Heating stove energy-saving control method and device and heating stove

Abstract

The invention relates to the field of smart home, and provides a heating stove energy-saving control method and device and a heating stove. The method comprises the steps that the heating stove set temperature set by a user is periodically obtained, and the outdoor temperature is obtained; an operation temperature prediction model is called, the operation temperature prediction model is obtained through training according to historical energy-saving sample data, and the historical energy-saving sample data comprises historical temperature combinations collected at the target indoor cooling rate; the historical temperature combination comprises historical heating stove operation temperature, historical indoor temperature and historical outdoor temperature; the heating stove set temperature and the outdoor temperature are input into the operation temperature prediction model, and the heating stove operation temperature output by the operation temperature prediction model is obtained; and periodically controlling the heating furnace to operate according to the heating furnace operating temperature. Energy is effectively saved on the premise that comfort is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to an energy-saving control method, device and boiler for heating furnaces. Background Technology

[0002] According to relevant technologies, existing boiler control technologies mainly rely on users manually setting a fixed temperature or control strategies based on simple timing (such as timed start-stop). While such solutions can maintain basic heating needs, to avoid discomfort caused by room temperature fluctuations, users often set the target heating temperature to a "safe threshold" higher than the actual demand. This passive compensation mechanism leads to the heating system operating under overload for extended periods, resulting in low energy efficiency.

[0003] Therefore, finding a precise energy-saving control method for heating boilers that ensures comfort has become a current research hotspot. Summary of the Invention

[0004] This invention provides an energy-saving control method, device, and boiler for heating furnaces, which achieves effective energy saving while ensuring comfort.

[0005] This invention provides an energy-saving control method for a heating boiler, the method comprising: periodically acquiring a user-set heating boiler temperature and an outdoor temperature; calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical heating boiler operating temperatures, historical indoor temperatures, and historical outdoor temperatures; inputting the heating boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the heating boiler operating temperature output by the operating temperature prediction model; and periodically controlling the heating boiler to operate according to the heating boiler operating temperature.

[0006] According to a heating boiler energy-saving control method provided by the present invention, the historical energy-saving sample data is obtained in the following manner: determining the target area where the user is located; obtaining multiple sets of historical temperature combinations in different rooms where different heating boilers are located within the target area, wherein the multiple sets of historical temperature combinations are multiple sets of historical temperature combinations with the same historical indoor temperature and / or historical outdoor temperature, the historical temperature combination including historical heating boiler operating temperature, historical indoor temperature and historical outdoor temperature; and performing energy-saving screening on the multiple sets of historical temperature combinations based on the indoor cooling rate under different rooms where different heating boilers are located to obtain historical energy-saving sample data.

[0007] According to the present invention, an energy-saving control method for heating boilers includes the following steps: First, based on the indoor cooling rate of different boilers in different indoor environments, energy-saving screening is performed on multiple historical temperature combinations to obtain historical energy-saving sample data. This includes: arranging the indoor cooling rates of different boilers in different indoor environments in ascending order to obtain an indoor cooling rate ranking sequence; second, identifying indoor cooling rates that are within a predetermined number of positions in the ranking sequence and are less than or equal to a rate threshold as target indoor cooling rates; third, selecting historical temperature combinations collected under the target indoor cooling rate from multiple historical temperature combinations; and finally, using the historical temperature combinations collected under the target indoor cooling rate as the historical energy-saving sample data.

[0008] According to the energy-saving control method for a heating boiler provided by the present invention, the operating temperature prediction model is trained in the following ways: a training dataset is constructed based on the historical energy-saving sample data, and the operating temperature prediction model is trained based on the training dataset to obtain a trained operating temperature prediction model; or a linear fit is performed based on the historical energy-saving sample data to obtain an operating temperature prediction model.

[0009] According to the present invention, an energy-saving control method for a heating boiler, after periodically controlling the heating boiler to operate at the heating boiler operating temperature, the method further includes: determining the user's heating preference; if the user's heating preference is a preference for high-temperature heating, adjusting the heating boiler operating temperature upwards according to a preset adjustment temperature to obtain an adjusted heating boiler operating temperature; if the user's heating preference is a preference for low-temperature heating, adjusting the heating boiler operating temperature downwards according to a preset adjustment temperature to obtain an adjusted heating boiler operating temperature; the periodic control of the heating boiler to operate at the heating boiler operating temperature includes: periodically controlling the heating boiler to operate at the adjusted heating boiler operating temperature.

