A data acquisition method and system for realizing household natural gas energy metering

Abstract

The embodiments of the present specification provide a data acquisition method and system for realizing household natural gas energy metering, the method comprising determining multiple gas sources in a natural gas transmission and distribution network that supply gas to a target user; determining the gas pressure of the natural gas provided by each of the gas sources to the target user according to the multiple user flows in the natural gas transmission and distribution network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each of the gas sources to the target user, and the network topology data; determining the gas transmission ratio of each of the gas sources to the target user based on the gas pressure of the natural gas provided by each of the gas sources to the target user; determining the mixed natural gas calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each of the gas sources to the target user; and determining the natural gas energy metering data of the target user based on the mixed natural gas calorific value and the gas consumption volume of the target user.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things technology, and in particular to a data acquisition method and system for realizing household natural gas energy metering. Background Art

[0002] Since the gas supply sources of some household gas pipelines are relatively complex, the household gas pipelines may include mixed natural gas from multiple gas sources. The calorific values ​​(calorific value per unit volume of natural gas) of different gas sources may be different. The calorific value detection of gas can often only be carried out in key departments (for example, the gas source). Therefore, it is difficult to obtain the calorific value of the mixed natural gas in the household gas pipeline, and thus it is difficult to accurately measure the energy consumption of users.

[0003] Therefore, it is necessary to provide a data acquisition method and system for realizing household natural gas energy metering, so as to accurately measure the energy of the user's gas consumption. Summary of the invention

[0004] One of the embodiments of this specification provides a data acquisition method for realizing household natural gas energy metering. The method includes: determining multiple gas sources that supply gas to target users in the natural gas transmission and distribution network; determining the gas pressure of the natural gas provided to the target user by each gas source based on the flow of multiple users in the natural gas transmission and distribution network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data; based on the gas pressure of the natural gas provided to the target user by each gas source, determining the gas transmission ratio of each gas source to the target user; based on the gas transmission ratio of each gas source to the target user, determining the mixed natural gas calorific value of the mixed natural gas used by the target user; based on the mixed natural gas calorific value and the gas consumption volume of the target user, determining the natural gas energy metering data of the target user.

[0005] One of the embodiments of the present specification provides a data acquisition system for realizing household natural gas energy metering, the system comprising: a gas source determination module, used to determine multiple gas sources in the natural gas transmission and distribution network that supply gas to a target user; a gas pressure determination module, used to determine the gas pressure of the natural gas provided by each gas source to the target user according to the multiple user flows in the natural gas transmission and distribution network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data; a ratio determination module, used to determine the gas transmission ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user; a calorific value determination module, used to determine the mixed natural gas calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user; and a metering determination module, used to determine the natural gas energy metering data of the target user based on the calorific value of the mixed natural gas and the gas consumption volume of the target user.

[0006] One of the embodiments of the present specification provides a data acquisition device for realizing household natural gas energy metering, including a processor, wherein the processor is used to execute a data acquisition method for realizing household natural gas energy metering.

[0007] One of the embodiments of the present specification provides a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a data acquisition method for realizing household natural gas energy metering. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0009] Figure 1 It is a schematic diagram of an application scenario of a data acquisition system for realizing household natural gas energy metering according to some embodiments of this specification;

[0010] Figure 2 is an exemplary block diagram of a data acquisition system for implementing household natural gas energy metering according to some embodiments of this specification;

[0011] Figure 3 is an exemplary flow chart of a data acquisition method for realizing household natural gas energy metering according to some embodiments of this specification;

[0012] Figure 4 is a schematic diagram of a natural gas transmission and distribution network according to some embodiments of this specification;

[0013] Figure 5 It is a schematic diagram of determining the failure risk of a gas source through a risk determination model according to some embodiments of this specification. DETAILED DESCRIPTION

[0014] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprises" and "includes" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0017] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0018] Figure 1 It is a schematic diagram of an application scenario 100 of a data acquisition system for realizing household natural gas energy metering according to some embodiments of this specification.

[0019] In some embodiments, the application scenario 100 may include a processing device 110, a network 120, a user terminal 130, and a storage device 140. The application scenario 100 may accurately measure the energy consumption of a user's gas by implementing the method and / or process disclosed in this specification.

