Method, System, Electronic Device and Storage Medium for Processing Energy Consumption Data

Abstract

The present invention provides a method, system, electronic device, and storage medium for processing energy usage data. The method includes: sending a data collection instruction to an end computing gateway, the data collection instruction being used to instruct the acquisition of first energy usage data from an energy usage data acquisition device; receiving the first energy usage data sent by the end computing gateway; obtaining a data parsing plug-in for parsing the first energy usage data based on a device type identifier of the energy usage data acquisition device; and performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain second energy usage data having a target data format. By performing data format conversion on the first energy usage data based on the data parsing plug-in, second energy usage data can be obtained, and the second energy usage data has the target data format. The data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified, and is easy to statistically analyze.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, system, electronic device and storage medium for processing energy usage data. Background Art

[0002] With the rise of big data cloud platform technology and the development of the trend of enterprises moving to the cloud, many industrial enterprises have begun to transform towards the Industrial Internet. Cloud-based analysis of energy data such as water, electricity, gas, and heat within the enterprise is not only a direction for the enterprise's transformation to the Industrial Internet, but also an important measure for the refined management of enterprise data to achieve energy conservation and emission reduction.

[0003] In order to analyze the energy consumption data of enterprises, it is necessary to obtain energy consumption data from various types of energy consumption data collection devices (such as smart electricity meters or smart gas meters deployed on the enterprise side, and smart electricity meters from different manufacturers deployed on the enterprise side). However, different types of energy consumption data collection devices generally use different data formats for reporting, which makes it difficult to statistically analyze the data reported by various types of energy consumption data collection devices. Summary of the Invention

[0004] The present invention provides a method, system, electronic device and storage medium for processing energy consumption data, which are used to solve the defect in the prior art that it is difficult to statistically analyze the data reported by various types of energy consumption data collection equipment, and to ensure that the data on the cloud platform is standardized and unified, and easy to statistically analyze.

[0005] In a first aspect, the present invention provides a method for processing energy usage data, comprising:

[0006] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0007] receiving the first energy usage data sent by the end computing gateway;

[0008] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0009] Based on the data parsing plug-in, data format conversion is performed on the first energy usage data to obtain second energy usage data in a target data format.

[0010] Optionally, according to a method for processing energy usage data provided by the present invention, obtaining a data parsing plug-in for parsing the first energy usage data based on a device type identifier of the energy usage data acquisition device includes:

[0011] Based on the data parsing plug-in table and the device type identifier, a data parsing plug-in corresponding to the device type identifier is obtained, wherein the data parsing plug-in table is used to represent a mapping relationship between the device type identifier and the data parsing plug-in.

[0012] Optionally, according to a method for processing energy usage data provided by the present invention, before acquiring the data parsing plug-in corresponding to the device type identifier based on the data parsing plug-in table and the device type identifier, the method further includes:

[0013] displaying a plurality of labels in a first data format;

[0014] receiving a first input from a user, wherein the first input is used to select a first tag matching a data format of the first energy usage data from among the multiple tags in the first data format;

[0015] In response to the first input, determining a data format of the first energy usage data based on a first data format corresponding to the first tag;

[0016] Displays labels for multiple data format conversion instructions;

[0017] receiving a second input from a user, where the second input is used to select a second tag from among the multiple data format conversion instruction tags, and the data format conversion instruction corresponding to the second tag is used to convert the data format of the first energy usage data;

[0018] In response to the second input, generating the data parsing plug-in based on the data format conversion instruction corresponding to the second tag;

[0019] Based on the device type identifier and the data parsing plug-in, the data parsing plug-in table is updated.

[0020] Optionally, according to a method for processing energy usage data provided by the present invention, before receiving the first energy usage data sent by the end computing gateway, the method further includes:

[0021] displaying a plurality of labels in a second data format;

[0022] receiving a third input from a user, wherein the third input is used to select a third tag from the plurality of tags in the second data format that matches the data format of the original data of the energy consumption data acquisition device;

[0023] In response to the third input, determining a data format of the raw data of the energy usage data collection device based on a second data format corresponding to the third tag;

[0024] A label showing a plurality of data pre-processing instructions, wherein the data pre-processing instructions are used to perform pre-processing on raw data reported by the energy consumption data collection device;

[0025] receiving a fourth input from a user, wherein the fourth input is used to select a fourth tag from among the tags of the plurality of data pre-processing instructions;

[0026] In response to the fourth input, a data preprocessing instruction corresponding to the fourth tag is sent to the end computing gateway, where the data preprocessing instruction corresponding to the fourth tag is used to preprocess the original data reported by the energy consumption data collection device to obtain the first energy consumption data.