[0010] According to a heating boiler energy-saving control method provided by the present invention, the user's heating preference is determined by the following method: obtaining the user's historical reference heating boiler set temperature, wherein the historical reference heating boiler set temperature is the historical heating boiler set temperature set by the user with the current outdoor temperature; if the historical reference heating boiler set temperature is greater than the heating boiler operating temperature, the user's heating preference is determined to be a preference for high-temperature heating; if the historical reference heating boiler set temperature is less than or equal to the heating boiler operating temperature, the user's heating preference is determined to be a preference for low-temperature heating.

[0011] According to the present invention, an energy-saving control method for a heating boiler is provided, wherein the outdoor temperature is a sequence of outdoor temperatures within a future preset time period; the step of inputting the set temperature of the heating boiler and the outdoor temperature into the operating temperature prediction model to obtain the operating temperature of the heating boiler output by the operating temperature prediction model includes: periodically inputting the set temperature of the heating boiler and the sequence of outdoor temperatures within a future preset time period into the operating temperature prediction model in chronological order to obtain the operating temperature sequence of the heating boiler output by the operating temperature prediction model in the future preset time period; the step of periodically controlling the heating boiler to operate according to the operating temperature of the heating boiler specifically includes: periodically controlling the heating boiler to operate according to the operating temperature sequence of the heating boiler within a future preset time period in chronological order.

[0012] This invention also provides an energy-saving control device for a heating boiler, the device comprising: an acquisition module for periodically acquiring a user-set heating boiler temperature and an outdoor temperature; a calling module for calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical heating boiler operating temperature, historical indoor temperature, and historical outdoor temperature; a processing module for inputting the heating boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the heating boiler operating temperature output by the operating temperature prediction model; and a control module for periodically controlling the heating boiler to operate according to the heating boiler operating temperature.

[0013] The present invention also provides a heating furnace, the heating furnace comprising: a heating furnace body and a processor, wherein the processor is configured to execute any of the heating furnace energy-saving control methods described herein.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the energy-saving control method for heating boilers as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the energy-saving control method for heating boilers as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the energy-saving control method for heating boilers as described above.

[0017] This invention provides an energy-saving control method, device, and boiler for a heating boiler. The method includes: periodically acquiring a user-set boiler temperature and an outdoor temperature; calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical boiler operating temperatures, historical indoor temperatures, and historical outdoor temperatures; inputting the boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the boiler operating temperature output by the operating temperature prediction model; and periodically controlling the boiler to operate according to the operating temperature. Since the operating temperature prediction model is trained based on historical energy-saving sample data, it can ensure that the boiler operating temperature predicted by the operating temperature prediction model can reduce energy consumption while maintaining the user-set comfort level, avoiding overheating, and achieving effective energy saving while ensuring comfort. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the hardware environment for an energy-saving control method for a heating boiler according to an embodiment of this application; Figure 2 This is a flowchart illustrating the energy-saving control method for heating boilers provided by the present invention.

[0020] Figure 3 This is a schematic diagram of the process for obtaining historical energy-saving sample data provided by the present invention.

[0021] Figure 4 This is a flowchart illustrating the process of obtaining historical energy-saving sample data by filtering multiple historical temperature combinations based on the indoor cooling rate of different heating boilers in different indoor environments, as provided by the present invention.

[0022] Figure 5 This is a schematic diagram of the process provided by the present invention for controlling the heating furnace to operate according to the operating temperature of the heating furnace.

[0023] Figure 6 This is a schematic diagram of the structure of the energy-saving control device for heating furnaces provided by the present invention.

[0024] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] According to one aspect of the embodiments of this application, an energy-saving control method for a heating boiler is provided. This energy-saving control method is widely applicable to whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, and intelligence house ecosystems. Optionally, in this embodiment, the above-mentioned energy-saving control method for a heating boiler can be applied to, for example... Figure 1 The hardware environment shown consists of terminal device 102 and server 104. For example... Figure 1 As shown, server 104 is connected to terminal device 102 via a network and can be used to provide services (such as application services) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data processing services for server 104.

[0028] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal device 102 may not be limited to PC, mobile phone, tablet computer, smart air conditioner, smart range hood, smart refrigerator, smart oven, smart stove, smart washing machine, smart water heater, smart washing equipment, smart dishwasher, smart projector, smart TV, smart clothes rack, smart curtains, smart audio-visual equipment, smart socket, smart speaker, smart speaker box, smart fresh air equipment, smart kitchen and bathroom equipment, smart bathroom equipment, smart robot vacuum cleaner, smart window cleaning robot, smart mopping robot, smart air purifier, smart steam oven, smart microwave oven, smart water heater, smart air purifier, smart water dispenser, smart door lock, etc.

