Method and equipment for automatically adjusting water supply temperature and medium

Abstract

The invention relates to a method and device for automatically adjusting the water supply temperature and a medium, and the method comprises the steps that in a target operation state, a first parameter set is input into a first model to output a first indoor temperature; if the first indoor temperature is matched with the set temperature, operation continues to be conducted at the current water supply temperature; otherwise, a candidate water supply temperature reference value is determined, and multiple candidate water supply temperatures are determined according to the candidate water supply temperature reference value and the difference value between the first indoor temperature and the set temperature; for each candidate water supply temperature, inputting the candidate water supply temperature and a second parameter set into a second model, and outputting corresponding second indoor temperature and second energy consumption information; and the target water supply temperature is determined according to the obtained data combination of the multiple sets of candidate water supply temperatures, the second indoor temperature and the second energy consumption information. The water supply temperature can be adjusted in time when needed by considering factors such as current indoor information, current rainfall information, current snowfall information and the like which may have special or extreme conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning, and in particular to a method, a device and a medium for automatically adjusting water supply temperature. Background Art

[0002] The water supply temperature refers to the temperature of the water provided by the water source or heating device in various water circulation systems, such as central air conditioning systems, heating systems or hot water supply systems. This temperature is crucial to ensure the efficiency of the system and meet user needs. In the central air conditioning system, the water supply temperature determines whether the system can effectively adjust the indoor environment to achieve the expected comfort level. Even under the operation of central air conditioning, the comfort level of indoor temperature is often affected by some relatively extreme or special circumstances. However, the existing technology often ignores the impact of these relatively extreme or special circumstances on the water supply temperature under the premise of ensuring indoor comfort. Summary of the invention

[0003] The first object of the present invention is to provide a method, device and medium for automatically adjusting the water supply temperature.

[0004] According to one aspect of the present application, a method for automatically adjusting water supply temperature is provided, the method comprising: In the target operation state, a first parameter set is input into the first model, and a first indoor temperature is output through the first model, wherein the first parameter set includes current water supply temperature, current indoor information, current rainfall information, and current snowfall information; If the first indoor temperature matches the set temperature, continue to operate at the current water supply temperature; otherwise, determine that the impact of the current indoor information, the current rainfall information, or the current snowfall information on the first indoor temperature reaches the target impact threshold, determine a candidate water supply temperature reference value, and determine multiple candidate water supply temperatures based on the candidate water supply temperature reference value, the difference between the first indoor temperature and the set temperature; For each candidate water supply temperature, the candidate water supply temperature and the second parameter set are input into the second model, and the second indoor temperature and the second energy consumption information corresponding to the candidate water supply temperature are output through the second model; The target water supply temperature is determined according to the obtained data combination of the multiple groups of candidate water supply temperatures, the second indoor temperature, and the second energy consumption information.

[0005] According to another aspect of the present application, a computer device for automatically adjusting water supply temperature is provided, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method described above.

[0006] According to another aspect of the present application, a computer-readable storage medium is provided, storing a computer program that can be loaded by a processor and execute the above method.

[0007] Compared with the prior art, the present application considers the factors that may exist in special circumstances or extreme circumstances such as the current indoor information, the current rainfall information, and the current snowfall information under the target operation state. By inputting the first parameter set containing the current indoor information, the current rainfall information, and the current snowfall information into the first model, the first indoor temperature is output. By detecting in advance whether the first indoor temperature matches the set temperature, when the first indoor temperature does not match the set temperature, the water supply temperature is adjusted in time. Based on the data combination of multiple groups of candidate water supply temperatures, second indoor temperatures, and second energy consumption information, the indoor temperature is adjusted in time under the premise of the lowest possible energy consumption, so that the indoor temperature reaches a comfortable temperature matching the set temperature as soon as possible. Specifically, when the first indoor temperature does not match the set temperature, a candidate water supply temperature reference value is determined, and multiple candidate water supply temperatures are determined according to the difference between the candidate water supply temperature reference value, the first indoor temperature, and the set temperature. For each candidate water supply temperature, the candidate water supply temperature and the second parameter set are input into the second model, and the second indoor temperature and the second energy consumption information corresponding to the candidate water supply temperature are output through the second model. Through the cooperation of the first model and the second model, multiple sets of data combinations of candidate water supply temperature, second indoor temperature, and second energy consumption information are obtained. The target water supply temperature is determined through the multiple sets of data combinations, and the current water supply temperature is adjusted in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flow chart of a method for automatically adjusting water supply temperature according to an embodiment of the present application is shown; Figure 2 A schematic diagram of the structure of a device for automatically adjusting the water supply temperature according to another embodiment of the present application is shown; Figure 3 An exemplary system is shown that can be used to implement the various embodiments described in this application. DETAILED DESCRIPTION

[0009] The present application is described in further detail below in conjunction with the accompanying drawings.

[0010] In a typical configuration of the present application, the terminal, the device of the service network and the trusted party all include one or more processors (eg, a central processing unit (CPU)), an input / output interface, a network interface and a memory.

[0011] Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash memory. Memory is an example of a computer-readable medium.