[0020] The processing device 110 may be used to process data and / or information from at least one component of the application scenario 100 or an external data source (e.g., a cloud data center). The processing device 110 may access data and / or information from the user terminal 130 and / or the storage device 140 through the network 120. The processing device 110 may be directly connected to the user terminal 130 and / or the storage device 140 to access information and / or data. For example, the processing device 110 may obtain feature sequences of multiple historical time points from the user terminal 130 and / or the storage device 140. The processing device 110 may process the obtained data and / or information. For example, the processing device 110 can determine multiple gas sources that supply gas to the target user in the natural gas transmission and distribution network, determine the gas pressure of the natural gas provided to the target user by each gas source based on the multiple user flows in the natural gas transmission and distribution network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data, determine the gas transmission ratio of each gas source to the target user based on the gas pressure of the natural gas provided to the target user by each gas source, determine the mixed natural gas calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user, and determine the natural gas energy metering data of the target user based on the mixed natural gas calorific value and the gas consumption volume of the target user. In some embodiments, the processing device 110 can be a single server or a server group. The processing device 110 can be local or remote. The processing device 110 can be implemented on a cloud platform.

[0021] The network 120 may include any suitable network that provides information and / or data exchange that can facilitate the application scenario 100. In some embodiments, one or more components of the application scenario 100 (e.g., the processing device 110, the user terminal 130, and / or the storage device 140) may exchange information and / or data via the network 120.

[0022] In some embodiments, the network 120 may be any one or more of a wired network or a wireless network. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include a wired or wireless network access point, such as a base station and / or a network switching point, through which one or more components of the application scenario 100 may be connected to the network 120 to exchange data and / or information.

[0023] The user terminal 130 refers to one or more terminals or software used by the user. In some embodiments, the user terminal 130 may include but is not limited to a smart phone, a tablet computer, a laptop computer, a desktop computer, etc. In some embodiments, the user terminal 130 may interact with other components in the application scenario 100 through the network 120. For example, the user terminal 130 may send one or more control instructions to the processing device 110 to control the processing device 110 to determine the natural gas energy metering data of the target user. For another example, the user terminal 130 may determine the natural gas energy metering data of the target user from the processing device 110.

[0024] The storage device 140 may be used to store data, instructions and / or any other information. In some embodiments, the storage device 140 may store data and / or information obtained from the processing device 110 and / or the user terminal 130, etc. For example, the storage device 140 may store information about multiple gas sources in the natural gas transmission and distribution network that supply gas to a target user. For another example, the storage device 140 may store a trained machine learning model. In some embodiments, the storage device 140 may include a large-capacity memory, a removable memory, etc., or any combination thereof.

[0025] It should be noted that application scenario 100 is provided only for the purpose of illustration and is not intended to limit the scope of this specification. For those of ordinary skill in the art, various modifications or variations can be made according to the description of this specification. For example, application scenario 100 can also include a database. However, these variations and modifications will not deviate from the scope of this specification.

[0026] Figure 2 It is an exemplary block diagram of a data acquisition system 200 for implementing household natural gas energy metering according to some embodiments of the present specification.

[0027] In some embodiments, the data acquisition system 200 for implementing household natural gas energy metering may include a gas source determination module 210 , a gas pressure determination module 220 , a ratio determination module 230 , a calorific value determination module 240 and a metering determination module 250 .

[0028] The gas source determination module 210 may be used to determine multiple gas sources in the natural gas transmission and distribution network that supply gas to target users.

[0029] The gas pressure determination module 220 can be used to determine the gas pressure of the natural gas provided by each gas source to the target user based on the flow rates of multiple users in the natural gas transmission and distribution pipeline network, the natural gas pressure of the pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data.

[0030] In some embodiments, the gas pressure determination module 220 can also be used to: for each gas source, determine the gas transmission path between the gas source and the target user, wherein the gas transmission path is the path from the target gas pressure detection node between the gas source and the target user to the target user; obtain the gas transmission characteristic vector of the gas transmission path according to the multiple user flows in the natural gas transmission and distribution pipeline network, the natural gas pressure of the target gas pressure detection node, and the pipeline network topology data; based on the gas transmission characteristic vector of the gas transmission path, obtain the gas pressure of the natural gas provided by the gas source to the target user through a gas pressure prediction model.