[0029] In another embodiment, the energy-saving control method for heating boilers provided in this application can be applied to smart home appliances. Smart home appliances refer to home appliances that incorporate microprocessors, sensor technology, and network communication technology, enabling them to automatically sense the status of the residential space, the appliance's own status, and its service status, and to automatically control and receive control commands from the home user, either inside or remotely. It is understood that smart home appliances are a component of smart homes.

[0030] The energy-saving control method for heating boilers provided by this invention can predict the minimum heating target temperature sequence required to maintain the comfortable temperature within a preset time period based on the user's desired indoor temperature, combined with weather forecasts and historical thermal performance data of the building, thereby achieving precise heating and energy saving.

[0031] Figure 2 This is a flowchart illustrating the energy-saving control method for heating boilers provided by the present invention.

[0032] The following will combine Figure 2 The process of the energy-saving control method for heating boilers provided by the present invention will be described.

[0033] In an exemplary embodiment of the present invention, combined with Figure 2 As can be seen, the energy-saving control method for heating boilers may include steps 210 to 240, and each step will be described below.

[0034] In step 210, the user-set boiler temperature and the outdoor temperature are periodically acquired.

[0035] In one embodiment, the user can set a set temperature for the boiler. Additionally, the user can acquire the outdoor temperature, which can be obtained in real-time from an outdoor temperature sensor or determined from weather forecasts. The user-set boiler temperature represents the desired indoor temperature.

[0036] In step 220, the operating temperature prediction model is invoked. The operating temperature prediction model is trained based on historical energy-saving sample data. The historical energy-saving sample data includes historical temperature combinations collected under the target indoor cooling rate. The historical temperature combinations include historical boiler operating temperature, historical indoor temperature, and historical outdoor temperature.

[0037] In one embodiment, a pre-trained operating temperature prediction model can be invoked. This model can be trained using a machine learning algorithm on historical energy-saving sample data. During training, historical indoor and outdoor temperatures can be used as input features, and historical boiler operating temperatures as the target variable, to train a regression model. The training objective is to minimize the error between the predicted and actual operating temperatures.

[0038] In another embodiment, the historical energy-saving sample data is a combination of historical temperatures collected under a target indoor cooling rate. Since the operating temperature prediction model is trained based on the historical energy-saving sample data, it can ensure that the operating temperature of the heating boiler predicted by the operating temperature prediction model can reduce energy consumption while maintaining the user's set comfort level, avoid overheating, and achieve effective energy saving while ensuring comfort.

[0039] In step 230, the boiler set temperature and outdoor temperature are input into the operating temperature prediction model to obtain the boiler operating temperature output by the operating temperature prediction model.

[0040] In step 240, the heating boiler is periodically controlled to operate according to the heating boiler operating temperature.

[0041] In another embodiment, the user-set boiler temperature and outdoor temperature can be input into the operating temperature prediction model. The operating temperature prediction model outputs a predicted boiler operating temperature. The target indoor cooling rate can be less than or equal to a rate threshold. This operating temperature is energy-efficient because it is predicted by the operating temperature prediction model trained on historical data at low cooling rates, thus avoiding unnecessary energy consumption.

[0042] This invention provides an energy-saving control method for a heating boiler, comprising: periodically acquiring the user-set heating boiler temperature and the outdoor temperature; calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical heating boiler operating temperature, historical indoor temperature, and historical outdoor temperature; inputting the heating boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the heating boiler operating temperature output by the operating temperature prediction model; and periodically controlling the heating boiler to operate according to the operating temperature. Since the operating temperature prediction model is trained based on historical energy-saving sample data, it can ensure that the heating boiler operating temperature predicted by the operating temperature prediction model can reduce energy consumption while maintaining the user-set comfort level, avoiding overheating, and achieving effective energy saving while ensuring comfort.

[0043] Figure 3 This is a schematic diagram of the process for obtaining historical energy-saving sample data provided by the present invention.

[0044] The following will combine Figure 3 The process of obtaining historical energy-saving sample data provided by the present invention will be described.

[0045] In an exemplary embodiment of the present invention, combined with Figure 3 As can be seen, obtaining historical energy-saving sample data may include steps 310 to 330, and each step will be described below.

[0046] In step 310, the target area where the user is located is determined.

[0047] In step 320, multiple sets of historical temperature combinations are obtained for different indoor spaces where different heating boilers are located within the target area. The multiple sets of historical temperature combinations are multiple sets of historical temperature combinations with the same historical indoor temperature and / or historical outdoor temperature. The historical temperature combinations include historical heating boiler operating temperature, historical indoor temperature and historical outdoor temperature.

[0048] It should be noted that different regions have different climate characteristics, and therefore have different requirements for the operating temperature of heating boilers. During application, the target area where the user is located can be determined, for example, target area A.

