Heat source selection method, temperature controller, electronic equipment and computer readable storage medium

Abstract

The invention provides a heat source selection method, a temperature controller, electronic equipment and a computer readable storage medium. The method comprises the following steps: judging whether a cloud server is accessed currently or not; if the cloud server is not accessed, acquiring locally stored planned rate data corresponding to each heat source, the planned rate data being obtained by rate data historically sent by the cloud server; and determining a target heat source according to the planned rate data. When the cloud server is accessed, the planned rate data is generated based on the rate data sent by the cloud server, so that when the cloud server is disconnected, the target heat source can be determined based on the planned rate data, and the effect of automatic heat source switching under the condition that the cloud server is not accessed is achieved.

Description

Technical Field

[0001] The present invention relates to the field of temperature control, and in particular to a heat source selection method, a temperature controller, an electronic device and a computer-readable storage medium. Background Art

[0002] The existing intelligent switching heat source algorithm can only be used when there is a network. When the connection with the cloud server is disconnected, the automatic switching of the heat source cannot be achieved. Summary of the invention

[0003] The main purpose of the present invention is to propose a heat source selection method, a temperature controller, an electronic device and a computer-readable storage medium, aiming to solve the problem in the prior art that the heat source cannot be automatically switched when the connection with the cloud server is disconnected.

[0004] To achieve the above object, the present invention provides a heat source selection method, the method comprising the steps of:

[0005] Determine whether the cloud server is currently connected;

[0006] If the cloud server is not connected, then obtaining the planned rate data corresponding to each heat source stored locally, wherein the planned rate data is obtained from the rate data historically sent by the cloud server;

[0007] A target heat source is determined based on the planned rate data.

[0008] Optionally, determining the target heat source according to the planned rate data includes:

[0009] Acquire a rate curve in the planned rate data, wherein the rate curve is a curve based on a system time and a rate ratio, wherein the rate ratio is a first heat source rate / a second heat source rate;

[0010] Obtaining the current system time, and determining a target rate ratio corresponding to the current system time on the rate curve;

[0011] Determine whether the target rate ratio is greater than 1;

[0012] If the target rate ratio is greater than 1, the heat source corresponding to the second heat source rate is used as the target heat source.

[0013] Optionally, the determining whether the cloud server is currently connected includes:

[0014] If the cloud server is connected, the desired heat source and real-time rate data sent by the cloud server are received;

[0015] Acquire the planned rate data stored locally, and update the planned rate data using the real-time rate data;

[0016] The desired heat source is used as the target heat source.

[0017] Optionally, the updating of the planned rate data by using the real-time rate data includes:

[0018] Obtain the time rate corresponding to the real-time rate data, and obtain the rate curve in the planned rate data;

[0019] Determining a rate point to be updated corresponding to the rate at the time on the rate curve;

[0020] Calculate the average rate of the moment and the rate of the rate point to be updated;

[0021] The rate point to be updated is updated to the rate average value.

[0022] Optionally, the calculating the rate average of the rate at the moment and the rate point to be updated includes:

[0023] Determine the time difference between the time rate and the current system time;

[0024] Matching a target weight corresponding to the time difference, wherein the target weight is negatively correlated with the time difference;

[0025] The rate at the time and the rate point to be updated are weighted averaged by the target weight to obtain the rate average value.

[0026] Optionally, updating the to-be-updated rate point to the rate average value includes:

[0027] Determine the rate difference between the rate at the moment and the rate point to be updated;

[0028] Determining whether the rate difference is greater than a preset difference threshold;

[0029] If the rate difference is greater than the preset difference threshold, the rate point to be updated is updated to the time rate.

[0030] Optionally, the updating of the planned rate data by using the real-time rate data includes:

[0031] Obtain the time rate corresponding to the real-time rate data, and obtain the rate curve in the planned rate data;

[0032] Determining a rate point to be updated corresponding to the rate at the time on the rate curve;

[0033] For the corresponding moment rate and the rate point to be updated, determining the rate difference between the moment rate and the rate point to be updated;

[0034] Determine the deviation number of the rate points to be updated whose rate difference is greater than a preset difference threshold;

[0035] Determine whether the deviation quantity is greater than a preset quantity threshold;

[0036] If the deviation amount is greater than the preset amount threshold, generating a latest rate curve according to the rate at the time;

[0037] The rate curve is replaced with the latest rate curve.

