Energy-saving intelligent water heater control method and system and water heater

Abstract

The invention relates to the technical field of water heater control, and particularly discloses an energy-saving intelligent water heater control method and system and a water heater. According to the method, firstly, historical control state information of the water heater is obtained, the historical control degree of the water heater is judged, and a control adjusting threshold value of the water heater is obtained through matching; the application state of the water heater is monitored, and the application control adjustment degree of the water heater is evaluated; the application control regulation degree of the water heater is compared with the control regulation threshold value of the water heater, finally, the water heater is controlled, regulated and optimized, the heating time and temperature of the water heater can be accurately controlled, unnecessary energy waste is avoided, the fault condition caused by improper regulation of the water heater is reduced by monitoring the working state of the water heater, and the service life of the water heater is prolonged. Therefore, the use safety of the water heater is improved, and the experience feeling of a user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water heater control, and in particular to an energy-saving intelligent water heater control method, system and water heater. Background Art

[0002] When controlling a water heater, the performance of the water heater itself is usually the problem, which cannot bring a good user experience. At the same time, traditional water heater control has problems such as high cost investment and high user operation requirements. Therefore, it is necessary to introduce a new water heater control technology to reduce investment costs and reduce user operation requirements. By performing multi-dimensional data processing on the water heater in multiple application scenarios, the control status of the water heater can be obtained, which can improve the accuracy of water heater control and user experience, and reduce the operational difficulty of water heater control.

[0003] For example, the invention patent with announcement number CN104778631B is a residential user electricity consumption mode optimization method for demand response, which includes the following steps: establishing a load response dynamic model of typical residential users' electrical equipment, including air conditioning load response model, water heater load response model and lighting load response model; determining the objective function of the electricity consumption mode optimization model with the goal of minimizing user electricity cost and maximizing electricity consumption mode satisfaction; establishing constraints of the electricity consumption mode optimization model, including indoor temperature, water heater water temperature, and lighting system adjustability constraints; using a particle swarm algorithm combined with grey theory to solve the model, obtain the state control variables of air conditioners, water heaters, and lighting loads in each time period, and determine the optimal operation mode of each electrical equipment; the above application can be applied to optimization examples of different residential electricity consumption scenarios, providing a specific reference plan for residential users to participate in demand response projects, and achieving the optimization effect of reducing electricity costs and load peaks while meeting electricity demand.

[0004] However, in the process of implementing the above-mentioned application embodiments, the present application discovered that the above-mentioned technology has at least the following technical problems: when ensuring the water temperature of the water heater, if the temperature of the water heater has reached no less than 60 degrees after one hour of heating, then forcing the water heater to be turned on for 3 hours is not enough to support the user's electricity comfort and satisfaction. The temperature of the water heater at each time point should be considered to ensure that the water heater is no longer in a heating state after reaching the ideal temperature, thereby satisfying the user's electricity comfort and satisfaction. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an energy-saving intelligent water heater control method, system and water heater, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an energy-saving intelligent water heater control method, including: obtaining historical control status information of the water heater, determining the historical control degree of the water heater, and matching to obtain the control adjustment threshold of the water heater; monitoring the application status of the water heater, and evaluating the application control adjustment degree of the water heater; comparing the application control adjustment degree of the water heater with the control adjustment threshold of the water heater, and finally optimizing the control and adjustment of the water heater.

[0007] As a further method, the control and regulation optimization of the water heater is carried out, and the specific analysis process is: comparing the application control regulation degree of the water heater with the control regulation threshold of the water heater, if the application control regulation degree of the water heater is higher than the control regulation threshold of the water heater, then performing difference processing on the application control regulation degree of the water heater and the control regulation threshold of the water heater to obtain the control regulation deviation value of the water heater, matching the control regulation deviation value of the water heater with the required regulation optimization degree corresponding to each control regulation deviation value interval defined in the intelligent control cloud platform to obtain the required regulation optimization degree of the water heater, and finally performing control and regulation optimization on the water heater.

[0008] As a further method, the application control adjustment degree of the water heater, the specific analysis process is:

[0009]

[0010] Where β represents the application control adjustment degree of the water heater, δ represents the influence coefficient of the water heater application situation, γ represents the influence coefficient of the water heater resource consumption, and g represents the influence coefficient of the water heater resource consumption. 1 It is represented by the weight factor corresponding to the predefined water heater application impact coefficient, g 2 It is represented as the weight factor corresponding to the predefined water heater resource consumption impact coefficient, and e is a natural constant.

[0011] As a further method, the water heater application situation influence coefficient, the specific analysis process is: according to the application status of the water heater, extract the water heater application situation related information and the water heater resource consumption related information; according to the water heater application situation related information, extract the number of heating times of the water heater within the set application monitoring period, and compare it with the duration corresponding to the application monitoring period to obtain the heating frequency of the water heater within the application monitoring period; obtain the water temperature value of the water heater at each application time point, and compare it with the water temperature adaptation value defined in the intelligent control cloud platform, thereby screening out the number of application time points corresponding to the water temperature value of the water heater higher than the temperature adaptation value, and record it as the number of high temperature time points of the water heater; according to the water temperature value of the water heater at each application time point, construct the water temperature change curve of the water heater, and extract and count the temperature rise angle values ​​corresponding to each temperature rise of the water heater; from the intelligent control cloud platform, extract the heating limit frequency and the temperature rise angle allowable value, and comprehensively analyze the water heater application situation influence coefficient.

[0012] As a further method, the water heater resource consumption impact coefficient has the following specific analysis process: based on the water heater resource consumption related information, the number of times the water heater is used within the set application monitoring cycle and the water consumption of each use are extracted; from the intelligent control cloud platform, the reference number of uses and the permitted water consumption are extracted, and the water heater resource consumption impact coefficient is comprehensively analyzed.