[0049] Furthermore, all available historical data within target area A can be obtained. This data originates from hundreds or thousands of different households, representing multiple historical temperature combinations in different rooms of different heating boilers. For each household, multiple historical temperature combinations from past heating seasons can be obtained. During application, this data can be categorized and grouped according to the criteria of the same historical indoor temperature and / or the same historical outdoor temperature, thereby allowing the filtering of all historical temperature combinations with the same historical indoor temperature; all historical temperature combinations with the same historical outdoor temperature; and all historical temperature combinations with both the same historical indoor and historical outdoor temperatures.

[0050] In step 330, based on the indoor cooling rate of different heating boilers in different indoor environments, energy-saving screening is performed on multiple sets of historical temperature combinations to obtain historical energy-saving sample data.

[0051] In another embodiment, the corresponding indoor cooling rate is determined for each historical temperature combination with a specific temperature characteristic. Furthermore, based on the indoor cooling rate of different indoor environments where different heating boilers are located—that is, the indoor cooling rate corresponding to each historical temperature combination with a specific temperature characteristic—multiple historical temperature combinations are screened to obtain historical energy-saving sample data.

[0052] The indoor cooling rate can be determined based on the outdoor temperature and can be expressed as: Indoor cooling rate = a × outdoor temperature + b, where a and b are personalized parameters of the coal mining machine, which can be obtained by fitting historical data.

[0053] In another embodiment, within each region, historical data can be grouped according to "same indoor temperature, same outdoor temperature, same heating target temperature". Within each group, data points are clustered according to cooling rate, and the cluster with the largest number of samples and the lowest cooling rate is selected. These samples represent "energy-saving paradigms" that consume less energy while achieving the same comfort level, thus yielding historical energy-saving sample data.

[0054] In this embodiment, since the historical energy-saving sample data is energy-saving data with lower energy consumption when achieving the same comfort effect, it ensures that the operating temperature prediction model trained based on the historical energy-saving sample data can predict the operating temperature of the heating boiler that reduces energy consumption while maintaining the user's set comfort level, thus avoiding overheating and achieving effective energy saving while ensuring comfort.

[0055] Figure 4 This is a flowchart illustrating the process of obtaining historical energy-saving sample data by filtering multiple historical temperature combinations based on the indoor cooling rate of different heating boilers in different indoor environments, as provided by the present invention.

[0056] The following will combine Figure 4 The present invention describes the process of obtaining historical energy-saving sample data by screening multiple historical temperature combinations based on the indoor cooling rate of different heating boilers in different indoor environments.

[0057] In an exemplary embodiment of the present invention, combined with Figure 4 As can be seen, based on the indoor cooling rate of different heating boilers in different rooms, energy-saving screening of multiple historical temperature combinations can be carried out to obtain historical energy-saving sample data, which may include steps 410 to 440. Each step will be described below.

[0058] In step 410, the indoor cooling rates of different heating boilers in different rooms are sorted in ascending order to obtain an indoor cooling rate sorting sequence.

[0059] In step 420, the indoor cooling rate that is located at the first preset number of positions in the indoor cooling rate sorting sequence and whose indoor cooling rate is less than or equal to the rate threshold is taken as the target indoor cooling rate.

[0060] In one embodiment, all indoor cooling rates can be sorted in descending order to form an indoor cooling rate sorting sequence. After sorting in ascending order, the data with the lowest rate is at the beginning of the sequence and the data with the highest rate is at the end of the sequence.

[0061] Furthermore, in the ascending sequence, scanning can begin from the beginning of the sequence (i.e., the end with the lowest rate) and proceed backwards. Rate values ​​that are located at the first preset number of positions in the sequence (such as the first 3) and whose indoor cooling rate is less than or equal to the rate threshold are identified as the target indoor cooling rate.

[0062] This embodiment ensures that the selected samples with the target indoor cooling rate have extremely low energy consumption levels and meet energy-saving standards.

[0063] In step 430, the historical temperature combination collected under the target indoor cooling rate is selected from multiple historical temperature combinations.

[0064] In step 440, the historical temperature combinations collected under the target indoor cooling rate are used as historical energy-saving sample data.

[0065] In another embodiment, from multiple sets of historical temperature combinations, those historical temperature combinations whose indoor cooling rate is marked as the target indoor cooling rate can be selected. These data records represent the temperature data generated during historical operation by the user group with the best building insulation performance and the most outstanding energy-saving effect within the target area.

[0066] Furthermore, the selected combinations of historical temperatures collected under the target indoor cooling rate can be used as the final historical energy-saving sample data for training the operating temperature prediction model.