[0038] To achieve the above object, the present invention further provides a temperature controller, the temperature controller comprising:

[0039] The first judgment module is used to judge whether the cloud server is currently connected;

[0040] A first acquisition module, for acquiring locally stored planned rate data corresponding to each heat source if the cloud server is not connected, wherein the planned rate data is obtained from rate data historically sent by the cloud server;

[0041] The first determination module is used to determine the target heat source according to the planned rate data.

[0042] To achieve the above objectives, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the heat source selection method described above when executed by the processor.

[0043] To achieve the above object, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the heat source selection method described above are implemented.

[0044] The present invention proposes a heat source selection method, a thermostat, an electronic device, and a computer-readable storage medium, which determine whether the cloud server is currently connected; if the cloud server is not connected, the locally stored planned rate data corresponding to each heat source is obtained, and the planned rate data is obtained from the rate data historically sent by the cloud server; the target heat source is determined according to the planned rate data. By generating the planned rate data based on the rate data sent by the cloud server when connected to the cloud server, the target heat source can be determined based on the planned rate data when the cloud server is disconnected, thereby achieving the effect of automatic heat source switching when the cloud server is not connected. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0047] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0048] Figure 1 This is a schematic flow chart of a first embodiment of a heat source selection method of the present invention;

[0049] Figure 2 is a schematic diagram of a heat source selection system in the heat source selection method of the present invention;

[0050] Figure 3 It is a module structure diagram of the temperature controller of the present invention;

[0051] Figure 4 It is a schematic diagram of the module structure of the electronic device of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0053] The disclosure below provides many different embodiments or examples to implement different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0054] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In order 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 in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work should fall within the scope of protection of the present application.

[0055] The present invention provides a heat source selection method, referring to Figure 1 , Figure 1 This is a schematic flow chart of a first embodiment of a heat source selection method of the present invention, wherein the method comprises the following steps:

[0056] Step S10, determining whether the cloud server is currently connected;

[0057] The cloud server is used to collect relevant information about the heat source and make control decisions for the target heat source; see Figure 2 ,In this embodiment, the entire heat source selection system includes a cloud server, a thermostat, a user terminal and an energy information source;

[0058] Among them, the energy information source end is used to provide relevant information of the heat source; for example, the energy information source segment may include the Energy Bureau and the Meteorological Bureau; the Energy Bureau can provide real-time prices corresponding to different heat sources, and the Meteorological Bureau can provide weather data;

[0059] The user terminal is a terminal associated with the thermostat. The user can set the price corresponding to each heat source of his application on the user terminal and upload the heat source price to the cloud server;

[0060] The cloud server can specifically include an algorithm cloud and an IoT cloud; the IoT cloud communicates with fixed-line terminals and thermostats, and users can actively upload heat source prices to the IoT cloud; the IoT cloud can also periodically query the heat source prices set by users, and the IoT cloud sends the heat source prices to the algorithm cloud, which receives price data and weather data sent by the energy information source.

[0061] You can choose between the price data sent by the energy information source and the heat source price data uploaded by the user. If you set the price data from the energy information source to take priority, then when you receive the price data sent by the energy information source, you will make a decision based on the price data instead of the heat source price reported by the user terminal.

[0062] The algorithm cloud determines the target heat source and rate data through relevant data; it can be understood that the selection of the target heat source is based on price priority, that is, the heat source with lower cost is selected as the target heat source; and different heat sources have different efficiencies and prices. Therefore, when determining the target heat source, the prices of different heat sources need to be unified in units and then compared. For example, in this embodiment, the rates of different heat sources are calculated separately; the rate is the ratio of cost to efficiency; in this embodiment and subsequent embodiments, heat pumps and natural gas are used as heat sources for explanation; for heat pumps, heat pumps use electricity as energy, and the heat pump rate of heat pumps is electricity cost / heat pump performance coefficient, where the heat pump performance coefficient is different based on different models and different outdoor temperatures. Therefore, for a specific heat pump system, a corresponding table between the heat pump performance coefficient and the outdoor temperature can be pre-set. After obtaining the weather data, the algorithm cloud matches the heat pump performance coefficient through the temperature value in the weather data, and then determines the rate of the heat pump; for natural gas, natural gas itself is used as energy, and the gas rate of natural gas is unit gas price / heating furnace efficiency, where the heating furnace efficiency can be pre-obtained based on the performance of specific natural gas equipment.

