analyze the first linear regression relationship between the first dependent variable and all independent variables of all preset time periods through multiple linear regression; the pressure difference data variable analysis module 600 is used to analyze the second linear regression relationship between the second dependent variable and all independent variables of all preset time periods through multiple linear regression; the temperature difference and pressure difference data prediction module 700 is used to predict a plurality of future temperature differences through the first linear regression relationship and predict a plurality of future pressure differences through the second linear regression relationship based on a plurality of preset prediction steps; the future temperature difference and pressure difference timestamp acquisition module 800 is used to acquire the first future timestamp when all future temperature differences are greater than or equal to a preset temperature threshold and the second future timestamp when all future pressure differences are greater than or equal to a preset pressure threshold; the hot water supply end function activation module 900 is used to activate the heating function of the hot water supply end on time or in advance for a preset duration based on the first future timestamp, and activate the pressurization function of the hot water supply end on time or in advance for a preset duration based on the second future timestamp.

[0104] Preferably, referring to Figure 3 , this embodiment provides a feasible preferred device setting method in practical applications. In order to make Figure 3 's label not conflict with Figure 2 's label, Figure 2 , Figure 4 , Figure 5 all adopt the double-zero labeling method.

[0105] Furthermore, the hot water supply optimization device further includes a real-time temperature difference acquisition module, a real-time temperature difference judgment module, and a heating function shutdown module that are electrically connected in sequence; the real-time temperature difference acquisition module is electrically connected to the hot water supply end function activation module 900, and the heating function shutdown module is electrically connected to the water usage data acquisition module 100.

[0106] Among them, the real-time temperature difference acquisition module is used to obtain the real-time temperature difference between the hot water supply end and the hot water return end through the hot water monitoring component at preset time intervals after the heating function is turned on; the real-time temperature difference judgment module is used to judge whether the real-time temperature difference is less than the preset temperature threshold based on each monitoring; the heating function shutdown module is used to, if so, turn off the heating function and return to execute the water usage data acquisition module 100.

[0107] Furthermore, the hot water supply optimization device further includes a real-time pressure difference acquisition module, a real-time pressure difference judgment module, and a pressurization function shutdown module that are electrically connected in sequence; the real-time pressure difference acquisition module is electrically connected to the hot water supply end function activation module 900, and the pressurization function shutdown module is electrically connected to the water usage data acquisition module 100.

[0108] Among them, the real-time pressure difference acquisition module is used to obtain the real-time pressure difference between the hot water supply end and the hot water return end through the hot water monitoring component at preset time intervals after the pressurization function is turned on; the real-time pressure difference judgment module is used to judge whether the real-time pressure difference is less than the preset pressure threshold based on each monitoring; the pressurization function shutdown module is used to, if so, turn off the pressurization function and return to execute the water usage data acquisition module 100.

[0109] Furthermore, the hot water supply optimization device further includes a residential building digital model acquisition module, a visualization style input module, a temperature-pressure difference input module, a countdown style input module, and a digital model sending module that are electrically connected in sequence; the residential building digital model acquisition module is electrically connected to the hot water supply end function activation module 900.

[0110] Among them, the residential building digital model acquisition module is used to acquire the digital model of the residential building; the visualization style input module is used to acquire the visualization styles of all water supply pipes, all water return pipes, all hot water usage ends, the hot water supply end, and the hot water return end and input them into the digital model; the temperature-pressure difference input module is used to acquire the temperature difference and pressure difference at the current moment and input them into the digital model; the countdown style input module is used to input the first future timestamp and the second future timestamp into the digital model in the form of a countdown; the digital model sending module is used to send the digital model to an external visual monitoring terminal.

[0111] Furthermore, the hot water supply optimization device further includes a heating function activation instruction generation module, a heating function activation instruction sending module, a pressurization function activation instruction generation module, and a pressurization function activation instruction sending module that are electrically connected in sequence; the heating function activation instruction generation module is electrically connected to the digital model sending module.

[0112] Among them, the heating function activation instruction generation module is used to generate a heating function activation instruction when the countdown of the first future timestamp reaches zero; the heating function activation instruction sending module is used to send the heating function activation instruction to the external hot water supply end; the pressurization function activation instruction generation module is used to generate a pressurization function activation instruction when the countdown of the second future timestamp reaches zero; the pressurization function activation instruction sending module is used to send the pressurization function activation instruction to the external hot water supply end.

[0113] It should be noted that this embodiment is a functional module item embodiment based on the above method embodiment. For additional content such as the preferences, expansions, limitations, and illustrative examples of this embodiment, please refer to the above method embodiment, and this embodiment will not be elaborated here.