[0067] In this embodiment, since the selected samples represent the records with the lowest cooling rate (i.e., the best thermal insulation performance) among all data, this establishes the highest standard of energy efficiency benchmark for training the operating temperature prediction model. The operating temperature prediction model trained based on these optimal samples recommends operating temperature parameters that represent the theoretically most energy-efficient operating strategy for the region.

[0068] In yet another exemplary embodiment of the present invention, the previously described embodiment will be used as an example for explanation. The temperature prediction model can be trained in the following manner: Based on the historical energy-saving sample data, a training dataset is constructed, and the operating temperature prediction model is trained on the training dataset to obtain a trained operating temperature prediction model, or A linear fitting was performed based on the historical energy-saving sample data to obtain the operating temperature prediction model.

[0069] In one embodiment, historical energy-saving sample data is constructed into a structured dataset, where the input features can be historical indoor and outdoor temperatures; the target variable is the historical operating temperature of the heating boiler. The operating temperature prediction model is trained using this training dataset to obtain a well-trained operating temperature prediction model.

[0070] In another embodiment, a linear relationship can be established based on historical energy-saving sample data. For example, the predicted boiler operating temperature = W1 × indoor temperature + C1 × outdoor temperature + C2, where W1, C1, and C2 are the linear coefficients to be determined. In application, linear regression techniques such as the least squares method can be used to solve for the optimal coefficients, and the calculated linear equation is the operating temperature prediction model.

[0071] During application, the user-defined boiler temperature setting and the current outdoor temperature can be input into the model to obtain the predicted boiler operating temperature.

[0072] Figure 5 This is a schematic diagram of the process provided by the present invention for periodically controlling the operation of the heating furnace according to the operating temperature of the heating furnace.

[0073] The following will combine Figure 5 The process of periodically controlling the operation of the heating furnace according to the operating temperature provided by the present invention will be described.

[0074] In an exemplary embodiment of the present invention, combined with Figure 5It can be seen that periodically controlling the heating boiler to operate according to the operating temperature of the heating boiler may include steps 510 to 540, and each step will be described below.

[0075] In step 510, the user's heating preferences are determined.

[0076] In step 520, if the user prefers high-temperature heating, the operating temperature of the heating boiler is increased according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating boiler.

[0077] In step 530, if the user prefers low-temperature heating, the operating temperature of the heating boiler is lowered according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating boiler.

[0078] In one embodiment, the user's heating preference can be determined. If the user prefers high-temperature heating, the boiler operating temperature predicted by the model can be increased according to a preset adjustment temperature. If the preset adjustment temperature is 1°C and the original predicted operating temperature is 60°C, the adjusted boiler operating temperature will be 62°C. The preset adjustment temperature can be adjusted according to actual conditions and is not specifically limited in this embodiment.

[0079] In another embodiment, if the user prefers low-temperature heating, the predicted operating temperature of the boiler can be lowered according to a preset adjustment temperature. If the preset adjustment temperature is 1°C and the original predicted operating temperature is 60°C, the adjusted boiler operating temperature is 58°C.

[0080] In step 540, the heating boiler is periodically controlled to operate at the adjusted heating boiler operating temperature.

[0081] In another embodiment, the adjusted temperature value can be sent to the boiler controller, and the boiler can be periodically controlled to operate at the personalized adjusted temperature, that is, to operate at the adjusted boiler operating temperature within the corresponding cycle.

[0082] In this embodiment, while maintaining the overall energy-saving framework, personalized adjustments are made based on different users' temperature preferences. This satisfies users' individual comfort needs while maintaining basic energy-saving effects. This differentiated approach significantly improves user experience and satisfaction, avoiding the discomfort that a one-size-fits-all energy-saving solution might cause.

[0083] In yet another exemplary embodiment of the present invention, continuing with the previously described embodiments, determining a user's heating preference can be achieved in the following manner: Obtain the user's historical reference boiler setting temperature, wherein the historical reference boiler setting temperature is the historical boiler setting temperature set by the user with the current outdoor temperature; If the historical reference boiler set temperature is higher than the boiler operating temperature, the user's heating preference is determined to be a preference for high-temperature heating. If the historical reference boiler set temperature is less than or equal to the boiler operating temperature, the user's heating preference is determined to be a preference for low-temperature heating.

[0084] In one embodiment, historical boiler setting temperatures set by the user under historical conditions similar to or the current outdoor temperature can be retrieved from historical data. For example, if the current outdoor temperature is 5°C, all boiler setting temperature records set by the user within the historical outdoor temperature range of 4°C-6°C can be retrieved. Furthermore, the average value or the most frequently occurring value is calculated as the historical reference boiler setting temperature.

[0085] In another embodiment, if the historical reference boiler set temperature is greater than the boiler operating temperature, it can be determined that the user's heating preference is a preference for high-temperature heating; if the historical reference boiler set temperature is less than or equal to the boiler operating temperature, it can be determined that the user's heating preference is a preference for low-temperature heating.