[0063] After the heat pump rate and gas rate are determined, the heat source with the lower rate can be used as the target heat source. It should be noted that in actual applications, the price of the heat source will be set in stages, and the rate of the heat source will change with the usage of the heat source. Therefore, the rate of the heat source needs to be updated based on the price corresponding to the actual use of the heat source, so as to achieve the lowest cost of heat source use.

[0064] After the target heat source is determined, the algorithm cloud sends the target heat source to the IoT cloud, and the IoT cloud sends the corresponding expected heat source to the thermostat, and the thermostat sets the target heat source as the expected heat source.

[0065] Step S20, if the cloud server is not connected, then obtain the planned rate data corresponding to each heat source stored locally, the planned rate data is obtained from the rate data historically sent by the cloud server;

[0066] When the cloud server is not connected, the desired heat source sent by the cloud server cannot be received; in order to still be able to select a lower-cost heat source when the cloud server is not connected, in this embodiment, the planned rate data is stored locally, and the planned rate data is obtained from the rate data previously sent by the cloud server.

[0067] Each time the cloud server sends the expected heat source, it will also send the corresponding rate data. The rate data is used to indicate the relationship between the rates of different heat sources at the corresponding time. Specifically, the rate data contains multiple points, namely the moment rates, where the points correspond to the size status between different heat sources at a specific moment. It should be noted that the rate data is predicted by the cloud server. For example, the cloud server predicts the tiered price and heat pump performance coefficient in the next period of time based on the actual use of each heat source and the weather forecast, and then predicts the rate of each heat source in the future period of time, thereby obtaining the corresponding rate data. The specific time period involved in the rate data can be set based on actual needs.

[0068] After receiving the rate data, the thermostat obtains the planned rate data based on the rate data. The planned rate data reflects the correlation between the rates of different heat sources, that is, which heat source generates less cost.

[0069] Step S30, determining a target heat source according to the planned rate data.

[0070] The planned rate data reflects the price relationship between different heat sources. Therefore, the target heat source with a lower price can be determined through the planned rate data.

[0071] This embodiment generates planned rate data based on the rate data sent by the cloud server when connected to the cloud server, so that when the connection with the cloud server is disconnected, the target heat source can be determined based on the planned rate data, thereby achieving the effect of automatic heat source switching when the cloud server is not connected.

[0072] Further, in the second embodiment of the heat source selection method of the present invention proposed based on the first embodiment of the present invention, the step S30 includes the steps of:

[0073] Step S31, obtaining a rate curve in the planned rate data, wherein the rate curve is based on a system time and a rate ratio, wherein the rate ratio is a first heat source rate / a second heat source rate;

[0074] Step S32, obtaining the current system time, and determining the target rate ratio corresponding to the current system time on the rate curve;

[0075] Step S33, determining whether the target rate ratio is greater than 1;

[0076] Step S34: if the target rate ratio is greater than 1, the heat source corresponding to the second heat source rate is used as the target heat source.

[0077] The rate curve is obtained from the rate data; it can be understood that the rate data includes the moment rate, and the moment rate includes the size status between different heat sources at a specific moment. Therefore, the moment rate can be used to find a point in a coordinate system with the system moment as the horizontal axis and the rate ratio as the vertical axis; the moment rate can directly include the rate ratio, or it can include the first heat source rate and the second heat source rate, and the rate ratio can be obtained by calculating the value of the first heat source rate / the second heat source rate.

[0078] The first heat source rate is the rate corresponding to the first heat source, and the second heat source rate is the rate corresponding to the second heat source. In this embodiment, natural gas is used as the first heat source and a heat pump is used as the second heat source as an example for explanation.