[0027] Optionally, according to a method for processing energy usage data provided by the present invention, the second energy usage data includes energy consumption data, device identification, enterprise identification, device geographic coordinates, and data collection timestamp. After performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain the second energy usage data in the target data format, the method further includes:

[0028] Based on a target statistical method, performing statistical analysis on the plurality of second energy usage data to obtain energy usage statistical information;

[0029] Sending the energy consumption statistical information to a user terminal;

[0030] The target statistical method includes any one or more of the following statistical methods: a statistical method by equipment, a statistical method by enterprise, a statistical method by industry, or a statistical method by region.

[0031] Optionally, according to a method for processing energy usage data provided by the present invention, the second energy usage data includes one or more energy consumption data, and after performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain the second energy usage data in the target data format, the method further includes:

[0032] Determining that the target energy consumption data is greater than a preset energy consumption value, sending a warning message to the user equipment, wherein the warning message is used to indicate that the target energy consumption data is greater than the preset energy consumption value;

[0033] The target energy consumption data is any one of one or more energy consumption data.

[0034] In a second aspect, the present invention further provides an energy consumption data processing system, comprising: a cloud platform, an end computing gateway, and an energy consumption data collection device, wherein the cloud platform is communicatively connected to the end computing gateway, and the end computing gateway is communicatively connected to the energy consumption data collection device via a 5G network, wherein:

[0035] The cloud platform is used to:

[0036] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0037] receiving the first energy usage data sent by the end computing gateway;

[0038] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0039] Based on the data parsing plug-in, convert the first energy usage data into a data format to obtain second energy usage data in a target data format;

[0040] The end computing gateway is used to:

[0041] Receiving a data collection instruction sent by the cloud platform;

[0042] In response to the data collection instruction, sending a request message for requesting to report energy consumption data to the energy consumption data collection device;

[0043] receiving raw data reported by the energy consumption data collection device, and performing data preprocessing operations based on the raw data to determine the first energy consumption data;

[0044] The first energy consumption data is sent to the cloud platform.

[0045] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for processing energy usage data as described above is implemented.

[0046] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for processing energy usage data.

[0047] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described methods for processing energy usage data.

[0048] The energy consumption data processing method, system, electronic device and storage medium provided by the present invention can obtain a data parsing plug-in for parsing the first energy consumption data based on the device type identification of the energy consumption data acquisition device, and then based on the data parsing plug-in, the first energy consumption data can be converted into a data format to obtain the second energy consumption data. The second energy consumption data has a target data format, and the data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified and easy to statistically analyze. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 This is one of the flow charts of the method for processing energy consumption data provided by the present invention;

[0051] Figure 2 This is the second flow chart of the method for processing energy consumption data provided by the present invention;

[0052] Figure 3 It is a structural diagram of the energy consumption data processing system provided by the present invention;

[0053] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0055] Figure 1 This is one of the flow charts of the method for processing energy consumption data provided by the present invention. Figure 1 As shown, the execution entity of the energy consumption data processing method can be a cloud platform. The method includes:

[0056] Step 101: Send a data collection instruction to an end computing gateway, wherein the data collection instruction is used to instruct an energy consumption data collection device to obtain first energy consumption data;

[0057] Specifically, in order to obtain energy usage data in a specified data format, a data collection instruction may be sent to the end computing gateway, so that the end computing gateway obtains the first energy usage data of the energy usage data collection device.

[0058] It can be understood that the end computing gateway can be a gateway device deployed on the enterprise side, which can communicate data with the energy consumption data collection device on the enterprise side. By receiving the data reported by the energy consumption data collection device, the first energy consumption data of the energy consumption data collection device can be obtained.

[0059] It is understandable that the end computing gateway can communicate with the end computing gateway through a mobile communication network (such as a 5G network) and send the data collection instruction to the end computing gateway.

[0060] Step 102: receiving the first energy usage data sent by the end computing gateway;

[0061] Specifically, the data collection instruction may instruct the end computing gateway to obtain the first energy usage data from the energy usage data collection device, and may receive the first energy usage data sent by the end computing gateway.

[0062] It is understandable that the end computing gateway can communicate with the end computing gateway through a mobile communication network (such as a 5G network) and receive the first energy usage data reported by the end computing gateway.

[0063] Step 103: obtaining a data parsing plug-in for parsing the first energy usage data based on the device type identifier of the energy usage data collection device;

[0064] Specifically, the device type identifier can indicate the type of the energy consumption data collection device. After receiving the first energy consumption data sent by the end computing gateway, a query can be performed in multiple data parsing plug-ins pre-stored on the cloud platform according to the device type identifier to obtain a data parsing plug-in for parsing the first energy consumption data.