[0012] Computer readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, Phase-Change Memory (PCM), Programmable Random Access Memory (PRAM), Static Random-Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of random access memory (RAM), Read-Only Memory (ROM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Flash memory or other memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0013] The devices referred to in this application include but are not limited to terminals, network devices, or devices formed by integrating terminals and network devices through a network. The terminal includes but is not limited to any mobile electronic product that can interact with a user (for example, interact with a user through a touchpad), such as a smart phone, a tablet computer, etc. The mobile electronic product can use any operating system, such as an Android operating system, an iOS operating system, etc. Among them, the network device includes an electronic device that can automatically perform numerical calculations and information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc. The network device includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud composed of multiple servers; here, the cloud is composed of a large number of computers or network servers based on cloud computing (Cloud Computing), wherein cloud computing is a type of distributed computing, a virtual supercomputer composed of a group of loosely coupled computer sets. The network includes but is not limited to the Internet, wide area network, metropolitan area network, local area network, VPN network, wireless self-organizing network (Ad Hoc network), etc. Preferably, the device may also be a program running on the terminal, network device, or a device formed by integrating the terminal and network device, network device, touch terminal, or network device and touch terminal through a network.

[0014] Of course, those skilled in the art should understand that the above-mentioned devices are only examples, and other existing or future devices that are applicable to the present application should also be included in the scope of protection of the present application and are included here by reference.

[0015] In the description of the present application, “plurality” means two or more, unless otherwise clearly and specifically defined.

[0016] refer to Figure 1An embodiment of the present invention provides a method for automatically adjusting water supply temperature, the method comprising step S11, step S12, step S13, and step S14. In step S11, under the target operating state, a first parameter set is input into a first model, and a first indoor temperature is output through the first model, wherein the first parameter set includes a current water supply temperature, current indoor information, current rainfall information, and current snowfall information; in step S12, if the first indoor temperature matches the set temperature, operation continues at the current water supply temperature; otherwise, it is determined that the influence of the current indoor information, the current rainfall information, or the current snowfall information on the first indoor temperature reaches a target influence threshold, a candidate water supply temperature reference value is determined, and a plurality of candidate water supply temperatures are determined according to the candidate water supply temperature reference value, the difference between the first indoor temperature and the set temperature; in step S13, for each candidate water supply temperature, the candidate water supply temperature and a second parameter set are input into a second model, and a second indoor temperature and a second energy consumption information corresponding to the candidate water supply temperature are output through the second model; in step S14, a target water supply temperature is determined according to a data combination of the obtained plurality of sets of candidate water supply temperatures, second indoor temperatures, and second energy consumption information.

[0017] Specifically, in step S11, under the target operating state, the first parameter set is input into the first model, and the first indoor temperature is output through the first model, wherein the first parameter set includes the current water supply temperature, the current indoor information, the current rainfall information, and the current snowfall information. In some embodiments, the target operating state includes the user switching the system to the operating state of the present solution that takes special circumstances into consideration. For example, a corresponding button is provided on the remote control device of the air conditioner, through which the target operating state is switched, or the target operating state is turned off. For example, in heavy rain, heavy snow, or when there are many people indoors, the user can switch to the target operating state through the button. In order to trigger the system to monitor in advance whether the first indoor temperature matches the set temperature by inputting the first parameter set into the first model, and to adjust the water supply temperature in time when it does not match. In other embodiments, the system may also monitor in real time, for example, the system monitors in real time whether the current indoor information, the current rainfall information, and the current snowfall information have reached the corresponding set threshold, and when at least one of the current indoor information, the current rainfall information, and the current snowfall information reaches the corresponding set threshold, the target operation state is automatically turned on, and when the corresponding set threshold is not reached, the target operation state is automatically turned off to achieve the purpose of energy-saving operation. For the determination of the current indoor information, the current rainfall information, and the current snowfall information, please refer to the following corresponding embodiments, which will not be repeated here. In some embodiments, the current indoor information includes but is not limited to the current number of people information, the current indoor humidity information, etc. In some embodiments, the current number of people information can be obtained by inputting the target feature data information into the third model. For the introduction of this part, please refer to the following corresponding embodiments, which will not be repeated here. In some embodiments, the current rainfall information and the current snowfall information can be obtained through weather forecast software or a meteorological station. In this embodiment, by inputting a first parameter set including the current indoor information, the current rainfall information, and the current snowfall information into the first model, the first indoor temperature that may be affected by the current indoor information, the current rainfall information, or the current snowfall information is output. This solution can adapt to complex environmental changes more flexibly.

[0018] In step S12, if the first indoor temperature matches the set temperature, continue to operate at the current water supply temperature; otherwise, determine that the impact of the current indoor information, the current rainfall information or the current snowfall information on the first indoor temperature reaches the target impact threshold, determine the candidate water supply temperature reference value, and determine multiple candidate water supply temperatures based on the candidate water supply temperature reference value and the difference between the first indoor temperature and the set temperature. In some embodiments, the first indoor temperature does not match the set temperature under the current operating state, including that the difference between the first indoor temperature and the set temperature is equal to or greater than the target difference. In some embodiments, the setting of the target difference can be larger. In other words, when the first indoor temperature is significantly less than or greater than the set temperature, it is determined that the water supply temperature needs to be adjusted in time so as to adjust the indoor temperature to the comfort range in time. In some embodiments, the current water supply temperature can be determined as the candidate water supply temperature reference value. In other embodiments, the candidate water supply temperature reference value can also be obtained through a physical model. For the introduction of this part, please refer to the corresponding embodiment below, which will not be repeated here. Further, multiple candidate water supply temperatures are determined based on the candidate water supply temperature reference value, the difference between the first indoor temperature and the set temperature. For example, based on the candidate water supply temperature reference value, the candidate water supply temperature reference value is adjusted according to the difference between the first indoor temperature and the set temperature to obtain the candidate water supply temperature. The candidate water supply temperature is then discretely processed to obtain multiple candidate water supply temperatures. This embodiment avoids unnecessary frequent adjustments and improves system stability. When the first indoor temperature does not match the set temperature, the adjustment of the water supply temperature is triggered; otherwise, the adjustment of the water supply temperature is not triggered, avoiding unnecessary operations and improving system stability and energy efficiency.