[0079] It can be understood that the rates of different heat sources have unified the measurement standards. Therefore, by comparing the sizes of the heat source rates, the cost level can be known. When the system time is determined, the target rate ratio corresponding to the system time is determined on the rate curve. If the target rate ratio is greater than 1, it means that the first heat source rate is greater than the second heat source rate. Therefore, the cost of the second heat source is less than the first heat source. Therefore, the heat source corresponding to the second heat source is used as the target heat source. On the contrary, if the target rate ratio is less than 1, it means that the first heat source rate is less than the second heat source rate. Therefore, the cost of the second heat source is greater than the first heat source. Therefore, the heat source corresponding to the first heat source is used as the target heat source. When the target rate ratio is equal to 1, it means that the cost generated by the first heat source and the second heat source is the same. Therefore, the current heat source can be kept unchanged.

[0080] Further, in a third embodiment of the heat source selection method of the present invention proposed based on the first embodiment of the present invention, the step S10 includes the following steps:

[0081] Step S40, if the cloud server is connected, receiving the expected heat source and real-time rate data sent by the cloud server;

[0082] Step S50, obtaining the planned rate data stored locally, and updating the planned rate data using the real-time rate data;

[0083] Step S60: taking the desired heat source as the target heat source.

[0084] The expected heat source is the heat source with the lowest cost determined by the cloud server; the real-time rate data is the latest rate data sent by the cloud server.

[0085] After receiving the desired heat source, the thermostat sets the target heat source as the desired heat source and supplies heat with the desired heat source.

[0086] The real-time rate data is obtained by the cloud server based on the latest relevant data obtained. Therefore, the real-time rate data is more accurate. Therefore, the locally stored planned rate data is updated through the real-time rate data so that the planned rate data is continuously updated to match the actual application scenario.

[0087] Furthermore, the step S50 includes the steps of:

[0088] Step S51, obtaining the time rate corresponding to the real-time rate data, and obtaining the rate curve in the planned rate data;

[0089] Step S52, determining a rate point to be updated corresponding to the rate at the time on the rate curve;

[0090] Step S53, calculating the average rate of the rate at the time and the rate point to be updated;

[0091] Step S54, updating the to-be-updated rate point to the rate average value.

[0092] The time rate includes the rate ratio corresponding to the specific time.

[0093] After determining the time rate, determine the rate point to be updated on the rate curve based on the same system time; and update the rate point by averaging the rate ratio corresponding to the two by means of an average value.

[0094] It should be noted that the rate curve stored locally is obtained or updated by historical rate data; and the time corresponding to the rate data of different periods may be different; it is understandable that if the rate data sent down at a single time contains more time rates, it is easy to cause a large pressure on the data processing of the cloud server, especially in the case where the user provides the heat source price, it is necessary to obtain rate data for the thermostats used by different users respectively; therefore, in this embodiment, the time staggered method can be used to reduce the number of time rates; for example, the number of time rates contained in the real-time rate data sent down every day is 24, and Adjacent time rates are separated by one hour; and for adjacent days, the corresponding time rates are separated by a deviation threshold, such as 10 minutes; for example, the time rates contained in the rate data generated yesterday correspond to 00:00, 01:00, 02:00, 03:00..., and the time rates contained in the rate data generated today correspond to 00:10, 01:10, 02:10, 03:10; the time rates are increased by 10 minutes in turn according to the number of days and cycled until the seventh day returns to 00:00, 01:00, 02:00, 03:00... In this case, the number of time rates to be issued every day is small, and at the same time, the thermostat generates and updates the time rate curve based on the rate data obtained in consecutive days, so that the rate curve can reflect the rate situation at multiple times and is smoother, so that the accuracy of the target heat source determination is improved while reducing the amount of data processing.

[0095] Furthermore, the step S53 comprises the steps of:

[0096] Step S531, determining the time difference between the instant rate and the current system time;

[0097] Step S532, matching a target weight corresponding to the time difference, wherein the target weight is negatively correlated with the time difference;

[0098] Step S533: performing weighted averaging of the rate at the time and the rate point to be updated by using the target weight to obtain the rate average value.