[0031] In some embodiments, the gas transmission path includes at least one pipe segment, and the gas transmission feature vector of the gas transmission path is composed of the pipe segment gas transmission feature vector of the at least one pipe segment. The gas pressure determination module 220 can also be used to: sort the pipe segment gas transmission feature vectors of the at least one pipe segment according to the gas transmission order to obtain a feature vector sequence; based on the feature vector sequence, obtain the gas pressure of the natural gas provided by the gas source to the target user through the gas pressure prediction model.

[0032] In some embodiments, the gas pressure determination module 220 can also be used to determine the gas supply ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user and the diameter of the gas supply path corresponding to each gas source.

[0033] The ratio determination module 230 may be used to determine the gas supply ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user.

[0034] The calorific value determination module 240 may be used to determine the calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user.

[0035] The metering determination module 250 may be configured to determine the natural gas energy metering data of the target user based on the calorific value of the mixed natural gas and the gas consumption volume of the target user.

[0036] In some embodiments, the data acquisition system 200 for implementing household natural gas energy metering may also include a risk determination module 260, which is used to obtain the measured value of the natural gas pressure provided by the gas source to the target user; based on the measured value of the natural gas pressure of the gas source and the natural gas pressure provided by the gas source to the target user obtained by the gas pressure prediction model, determine the failure risk of the gas source.

[0037] In some embodiments, the data acquisition system 200 for implementing household natural gas energy metering may also include a prediction adjustment module 270, which is used to obtain the measured value of the natural gas pressure provided by at least one gas source to the target user; based on the measured value of the natural gas pressure provided by the at least one gas source to the target user, adjust the natural gas pressure provided by the at least one gas source to the target user obtained by the gas pressure prediction model.

[0038] For more information about the gas source determination module 210, the gas pressure determination module 220, the ratio determination module 230, the calorific value determination module 240, the metering determination module 250, the risk determination module 260, and the prediction adjustment module 270, see Figure 3 The related descriptions will not be repeated here.

[0039] Figure 3 This is an exemplary flow chart for generating energy metering data according to some embodiments of this specification. Since the gas supply sources of some household gas pipelines are relatively complex, the household gas pipelines may include mixed natural gas from multiple gas sources, and the calorific value (calorific value per unit volume of natural gas) of different gas sources may be different. The calorific value detection of gas can often only be performed in key departments (for example, gas sources), so it is difficult to obtain the calorific value of the mixed natural gas in the household gas pipeline, and thus it is difficult to accurately measure the energy consumption of the user's gas. Therefore, a more accurate energy metering method is needed, such as Figure 3 As shown, in some embodiments, generating energy metering data may include the following steps.

[0040] Step 310 , determining multiple gas sources in the natural gas transmission and distribution network that supply gas to the target user. In some embodiments, step 310 may be performed by the gas source determination module 210 .

[0041] The natural gas transmission and distribution network can be composed of multiple nodes, and two nodes can be connected by a natural gas pipeline. The nodes can be of different types, for example, a gas source node for providing natural gas, a user node for using natural gas, a pressure detection node for detecting the natural gas pressure, a connection node between two natural gas pipelines, etc.

[0042] In some embodiments, the gas source determination module 210 may obtain the natural gas transmission and distribution network from the user terminal 130 , the storage device 140 , and / or an external data source.

[0043] The target user may be a natural gas user corresponding to a user node in the natural gas transmission and distribution network.

[0044] In some embodiments, the gas source determination module 210 may determine multiple gas sources for supplying gas to the target user based on the natural gas transmission and distribution pipeline network. For example, the gas source determination module 210 may determine multiple gas source nodes connected to the user node corresponding to the target user based on the natural gas transmission and distribution pipeline network, and use the gas sources corresponding to the multiple gas source nodes as multiple gas sources for supplying gas to the target user. Figure 4 For user 2, the node corresponding to gas source S2 is connected to the node corresponding to user 2 through natural gas pipelines L1 and L2, and the node corresponding to gas source S1 is connected to the node corresponding to user 2 through natural gas pipelines L3, L4, L5 and L6. The gas source determination module 210 can determine that the gas sources supplying gas to user 2 include gas source S1 and gas source S2.