[0019] In step S13, for each candidate water supply temperature, the candidate water supply temperature and the second parameter set are input into the second model, and the second indoor temperature and the second energy consumption information corresponding to the candidate water supply temperature are output through the second model. In this embodiment, a second model is also provided, and the second indoor temperature and the second energy consumption information corresponding to the candidate water supply temperature are obtained by inputting the candidate water supply temperature and the second parameter set corresponding to the candidate water supply temperature into the second model. In some embodiments, the second model includes a related model of the first model, and the first parameter set as a whole includes the current moment, and the moments before the current moment, and the water supply temperature at each moment, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, first energy consumption information, and the return water temperature at the previous moment, and a matrix composed of the outdoor temperature prediction value at the next moment. For each candidate water supply temperature, the candidate water supply temperature is used as the water supply temperature at the current moment in the first parameter set, and the energy consumption information at the current moment is removed from the first parameter set. In other words, the second parameter set includes the current moment, the moments before the current moment, and the water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, first energy consumption information, and the return water temperature at the previous moment, and the matrix composed of the outdoor temperature prediction value at the next moment, wherein the water supply temperature at the current moment is removed, the water supply temperature at the current moment is replaced by the candidate water supply temperature, and the energy consumption information at the current moment is removed. In this embodiment, when training the first model and the second model, the training data can be shared, and the input and output of the first model and the second model are different, so the workload of training the first model and the second model can be greatly reduced, saving costs. In some embodiments, the outdoor temperature prediction value can be obtained through the meteorological station. In some embodiments, the first model is trained by the following method: based on the long short-term memory network, the long short-term memory network is trained by a first parameter set at multiple different moments to obtain the first model, wherein the first parameter set at each moment includes the first moment, and the moments before the first moment, as well as the water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information at each moment, and the return water temperature at the previous moment of the first moment, and a matrix composed of the outdoor temperature prediction value at the next moment of the first moment, where n is a positive integer.In some embodiments, the second model can be trained by the following method: collect historical data (including system operation data at various water supply temperatures, ensure data diversity, cover different water supply temperatures, environmental conditions and system states), data content includes: event sequence data (time points at the current moment and the previous n moments), data at each moment (water supply temperature (including values ​​within the candidate water supply temperature range), indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, energy consumption information), return water temperature at the previous moment, and predicted outdoor temperature at the next moment. Then preprocess the data. Then, based on the long short-term memory network (LSTM), define input and output, that is, the input includes a second parameter set, and the output includes a second indoor temperature and a second energy consumption information, and train the second model.

[0020] In step S14, the target water supply temperature is determined based on the obtained data combination of multiple groups of candidate water supply temperatures, the second indoor temperature, and the second energy consumption information. In some embodiments, the target water supply temperature can be determined by optimizing the objective function. For example, the optimization objective function is defined as: , where J includes the objective function value; Including a first weight coefficient, reflecting the preference for comfort; Including a second weight coefficient, reflecting the preference for energy consumption; Including the second indoor temperature, the In some embodiments, in order to ensure indoor comfort (for example, the indoor temperature reaches or is close to the set temperature), you can set Greater than or much greater than . The candidate water supply temperature corresponding to the minimum objective function value is used as the target water supply temperature. In other embodiments, the difference between each second indoor temperature and the set temperature may be calculated first, and only the candidate water supply temperatures corresponding to the second indoor temperatures whose differences are within the target difference interval are retained, and from the retained candidate water supply temperatures, the candidate water supply temperature with the minimum second energy consumption information is used as the target water supply temperature. Of course, the above-described method of determining the target water supply temperature based on the obtained data combination of multiple groups of candidate water supply temperatures, second indoor temperatures, and second energy consumption information is only an example, and other existing or future methods that may appear, if applicable to the present application, are also within the scope of protection of the present application and are included herein by reference.