[0114] This embodiment respectively obtains the water usage data of each hot water usage end through a hot water monitor based on a number of preset time periods; obtains the water supply data of the hot water supply end and the return water data of the hot water return end through the hot water monitor based on a number of preset time periods; obtains the temperature difference and pressure difference between the water supply data and the return water data based on the same preset time period; defines all the water usage data of the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable; analyzes the first linear regression relationship between the first dependent variable and all the independent variables of all the preset time periods through multiple linear regression; analyzes the second linear regression relationship between the second dependent variable and all the independent variables of all the preset time periods through multiple linear regression; predicts a number of future temperature differences based on the first linear regression relationship and a number of future pressure differences based on the second linear regression relationship based on a number of preset prediction steps; obtains the first future timestamp when all the future temperature differences are greater than or equal to the preset temperature threshold, and the second future timestamp when all the future pressure differences are greater than or equal to the preset pressure threshold; activates the heating function of the hot water supply end on time or in advance of the preset duration based on the first future timestamp, and activates the pressurization function of the hot water supply end on time or in advance of the preset duration based on the second future timestamp. This embodiment respectively analyzes the relationship between the water temperature and the water usage habits of the residents, and the relationship between the water pressure and the water usage habits of the residents. Both are from the same hot water supply system, so that although the two sets of data are respectively subjected to linear regression, the two linear regressions are related to each other, making the two types of data obtained by subsequent prediction related to each other and not deviating from the data. Moreover, the linear regression coefficients obtained by the analysis intuitively reflect the water usage habits of each household in this residential building, making the results of the predicted data also strongly related, making the predicted data accurate. Finally, a corresponding supply plan is formulated according to the performance of the predicted data, so that each household can use hot water smoothly and efficiently. This embodiment is fully automatically calculated by a computer without the need for manual participation, avoiding the empirical error of subjective adjustment. Moreover, this embodiment realizes the prediction functions of heating and pressurization, making the adjustment of hot water supply have foresight.

[0115] As shown Figure 4 in the figure, an embodiment of an electronic device is provided in this embodiment. In this embodiment, the electronic device 1000 includes a processor 10001 and a memory 10002 coupled to the processor 10001.

[0116] The memory 10002 stores program instructions for implementing the hot water supply optimization method of the residential building in any of the above embodiments.

[0117] The processor 10001 is configured to execute the program instructions stored in the memory 10002 to optimize the hot water supply of the residential building.

[0118] Among them, the processor 10001 can also be called a CPU (Central Processing Unit, central processing unit). The processor 10001 may be an integrated circuit chip with data processing capabilities. The processor 10001 can also be a general-purpose processor, a digital data processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0119] Furthermore, Figure 5 is a schematic structural diagram of a storage medium according to an embodiment of the present application. The storage medium 1100 of the embodiment of the present application stores program instructions 11001 that can implement all the above methods. Among them, the program instructions 11001 can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0120] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0121] In addition, in each embodiment of the present application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. The above is only the implementation manner of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of the present application by the same token.

[0122] The specific implementation manners of the present application have been described in detail above, but they are only examples. The present application is not limited to the specific implementation manners described above. For those skilled in the art, any equivalent modification or substitution to the present application is also within the scope of the present application. Therefore, all equal transformations, modifications, improvements, etc. made without departing from the spirit and principle of the present application should be covered within the scope of the present application.

Claims

1. An optimization method for hot water supply in a residential building, the residential building having at least two floors, each floor having a water supply pipe and a water return pipe that are interconnected, each water supply pipe having at least two hot water usage ends, all water supply pipes being connected to a hot water supply end outside the residential building, all water return pipes being connected to a hot water return end outside the residential building, and hot water monitoring components being installed at all hot water usage ends, the hot water supply end, and the hot water return end, characterized in that, The described hot water supply optimization method includes: Step S1, obtaining the water usage data of each hot water usage end respectively through the hot water monitoring component based on a plurality of preset time periods; Step S2, obtaining the water supply data of the hot water supply end and the return water data of the hot water return end through the hot water monitoring component based on a plurality of the preset time periods; Step S3, obtaining the temperature difference and pressure difference between the water supply data and the return water data based on the same preset time period; Step S4, defining all the water usage data of the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable; Step S5, analyzing the first linear regression relationship between the first dependent variable and all the independent variables of all the preset time periods through multiple linear regression; Step S6, analyzing the second linear regression relationship between the second dependent variable and all the independent variables of all the preset time periods through the multiple linear regression; Step S7, predicting a plurality of future temperature differences through the first linear regression relationship and predicting a plurality of future pressure differences through the second linear regression relationship based on a plurality of preset prediction steps; Step S8, obtaining the first future timestamp when all the future temperature differences are greater than or equal to a preset temperature threshold, and the second future timestamp when all the future pressure differences are greater than or equal to a preset pressure threshold; Step S9, turning on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turning on the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp.