[0013] As a further method, the control adjustment threshold of the water heater is obtained by matching. The specific matching process is: by obtaining the historical control state information of the water heater, extracting the historical working state association information of the water heater, the historical energy consumption association information of the water heater and the historical maintenance association information of the water heater, respectively determining the influence degree coefficient of the historical working state of the water heater, the influence degree coefficient of the historical energy consumption of the water heater and the influence degree coefficient of the historical maintenance of the water heater, and comprehensively analyzing them to obtain the historical control degree of the water heater. The specific analysis process is:

[0014]

[0015] Where α represents the historical control degree of the water heater, It is expressed as the influence coefficient of the historical working status of the water heater, is the influence coefficient of the historical energy consumption of the water heater, τ is the influence coefficient of the historical maintenance of the water heater, b 1 It is represented by the weight factor corresponding to the predefined influence coefficient of the historical working state of the water heater, b 2 It is represented by the weight factor corresponding to the predefined coefficient of the historical energy consumption of the water heater, b 3It is represented as the weight factor corresponding to the predefined water heater historical maintenance influence coefficient, and e is a natural constant; the historical control degree of the water heater is matched with the control adjustment threshold corresponding to each historical control degree defined in the intelligent control cloud platform to obtain the control adjustment threshold of the water heater.

[0016] As a further method, the influence coefficient of the historical working state of the water heater is specifically analyzed as follows: based on the related information of the historical working state of the water heater, the heating duration, the average heating power and the water level change difference of the water heater within the set historical working detection cycle are extracted; from the intelligent control cloud platform, the heating duration reference duration, the heating limit power and the water level change reference difference are extracted to comprehensively analyze the influence coefficient of the historical working state of the water heater.

[0017] As a further method, the water heater historical energy consumption impact coefficient and the water heater historical maintenance impact coefficient have a specific analysis process as follows: based on the water heater historical energy consumption related information, the historical average electricity consumption of the water heater within the set historical working detection cycle and the historical electricity load at each working time point are extracted; from the intelligent control cloud platform, the historical electricity consumption boundary quantity and the historical electricity load boundary quantity are extracted, and the water heater historical energy consumption impact coefficient is comprehensively analyzed; based on the water heater historical maintenance related information, the number of automatic cleaning times of the water heater within the set historical working detection cycle is extracted, and compared with the duration corresponding to the historical working detection cycle, the automatic cleaning frequency of the water heater within the historical working detection cycle is obtained; from the intelligent control cloud platform, the automatic cleaning reference number and the cleaning reference frequency are extracted, and the water heater historical maintenance impact coefficient is comprehensively analyzed.

[0018] The second aspect of the present invention provides an energy-saving intelligent water heater control system, including: a control adjustment threshold matching module, which is used to obtain the historical control status information of the water heater, determine the historical control degree of the water heater, and match the control adjustment threshold of the water heater; an application control adjustment degree evaluation module, which is used to monitor the application status of the water heater and evaluate the application control adjustment degree of the water heater; a control adjustment optimization module, which is used to compare the application control adjustment degree of the water heater with the control adjustment threshold of the water heater, and finally optimize the control adjustment of the water heater.

[0019] The third aspect of the present invention provides an energy-saving water heater, comprising: an energy-saving water heater and an intelligent control cloud platform; the energy-saving water heater and the intelligent control cloud platform are connected via the Internet, and the water heater is intelligently controlled via a remote monitoring function; a power sensor for obtaining the heating power of the water heater at each working time point; a water level sensor for obtaining the water level of the water heater at the initial time point and the end time point of a set historical working detection cycle; a temperature sensor for obtaining the water temperature value of the water heater at each application time point; a processor for obtaining the heating power, water level and water temperature values ​​and performing analysis and processing, thereby controlling, adjusting and optimizing the water heater.

[0020] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0021] (1) The present invention provides an energy-saving intelligent water heater control method, system and water heater. First, the historical control degree of the water heater is determined, and the control adjustment threshold of the water heater is matched; the applied control adjustment degree of the water heater is evaluated and compared with the control adjustment threshold of the water heater, and finally the control adjustment of the water heater is optimized. The heating time and temperature of the water heater can be accurately controlled to avoid unnecessary energy waste. By monitoring the working status of the water heater, it helps to reduce malfunctions caused by improper adjustment of the water heater, thereby improving the safety of the water heater and enhancing the user experience.

[0022] (2) The present invention obtains the historical control status information of the water heater, determines the historical control degree of the water heater, and matches the control adjustment threshold of the water heater. It can accurately obtain the control status of the water heater when it is not in use, and provide more accurate data support for the subsequent optimization of the control and adjustment of the water heater. At the same time, it can predict the occurrence of water heater failures and ensure the stable operation of the water heater by taking corresponding maintenance measures in a timely manner.

[0023] (3) The present invention monitors the application status of the water heater and evaluates the application control adjustment degree of the water heater; compares the application control adjustment degree of the water heater with the control adjustment threshold of the water heater, and finally optimizes the control and adjustment of the water heater. It can grasp the energy usage of the water heater in real time and provide a suitable usage status according to the actual needs of the user, thereby optimizing the energy utilization efficiency of the water heater and improving the user's comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0025] Figure 1The figure is a schematic flow chart of the method steps of the present invention.

[0026] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0027] Figure 3 It is a schematic diagram of the water temperature change line involved in the present invention.

[0028] Figure numerals: 1, temperature rise angle value, 2, first horizontal straight line. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0030] Reference Figure 1 As shown, the first aspect of the present invention provides an energy-saving intelligent water heater control method, including: obtaining historical control status information of the water heater, determining the historical control degree of the water heater, and matching to obtain the control adjustment threshold of the water heater.