[0065] Optionally, after determining the data parsing plug-in for parsing the first energy usage data, the data parsing plug-in may be dynamically loaded. After loading, the data parsing plug-in can be used to parse the first energy usage data.

[0066] Optionally, the first energy usage data may include a device type identifier of the energy usage data collection device.

[0067] Optionally, the first energy consumption data may include a device identification of the energy consumption data collection device. Based on the device identification, pre-stored information of the energy consumption data collection device may be queried to obtain a device type identification of the energy consumption data collection device.

[0068] Step 104 : Based on the data parsing plug-in, convert the data format of the first energy usage data to obtain second energy usage data in a target data format.

[0069] Specifically, after obtaining the data parsing plug-in, the data parsing plug-in may be used to convert the format of the first energy usage data to obtain second energy usage data having a target data format.

[0070] Optionally, the target data format may be a pre-specified data format, which may meet the format requirements for statistical analysis of energy consumption data.

[0071] The energy consumption data processing method provided by the present invention can obtain a data parsing plug-in for parsing the first energy consumption data based on the device type identification of the energy consumption data acquisition device, and then based on the data parsing plug-in, the data format of the first energy consumption data can be converted to obtain the second energy consumption data. The second energy consumption data has a target data format, and the data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified and easy to statistically analyze.

[0072] Optionally, the acquiring, based on the device type identifier of the energy consumption data collection device, a data parsing plug-in for parsing the first energy consumption data includes:

[0073] Based on the data parsing plug-in table and the device type identifier, a data parsing plug-in corresponding to the device type identifier is obtained, wherein the data parsing plug-in table is used to represent a mapping relationship between the device type identifier and the data parsing plug-in.

[0074] Specifically, after receiving the first energy usage data sent by the end computing gateway, you can query the data parsing plug-in table to obtain the data parsing plug-in corresponding to the device type identifier. After obtaining the data parsing plug-in, you can use the data parsing plug-in to convert the format of the first energy usage data to obtain the second energy usage data with the target data format.

[0075] It is understandable that the cloud platform can pre-install data parsing plug-ins corresponding to various types of energy consumption data collection devices, and can be pre-configured with a data parsing plug-in table, which can represent the mapping relationship between device type identifiers and data parsing plug-ins.

[0076] Optionally, the cloud platform may query the data parsing plug-in table, obtain the data parsing plug-in corresponding to the device type identifier, and dynamically load the data parsing plug-in. After loading, the data parsing plug-in can be used to parse the first energy usage data.

[0077] Therefore, by querying the data parsing plug-in table, the data parsing plug-in for parsing the first energy consumption data can be obtained, and then based on the data parsing plug-in, the data format of the first energy consumption data can be converted to obtain the second energy consumption data. The data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified, and easy to statistically analyze.

[0078] Optionally, before acquiring the data parsing plug-in corresponding to the device type identifier based on the data parsing plug-in table and the device type identifier, the method further includes:

[0079] displaying a plurality of labels in a first data format;

[0080] receiving a first input from a user, wherein the first input is used to select a first tag matching a data format of the first energy usage data from among the multiple tags in the first data format;

[0081] In response to the first input, determining a data format of the first energy usage data based on a first data format corresponding to the first tag;

[0082] Displays labels for multiple data format conversion instructions;

[0083] receiving a second input from a user, where the second input is used to select a second tag from among the multiple data format conversion instruction tags, and the data format conversion instruction corresponding to the second tag is used to convert the data format of the first energy usage data;

[0084] In response to the second input, generating the data parsing plug-in based on the data format conversion instruction corresponding to the second tag;

[0085] Based on the device type identifier and the data parsing plug-in, the data parsing plug-in table is updated.

[0086] Specifically, before obtaining the data parsing plug-in corresponding to the device type identifier based on the data parsing plug-in table and the device type identifier, the data parsing plug-in table can be updated. To update the data parsing plug-in table, multiple labels of the first data format can be displayed, where each first data format can be a type of data format, and each first data format corresponds to a label. Then, a first input from a user can be received. The first input can be used to select a first label that matches the data format of the first energy usage data from the multiple labels of the first data format. Then, in response to the first input, the data format of the first energy usage data can be determined based on the first data format corresponding to the first label.