[0021] In some embodiments, determining a candidate water supply temperature reference value, and determining a plurality of candidate water supply temperatures according to the candidate water supply temperature reference value, a difference between the first indoor temperature and the set temperature, comprises: determining the candidate water supply temperature reference value by means of a physical model, wherein the physical model comprises: {T}_{in}(t)={T}_{out}(t)+\frac {pI(t)} {\alpha}-{c}_{a}{m}_{a}({T}_{g}-{T}_{h})R-{\left [ {{T}_{out}(t)+\frac {pI(t)} {\alpha}-{c}_{a}{m}_{a}({T}_{g}-{T}_{h})R-{T}_{in}(t-1)} \right ]e}^{-\frac {\Delta t} {RC}} , here, Including the current indoor temperature, including the current outdoor air temperature, Including the surface solar absorption rate, Including the current solar radiation intensity hitting the wall, Including the external surface heat release coefficient, Including the specific heat capacity of the refrigerant, Including the mass flow rate of refrigerant, Including candidate water supply temperature reference values, Including the current return water temperature, Including the effective heat transfer resistance of the building envelope, C including the effective heat capacity of the indoor air, Including the indoor temperature at the previous moment, Including the indoor and outdoor temperature difference, e includes the first coefficient; the candidate water supply temperature is determined by substituting the difference between the first indoor temperature and the set temperature and the candidate water supply temperature reference value into the candidate water supply temperature calculation formula, wherein the candidate water supply temperature calculation formula includes: , here, including candidate water supply temperatures, Including candidate water supply temperature reference values, Including adjustment factors, Including the difference between the first indoor temperature and the set temperature; by discretizing the candidate water supply temperatures, multiple candidate water supply temperatures are obtained. The physical model includes a thermal response model, and the equivalent thermal parameter model ETP (Equivalent Thermal Parameter) is generally used to reflect the thermal dynamic process of the air-conditioning unit. In some embodiments, the thermal response model describes the dynamic relationship between the indoor temperature and the cooling capacity of the refrigerator, which is the basis for energy consumption modeling of the air-conditioning system. The equivalent thermal parameter model ETP (Equivalent Thermal Parameter) is generally used to reflect the thermal dynamic process of the air-conditioning unit. Its expression can be expressed as follows: {T}_{in}(t)={T}_{0}(t)-{\left [ {{T}_{0}(t)-{T}_{in}(t-1)} \right ]e}^{-\frac {\Delta t} {RC}} , S(t)=0; {T}_{in}(t)={T}_{0}(t)-QR-{\left [ {{T}_{0}(t)-QR-{T}_{in}(t-1)} \right ]e}^{-\frac {\Delta t} {RC}} , S(t)=1.

[0022] In the above formula, Including indoor temperature at time t, °C; Includes the outdoor comprehensive temperature at time t, °C; It includes the indoor temperature at time (t-1), ℃; Q includes the cooling capacity, W; R includes the effective heat transfer resistance of the enclosure structure, ℃ / W; C includes the effective heat capacity of the indoor air, J / ℃; S includes the start and stop time of the air conditioning system, 0 for shutdown and 1 for startup. Here, the outdoor comprehensive temperature The comprehensive outdoor temperature, including radiation, can be calculated using the following formula: , here, Includes outdoor air temperature at time t, °C; Including the surface solar absorption rate, which can be taken as 0.85; I (t) includes the solar radiation intensity hitting the wall at time t, W / ; Including external surface heat release coefficient, W / •℃, can be taken as 18.6. The solar radiation intensity I (t) can be found in the heating, ventilation and air conditioning design specification GBJ19-87. In some embodiments, the cooling capacity Q can be calculated by the following formula: , here, Includes refrigerator specific heat capacity, J / (kg•℃); Including the mass flow rate of refrigerant, kg / s; Including chilled water supply temperature, °C; Including chilled water return temperature, ℃. Establishing the relationship between indoor temperature and chilled water supply temperature, chilled water return temperature and outdoor comprehensive temperature can be expressed by the above-mentioned first calculation formula. In some embodiments, the first coefficient e can be obtained through multiple sets of historical data. For example, by substituting the above-mentioned physical model related parameters at multiple different times into the physical model, multiple first candidate coefficients are obtained. The average value of the multiple first candidate coefficients obtained is taken as the first coefficient. In this embodiment, since the first indoor temperature obtained by the first model is obtained on the basis of considering possible extreme conditions (for example, current indoor information, current rainfall information, current snowfall information). The candidate water supply temperature reference value obtained by the physical model is obtained under relatively steady-state conditions. Therefore, it is necessary to adjust the candidate water supply temperature reference value. In some embodiments, the candidate water supply temperature reference value can be adjusted by substituting the difference between the first indoor temperature and the set temperature and the candidate water supply temperature reference value into the candidate water supply temperature calculation formula to obtain the candidate water supply temperature. In some embodiments, the adjustment factor It can be determined by any of the following methods. Method 1, regression analysis based on historical data: collect historical data (for example, collect data on the impact of changes in different water supply temperatures on indoor temperature); regression modeling (for example, use regression analysis techniques (such as linear regression, multivariate linear regression, etc.) to establish a relationship model between water supply temperature and indoor temperature changes. For example, through historical data, the ratio of water supply temperature change to indoor temperature change is obtained, that is, how many degrees of indoor temperature change will be caused by each degree of water supply temperature); determine the adjustment factor (for example, determine the adjustment factor based on the ratio obtained by the regression model. For example, if the model shows that for every 1 degree change in water supply temperature, the indoor temperature changes by 0.2 degrees, then the adjustment factor is determined to be 0.2). Method 2, experimental testing based on system response: set the initial adjustment factor (for example, select a reasonable initial adjustment factor (such as 0.5 or 0.3), test it in the actual system, and when selecting the initial value, refer to the typical values ​​of similar systems. value, or set it according to engineering experience); test the effect of adjusting the water supply temperature in a small range (for example, while keeping other conditions unchanged, increase or decrease the water supply temperature in a small range (such as by 1 degree), observe the impact on the indoor temperature, and record the actual response of the water supply temperature change and the indoor temperature); adjust and determine value (for example, compare the actual change in indoor temperature with the expected set value, and gradually adjust until the water supply temperature adjustment effectively controls the indoor temperature close to the set value. If the system responds slowly, reduce value to prevent over-adjustment; if the system responds slowly, it can be appropriately increased In some embodiments, the adjustment factor can be pre-set in the system and directly called when used. In other embodiments, the indoor information, rainfall information, and snowfall information correspond to Different, the system pre-associates the corresponding indoor information, rainfall information, and snowfall information through mapping relationships. In some embodiments, if only one of the current indoor information, the current rainfall information, and the current snowfall information reaches the corresponding threshold, then the value is determined from the mapping relationship based on the item. In other embodiments, the weights of the current indoor information, the current rainfall information, and the current snowfall information are preset, so that when multiple items of the current indoor information, the current rainfall information, and the current snowfall information reach corresponding thresholds, the item corresponding to the item with the highest weight among the multiple items is determined. . In some embodiments, after the candidate water supply temperature is determined, the candidate water supply temperature is discretized to obtain multiple candidate water supply temperatures. For example: based on the expansion temperature and the discrete interval temperature, the candidate water supply temperature is discretized up and down to obtain multiple candidate water supply temperatures. In some embodiments, the expansion temperature can be 1.5°C, and the discrete interval temperature can be 0.5°C. That is, the candidate water supply temperature is expanded up and down by 1.5°C, and the discrete interval is 0.5°C, and we get \left [ {{T}_{g1}-1.5,{T}_{g1}-1,{T}_{g1}-0.5,{T}_{g1},{T}_{g1}+0.5,{T}_{g1}+1,{T}_{g1}+1.5} \right ] ,in, , , , , , , Of course, those skilled in the art will appreciate that the above-mentioned expansion temperatures and discrete interval temperatures are only examples, and other existing or future expansion temperatures and discrete interval temperatures that are applicable to the present application are also within the scope of protection of the present application and are included herein by reference.