[0031] Specifically, the influence coefficient of the historical working state of the water heater is analyzed in the following specific process:

[0032] According to the historical control state information of the water heater, historical working state related information of the water heater, historical energy consumption related information of the water heater and historical maintenance related information of the water heater are extracted.

[0033] According to the historical working status associated information of the water heater, the heating duration, heating power average value and water level change difference of the water heater within the set historical working detection cycle are extracted, wherein the heating duration is obtained by directly obtaining the heating start time and heating end time of the water heater within the historical working detection cycle from the intelligent control cloud platform, and the heating start time and heating end time are processed by difference, so as to obtain the heating duration of the water heater within the set historical working detection cycle; the heating power average value of the water heater within the set historical working detection cycle is obtained by real-time acquisition of the heating power of the water heater at each working time point through the power sensor carried by the water heater itself, and the heating power average value of the water heater within the set historical working detection cycle is obtained by calculation; the water level change difference of the water heater within the set historical working detection cycle is located by the water level sensor carried by the water heater itself, and the water level of the water heater at the initial time point and the end time point of the set historical working detection cycle is located, and the water level change difference of the water heater within the set historical working detection cycle is determined by difference processing.

[0034] The reference duration of heating, the defined heating power and the reference difference of water level change are extracted from the intelligent control cloud platform.

[0035] The influence coefficient of the historical working state of the water heater is comprehensively analyzed. In a specific embodiment, the different working states of the water heater can be simulated through experimental testing methods, and relevant data can be recorded. By comparing the performance parameters under different working states, such as heating speed, energy consumption, etc., their influence on the performance of the water heater is evaluated. According to the experimental results, the influence coefficient of the historical working state of the water heater is calculated.

[0036] The above-mentioned coefficient of influence degree of historical working state of the water heater is obtained by comprehensive analysis of the heating duration, heating power average value and water level change difference of the water heater in the set historical working detection cycle in this embodiment, and is used to determine the value of the influence degree of historical working state of the water heater. In this embodiment, a more accurate calculation method is adopted to obtain it, and the specific expression is:

[0037]

[0038] in It is expressed as the coefficient of influence of the historical working state of the water heater. In this embodiment, the duration of heating directly determines the speed of increase of the water temperature inside the water heater. If the heating duration is too long, it may mean that the heating efficiency of the water heater is low, or the thermal insulation performance of the water heater is poor, resulting in large heat loss, and longer heating time is required to compensate for these losses. Long-term heating may increase the energy consumption of the water heater, and may cause the parts of the water heater to wear faster, shortening the service life of the water heater; if the average heating power is low, the speed at which the water heater heats water will slow down, which may cause the user to wait for hot water for a longer time, reducing the user experience. Low-power heating may mean that the water heater takes a longer time to reach the set temperature, increasing energy consumption; too large a difference in water level change may indicate that the water heater is unstable during the water supply process, which may be caused by unstable water inlet flow, large changes in water outlet, or inaccurate water level control of the water heater itself. This instability may cause users to encounter problems such as water temperature fluctuations and insufficient water when using hot water, reducing the use effect of the water heater.

[0039] JR represents the duration of the heating of the water heater within the set historical working detection cycle, which refers to the time period from the start of heating to the stop of heating. The length of this period usually depends on factors such as the target temperature to be achieved and the heating power of the water heater.

[0040] JR' stands for the reference duration of heating, which refers to the standard value of the duration of heating.

[0041] GL is expressed as the average value of the heating power of the water heater within the set historical work detection cycle. It refers to the heating capacity of the water heater within the historical work detection cycle. The average power can reflect the overall energy consumption of the water heater and help evaluate the efficiency and performance of the water heater.

[0042] GL' stands for the limited heating power, which refers to the minimum value allowed when discussing the heating power.

[0043] ΔSW is expressed as the water level change difference of the water heater within the set historical work detection cycle, which refers to the change in water volume of the water heater during the historical work detection cycle. A large water level change difference may indicate that there is instability in the water supply or water output process of the water heater.

[0044] ΔSW' represents the reference difference of water level change, which refers to the reference standard of the water level change difference.

[0045] a 1 Expressed as a correction factor corresponding to the predefined heating duration, a 2 It is expressed as the correction factor corresponding to the predefined average heating power, a 3 It is expressed as the correction factor corresponding to the predefined water level change difference, and e is a natural constant.

[0046] Furthermore, the water heater historical energy consumption influence coefficient and the water heater historical maintenance influence coefficient are specifically analyzed as follows:

[0047] Based on the historical energy consumption related information of the water heater, the historical average electricity consumption of the water heater within the set historical working detection cycle and the historical electricity load at each working time point are extracted. The above-mentioned working time points are obtained by randomly arranging the historical working detection cycle as each working time point. The historical average electricity consumption of the water heater within the set historical working detection cycle and the historical electricity load at each working time point can be collected in real time by the smart meter carried by the water heater itself.

[0048] The historical electricity consumption boundary quantity and the historical electricity load boundary quantity are extracted from the intelligent control cloud platform.

[0049] The influence coefficient of the historical energy consumption of the water heater is comprehensively analyzed. In a specific embodiment, a suitable evaluation model can be selected to comprehensively consider factors such as the energy consumption level, energy consumption stability, and energy efficiency ratio of the water heater, and these factors can be quantified into a specific coefficient to obtain the influence coefficient of the historical energy consumption of the water heater.