[0087] Specifically, after determining the data format of the first energy consumption data, multiple labels of data format conversion instructions can be displayed. A data format conversion instruction can be a type of data format conversion instruction, and a data format conversion instruction corresponds to a label. Then, the user's second input can be received. The second input can be used to select a second label from multiple data format conversion instruction labels, and then, in response to the data format conversion instruction corresponding to the second label, a data parsing plug-in can be generated, and then based on the device type identifier and the data parsing plug-in, the data parsing plug-in table can be updated.

[0088] It is understandable that the cloud platform may be pre-configured with multiple labels in the first data format, and may display multiple labels in the first data format for user selection. By receiving the user's first input, the data format of the first energy usage data may be determined.

[0089] It can be understood that the cloud platform can be pre-configured with multiple labels of data format conversion instructions, and can display multiple labels of data format conversion instructions for users to choose from. By receiving the user's second input, the conversion instruction for converting the data format of the first energy usage data can be determined, and then a data parsing plug-in can be generated based on the determined conversion instruction. Subsequently, by loading the data parsing plug-in, the first energy usage data can be parsed to obtain the second energy usage data with the target data format.

[0090] Therefore, through human-computer interaction between the cloud platform and the user, a data parsing plug-in can be generated, and then based on the device type identification and the data parsing plug-in, the data parsing plug-in table can be updated.

[0091] Optionally, before receiving the first energy usage data sent by the end computing gateway, the method further includes:

[0092] displaying a plurality of labels in a second data format;

[0093] receiving a third input from a user, wherein the third input is used to select a third tag from the plurality of tags in the second data format that matches the data format of the original data of the energy consumption data acquisition device;

[0094] In response to the third input, determining a data format of the raw data of the energy usage data collection device based on a second data format corresponding to the third tag;

[0095] A label showing a plurality of data pre-processing instructions, wherein the data pre-processing instructions are used to perform pre-processing on raw data reported by the energy consumption data collection device;

[0096] receiving a fourth input from a user, wherein the fourth input is used to select a fourth tag from among the tags of the plurality of data pre-processing instructions;

[0097] In response to the fourth input, a data preprocessing instruction corresponding to the fourth tag is sent to the end computing gateway, where the data preprocessing instruction corresponding to the fourth tag is used to preprocess the original data reported by the energy consumption data collection device to obtain the first energy consumption data.

[0098] Specifically, before receiving the first energy usage data sent by the receiving computing gateway, the peer computing gateway configures a data preprocessing instruction. To determine the data preprocessing instruction, multiple labels of second data formats can be displayed, where each second data format can be a type of data format, and each second data format corresponds to a label. A third input from a user can be received, and the third input can be used to select a third label from the multiple labels of the second data format that matches the data format of the raw data of the energy usage data collection device. In response to the third input, the data format of the raw data of the energy usage data collection device can be determined based on the second data format corresponding to the third label.

[0099] Specifically, after determining the data format of the original data of the energy consumption data acquisition device, multiple labels of data preprocessing instructions can be displayed. One data preprocessing instruction can represent a type of data preprocessing instruction, and one data preprocessing instruction corresponds to one label. Then, the user's fourth input can be received. The fourth input can be used to select a fourth label from multiple labels of data preprocessing instructions. Then, in response to the fourth input, the data preprocessing instruction corresponding to the fourth label can be sent to the end computing gateway to implement the configuration of the data preprocessing instruction on the end computing gateway.

[0100] It is understandable that the cloud platform may be pre-configured with multiple labels in the second data format, and may display multiple labels in the second data format for user selection. By receiving the user's third input, the data format of the original data may be determined.

[0101] It can be understood that the cloud platform can be pre-configured with multiple labels of data preprocessing instructions, and can display multiple labels of data preprocessing instructions for users to choose from. By receiving the user's fourth input, the preprocessing instructions for preprocessing the original data reported by the energy data acquisition device can be determined, and the determined preprocessing instructions can be sent to the end computing gateway.

[0102] Therefore, by issuing preprocessing instructions to the end computing gateway, the end computing gateway can be instructed to preprocess the original data reported by the energy consumption data collection device, and the unnecessary data of the energy consumption data collection device can be shielded, thereby reducing the processing volume of data conversion on the cloud platform.

[0103] Optionally, the second energy usage data includes energy consumption data, device identification, enterprise identification, device geographic coordinates, and data collection timestamp. After performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain the second energy usage data in the target data format, the method further includes:

[0104] Based on a target statistical method, performing statistical analysis on the plurality of second energy usage data to obtain energy usage statistical information;

[0105] Sending the energy consumption statistical information to a user terminal;

[0106] The target statistical method includes any one or more of the following statistical methods: a statistical method by equipment, a statistical method by enterprise, a statistical method by industry, or a statistical method by region.