[0045] Step 320, based on the flow of multiple users in the natural gas transmission and distribution network, the natural gas pressure of the pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data, determine the gas pressure of the natural gas provided by each gas source to the target user. In some embodiments, step 320 can be performed by the gas pressure determination module 220.

[0046] The pipeline network topology data can characterize the connection relationship between each node in the natural gas transmission and distribution pipeline network.

[0047] In some embodiments, the gas pressure determination module 220 can determine the gas pressure of the natural gas provided to the target user by each gas source according to the flow rates of multiple users in the natural gas transmission and distribution pipeline network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data in any manner. For example, the gas pressure of the natural gas provided to the target user by each gas source can be determined manually according to the flow rates of multiple users in the natural gas transmission and distribution pipeline network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data.

[0048] In some embodiments, the air pressure determination module 220 can obtain the air pressure of the natural gas provided by the gas source to the target user through an air pressure prediction model, wherein the air pressure prediction model can be a machine learning model for determining the air pressure of the natural gas provided by the gas source to the target user. In some embodiments, for each gas source, the air pressure determination module 220 can first determine the gas transmission path from the gas source to the target user, and obtain the gas transmission feature vector of the gas transmission path based on the gas transmission feature vector of the gas transmission path through the air pressure prediction model, wherein the gas transmission path is the path from the target air pressure detection node between the gas source and the target user to the target user, and the target air pressure detection node is the air pressure detection node closest to the target user in the connection path between the gas source and the target user. Still with Figure 4For example, the gas source S2 first reaches node 5 through the natural gas pipeline L1, where node 5 is a gas pressure detection node, and then reaches the node corresponding to user 2 from node 5 through the natural gas pipeline L2. Therefore, node 5 is the target gas pressure detection node, and the path between node 5 and the node corresponding to user 2 (i.e., natural gas pipeline L2) is the gas transmission path.

[0049] In some embodiments, the parameters of the air pressure prediction model can be obtained by training multiple labeled training samples. In some embodiments, the air pressure determination module 220 can obtain multiple training samples, each training sample can include a gas transmission feature vector of a sample gas transmission path corresponding to a sample target user. In some embodiments, the air pressure determination module 220 can obtain training samples from the user terminal 130, the storage device 140 and / or an external data source. The label of the training sample is the gas pressure of the natural gas provided to the target user by the gas source corresponding to the sample gas transmission path. In some embodiments, the label of the training sample can be obtained in a variety of ways, for example, by manual annotation, or for example, from a user platform, a service platform, a sensor network platform, an object platform and / or an external data source.

[0050] The air pressure determination module 220 can train the initial air pressure prediction model through multiple training samples and their corresponding labels until the initial air pressure prediction model meets the preset conditions, thereby obtaining a trained air pressure prediction model. In some embodiments, the parameters of the initial air pressure prediction model can be iteratively updated based on the multiple training samples so that the initial air pressure prediction model meets the preset conditions, wherein the preset conditions can be that the loss function converges, the loss function value is less than the preset value, or the number of iterations is greater than the preset number of times. When the initial air pressure prediction model meets the preset conditions, the model training is completed, and a trained air pressure prediction model is obtained.

[0051] In some embodiments, the air pressure prediction model may include a combination of one or more of a convolutional neural network (CNN), a recurrent neural network (RNN), a multi-layer neural network (MLP), a generative adversarial neural network (GAN), and the like.

[0052] In some embodiments, a gas transmission characteristic vector of a gas transmission path is obtained based on the flow rates of multiple users in a natural gas transmission and distribution network, the natural gas pressure of a target gas pressure detection node, and the network topology data; based on the gas transmission characteristic vector of the gas transmission path, the gas pressure of the natural gas provided by the gas source to the target user is obtained through a gas pressure prediction model, so that the gas pressure of the natural gas provided by the gas source to the target user can be determined more accurately and quickly.