[0050] The above-mentioned water heater historical energy consumption impact coefficient, in this embodiment, is obtained by comprehensive analysis of the historical average power consumption of the water heater within the set historical working detection cycle and the historical power load at each working time point, and is used to determine the value of the water heater historical energy consumption impact. In this embodiment, a more accurate calculation method is used to obtain it, and the specific expression is:

[0051]

[0052] in It is expressed as the coefficient of influence of historical energy consumption of water heater. In this embodiment, higher historical average electricity consumption and historical electricity load mean that the water heater consumes more electricity, which directly leads to increased electricity bill of the user; larger historical electricity load may reflect that the energy efficiency of water heater is not high. If the water heater needs to consume more electricity while providing the same amount of heat, then its energy efficiency ratio will be lower, which not only increases energy waste, but also may affect the service life of water heater; if the historical average electricity consumption and historical electricity load of water heater are very high, then its energy saving effect will be relatively small; therefore, it is necessary to comprehensively consider the negative impact of historical average electricity consumption and historical electricity load on the coefficient of influence of historical energy consumption of water heater, so as to reduce the performance problems of water heater caused by insufficient energy consumption.

[0053] YD represents the average historical electricity consumption of the water heater during the set historical work detection cycle. It refers to the average value of the total electricity consumption of the water heater during a specific historical work detection cycle. This data is obtained by recording and collecting the actual electricity consumption of the water heater over a period of time and performing statistical analysis.

[0054] YD' represents the historical electricity consumption limit, which refers to the maximum allowable value of historical electricity consumption.

[0055] RQ i It is expressed as the historical power load of the water heater at the i-th working time point, which refers to the specific value of the power load consumed by the water heater at a specific time point. The historical power load reflects the power consumption of the water heater at different time points, which helps to understand the power consumption pattern, peak load, load change and other characteristics of the water heater.

[0056] i is the number of each working time point, i=1,2,3,...,m, m is the number of working time points.

[0057] RQ' represents the historical electricity load limit, which refers to the maximum value of the historical electricity load.

[0058] a 4 It is represented by the correction factor corresponding to the predefined historical average electricity consumption, a 5It is expressed as a correction factor corresponding to the predefined historical electricity load, and e is a natural constant.

[0059] Based on the historical maintenance-related information of the water heater, the number of automatic cleaning times of the water heater within the set historical work detection cycle is extracted, and compared with the duration corresponding to the historical work detection cycle, the automatic cleaning frequency of the water heater within the historical work detection cycle is obtained, wherein the number of automatic cleaning times of the water heater within the set historical work detection cycle is directly obtained through the intelligent control cloud platform; the automatic cleaning frequency of the water heater within the historical work detection cycle is obtained by performing ratio processing on the number of automatic cleaning times and the duration corresponding to the historical work detection cycle.

[0060] The automatic cleaning reference times and cleaning reference frequencies are extracted from the intelligent control cloud platform.

[0061] Comprehensively analyze the water heater historical maintenance impact coefficient. In a specific embodiment, the historical maintenance of the water heater can be compared with the average maintenance of similar water heaters through a comparative analysis method to obtain the water heater historical maintenance impact coefficient.

[0062] The above-mentioned water heater historical maintenance influence coefficient, in this embodiment, is obtained by comprehensive analysis of the number of automatic cleaning times of the water heater within the set historical work detection cycle and the automatic cleaning frequency of the water heater within the historical work detection cycle, and is used to determine the value of the water heater historical maintenance influence. In this embodiment, a more accurate calculation method is used to obtain it, and the specific expression is:

[0063]

[0064] Wherein τ represents the influence coefficient of the historical maintenance of the water heater. In this embodiment, if the number and frequency of automatic cleaning of the water heater are too low, a large amount of scale, dirt and impurities may accumulate inside the water heater. These accumulations will adhere to the heating element, pipes and water storage tank of the water heater, resulting in reduced heat conduction efficiency and slower heating speed of the water heater, thereby affecting its overall performance. The accumulation of scale and dirt may also cause blockage or damage to certain parts of the water heater, increasing the risk of failure. If it is not cleaned for a long time, it may cause more serious failures and even require replacement of the entire water heater. Frequent automatic cleaning processes may increase the wear of internal parts of the water heater, especially the cleaning mechanism and related sensors. Too many cleaning times will also lead to unnecessary energy waste, increase the user's operating costs, and interrupt the user's normal water use plan. Therefore, in order to maintain the good performance of the water heater and extend its service life, the user can reasonably arrange the number and frequency of automatic cleaning of the water heater according to factors such as water quality, usage time and water heater type.

[0065] CS is expressed as the number of automatic cleaning times of the water heater within the set historical work detection cycle. It refers to the number of times the water heater automatically performs the cleaning function within a specific historical work detection cycle. This number usually depends on multiple factors. For example, if the water quality is hard or the water heater has been used for a long time, more frequent automatic cleaning may be required to remove scale and dirt to maintain the performance and efficiency of the water heater.

[0066] CS' stands for the automatic cleaning reference number, which refers to the reference standard of the automatic cleaning number.

[0067] PL represents the automatic cleaning frequency of the water heater within the set historical work detection cycle, which refers to the cycle or frequency of automatic cleaning of the water heater, such as cleaning once a day, once a week, or once a month.

[0068] PL' stands for Clean Reference Frequency, which is the reference frequency when discussing the cleaning frequency.

[0069] a 6 It is expressed as the correction factor corresponding to the predefined number of automatic cleaning times, a 7 It is expressed as the correction factor corresponding to the predefined automatic cleaning frequency, and e is a natural constant.

[0070] Specifically, the matching obtains the control adjustment threshold of the water heater. In a specific embodiment, the control parameters, mode switching, temperature setting and other information during operation can be obtained through the self-monitoring and recording functions of the water heater itself, so as to obtain the historical control degree of the water heater.