[0086] In this embodiment, by comparing the user's historical temperature settings with the model's predicted temperature, a completely objective and quantifiable standard for preference judgment can be established. This accurately reflects the user's true temperature preference under the same environmental conditions, greatly improving the reliability of preference identification.

[0087] In yet another exemplary embodiment of the present invention, the above-described embodiments will be used as examples for further explanation. The outdoor temperature can be a sequence of outdoor temperatures within a preset time period in the future. The process of inputting the boiler's set temperature and the outdoor temperature into the operating temperature prediction model to obtain the boiler's operating temperature output by the model can be achieved in the following way: According to the time sequence, the set temperature of the heating boiler and the outdoor temperature sequence within the future preset time period are periodically input into the operating temperature prediction model to obtain the operating temperature sequence of the heating boiler within the future preset time period output by the operating temperature prediction model. The periodic control of the heating boiler to operate according to its operating temperature can be achieved in the following ways: According to the time sequence, the heating boiler is periodically controlled to operate according to the heating boiler operating temperature sequence within a future preset time period.

[0088] In one embodiment, an outdoor temperature sequence within a preset time period can be obtained. For example, an outdoor temperature prediction sequence for the next 24 hours at 1-hour intervals can be obtained.

[0089] Furthermore, the set temperature of the heating boiler and the outdoor temperature sequence for a future preset time period are simultaneously input into the operating temperature prediction model. The operating temperature prediction model outputs the corresponding operating temperature sequence of the heating boiler for the future preset time period. In application, the heating boiler can be controlled to operate according to the operating temperature sequence for the future preset time period.

[0090] In this embodiment, based on the outdoor temperature sequence within a preset time period, such as a 24-hour weather forecast, a heating furnace operating temperature sequence for a future preset time period is generated, enabling the coal-fired furnace to change from a passive response to an active planning approach, resulting in more stable operation and higher energy efficiency.

[0091] As described above, the energy-saving control method for a heating furnace provided by this invention uses a model to dynamically find the theoretical minimum energy consumption point to maintain the user's set comfort level, thus fundamentally avoiding overheating. In addition, it respects the user's personalized comfort needs and the physical characteristics of the house, achieving precise control of the coal-fired furnace.

[0092] The energy-saving control device for heating boilers provided by the present invention is described below. The energy-saving control device for heating boilers described below can be referred to in correspondence with the energy-saving control method for heating boilers described above.

[0093] Figure 6 This is a schematic diagram of the structure of the energy-saving control device for heating furnaces provided by the present invention.

[0094] In an exemplary embodiment of the present invention, combined with Figure 6 As can be seen, the energy-saving control device for heating boilers may include an acquisition module 610, a calling module 620, a processing module 630, and a control module 640. Each module will be described in detail below.

[0095] The acquisition module 610 can be configured to periodically acquire the user-set boiler temperature and the outdoor temperature; The calling module 620 can be configured to call the operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data includes historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations include historical boiler operating temperature, historical indoor temperature and historical outdoor temperature; Processing module 630 can be configured to input the set temperature of the heating furnace and the outdoor temperature into the operating temperature prediction model to obtain the operating temperature of the heating furnace output by the operating temperature prediction model; The control module 640 can be configured to periodically control the heating furnace to operate at the heating furnace operating temperature.

[0096] In an exemplary embodiment of the present invention, the calling module 620 can obtain historical energy-saving sample data in the following manner: Determine the target area where the user is located; Obtain multiple sets of historical temperature combinations for different indoor spaces where different heating boilers are located within the target area. The multiple sets of historical temperature combinations are multiple sets of historical temperature combinations with the same historical indoor temperature and / or historical outdoor temperature. The historical temperature combinations include historical heating boiler operating temperature, historical indoor temperature, and historical outdoor temperature. Based on the indoor cooling rate of different heating boilers in different indoor environments, energy-saving screening was performed on multiple historical temperature combinations to obtain historical energy-saving sample data.

[0097] In an exemplary embodiment of the present invention, the calling module 620 can perform energy-saving screening on multiple historical temperature combinations based on the indoor cooling rate of different heating boilers in different indoor environments, and obtain historical energy-saving sample data: The indoor cooling rates of different heating boilers in different rooms are sorted in ascending order to obtain the indoor cooling rate sorting sequence. The indoor cooling rate that is located at the first preset number of positions in the indoor cooling rate sorting sequence and that is less than or equal to the rate threshold is taken as the target indoor cooling rate. The historical temperature combination that was collected under the target indoor cooling rate was selected from multiple historical temperature combinations. The historical temperature data collected at the target indoor cooling rate will be used as the historical energy-saving sample data.