[0053] In some embodiments, the gas transmission path may be composed of at least one natural gas pipeline, and the gas transmission feature vector of the gas transmission path may be composed of the pipeline feature vector of at least one natural gas pipeline, wherein the pipeline feature vector may include at least one of the natural gas pressure of the target gas pressure detection node, the pipeline type (e.g., long-distance gas transmission pipeline, distribution pipeline, user introduction pipe, indoor gas pipeline, industrial enterprise gas pipeline, etc.), the number of associated branches, the number of associated user nodes, the total gas consumption of the associated user nodes, etc., the number of associated branches is the number of other natural gas pipelines connected to the natural gas pipeline, and the number of associated user nodes is the number of user nodes connected to the natural gas pipeline. In some embodiments, the pipe segment feature also includes at least one of the associated user node type distribution (e.g., industry, residential, office, etc.), gas transmission time type (e.g., rest day, working day, etc.), environmental characteristics (e.g., temperature, etc.), etc.

[0054] In some embodiments, the gas pressure determination module 220 may sort the pipeline gas transmission feature vectors of at least one pipeline segment according to the gas transmission sequence to obtain a feature vector sequence, wherein the gas transmission sequence is the sequence of the natural gas pipelines through which the natural gas is transported from the target gas pressure detection node to the target user. Figure 4 For example, the gas source S1 that provides natural gas to user 2 has a gas transmission order corresponding to user 2: L5→L4→L3. Therefore, the gas pressure determination module 220 can sort the pipeline gas transmission feature vectors of pipeline sections L5, L4, and L3 according to the gas transmission order to obtain a feature vector sequence (L5, L4, L3).

[0055] In some embodiments, the length of the feature vector sequence may be a fixed value, for example, 8 pipeline gas transmission feature vectors. When the number of pipelines included in the gas transmission path is less than 8, the air pressure determination module 220 may fill the feature vector sequence with data so that the length of the feature vector sequence reaches the fixed value. Figure 4 For example, for the feature vector sequence (L5, L4, L3), the air pressure determination module 220 performs data padding so that the feature vector sequence length reaches the fixed value (for example, 6) and the feature vector sequence is (L5, L4, L3, 0, 0, 0).

[0056] In some embodiments, the input of the gas pressure prediction model may be a feature vector sequence, and the output of the gas pressure prediction model may be the gas pressure of the natural gas provided by the gas source to the target user.

[0057] In some embodiments, the gas transmission feature vectors of at least one pipeline segment are sorted according to the gas transmission order to obtain a feature vector sequence. Based on the feature vector sequence, the pressure of the natural gas provided by the gas source to the target user is obtained through a gas pressure prediction model. The impact of the upstream and downstream pipeline segments on the gas transmission of the intermediate pipeline segment can be taken into account when the gas pressure prediction model is used for prediction, so that the predicted natural gas pressure provided by the gas source to the target user is more accurate.

[0058] In some embodiments, the risk determination module 260 and / or the prediction adjustment module 270 may obtain a measured value of the natural gas pressure provided by at least one gas source to the target user, wherein the measured value of the natural gas pressure provided by the gas source to the target user is the natural gas pressure actually provided by the gas source to the target user. In some embodiments, the gas pressure determination module 220 may obtain the natural gas transmission and distribution network from the user terminal 130, the storage device 140 and / or an external data source.

[0059] In some embodiments, the prediction adjustment module 270 can adjust the gas pressure of the natural gas provided to the target user by at least one gas source obtained by the gas pressure prediction model based on the measured value of the natural gas pressure provided to the target user by at least one gas source. For example, the prediction adjustment module 270 can use the measured value of the natural gas pressure provided by the gas source to the target user to replace the gas pressure of the natural gas provided by the gas source to the target user obtained by the gas pressure prediction model. For another example, the prediction adjustment module 270 can use the measured value of the natural gas pressure provided by the gas source to the target user to modify the gas pressure of the natural gas provided by the gas source to other target users obtained by the gas pressure prediction model. Figure 4 For example, for gas source S1, which provides natural gas to users 2 and 3, when the measured value of the natural gas pressure provided by the gas source to user 2 is greater than the natural gas pressure provided by the gas source to user 2 obtained by the pressure prediction model, the prediction adjustment module 270 can increase the natural gas pressure provided by the gas source to user 3 obtained by the pressure prediction model. For example, the prediction adjustment module 270 can determine the adjustment value of the natural gas pressure provided by the gas source to user 3 obtained by adjusting the pressure prediction model according to the following formula:

[0060] The adjustment value of the gas pressure of the natural gas provided by the gas source S2 to the user 3 = the adjustment value of the predicted value of the natural gas pressure provided by the gas source S2 to the user 2 / (a*number of users);

[0061] Among them, a is a preset coefficient, the adjustment value of the predicted value of the natural gas pressure provided by gas source S2 to user 2 = the actual measured value of the natural gas pressure provided by gas source S2 to user 2 - the pressure of the natural gas provided by the gas source to user 2 obtained by the pressure prediction model, and the number of users is the total number of users provided with natural gas by gas source S2.

[0062] In some embodiments, by adjusting the pressure of natural gas provided by at least one gas source to the target user obtained by a pressure prediction model based on the actual measured value of the natural gas pressure provided by at least one gas source to the target user, the gas supply ratio of each gas source to the target user determined based on the pressure of the natural gas provided to the target user by multiple gas sources can be made more accurate, thereby making the natural gas energy metering data determined for the target user more accurate.

[0063] In some embodiments, the risk determination module 260 may determine the failure risk of the gas source based on the measured value of the natural gas pressure of the gas source and the pressure of the natural gas provided to the target user by the gas source obtained by the pressure prediction model. For example, when the difference between the measured value of the natural gas pressure of the gas source and the pressure of the natural gas provided to the target user by the gas source obtained by the pressure prediction model is greater than a preset difference threshold, the risk determination module 260 may determine that there is a fault in the gas source and / or the natural gas pipeline between the gas source and the target user. It can be understood that the greater the difference between the measured value of the natural gas pressure of the gas source and the pressure of the natural gas provided to the target user by the gas source obtained by the pressure prediction model, the greater the failure risk of the gas source.

[0064] Reference Figure 5 In some embodiments, the risk determination module 260 can determine the failure risk 540 of the gas source through the risk determination model 510 based on the measured value 520 of the natural gas pressure of the gas source and the gas pressure 530 of the natural gas provided to the target user by the gas source obtained by the gas pressure prediction model 550. The risk determination model 510 is a machine learning model for determining the failure risk of the gas source. The input of the risk determination model 510 is the measured value 520 of the natural gas pressure of the gas source and the gas pressure 530 of the natural gas provided to the target user by the gas source obtained by the gas pressure prediction model 550. The output of the risk determination model 510 can be the failure risk 540 of the gas source, wherein the failure risk 540 of the gas source can be in any form. For example, the failure risk 540 of the gas source can be represented by an integer between 0 and 10, and the larger the value, the greater the risk. The training and structure of the risk determination model are similar to those of the gas pressure prediction model. For more descriptions of the risk determination model, please refer to the relevant descriptions of the gas pressure prediction model, which will not be repeated here. It is worth noting that the sample data used to train the risk determination model includes the measured value of the natural gas pressure of the sample gas source and the natural gas pressure provided by the sample gas source to the target user obtained by the gas pressure prediction model. The label of the sample data is the failure risk value of the sample gas source. In some embodiments, the label of the sample data can be obtained in any way, for example, manual labeling.

[0065] In some embodiments, the failure risk of the gas source is determined based on the measured value of the natural gas pressure of the gas source and the pressure of the natural gas provided by the gas source to the target user obtained by a gas pressure prediction model, which can effectively remind operators to inspect the gas source and / or the natural gas pipeline between the gas source and the target user.

[0066] Step 330 , based on the gas pressure of the natural gas provided by each gas source to the target user, determine the gas supply ratio of each gas source to the target user. In some embodiments, step 330 may be performed by the ratio determination module 230 .