[0099] It can be understood that the closer to the current system time, the more the moment rate is calculated based on real data and the more it can reflect the actual rate; and the closer to the current system time, the higher the predicted component of the moment rate and the greater the possibility of error. Therefore, in this embodiment, different target weights are set for different time differences. The closer to the current system time, the higher the target weight of the moment rate, and the farther from the current system time, the smaller the target weight of the moment rate; the sum of the target weight and the weight of the rate point to be updated is 1, and the rate average value is obtained by weighted averaging, so that the average of the rate curve is more accurate.

[0100] In other embodiments, averaging can also be performed through a sliding window. For example, the length of the sliding window is set to 3, and the step size of the sliding window is set to 1. Then, within each time window, the sliding window averages all the rate points to be updated corresponding to three consecutive moments with the moment rate, and the average value obtained is the rate average corresponding to the first rate point to be updated in the window.

[0101] Furthermore, the step S54 comprises the steps of:

[0102] Step S541, determining the rate difference between the rate at the moment and the rate point to be updated;

[0103] Step S542, determining whether the rate difference is greater than a preset difference threshold;

[0104] Step S543: If the rate difference is greater than the preset difference threshold, the rate point to be updated is updated to the time rate.

[0105] The rate difference is used to indicate the degree of difference between the moment rate and the rate point to be updated; it is understandable that the larger the rate difference, the greater the deviation between the two, and the moment rate is the latest issued, therefore, the accuracy of the moment rate is considered to be greater than the rate point to be updated, therefore, when the rate difference is too large, specifically, when the rate difference is greater than the preset difference threshold, it is considered that the error of the rate point to be updated is too large, at this time, the rate point to be updated is eliminated and replaced with the moment rate; the specific value of the preset difference threshold can be set based on actual needs, such as 5%.

[0106] When the rate difference is less than the preset difference threshold, the rate average value is calculated based on the above method, and the rate point to be updated is updated to the rate average value.

[0107] Furthermore, the step S50 includes the steps of:

[0108] Step S51, obtaining the time rate corresponding to the real-time rate data, and obtaining the rate curve in the planned rate data;

[0109] Step S52, determining a rate point to be updated corresponding to the rate at the time on the rate curve;

[0110] Step S53, determining the rate difference between the time rate and the rate point to be updated for the corresponding time rate and the rate point to be updated;

[0111] Step S54, determining the deviation number of the rate points to be updated whose rate difference is greater than a preset difference threshold;

[0112] Step S55, determining whether the deviation quantity is greater than a preset quantity threshold;

[0113] Step S56, if the deviation amount is greater than the preset amount threshold, generating a latest rate curve according to the rate at the moment;

[0114] Step S57: replacing the rate curve with the latest rate curve.

[0115] When there are too many updated rate points with large errors in the rate curve, specifically, when the number of deviations is greater than a preset threshold, it is considered that the overall error of the rate curve is too large. Therefore, in order to eliminate the impact of the error as much as possible, the rate curve is regenerated based on the momentary rate in the real-time rate data, that is, the latest rate curve, and the latest rate curve replaces the rate curve.

[0116] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0117] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0118] The present application also provides a temperature controller for implementing the above heat source selection method, see Figure 3 , the thermostat includes:

[0119] The first determination module 10 is used to determine whether the cloud server is currently connected;

[0120] A first acquisition module 20, for acquiring locally stored planned rate data corresponding to each heat source if the cloud server is not connected, wherein the planned rate data is obtained from the rate data historically sent by the cloud server;

[0121] The first determination module 30 is used to determine a target heat source according to the planned rate data.

[0122] When the thermostat is connected to the cloud server, it generates planned rate data based on the rate data sent by the cloud server, so that when the connection with the cloud server is disconnected, the target heat source can be determined based on the planned rate data, thereby achieving the effect of automatic heat source switching when the cloud server is not connected.

[0123] It should be noted that the first judgment module 10 in this embodiment can be used to execute step S10 in the embodiment of the present application, the first acquisition module 20 in this embodiment can be used to execute step S20 in the embodiment of the present application, and the first determination module 30 in this embodiment can be used to execute step S30 in the embodiment of the present application.