[0023] In some embodiments, the current indoor information includes the current number of people information, and the current number of people information is output by inputting the target feature data information into the third model. In some embodiments, the current number of people information is determined by inputting the target feature data information into the third model. In some embodiments, the target feature data information includes at least one of the following: current infrared signal direction information; current wireless signal strength related information. For example, between multiple infrared sensors arranged side by side in the horizontal direction, the direction from the infrared sensor that first receives the infrared signal to the infrared sensor that last receives the infrared signal is the infrared signal direction information. In some embodiments, the infrared signal direction information can be used to determine whether the user is entering the room or going out of the room. For example, setting the direction from infrared sensor 1 to infrared sensor 2 is determined as forward, recorded as +1, which can indicate that the user enters the room, and setting the direction from infrared sensor 2 to infrared sensor 1 is determined as reverse, which can indicate that the user is going out of the room, recorded as -1. Wireless signal strength information. For example, WI-FI signal strength information. For example, an infrared device is provided at the indoor entrance and exit, and the infrared device includes a first infrared sensor and a second infrared sensor arranged in parallel in the horizontal direction. The infrared signal direction information is obtained by the following method: the first infrared signal and the second infrared signal are obtained by the first infrared sensor and the second infrared sensor respectively; the infrared signal direction information is determined according to the time sequence of obtaining the first infrared signal and the second infrared signal, wherein the infrared signal direction information includes forward and reverse directions. When the first infrared signal is obtained first and then the second infrared signal is obtained, the infrared direction information is determined to be forward, which means that the user enters the room. When the second infrared signal is obtained first and then the first infrared signal is obtained, the infrared direction information is determined to be reverse, which means that the user goes out. In some embodiments, when multiple people enter or leave the room at the same time, it is not accurate enough to determine the current number of people only by infrared direction information. In order to improve the accuracy, it can also be combined with the current wireless signal strength related information. In some embodiments, the current wireless signal strength related information includes but is not limited to the current area information, the current layout information, the initial wireless signal strength information, and the current wireless signal strength information. In some embodiments, the current area information includes but is not limited to the indoor area information, or the area information of the area covered by the air conditioning system. In some embodiments, the layout information includes but is not limited to open, moderate, crowded, etc. In some embodiments, the initial wireless signal strength information includes the strength information of the wireless signal when no device receives the scattered Wi-Fi signal (for example, the Wi-Fi signal sent by the Wi-Fi access point (AP) is received by only one RSSI receiving device, and the RSSI value of the Wi-Fi signal is used as the initial wireless signal strength information). Since the wireless signal strength information may also be affected by the indoor area information, layout information, and the initial wireless signal strength information, the wireless signal strength related information of this embodiment includes the area information, layout information, and the initial wireless signal strength information.Of course, those skilled in the art will understand that the above target feature data information is only for example, and other existing or future target feature data information, if applicable to the present application, is also within the scope of protection of the present application and is included herein by reference.

[0024] In some embodiments, the third model is obtained by training through the following scheme: based on a machine learning algorithm, the third model is obtained by training through a combination of data of multiple sets of infrared signal direction information and wireless signal strength related information. Here, those skilled in the art can understand that the machine learning algorithm includes but is not limited to a supervised learning algorithm and a deep learning algorithm. For example, the third model is obtained by training through a large amount of infrared signal direction information, wireless signal strength related information data combination, and the number of people information corresponding to each data combination, so as to achieve the output of the corresponding current number of people information by inputting the current infrared signal information and wireless signal strength information into the third model.