[0067] In some embodiments, the ratio determination module 230 can directly determine the gas transmission ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user. For example, the ratio determination module 230 can determine the gas transmission ratio of each gas source to the target user based on the ratio of the gas pressure of the natural gas provided by each gas source to the target user to the total gas pressure. For example, the gas pressure provided by gas source 1 to the target user is 0.02MPa, the gas pressure provided by gas source 2 to the target user is 0.01MPa, and the gas pressure provided by gas source 3 to the target user is 0.02MPa, then the gas transmission ratio provided by gas source 1 to the target user = 0.02 / (0.02+0.01+0.02) = 0.4.

[0068] In some embodiments, the ratio determination module 230 may determine the gas transmission ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user and the diameter of the gas transmission path corresponding to each gas source. For example, the greater the gas pressure of the natural gas provided by the gas source to the target user, the greater the diameter of the gas transmission path corresponding to the gas source, and the greater the gas transmission ratio of the gas source to the target user, wherein, if the gas transmission path corresponding to the gas source is composed of multiple natural gas pipelines, the diameter of the gas transmission path corresponding to the gas source is the average of the diameters of the multiple natural gas pipelines.

[0069] In some embodiments, the ratio determination module 230 may determine the gas transmission ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user and the diameter of the gas transmission path corresponding to each gas source by the following formula:

[0070]

[0071] Among them, A n is the gas transmission ratio of the nth gas source, P n is the gas pressure of the natural gas provided by the nth gas source to the target user, D n is the diameter of the gas transmission path corresponding to the nth gas source, m is the total number of gas sources providing natural gas to the target user, P i is the gas pressure of the natural gas provided by the i-th gas source to the target user, D iis the diameter of the gas transmission path corresponding to the i-th gas source.

[0072] In some embodiments, by determining the gas delivery ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user and the diameter of the gas delivery path corresponding to each gas source, the gas delivery ratio of each gas source to the target user can be determined more accurately.

[0073] Step 340 , based on the gas transmission ratio of each gas source to the target user, determine the mixed natural gas calorific value of the mixed natural gas used by the target user. In some embodiments, step 340 may be performed by the calorific value determination module 240 .

[0074] In some embodiments, the calorific value determination module 240 can determine the calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user and the calorific value of each gas source, wherein the calorific value of each gas source refers to the heat that can be released by burning a unit volume or mass of natural gas provided by the gas source. In some embodiments, the calorific value determination module 240 can determine the calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user and the calorific value of each gas source by the following formula:

[0075]

[0076] Where Q is the calorific value of the mixed natural gas used by the target user, Q i is the calorific value of the natural gas source that provides natural gas to the target user, A i is the gas transmission ratio of the i-th gas source providing natural gas to the target user, and m is the total number of gas sources providing natural gas to the target user.

[0077] Step 350 , based on the calorific value of the mixed natural gas and the gas consumption volume of the target user, determine the natural gas energy metering data of the target user. In some embodiments, step 350 may be performed by the metering determination module 250 .

[0078] In some embodiments, the metering determination module 250 may determine the natural gas energy metering data of the target user based on the product of the mixed natural gas calorific value and the gas consumption volume of the target user.

[0079] In some embodiments, the pressure of natural gas provided by each gas source to the target user can be determined based on the flow rates of multiple users in the pipeline network, the natural gas pressures of pressure detection nodes in the gas transmission paths from each gas source to the target user, and the pipeline network topology data. Based on the pressures of natural gas provided by multiple gas sources to the target user, the gas transmission ratio of each gas source to the target user can be determined. Based on the gas transmission ratio of multiple gas sources to the target user, the mixed natural gas calorific value of the mixed natural gas used by the target user can be obtained. Based on the calorific value of the mixed natural gas and the gas consumption volume of the target user, more accurate natural gas energy metering data for the target user can be determined.

[0080] One of the embodiments of the present specification provides a data acquisition device for realizing household natural gas energy metering, including a processor, wherein the processor is used to execute a data acquisition method for realizing household natural gas energy metering.

[0081] One of the embodiments of the present specification provides a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a data acquisition method for realizing household natural gas energy metering.