[0124] Furthermore, the first determining module includes:

[0125] A first acquisition unit is used to acquire a rate curve in the planned rate data, wherein the rate curve is a curve based on a system time and a rate ratio, wherein the rate ratio is a first heat source rate / a second heat source rate;

[0126] A second acquisition unit, configured to acquire a current system time and determine a target rate ratio corresponding to the current system time on the rate curve;

[0127] A first judgment unit, used to judge whether the target rate ratio is greater than 1;

[0128] The first execution unit is configured to use the heat source corresponding to the second heat source rate as the target heat source if the target rate ratio is greater than 1.

[0129] Furthermore, the temperature controller also includes:

[0130] A first receiving module, for receiving the desired heat source and real-time rate data sent by the cloud server if the cloud server is connected;

[0131] A second acquisition module is used to acquire the planned rate data stored locally and update the planned rate data using the real-time rate data;

[0132] The first execution module is used to use the expected heat source as the target heat source.

[0133] Furthermore, the second obtaining includes:

[0134] A third acquisition unit is used to acquire the time rate corresponding to the real-time rate data and acquire the rate curve in the planned rate data;

[0135] A first determining unit, configured to determine a rate point to be updated corresponding to the rate at the moment on the rate curve;

[0136] A first calculation unit, used for calculating the rate at the moment and the rate average of the rate point to be updated;

[0137] The first updating unit is used to update the rate point to be updated to the rate average value.

[0138] Furthermore, the first computing unit includes:

[0139] A first determining subunit, used to determine the time difference between the moment rate and the current system time;

[0140] A first matching subunit, configured to match a target weight corresponding to the time difference, wherein the target weight is negatively correlated with the time difference;

[0141] The first calculation subunit is used to perform weighted averaging of the moment rate and the rate point to be updated by using the target weight to obtain the rate average value.

[0142] Furthermore, the first updating unit includes:

[0143] A second determination subunit, used to determine the rate difference between the rate at the moment and the rate point to be updated;

[0144] A first judgment subunit, used to judge whether the rate difference is greater than a preset difference threshold;

[0145] The first updating subunit is used to update the rate point to be updated to the moment rate if the rate difference is greater than the preset difference threshold.

[0146] Furthermore, the second acquisition module includes:

[0147] A fourth acquisition unit, configured to acquire the time rate corresponding to the real-time rate data, and acquire the rate curve in the planned rate data;

[0148] A second determining unit, configured to determine a rate point to be updated corresponding to the rate at the moment on the rate curve;

[0149] A third determining unit, configured to determine a rate difference between the rate at the moment and the rate point to be updated for the corresponding rate at the moment and the rate point to be updated;

[0150] A fourth determining unit, configured to determine the number of deviations of the rate points to be updated whose rate difference is greater than a preset difference threshold;

[0151] A second judgment unit is used to judge whether the deviation quantity is greater than a preset quantity threshold;

[0152] A first generating unit, configured to generate a latest rate curve according to the rate at the moment if the deviation amount is greater than the preset amount threshold;

[0153] The first replacing unit is used to replace the rate curve with the latest rate curve.

[0154] Reference Figure 4 In terms of hardware structure, the electronic device may include components such as a communication module 10, a memory 20, and a processor 30. In the electronic device, the processor 30 is connected to the memory 20 and the communication module 10 respectively, and a computer program is stored in the memory 20. The computer program is executed by the processor 30 at the same time, and the steps of the above method embodiment are implemented when the computer program is executed.

[0155] The communication module 10 can be connected to an external communication device through a network. The communication module 10 can receive requests from an external communication device, and can also send requests, instructions and information to the external communication device, which can be other electronic devices, servers or Internet of Things devices, such as televisions, etc.

[0156] The memory 20 can be used to store software programs and various data. The memory 20 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function (such as determining whether the cloud server is currently connected), etc.; the data storage area can include a database, and the data storage area can store data or information created according to the use of the system, etc. In addition, the memory 20 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0157] The processor 30 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 20, and calling data stored in the memory 20, so as to monitor the electronic device as a whole. The processor 30 may include one or more processing units; optionally, the processor 30 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 30.