[0025] Figure 2 The schematic diagram of the structure of the device for automatically adjusting the water supply temperature according to an embodiment of the present application is shown, and the device includes a first module, a second module, a third module, and a fourth module. The first module is used to input the first parameter set into the first model under the target operation state, and output the first indoor temperature through the first model, wherein the first parameter set includes the current water supply temperature, the current indoor information, the current rainfall information, and the current snowfall information; the first module is used to continue to operate at the current water supply temperature if the first indoor temperature matches the set temperature; otherwise, it is determined that the influence of the current indoor information, the current rainfall information, or the current snowfall information on the first indoor temperature reaches the target influence threshold, determine the candidate water supply temperature reference value, and determine multiple candidate water supply temperatures according to the difference between the candidate water supply temperature reference value, the first indoor temperature and the set temperature; the third module is used to input the candidate water supply temperature and the second parameter set into the second model for each candidate water supply temperature, and output the second indoor temperature and the second energy consumption information corresponding to the candidate water supply temperature through the second model; the fourth module is used to determine the target water supply temperature according to the obtained data combination of multiple groups of candidate water supply temperatures, second indoor temperatures, and second energy consumption information.

[0026] Here, the specific implementations corresponding to module 11, module 12, module 13, and module 14 are the same or similar to the specific embodiments of step S11, step S12, step S13, and step S14, and are therefore not repeated here and are included herein by reference.

[0027] In some embodiments, determining a candidate water supply temperature reference value, and determining a plurality of candidate water supply temperatures according to the candidate water supply temperature reference value, a difference between the first indoor temperature and the set temperature, comprises: determining the candidate water supply temperature reference value by means of a physical model, wherein the physical model comprises: {T}_{in}(t)={T}_{out}(t)+\frac {pI(t)} {\alpha}-{c}_{a}{m}_{a}({T}_{g}-{T}_{h})R-{\left [ {{T}_{out}(t)+\frac {pI(t)} {\alpha}-{c}_{a}{m}_{a}({T}_{g}-{T}_{h})R-{T}_{in}(t-1)} \right ]e}^{-\frac {\Delta t} {RC}} , here, Including the current indoor temperature, including the current outdoor air temperature, Including the surface solar absorption rate, Including the current solar radiation intensity hitting the wall, Including the external surface heat release coefficient, Including the specific heat capacity of the refrigerant, Including the mass flow rate of refrigerant, Including candidate water supply temperature reference values, Including the current return water temperature, Including the effective heat transfer resistance of the building envelope, C including the effective heat capacity of the indoor air, Including the indoor temperature at the previous moment, e includes the first coefficient; the candidate water supply temperature is determined by substituting the difference between the first indoor temperature and the set temperature and the candidate water supply temperature reference value into the candidate water supply temperature calculation formula, wherein the candidate water supply temperature calculation formula includes: , here, including candidate water supply temperatures, Including candidate water supply temperature reference values, Including adjustment factors, Including the difference between the first indoor temperature and the set temperature; by discretely processing the candidate water supply temperatures, multiple candidate water supply temperatures are obtained.

[0028] Here, the specific implementation methods corresponding to modules 1 and 2 are the same as or similar to the specific implementation method of step S12, and thus will not be described in detail but are included herein by reference.

[0029] In some embodiments, the current indoor information includes information about the current number of people, and the current number of people information is output by inputting target feature data information into a third model.

[0030] In some embodiments, the target characteristic data information includes at least one of the following: infrared signal direction information; wireless signal strength related information.

[0031] In some embodiments, an infrared device is installed at the indoor entrance and exit, and the infrared device includes a first infrared sensor and a second infrared sensor arranged in parallel along the horizontal direction. The infrared signal direction information is obtained by the following method: the first infrared signal and the second infrared signal are obtained by the first infrared sensor and the second infrared sensor respectively; the infrared signal direction information is determined according to the time sequence of obtaining the first infrared signal and the second infrared signal, wherein the infrared signal direction information includes forward and reverse. When the first infrared signal is obtained first and then the second infrared signal is obtained, the infrared direction information is determined to be forward; when the second infrared signal is obtained first and then the first infrared signal is obtained, the infrared direction information is determined to be reverse.

[0032] In some embodiments, based on a machine learning algorithm, the third model is obtained by training a data combination of multiple groups of infrared signal direction information and wireless signal strength related information.

[0033] Here, the specific implementation corresponding to module 15 is the same as or similar to the specific implementation of step S15, and thus will not be described in detail and is included herein by reference.

[0034] In some embodiments, the second model includes a related model of the first model, and the first parameter set includes the current moment, the moments before the current moment, and the water supply temperature at each moment, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, first energy consumption information, and the return water temperature at the previous moment, and a matrix consisting of the outdoor temperature prediction value at the next moment; for each candidate water supply temperature, the candidate water supply temperature is used as the water supply temperature at the current moment in the first parameter set, and the second parameter set includes the current moment, the moments before the current moment, and the water supply temperature at each moment, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, and the return water temperature at the previous moment, and a matrix consisting of the outdoor temperature prediction value at the next moment, where n is a positive integer.

[0035] In some embodiments, the first model is trained by the following method: based on the long short-term memory network, the long short-term memory network is trained by a first parameter set at multiple different moments to obtain the first model, wherein the first parameter set at each moment includes the first moment, and the moments before the first moment, as well as the water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information at each moment, and the return water temperature at the previous moment of the first moment, and a matrix composed of the outdoor temperature prediction value at the next moment of the first moment, where n is a positive integer.