[0082] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0083] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0084] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0085] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0086] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0087] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0088] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A data acquisition method for realizing household natural gas energy metering, generating energy metering data, comprising: Identify multiple gas sources in the natural gas transmission and distribution network that supply gas to target users; Determining the gas pressure of the natural gas provided by each gas source to the target user according to the flow of multiple users in the natural gas transmission and distribution pipeline network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data, including: For each gas source, Determine a gas transmission path from the gas source to the target user, wherein the gas transmission path is a path from a target gas pressure detection node between the gas source and the target user to the target user; Acquire a gas transmission feature vector of the gas transmission path according to the multiple user flows in the natural gas transmission and distribution pipeline network, the natural gas pressure of the target gas pressure detection node, and the pipeline network topology data; Based on the gas transmission characteristic vector of the gas transmission path, obtaining the gas pressure of the natural gas provided by the gas source to the target user through a gas pressure prediction model; Determining the gas supply ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user; Determining the mixed natural gas calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user; The natural gas energy metering data of the target user is determined based on the calorific value of the mixed natural gas and the gas consumption volume of the target user.

2. The method according to claim 1, wherein the gas pressure of the natural gas provided by the gas source to the target user is obtained through a gas pressure prediction model based on the gas transmission characteristic vector of the gas transmission path, comprising: The gas transmission path includes at least one pipe segment, and the gas transmission feature vector of the gas transmission path is composed of the pipe segment gas transmission feature vector of the at least one pipe segment; sorting the pipeline gas transmission feature vectors of the at least one pipeline segment according to the gas transmission order to obtain a feature vector sequence; Based on the feature vector sequence, the gas pressure of the natural gas provided by the gas source to the target user is obtained through the gas pressure prediction model.

3. The method according to claim 1, wherein the gas supply ratio of each gas source to the target user is determined based on the gas pressure of the natural gas respectively provided to the target user by the plurality of gas sources, comprising: Based on the gas pressure of the natural gas provided by each gas source to the target user and the diameter of the gas transmission path corresponding to each gas source, the gas transmission ratio of each gas source to the target user is determined.

4. The method of claim 3, further comprising: Obtaining a measured value of the natural gas pressure provided by the gas source to the target user; The failure risk of the gas source is determined based on the measured value of the natural gas pressure of the gas source and the pressure of the natural gas provided by the gas source to the target user obtained by the gas pressure prediction model.

5. The method of claim 1, further comprising: Obtaining a measured value of the natural gas pressure provided by at least one gas source to a target user; Based on the measured value of the natural gas pressure provided by the at least one gas source to the target user, the gas pressure of the natural gas provided by the at least one gas source to the target user obtained by the gas pressure prediction model is adjusted.

6. A data acquisition system for realizing household natural gas energy metering, comprising: A gas source determination module is used to determine multiple gas sources in the natural gas transmission and distribution network that supply gas to target users; A gas pressure determination module is used to determine the gas pressure of the natural gas provided by each gas source to the target user according to the flow of multiple users in the natural gas transmission and distribution pipeline network, the natural gas pressure of the gas pressure detection node in the gas transmission path from each gas source to the target user, and the pipeline network topology data, including: For each gas source, Determine a gas transmission path from the gas source to the target user, wherein the gas transmission path is a path from a target gas pressure detection node between the gas source and the target user to the target user; Acquire a gas transmission feature vector of the gas transmission path according to the multiple user flows in the natural gas transmission and distribution pipeline network, the natural gas pressure of the target gas pressure detection node, and the pipeline network topology data; Based on the gas transmission characteristic vector of the gas transmission path, obtaining the gas pressure of the natural gas provided by the gas source to the target user through a gas pressure prediction model; A ratio determination module, used for determining the gas supply ratio of each gas source to the target user based on the gas pressure of the natural gas provided by each gas source to the target user; A calorific value determination module, used to determine the calorific value of the mixed natural gas used by the target user based on the gas transmission ratio of each gas source to the target user; The metering determination module is used to determine the natural gas energy metering data of the target user based on the calorific value of the mixed natural gas and the gas consumption volume of the target user.

7. A data acquisition device for realizing household natural gas energy metering, comprising a processor, wherein the processor is used to execute the data acquisition method for realizing household natural gas energy metering according to any one of claims 1 to 5.

8. A computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the data acquisition method for realizing household natural gas energy metering according to any one of claims 1 to 5.

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