[0071] The historical control degree of the water heater is obtained in this embodiment through comprehensive analysis of the influence coefficient of the historical working state of the water heater, the influence coefficient of the historical energy consumption of the water heater and the influence coefficient of the historical maintenance of the water heater. In this embodiment, a more accurate calculation method is used to obtain the control degree. The specific expression is:

[0072]

[0073] Wherein α represents the historical control degree of the water heater. In this embodiment, if the water heater frequently appears unstable in the historical working cycle, such as long heating time, large water level change, etc., in this case, the historical control degree of the water heater may be affected, resulting in unstable control strategy, making it difficult to achieve the expected hot water supply effect, affecting the performance and energy consumption of the water heater; a high historical energy consumption impact coefficient may mean that the water heater has had a high energy consumption in the past period of time. In this case, the historical control degree of the water heater may be difficult to achieve the energy-saving goal, resulting in reduced energy efficiency; if the water heater is not in good historical maintenance condition, its performance and efficiency may be affected, and may even cause the failure rate of the water heater to increase; therefore, when evaluating the historical control degree of the water heater, it is necessary to comprehensively consider the negative impact of these factors to improve the stability of the control strategy.

[0074] It is expressed as the influence coefficient of the historical working state of the water heater, which is obtained by comprehensively analyzing the heating duration, the average heating power and the water level change difference of the water heater within the set historical working detection cycle.

[0075] It is expressed as the water heater historical energy consumption impact coefficient, which is obtained by comprehensively analyzing the historical average electricity consumption of the water heater within the set historical working detection period and the historical electricity load at each working time point.

[0076] τ represents the influence coefficient of historical maintenance of the water heater, which is obtained by comprehensively analyzing the number of automatic cleaning times of the water heater within the set historical working detection cycle and the automatic cleaning frequency of the water heater within the historical working detection cycle.

[0077] b 1 It is represented by the weight factor corresponding to the predefined influence coefficient of the historical working state of the water heater, b 2 It is represented by the weight factor corresponding to the predefined coefficient of the historical energy consumption of the water heater, b 3 It is expressed as the weight factor corresponding to the predefined water heater historical maintenance influence coefficient, and e is a natural constant.

[0078] The historical control degree of the water heater is matched with the control adjustment threshold corresponding to each historical control degree defined in the intelligent control cloud platform to obtain the control adjustment threshold of the water heater.

[0079] Monitor the application status of the water heater and evaluate the application control adjustment degree of the water heater.

[0080] Specifically, the water heater application situation affects the degree coefficient, and the specific analysis process is as follows:

[0081] According to the application status of the water heater, information related to the application status of the water heater and information related to the resource consumption of the water heater are extracted.

[0082] According to the associated information of the water heater application, the number of heating times of the water heater within the set application monitoring period is extracted and compared with the duration corresponding to the application monitoring period to obtain the heating frequency of the water heater within the application monitoring period, wherein the number of heating times of the water heater within the set application monitoring period is directly obtained through the intelligent control cloud platform; the heating frequency of the water heater within the application monitoring period is obtained by comparing the obtained number of heating times with the duration corresponding to the application monitoring period to obtain the heating frequency of the water heater within the application monitoring period.

[0083] In this embodiment, the duration corresponding to the above-mentioned historical work detection cycle and the duration corresponding to the application monitoring cycle may be equal to or different from each other.

[0084] The water temperature value of the water heater at each application time point is obtained, and compared with the water temperature adaptation value defined in the intelligent control cloud platform. The number of application time points at which the water temperature value of the water heater is higher than the temperature adaptation value is screened out, and recorded as the number of high-temperature time points of the water heater. The acquisition method of each application time point is to randomly arrange the application monitoring period as each application time point; the water temperature value of the water heater at each application time point can be obtained in real time from the temperature sensor carried by the water heater itself.

[0085] According to the water temperature value of the water heater at each application time point, the water temperature change curve of the water heater is constructed, such as Figure 3 As shown, the horizontal axis of the water temperature change line of the water heater is the application time point, the unit is second; the vertical axis is the water temperature value, the unit is Celsius.

[0086] Extract and count the temperature rise angle values ​​corresponding to each temperature rise of the water heater, such as Figure 3 As shown in the figure, the specific process of obtaining the temperature rise angle value is as follows:

[0087] According to the water temperature change line of the water heater, a temperature rising straight line is located, and according to Figure 3 The first horizontal straight line (2) in the figure is obtained, and the minimum angle value of the intersection between the temperature rising straight line and the first horizontal straight line (2) is obtained, and recorded as the temperature rising angle value.

[0088] The heating limit frequency and the allowable value of the heating angle are extracted from the intelligent control cloud platform.

[0089] Comprehensively analyze the influence coefficient of water heater application. In a specific embodiment, the use data of the water heater can be collected through big data statistics, including daily water consumption, usage time, temperature setting, working mode, etc., and a prediction model is established based on these data to obtain the influence coefficient of the water heater application.

[0090] The above-mentioned water heater application influence coefficient is obtained by comprehensive analysis of the number of high-temperature time points of the water heater, the heating frequency of the water heater in the application monitoring period, and the temperature rise angle value in this embodiment, and is used to determine the value of the influence degree of the water heater application condition. In this embodiment, a more accurate calculation method is used to obtain the value, and the specific expression is:

[0091]

[0092] Wherein δ represents the coefficient of influence of water heater application. In this embodiment, a large number of high-temperature time points means that the water heater is in a high-temperature state for many times or longer during use, which may lead to an increase in energy consumption. Frequent high-temperature heating not only increases electricity consumption, but also may cause additional burden on the heating element of the water heater. During use, a low heating frequency may cause the temperature of the water heater to fail to reach the required temperature value or the user needs to wait for a long time, and the loss of heating energy and the conversion efficiency may be affected. A small heating angle value not only means that the temperature of the water heater rises slowly during the heating process, which also increases the time for users to wait for hot water, but also a small heating angle value makes it difficult to maintain the water temperature within a stable range, which means that the water heater may require more energy to reach and maintain the temperature set by the user, thereby increasing energy consumption. In summary, a large number of high-temperature time points, a low heating frequency and a heating angle value will cause the water heater to be negatively affected in terms of the coefficient of influence of the application situation, which is manifested in a decline in user experience, a decrease in energy efficiency and a poor overall performance evaluation.