2. The optimized hot water supply method according to claim 1, characterized in that Step S9, turning on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turning on the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp. After that, it further includes: Step S10, after the heating function is turned on, obtaining the real-time temperature difference between the hot water supply end and the hot water return end through the hot water monitoring component at intervals of the preset time period; Step S20, judging whether the real-time temperature difference is less than the preset temperature threshold each time of monitoring. If so, execute Step S30; Step S30, turning off the heating function and returning to Step S1.

3. The hot water supply optimization method according to claim 1, characterized in that Step S9, turning on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turning on the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp. After that, it further includes: Step S100, after the pressurization function is turned on, obtaining the real-time pressure difference between the hot water supply end and the hot water return end through the hot water monitoring component at intervals of the preset time period; Step S200, judging whether the real-time pressure difference is less than the preset pressure threshold each time of monitoring. If so, Step S300; Step S300, turning off the pressurization function and returning to Step S1.

4. The hot water supply optimization method according to claim 1, characterized in that Step S9, turn on the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and turn on the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp. After that, it further includes: Step S1000, obtain the digital model of the residential building; Step S2000, obtain the visualization styles of all water supply pipes, all return water pipes, all hot water usage ends, the hot water supply end, and the hot water return end, and input them into the digital model; Step S3000, obtain the temperature difference and pressure difference at the current moment and input them into the digital model; Step S4000, input the first future timestamp and the second future timestamp into the digital model in a countdown style respectively; Step S5000, send the digital model to an external visual monitoring terminal.

5. The hot water supply optimization method according to claim 4, characterized in that Step S5000, send the digital model to an external visual monitoring terminal. After that, it further includes: Step S10000, generate a heating function activation instruction when the countdown of the first future timestamp reaches zero; Step S20000, send the heating function activation instruction to the external hot water supply end; Step S30000, generate a pressurization function activation instruction when the countdown of the second future timestamp reaches zero; Step S40000, send the pressurization function activation instruction to the external hot water supply end.

6. An optimized device for hot water supply of a residential building, the hot water supply optimization device being applied to the hot water supply optimization method according to any one of claims 1 to 5, characterized in that, The hot water supply optimization device includes: A water usage data acquisition module, which is used to acquire the water usage data of each hot water usage end respectively through the hot water monitoring device based on a plurality of the preset time periods; A supply and return water data acquisition module, which is used to acquire the water supply data of the hot water supply end and the return water data of the hot water return end through the hot water monitoring device based on a plurality of the preset time periods; A temperature and pressure difference data acquisition module, which is used to acquire the temperature difference and pressure difference between the water supply data and the return water data based on the same preset time period; A data variable definition module, which is used to define all the water usage data in the same preset time period as a set of independent variables, the temperature difference as the first dependent variable, and the pressure difference as the second dependent variable; A temperature difference data variable analysis module, which is used to analyze the first linear regression relationship between the first dependent variable and all the independent variables in all the preset time periods through multiple linear regression; A pressure difference data variable analysis module, which is used to analyze the second linear regression relationship between the second dependent variable and all the independent variables in all the preset time periods through the multiple linear regression; A temperature and pressure difference data prediction module, which is used to predict a plurality of future temperature differences through the first linear regression relationship and predict a plurality of future pressure differences through the second linear regression relationship based on a plurality of preset prediction steps; A future temperature and pressure difference timestamp acquisition module, which is used to acquire the first future timestamp when all the future temperature differences are greater than or equal to a preset temperature threshold, and the second future timestamp when all the future pressure differences are greater than or equal to a preset pressure threshold; A hot water supply end function activation module, which is used to activate the heating function of the hot water supply end on time or in advance by a preset duration based on the first future timestamp, and activate the pressurization function of the hot water supply end on time or in advance by the preset duration based on the second future timestamp.

7. An electronic device, characterized in that, It includes a processor and a memory coupled to the processor. The memory stores program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the hot water supply optimization method according to any one of claims 1 to 5.

8. A storage medium, characterized in that, Program instructions are stored in the storage medium, and when the program instructions are executed by a processor, they can implement the hot water supply optimization method according to any one of claims 1 to 5.

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