[0098] In an exemplary embodiment of the present invention, the calling module 620 may train the operating temperature prediction model in the following manner: Based on the historical energy-saving sample data, a training dataset is constructed, and the operating temperature prediction model is trained on the training dataset to obtain a trained operating temperature prediction model, or A linear fitting was performed based on the historical energy-saving sample data to obtain the operating temperature prediction model.

[0099] In an exemplary embodiment of the present invention, the control module 640 may further be configured to: Determine the user's heating preferences; If the user prefers high-temperature heating, the operating temperature of the heating furnace is increased according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating furnace. If the user prefers low-temperature heating, the operating temperature of the heating boiler is lowered according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating boiler. The control module 640 can periodically control the heating boiler to operate according to its operating temperature in the following manner: The heating boiler is periodically controlled to operate at the adjusted operating temperature.

[0100] In an exemplary embodiment of the present invention, the control module 640 may determine the user's heating preference in the following manner: Obtain the user's historical reference boiler setting temperature, wherein the historical reference boiler setting temperature is the historical boiler setting temperature set by the user with the current outdoor temperature; If the historical reference boiler set temperature is greater than the boiler operating temperature, the user's heating preference is determined to be a preference for high-temperature heating. If the historical reference boiler set temperature is less than or equal to the boiler operating temperature, the user's heating preference is determined to be a preference for low-temperature heating.

[0101] In an exemplary embodiment of the present invention, the outdoor temperature is a sequence of outdoor temperatures within a preset future time period; The processing module 630 can input the set temperature of the heating boiler and the outdoor temperature into the operating temperature prediction model in the following way to obtain the operating temperature of the heating boiler output by the operating temperature prediction model: According to the time sequence, the set temperature of the heating boiler and the outdoor temperature sequence within a future preset time period are periodically input into the operating temperature prediction model to obtain the operating temperature sequence of the heating boiler within the future preset time period output by the operating temperature prediction model. The control module 640 can periodically control the heating boiler to operate according to its operating temperature in the following manner: According to the time sequence, the heating furnace is periodically controlled to operate according to the heating furnace operating temperature sequence within a future preset time period.

[0102] Based on the same inventive concept, the present invention also provides a heating stove, which will be described below in conjunction with the following embodiments.

[0103] In an exemplary embodiment of the present invention, the heating boiler may include a boiler body and a processor, wherein the processor is used to execute the energy-saving control method for the heating boiler described in any embodiment. The heating boiler provided by the present invention achieves effective energy saving while ensuring comfort.

[0104] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740, wherein the processor 710, the communication interface 720, and the memory 730 communicate with each other through the communication bus 740. The processor 710 can call logic instructions in the memory 730 to execute a boiler energy-saving control method, which includes: periodically acquiring the user-set boiler temperature and the outdoor temperature; calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical boiler operating temperature, historical indoor temperature, and historical outdoor temperature; inputting the boiler temperature and the outdoor temperature into the operating temperature prediction model to obtain the boiler operating temperature output by the operating temperature prediction model; and periodically controlling the boiler to operate according to the boiler operating temperature.

[0105] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the energy-saving control method for the heating boiler provided by the above methods. The method includes: periodically acquiring the user-set heating boiler temperature and the outdoor temperature; calling an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical heating boiler operating temperature, historical indoor temperature and historical outdoor temperature; inputting the heating boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the heating boiler operating temperature output by the operating temperature prediction model; and periodically controlling the heating boiler to operate according to the heating boiler operating temperature.

[0107] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the energy-saving control method for a heating boiler provided by the methods described above. The method includes: periodically acquiring a user-set heating boiler temperature and an outdoor temperature; invoking an operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data including historical temperature combinations collected under a target indoor cooling rate, the historical temperature combinations including historical heating boiler operating temperatures, historical indoor temperatures, and historical outdoor temperatures; inputting the heating boiler set temperature and the outdoor temperature into the operating temperature prediction model to obtain the heating boiler operating temperature output by the operating temperature prediction model; and periodically controlling the heating boiler to operate according to the heating boiler operating temperature.

[0108] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for energy-saving control of a heating boiler, characterized in that, The method includes: Periodically obtain the user-set boiler temperature and the outdoor temperature; The operating temperature prediction model is invoked, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data includes historical temperature combinations collected under the target indoor cooling rate, the historical temperature combinations include historical heating boiler operating temperature, historical indoor temperature and historical outdoor temperature; The boiler's set temperature and the outdoor temperature are input into the operating temperature prediction model to obtain the boiler's operating temperature output by the operating temperature prediction model. The heating boiler is periodically controlled to operate at the specified operating temperature.