[0093] R represents the number of high-temperature time points of the water heater, which refers to the number of application time points at which the water temperature of the water heater is higher than the temperature adaptation value, recorded as the number of high-temperature time points of the water heater.

[0094] WD is the heating frequency of the water heater during the application monitoring cycle. It refers to the frequency of the water heater's heating operation during the application monitoring cycle. It can represent the number of times the water heater completes the heating cycle per second, per minute or per hour, depending on the design and characteristics of the water heater.

[0095] WD' represents the heating limit frequency, which refers to the minimum value allowed when discussing the heating frequency.

[0096] CX jIt is represented as the temperature rise angle value corresponding to the j-th temperature rise of the water heater, which refers to the minimum angle value of the intersection between the temperature rise straight line and the first horizontal straight line.

[0097] j is the number of each temperature rise, j=1,2,3,...,n, and n is the number of temperature rises.

[0098] CX' represents the allowable value of the temperature rise angle, which refers to the minimum value of the temperature rise angle.

[0099] f 1 It is expressed as the impact factor corresponding to a predefined single high temperature time point, f 2 Expressed as the correction factor corresponding to the predefined heating frequency, f 3 It is expressed as the correction factor corresponding to the predefined temperature rise angle value, and e is a natural constant.

[0100] Furthermore, the water heater resource consumption influence coefficient is specifically analyzed as follows:

[0101] Based on the water heater resource consumption related information, the number of times the water heater is used within the set application monitoring cycle and the water consumption of each use are extracted, where the number of times the water heater is used within the set application monitoring cycle and the water consumption of each use can be directly extracted from the intelligent control cloud platform.

[0102] The reference usage times and water consumption permit are extracted from the intelligent control cloud platform.

[0103] Comprehensively analyze the water heater resource consumption impact coefficient. In a specific embodiment, a large amount of energy consumption data of water heaters in actual use can be collected through data analysis methods, and the data can be processed and analyzed using statistical and data analysis methods to obtain the water heater resource consumption impact coefficient.

[0104] The resource consumption impact coefficient of the water heater is obtained by comprehensively analyzing the number of times the water heater is used within a set application monitoring cycle and the water consumption of each use in this embodiment, and is used to determine the value of the resource consumption impact of the water heater. In this embodiment, a more accurate calculation method is used to obtain the value, and the specific expression is:

[0105]

[0106] Wherein γ represents the coefficient of the influence degree of water heater resource consumption. In this embodiment, each time the water heater is used, electric energy is consumed to heat the cold water to the set temperature. Therefore, an increase in the number of uses means that more electric energy or gas is consumed. An increase in water consumption will also lead to an increase in resource consumption. When the water heater provides more hot water, it must consume more energy to heat the water, which not only increases the electricity bill, but may also impose a greater burden on the environment. In addition, if the water heater has low energy efficiency, an increase in the number of uses and water consumption will further aggravate the problem of resource consumption. In summary, the number of uses of the water heater and the water consumption have a direct negative impact on the resource consumption of the water heater. Therefore, choosing an energy-efficient water heater and reasonably controlling the number of uses and water consumption are effective measures to reduce the resource consumption of the water heater.

[0107] DL is the number of times the water heater is used within the set application monitoring cycle, which refers to the total number of times the water heater is started and provides hot water within this cycle. This is usually related to factors such as the user's living habits, the number of family members, and the demand for hot water.

[0108] DL' stands for the usage reference number, which refers to the reference standard of usage number.

[0109] RQ k The water consumption of the kth use of the water heater within the set application monitoring period is expressed as the amount of water consumed each time the water heater is used, which depends on multiple factors, including the water temperature set by the user, the duration of showering or washing, and the water output efficiency of the water heater.

[0110] k is the number used each time, k=1, 2, 3, ..., t, t is the number of the number used each time.

[0111] RQ' stands for the permitted water consumption, which refers to the maximum water consumption.

[0112] f 4 It is expressed as the correction factor corresponding to the predefined number of uses, f 5 It is expressed as the correction factor corresponding to the predefined water consumption, and e is a natural constant.

[0113] Specifically, the application control adjustment degree of the water heater, in a specific embodiment, can be obtained through the intelligent control system carried by the water heater itself, such as an intelligent constant temperature system, intelligent water-saving technology, etc., and more detailed control and adjustment information can be obtained through a connected smart device to obtain the application control adjustment degree of the water heater.

[0114] The application control adjustment degree of the water heater is obtained by comprehensive analysis of the water heater application situation influence coefficient and the water heater resource consumption influence coefficient in this embodiment. In order to determine the value of the application control adjustment of the water heater, a more accurate calculation method is used in this embodiment to obtain the value. The specific expression is:

[0115]

[0116] Wherein β represents the application control adjustment degree of the water heater. In this embodiment, when the application situation influence degree coefficient of the water heater is high, it means that the use of the water heater is restricted by a variety of actual use conditions or scenarios, which may cause the user to be unable to fully exert the performance of the water heater or achieve the ideal hot water effect when adjusting the water heater parameters; if the resource consumption influence degree coefficient of the water heater is large, in order to save energy and reduce operating costs, the user may be forced to limit the control adjustment range of the water heater, such as lowering the set temperature or reducing the usage time; when the application control adjustment degree of the water heater is restricted by the application situation influence degree coefficient and the resource consumption influence degree coefficient, the user may feel dissatisfied or disappointed. For example, when taking a bath, if the water heater cannot maintain a stable water temperature or flow, it will affect the user's comfort and experience; in order to mitigate these negative effects, when calculating the application control adjustment degree of the water heater, these parameters should be fully considered so that the water heater can be controlled more intelligently and flexibly to adapt to different application scenarios and resource consumption requirements.