[0158] although Figure 4 Although not shown, the electronic device may further include a circuit control module, which is used to connect to a power source to ensure the normal operation of other components. Figure 4 The electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0159] The present invention also provides a computer-readable storage medium on which a computer program is stored. The computer-readable storage medium may be Figure 4 The memory 20 in the electronic device may also be at least one of a ROM (Read-Only Memory) / RAM (Random Access Memory), a magnetic disk, and an optical disk. The computer-readable storage medium includes a number of instructions for enabling a terminal device with a processor (which may be a television, a car, a mobile phone, a computer, a server, a terminal, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0160] In the present invention, the terms "first", "second", "third", "fourth" and "fifth" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0161] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0162] Although the embodiments of the present invention have been shown and described above, the scope of protection of the present invention is not limited thereto. It is understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art can change, modify and replace the above embodiments within the scope of the present invention, and these changes, modifications and replacements should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A heat source selection method, characterized in that: The heat source selection method comprises: Determine whether the cloud server is currently connected; If the cloud server is not connected, then obtaining the planned rate data corresponding to each heat source stored locally, wherein the planned rate data is obtained from the rate data historically sent by the cloud server; A target heat source is determined based on the planned rate data.

2. The heat source selection method according to claim 1, characterized in that: Determining the target heat source according to the planned rate data includes: Acquire a rate curve in the planned rate data, wherein the rate curve is a curve based on a system time and a rate ratio, wherein the rate ratio is a first heat source rate / a second heat source rate; Obtaining the current system time, and determining a target rate ratio corresponding to the current system time on the rate curve; Determine whether the target rate ratio is greater than 1; If the target rate ratio is greater than 1, the heat source corresponding to the second heat source rate is used as the target heat source.

3. The heat source selection method according to claim 1, characterized in that: The step of determining whether the cloud server is currently connected includes: If the cloud server is connected, the desired heat source and real-time rate data sent by the cloud server are received; Acquire the planned rate data stored locally, and update the planned rate data using the real-time rate data; The desired heat source is used as the target heat source.

4. The heat source selection method according to claim 3, characterized in that: The updating of the planned rate data by using the real-time rate data comprises: Obtain the time rate corresponding to the real-time rate data, and obtain the rate curve in the planned rate data; Determining a rate point to be updated corresponding to the rate at the time on the rate curve; Calculate the average rate of the moment and the rate of the rate point to be updated; The rate point to be updated is updated to the rate average value.

5. The heat source selection method according to claim 4, characterized in that: The calculating of the rate average of the rate at the time and the rate point to be updated comprises: Determine the time difference between the time rate and the current system time; Matching a target weight corresponding to the time difference, wherein the target weight is negatively correlated with the time difference; The rate at the time and the rate point to be updated are weighted averaged by the target weight to obtain the rate average value.

6. The heat source selection method according to claim 4, characterized in that: The updating of the to-be-updated rate point to the rate average value comprises: Determine the rate difference between the rate at the moment and the rate point to be updated; Determining whether the rate difference is greater than a preset difference threshold; If the rate difference is greater than the preset difference threshold, the rate point to be updated is updated to the time rate.

7. The heat source selection method according to claim 3, characterized in that: The updating of the planned rate data by using the real-time rate data comprises: Obtain the time rate corresponding to the real-time rate data, and obtain the rate curve in the planned rate data; Determining a rate point to be updated corresponding to the rate at the time on the rate curve; For the corresponding moment rate and the rate point to be updated, determining the rate difference between the moment rate and the rate point to be updated; Determine the deviation number of the rate points to be updated whose rate difference is greater than a preset difference threshold; Determine whether the deviation quantity is greater than a preset quantity threshold; If the deviation amount is greater than the preset amount threshold, generating a latest rate curve according to the rate at the time; The rate curve is replaced with the latest rate curve.

8. A thermostat, characterized in that: The thermostat comprises: The first judgment module is used to judge whether the cloud server is currently connected; A first acquisition module, for acquiring locally stored planned rate data corresponding to each heat source if the cloud server is not connected, wherein the planned rate data is obtained from rate data historically sent by the cloud server; The first determination module is used to determine the target heat source according to the planned rate data.

9. An electronic device, characterized in that: The electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the heat source selection method according to any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the heat source selection method according to any one of claims 1 to 7 are implemented.

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