2. The energy-saving control method for a heating boiler according to claim 1, characterized in that, The historical energy-saving sample data was obtained in the following way: Determine the target area where the user is located; Obtain multiple sets of historical temperature combinations for different indoor spaces where different heating boilers are located within the target area. The multiple sets of historical temperature combinations are multiple sets of historical temperature combinations with the same historical indoor temperature and / or historical outdoor temperature. The historical temperature combinations include historical heating boiler operating temperature, historical indoor temperature, and historical outdoor temperature. Based on the indoor cooling rate of different heating boilers in different indoor environments, energy-saving screening was performed on multiple historical temperature combinations to obtain historical energy-saving sample data.

3. The energy-saving control method for heating boilers according to claim 2, characterized in that, The method involves screening multiple historical temperature combinations based on the indoor cooling rate of different heating boilers in different indoor environments to obtain historical energy-saving sample data, including: The indoor cooling rates of different heating boilers in different rooms are sorted in ascending order to obtain the indoor cooling rate sorting sequence. The indoor cooling rate that is located at the first preset number of positions in the indoor cooling rate sorting sequence and that is less than or equal to the rate threshold is taken as the target indoor cooling rate. The historical temperature combination that was collected under the target indoor cooling rate was selected from multiple historical temperature combinations. The historical temperature data collected at the target indoor cooling rate will be used as the historical energy-saving sample data.

4. The energy-saving control method for a heating boiler according to any one of claims 1 to 3, characterized in that, The operating temperature prediction model was trained using the following method: Based on the historical energy-saving sample data, a training dataset is constructed, and the operating temperature prediction model is trained on the training dataset to obtain a trained operating temperature prediction model, or A linear fitting was performed based on the historical energy-saving sample data to obtain the operating temperature prediction model.

5. The energy-saving control method for a heating boiler according to claim 1, characterized in that, After periodically controlling the heating boiler to operate at the boiler's operating temperature, the method further includes: Determine the user's heating preferences; If the user prefers high-temperature heating, the operating temperature of the heating furnace is increased according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating furnace. If the user prefers low-temperature heating, the operating temperature of the heating boiler is lowered according to the preset adjustment temperature to obtain the adjusted operating temperature of the heating boiler. The periodic control of the heating boiler to operate according to the boiler's operating temperature includes: The heating boiler is periodically controlled to operate at the adjusted operating temperature.

6. The energy-saving control method for a heating boiler according to claim 5, characterized in that, The user's heating preference is determined in the following way: Obtain the user's historical reference boiler setting temperature, wherein the historical reference boiler setting temperature is the historical boiler setting temperature set by the user with the current outdoor temperature; If the historical reference boiler set temperature is greater than the boiler operating temperature, the user's heating preference is determined to be a preference for high-temperature heating. If the historical reference boiler set temperature is less than or equal to the boiler operating temperature, the user's heating preference is determined to be a preference for low-temperature heating.

7. The energy-saving control method for a heating boiler according to claim 1, characterized in that, The outdoor temperature is a sequence of outdoor temperatures within a preset time period in the future; The step of inputting the set temperature of the heating boiler and the outdoor temperature into the operating temperature prediction model to obtain the operating temperature of the heating boiler output by the operating temperature prediction model includes: According to the time sequence, the set temperature of the heating boiler and the outdoor temperature sequence within a future preset time period are periodically input into the operating temperature prediction model to obtain the operating temperature sequence of the heating boiler within the future preset time period output by the operating temperature prediction model. The periodic control of the heating boiler to operate according to its operating temperature specifically includes: According to the time sequence, the heating furnace is periodically controlled to operate according to the heating furnace operating temperature sequence within a future preset time period.

8. An energy-saving control device for a heating boiler, characterized in that, The device includes: The acquisition module is used to periodically acquire the user-set boiler temperature and the outdoor temperature. The calling module is used to call the operating temperature prediction model, wherein the operating temperature prediction model is trained based on historical energy-saving sample data, the historical energy-saving sample data includes historical temperature combinations collected under the target indoor cooling rate, and the historical temperature combinations include historical heating boiler operating temperature, historical indoor temperature and historical outdoor temperature. The processing module is used to input the set temperature of the heating boiler and the outdoor temperature into the operating temperature prediction model to obtain the operating temperature of the heating boiler output by the operating temperature prediction model. The control module is used to periodically control the heating furnace to operate according to the operating temperature of the heating furnace.

9. A heating stove, characterized in that, The heating furnace includes: The boiler body, and A processor, wherein the processor is configured to execute the energy-saving control method for a heating boiler according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the energy-saving control method for the heating boiler as described in any one of claims 1 to 7.

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