[0117] δ is the influence coefficient of the water heater application, which is obtained by comprehensively analyzing the number of high-temperature time points of the water heater, the heating frequency of the water heater during the application monitoring period, and the temperature rise angle value.

[0118] γ represents the resource consumption impact coefficient of the water heater, which is obtained by comprehensively analyzing the number of times the water heater is used within a set application monitoring cycle and the water consumption of each use.

[0119] g 1 It is represented by the weight factor corresponding to the predefined water heater application impact coefficient, g 2 It is represented as the weight factor corresponding to the predefined water heater resource consumption impact coefficient, and e is a natural constant.

[0120] The application control adjustment degree of the water heater is compared with the control adjustment threshold of the water heater, and finally the control adjustment of the water heater is optimized.

[0121] Specifically, the control and adjustment optimization of the water heater includes the following specific analysis process:

[0122] The application control adjustment degree of the water heater is compared with the control adjustment threshold of the water heater. If the application control adjustment degree of the water heater is higher than the control adjustment threshold of the water heater, the control system of the water heater may be difficult to stably maintain within the parameter range set by the user, which may cause large fluctuations in water temperature and unstable flow, affecting the user experience; unstable control may lead to reduced energy utilization efficiency of the water heater; excessively high application control adjustment degree may increase the safety risk of the water heater.

[0123] The application control adjustment degree of the water heater is differenced with the control adjustment threshold of the water heater to obtain the control adjustment deviation value of the water heater. The control adjustment deviation value of the water heater is matched with the required adjustment optimization degree corresponding to each control adjustment deviation value interval defined in the intelligent control cloud platform to obtain the required adjustment optimization degree of the water heater, and finally the control adjustment optimization of the water heater is performed.

[0124] In this design example, the above-mentioned control and adjustment optimization of the water heater is carried out, and the specific optimization process is as follows: during the use of the water heater, due to the influence of factors such as water quality and use environment, its control system may deviate. Therefore, it is necessary to regularly calibrate and debug the control system of the water heater; according to the actual water demand of the user, reasonably set the temperature, flow rate and other parameters of the water heater; regularly clean the inner tank, heating tube and other components of the water heater to ensure their good working condition. At the same time, regularly check the control system, sensors and other components of the water heater to ensure their normal operation.

[0125] Reference Figure 2 As shown, the second aspect of the present invention provides an energy-saving intelligent water heater control system, including: a control regulation threshold matching module, an application control regulation degree evaluation module, and a control regulation optimization module.

[0126] The second aspect of the present invention provides an energy-saving intelligent water heater control system, which also includes: an intelligent control cloud platform, which is used to store a reference duration of heating, a defined heating power, a reference difference in water level changes, a historical defined amount of electricity consumption, a historical defined amount of electricity load, a reference number of automatic cleaning times, a reference frequency of cleaning, a control adjustment threshold corresponding to each historical control degree, a water temperature adaptation value, a heating defined frequency, a temperature rise angle allowable value, a reference number of uses, a water consumption allowable amount, and an optimization degree that needs to be adjusted corresponding to each control adjustment deviation value interval.

[0127] The control regulation threshold matching module is connected to the application control regulation degree evaluation module, the application control regulation degree evaluation module is connected to the control regulation optimization module, and the control regulation threshold matching module, the application control regulation degree evaluation module and the control regulation optimization module are all connected to the intelligent control cloud platform.

[0128] The control adjustment threshold matching module is used to obtain historical control state information of the water heater, determine the historical control degree of the water heater, and match the control adjustment threshold of the water heater.

[0129] The application control adjustment degree evaluation module is used to monitor the application status of the water heater and evaluate the application control adjustment degree of the water heater.

[0130] The control regulation optimization module is used to compare the application control regulation degree of the water heater with the control regulation threshold of the water heater, and finally optimize the control regulation of the water heater.

[0131] The third aspect of the present invention provides an energy-saving water heater, comprising: an energy-saving water heater and an intelligent control cloud platform; the energy-saving water heater and the intelligent control cloud platform are connected via the Internet, and the water heater is intelligently controlled via a remote monitoring function; a power sensor for obtaining the heating power of the water heater at each working time point; a water level sensor for obtaining the water level of the water heater at the initial time point and the end time point of a set historical working detection cycle; a temperature sensor for obtaining the water temperature value of the water heater at each application time point; a processor for obtaining the heating power, water level and water temperature values ​​and performing analysis and processing, thereby controlling, adjusting and optimizing the water heater.

[0132] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An energy-saving intelligent water heater control method, characterized in that: include: Obtain historical control status information of the water heater, determine the historical control degree of the water heater, and match the control adjustment threshold of the water heater; Monitor the application status of the water heater and evaluate the application control adjustment degree of the water heater; The application control adjustment degree of the water heater is compared with the control adjustment threshold of the water heater, and finally the control adjustment of the water heater is optimized.

2. The energy-saving intelligent water heater control method according to claim 1, characterized in that: The specific analysis process of controlling and adjusting the water heater is as follows: The application control adjustment degree of the water heater is compared with the control adjustment threshold of the water heater. If the application control adjustment degree of the water heater is higher than the control adjustment threshold of the water heater, the application control adjustment degree of the water heater and the control adjustment threshold of the water heater are differenced to obtain the control adjustment deviation value of the water heater. The control adjustment deviation value of the water heater is matched with the required adjustment optimization degree corresponding to each control adjustment deviation value interval defined in the intelligent control cloud platform to obtain the required adjustment optimization degree of the water heater, and finally the control adjustment optimization of the water heater is performed.