[0036] In addition to the methods and devices described in the above embodiments, the present application also provides a computer-readable storage medium, which stores computer code. When the computer code is executed, the method described in any of the preceding items is executed.

[0037] The present application also provides a computer program product. When the computer program product is executed by a computer device, the method described in any of the preceding items is executed.

[0038] The present application also provides a computer device, the computer device comprising: one or more processors; a memory for storing one or more computer programs; When the one or more computer programs are executed by the one or more processors, the one or more processors are caused to implement the method as described in any of the preceding items.

[0039] Figure 3 An exemplary system that can be used to implement various embodiments described in this application is shown; like Figure 3 In some embodiments shown, the system 300 can be used as any of the devices in the various described embodiments. In some embodiments, the system 300 may include one or more computer-readable media (e.g., system memory or NVM / storage device 320) with instructions and one or more processors (e.g., (one or more) processors 305) coupled to the one or more computer-readable media and configured to execute instructions to implement modules to perform the actions described in this application.

[0040] For one embodiment, system control module 310 may include any suitable interface controller to provide any suitable interface to at least one of processor(s) 305 and / or any suitable device or component in communication with system control module 310 .

[0041] The system control module 310 may include a memory controller module 330 to provide an interface to the system memory 315. The memory controller module 330 may be a hardware module, a software module, and / or a firmware module.

[0042] The system memory 315 may be used, for example, to load and store data and / or instructions for the system 300. For one embodiment, the system memory 315 may include any suitable volatile memory, such as a suitable DRAM. In some embodiments, the system memory 315 may include double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).

[0043] For one embodiment, system control module 310 may include one or more input / output (I / O) controllers to provide interfaces to NVM / storage device 320 and communication interface(s) 325 .

[0044] For example, NVM / storage device 320 may be used to store data and / or instructions. NVM / storage device 320 may include any suitable non-volatile memory (e.g., flash memory) and / or may include any suitable non-volatile storage device(s) (e.g., one or more hard disk drives (HDDs), one or more compact disk (CD) drives, and / or one or more digital versatile disk (DVD) drives).

[0045] NVM / storage device 320 may include storage resources that are physically part of the device on which system 300 is installed, or it may be accessible to the device without being part of the device. For example, NVM / storage device 320 may be accessed over a network via communication interface(s) 325.

[0046] Communication interface(s) 325 may provide an interface for system 300 to communicate over one or more networks and / or with any other suitable devices. System 300 may wirelessly communicate with one or more components of a wireless network in accordance with any of one or more wireless network standards and / or protocols.

[0047] For one embodiment, at least one of the processor(s) 305 may be packaged together with the logic of one or more controllers of the system control module 310 (e.g., the memory controller module 330). For one embodiment, at least one of the processor(s) 305 may be packaged together with the logic of one or more controllers of the system control module 310 to form a system-in-package (SiP). For one embodiment, at least one of the processor(s) 305 may be integrated on the same die with the logic of one or more controllers of the system control module 310. For one embodiment, at least one of the processor(s) 305 may be integrated on the same die with the logic of one or more controllers of the system control module 310 to form a system on chip (SoC).

[0048] In various embodiments, the system 300 may be, but is not limited to: a server, a workstation, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet computer, a netbook, etc.). In various embodiments, the system 300 may have more or fewer components and / or a different architecture. For example, in some embodiments, the system 300 includes one or more cameras, a keyboard, a liquid crystal display (LCD) screen (including a touch screen display), a non-volatile memory port, multiple antennas, a graphics chip, an application specific integrated circuit (ASIC), and a speaker.

[0049] It should be noted that the present application can be implemented in software and / or a combination of software and hardware, for example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In one embodiment, the software program of the present application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of the present application (including related data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and the like. In addition, some steps or functions of the present application can be implemented using hardware, for example, as a circuit that cooperates with a processor to perform various steps or functions.

[0050] In addition, a part of the present application may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present application through the operation of the computer. Those skilled in the art should understand that the existence of computer program instructions in computer-readable media includes but is not limited to source files, executable files, installation package files, etc., and accordingly, the way in which computer program instructions are executed by a computer includes but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0051] Communication media include media by which communication signals containing, for example, computer readable instructions, data structures, program modules, or other data are transmitted from one system to another. Communication media may include guided transmission media such as cables and wires (e.g., fiber optic, coaxial, etc.) and wireless (unguided transmission) media that can propagate energy waves, such as acoustic, electromagnetic, RF, microwave, and infrared. Computer readable instructions, data structures, program modules, or other data may be embodied as a modulated data signal in, for example, a wireless medium such as a carrier wave or similar mechanism such as embodied as part of spread spectrum technology. The term "modulated data signal" refers to a signal whose one or more characteristics are changed or set in such a manner as to encode information in the signal. Modulation may be analog, digital, or a hybrid modulation technique.

[0052] By way of example and not limitation, computer-readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media include, but are not limited to, volatile memory, such as random access memory (RAM, DRAM, SRAM); and non-volatile memory, such as flash memory, various read-only memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic / ferroelectric memories (MRAM, FeRAM); and magnetic and optical storage devices (hard disks, magnetic tapes, CDs, DVDs); or other media now known or later developed that can store computer-readable information / data for use with a computer system.