3. The energy-saving intelligent water heater control method according to claim 2, characterized in that: The application control adjustment degree of the water heater is specifically analyzed by the formula: Wherein β represents the application control adjustment degree of the water heater, δ represents the influence coefficient of the water heater application situation, γ represents the influence coefficient of the water heater resource consumption, g1 represents the weight factor corresponding to the predefined influence coefficient of the water heater application situation, g2 represents the weight factor corresponding to the predefined influence coefficient of the water heater resource consumption, and e is a natural constant.

4. The energy-saving intelligent water heater control method according to claim 3, characterized in that: The water heater application situation affects the coefficient of degree, and the specific analysis process is as follows: According to the application status of the water heater, extract the application status related information of the water heater and the resource consumption related information of the water heater; According to the water heater application related information, the number of heating times of the water heater within the set application monitoring period is extracted, and compared with the duration corresponding to the application monitoring period to obtain the heating frequency of the water heater within the application monitoring period; Obtain the water temperature value of the water heater at each application time point, and compare it with the water temperature adaptation value defined in the intelligent control cloud platform, thereby screening out the number of application time points where the water temperature value of the water heater is higher than the temperature adaptation value, and record it as the number of high temperature time points of the water heater; According to the water temperature value of the water heater at each application time point, a water temperature change curve of the water heater is constructed, from which the temperature rise angle value corresponding to each temperature rise of the water heater is extracted and counted; The heating limit frequency and the allowable value of the temperature rise angle are extracted from the intelligent control cloud platform, and the influence coefficient of the water heater application situation is comprehensively analyzed.

5. The energy-saving intelligent water heater control method according to claim 3, characterized in that: The specific analysis process of the water heater resource consumption influence coefficient is as follows: According to the water heater resource consumption correlation information, the number of times the water heater is used within the set application monitoring period and the water consumption of each use are extracted; The reference usage times and permitted water consumption are extracted from the intelligent control cloud platform, and the coefficient of influence of water heater resource consumption is comprehensively analyzed.

6. The energy-saving intelligent water heater control method according to claim 1, characterized in that: The control adjustment threshold of the water heater is obtained by matching, and the specific matching process is: By obtaining the historical control status information of the water heater, the historical working status association information of the water heater, the historical energy consumption association information of the water heater and the historical maintenance association information of the water heater are extracted, and the influence degree coefficient of the historical working status of the water heater, the influence degree coefficient of the historical energy consumption of the water heater and the influence degree coefficient of the historical maintenance of the water heater are determined respectively. Comprehensive analysis is performed to obtain the historical control degree of the water heater. The specific analysis process is as follows: Where α represents the historical control degree of the water heater, denoted as the influence coefficient of the historical working state of the water heater, θdenoted as the influence coefficient of the historical energy consumption of the water heater, τdenoted as the influence coefficient of the historical maintenance of the water heater, b1denoted as the weight factor corresponding to the predefined influence coefficient of the historical working state of the water heater, b2denoted as the weight factor corresponding to the predefined influence coefficient of the historical energy consumption of the water heater, b3denoted as the weight factor corresponding to the predefined influence coefficient of the historical maintenance of the water heater, and edenoted as a natural constant; The historical control degree of the water heater is matched with the control adjustment threshold corresponding to each historical control degree defined in the intelligent control cloud platform to obtain the control adjustment threshold of the water heater.

7. The energy-saving intelligent water heater control method according to claim 6, characterized in that: The influence coefficient of the historical working state of the water heater is analyzed in detail as follows: According to the historical working status association information of the water heater, the heating duration, heating power average value and water level change difference of the water heater within the set historical working detection cycle are extracted; The reference duration of heating, the defined heating power and the reference difference of water level change are extracted from the intelligent control cloud platform, and the influence coefficient of the historical working status of the water heater is comprehensively analyzed.

8. The energy-saving intelligent water heater control method according to claim 6, characterized in that: The specific analysis process of the influence coefficient of the water heater's historical energy consumption and the influence coefficient of the water heater's historical maintenance is as follows: According to the historical energy consumption correlation information of the water heater, the historical average power consumption of the water heater within the set historical working detection period and the historical power load at each working time point are extracted; From the intelligent control cloud platform, the historical electricity consumption boundary quantity and the historical electricity load boundary quantity are extracted, and the influence coefficient of the historical energy consumption of the water heater is comprehensively analyzed; According to the historical maintenance related information of the water heater, the number of automatic cleaning times of the water heater within the set historical working detection cycle is extracted, and compared with the duration corresponding to the historical working detection cycle, the automatic cleaning frequency of the water heater within the historical working detection cycle is obtained; The automatic cleaning reference times and cleaning reference frequency are extracted from the intelligent control cloud platform, and the influence coefficient of the water heater's historical maintenance is comprehensively analyzed.

9. An energy-saving intelligent water heater control system, characterized in that: include: A control adjustment threshold matching module is used to obtain historical control status information of the water heater, determine the historical control degree of the water heater, and match the control adjustment threshold of the water heater; An application control regulation degree evaluation module is used to monitor the application status of the water heater and evaluate the application control regulation degree of the water heater; The control and regulation optimization module is used to compare the application control and regulation degree of the water heater with the control and regulation threshold of the water heater, and finally optimize the control and regulation of the water heater.

10. An energy-saving water heater using any one of the energy-saving intelligent water heater control methods of claims 1 to 8, characterized in that: include: Energy-saving water heaters and intelligent control cloud platform; The energy-saving water heater and the intelligent control cloud platform are connected via the Internet, and the water heater is intelligently controlled via a remote monitoring function; A power sensor is used to obtain the heating power of the water heater at each working time point; A water level sensor is used to obtain the water level of the water heater at the initial time point and the end time point of the set historical working detection cycle; A temperature sensor is used to obtain the water temperature value of the water heater at each application time point; The processor is used to obtain the heating power, water level and water temperature values ​​and analyze and process them, thereby controlling, adjusting and optimizing the water heater.

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