[0053] Here, according to one embodiment of the present application, a device is included, which includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein, when the computer program instructions are executed by the processor, the device is triggered to run the methods and / or technical solutions based on the aforementioned multiple embodiments of the present application.

[0054] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or essential features of the present application.

Claims

1. A method for automatically adjusting water supply temperature, characterized in that: The method comprises: In the target operation state, a first parameter set is input into a first model, and a first indoor temperature is output through the first model, wherein the first parameter set includes current water supply temperature, current indoor information, current rainfall information, and current snowfall information; If the first indoor temperature matches the set temperature, continue to operate at the current water supply temperature; otherwise, determine that the impact of the current indoor information, the current rainfall information, or the current snowfall information on the first indoor temperature reaches the target impact threshold, determine a candidate water supply temperature reference value, and determine multiple candidate water supply temperatures based on the candidate water supply temperature reference value, the difference between the first indoor temperature and the set temperature; For each candidate water supply temperature, input the candidate water supply temperature and a second parameter set into a second model, and output a second indoor temperature and second energy consumption information corresponding to the candidate water supply temperature through the second model; The target water supply temperature is determined according to the obtained data combination of the multiple groups of candidate water supply temperatures, the second indoor temperature, and the second energy consumption information.

2. The method according to claim 1, characterized in that The step of determining a candidate water supply temperature reference value, and determining a plurality of candidate water supply temperatures according to the candidate water supply temperature reference value, a difference between the first indoor temperature and the set temperature, comprises: The candidate water supply temperature reference value is determined by a physical model, wherein the physical model includes: , here, the Including the current indoor temperature, the including the current outdoor air temperature, the Including the surface solar absorption rate, the Including the current solar radiation intensity hitting the wall, Including the outer surface heat release coefficient, the Including the refrigerant specific heat capacity, the Including the mass flow rate of the refrigerant, the Including candidate water supply temperature reference value, the Including the current return water temperature, the includes the effective heat transfer resistance of the enclosure structure, C includes the effective heat capacity of indoor air, Including the indoor temperature at the previous moment, including the indoor and outdoor temperature difference, said e including said first coefficient; The candidate water supply temperature is determined by substituting the difference between the first indoor temperature and the set temperature and the candidate water supply temperature reference value into a candidate water supply temperature calculation formula, wherein the candidate water supply temperature calculation formula includes: , here, the including the candidate water supply temperature, the Including the candidate water supply temperature reference value, the Including the adjustment factor, the including a difference between the first indoor temperature and a set temperature; By performing discretization processing on the candidate water supply temperatures, a plurality of candidate water supply temperatures are obtained.

3. The method according to claim 1, characterized in that The current indoor information includes current number of people information, and the current number of people information is output by inputting target feature data information into the third model.

4. The method according to claim 3, characterized in that The target characteristic data information includes at least one of the following: Current infrared signal direction information; Information about the current wireless signal strength.

5. The method according to claim 4, characterized in that An infrared device is provided at the indoor entrance and exit, and the infrared device includes a first infrared sensor and a second infrared sensor arranged in parallel in the horizontal direction. The infrared signal direction information is obtained by the following method: Acquire a first infrared signal and a second infrared signal through the first infrared sensor and the second infrared sensor respectively; The infrared signal direction information is determined according to the time sequence of acquiring the first infrared signal and the second infrared signal, wherein the infrared signal direction information includes forward and reverse. When the first infrared signal is acquired first and then the second infrared signal is acquired, the infrared direction information is determined to be forward; when the second infrared signal is acquired first and then the first infrared signal is acquired, the infrared direction information is determined to be reverse.

6. The method according to claim 3, characterized in that The third model is trained by the following scheme: Based on a machine learning algorithm, the third model is obtained by training a data combination of multiple groups of infrared signal direction information and wireless signal strength related information, so that the current number of people information is output through the third model by inputting the current infrared signal direction information and the current wireless signal strength related information into the third model.

7. The method according to claim 1, characterized in that The first parameter set includes the current moment, the moments before the current moment, and the water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, first energy consumption information, and the return water temperature at the previous moment, and a matrix composed of the outdoor temperature prediction value at the next moment at each moment; the second model includes a related model of the first model, and for each candidate water supply temperature, the second parameter set includes the current moment, the moments before the current moment, and the water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information, energy consumption information, and the return water temperature at the previous moment, and a matrix composed of the outdoor temperature prediction value at the next moment, wherein the water supply temperature at the current moment in the second parameter set is the candidate water supply temperature, and compared with the first parameter set, the energy consumption information at the current moment is removed from the second parameter set, and here, n is a positive integer.

8. The method according to claim 7, characterized in that The first model is trained by the following method: Based on the long short-term memory network, the long short-term memory network is trained by a first parameter set at multiple different moments to obtain the first model, wherein the first parameter set at each moment includes the first moment, the moments before the first moment, and a matrix consisting of water supply temperature, indoor information, rainfall information, snowfall information, indoor temperature information, outdoor temperature information, indoor humidity information, return water temperature information at each moment, and the return water temperature at the moment before the first moment, and the outdoor temperature prediction value at the next moment of the first moment, where n is a positive integer.

9. A computer device for automatically adjusting water supply temperature, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes any one of the methods of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 8.

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