[0107] Specifically, the target statistical method may include one or more statistical methods. After obtaining the second energy consumption data, statistical analysis can be performed on multiple second energy consumption data based on the target statistical method to obtain energy consumption statistical information, and then the enterprise energy consumption statistical information can be sent to the user terminal.

[0108] It can be understood that the second energy consumption data may include energy consumption data, device identification, enterprise identification, device geographic coordinates and data collection timestamp. The energy consumption data may be the energy consumption data collected by the energy data collection device, the device identification may be the unique identification of the energy data collection device, the enterprise identification may indicate the enterprise to which the energy data collection device belongs, the device geographic coordinates may indicate the location of the energy data collection device, and the data collection timestamp may indicate the time when the energy data collection device reports the data.

[0109] It can be understood that the method of statistics by equipment can be a method of conducting energy statistics with energy-consuming equipment (production lines or factories, etc.) monitored by designated energy data collection equipment as the statistical objects; the method of statistics by enterprise can be a method of conducting energy statistics with designated enterprises as the statistical objects; the method of statistics by industry can be a method of conducting energy statistics with designated industries as the statistical objects; the method of statistics by region can be a method of conducting energy statistics with designated geographical areas as the statistical objects.

[0110] Therefore, the target statistical method can include multiple statistical methods, and then statistical analysis of energy consumption data can be performed based on multiple statistical methods to obtain multi-dimensional energy consumption statistical information. By sending the energy consumption statistical information to the user device, multi-dimensional energy consumption statistics can be displayed to the user, which can help the user analyze energy consumption more quickly and accurately and improve work efficiency.

[0111] Optionally, the second energy usage data includes one or more energy consumption data. After performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain the second energy usage data in the target data format, the method further includes:

[0112] Determining that the target energy consumption data is greater than a preset energy consumption value, sending a warning message to the user equipment, wherein the warning message is used to indicate that the target energy consumption data is greater than the preset energy consumption value;

[0113] The target energy consumption data is any one of one or more energy consumption data.

[0114] Specifically, after obtaining the second energy consumption data, it can be determined whether the target energy consumption data is greater than the preset energy consumption value. If it is determined that the target energy consumption data is greater than the preset energy consumption value, an early warning message can be sent to the user device to inform the user that the target energy consumption data is greater than the preset energy consumption value.

[0115] Therefore, by monitoring energy consumption data, a real-time energy consumption warning function can be realized.

[0116] Optionally, Figure 2 This is the second flow chart of the method for processing energy consumption data provided by the present invention. Figure 2 As shown, the method for processing energy consumption data includes steps 201 to 211:

[0117] Step 201: The user device sends a data collection task to the cloud platform;

[0118] Step 202: The cloud platform generates a data collection instruction based on the data collection task and sends the data collection instruction to the end computing gateway;

[0119] Step 203: The end computing gateway sends a data collection instruction to the energy consumption data collection device;

[0120] Step 204: The energy consumption data collection device reports the raw data to the end computing gateway;

[0121] Step 205: The end computing gateway pre-processes the raw data reported by the energy consumption data collection device to obtain first energy consumption data;

[0122] Step 206: The end computing gateway sends the first energy usage data to the cloud platform;

[0123] Step 207: The cloud platform analyzes the first energy usage data to obtain second energy usage data.

[0124] Step 208: The cloud platform sends the second energy usage data to the user device, and displays the energy usage data on the user device;

[0125] Step 209: The cloud platform performs statistical analysis on the plurality of second energy consumption data to obtain energy consumption statistical information, and can monitor in real time whether the target energy consumption data is greater than a preset energy consumption value;

[0126] Step 210: The cloud platform sends the energy usage statistics to the user device, and the energy usage statistics are displayed on the user device;

[0127] In step 211 , if the cloud platform determines that the target energy consumption data is greater than the preset energy consumption value, it sends a warning message to the user device.

[0128] The energy consumption data processing method provided by the present invention can obtain a data parsing plug-in for parsing the first energy consumption data based on the device type identification of the energy consumption data acquisition device, and then based on the data parsing plug-in, the data format of the first energy consumption data can be converted to obtain the second energy consumption data. The second energy consumption data has a target data format, and the data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified and easy to statistically analyze.

[0129] Figure 3 This is a schematic diagram of the structure of the energy consumption data processing system provided by the present invention. Figure 3 As shown, the system includes: a cloud platform 301, an end computing gateway 302 and an energy consumption data collection device 303, wherein the cloud platform 301 is communicatively connected to the end computing gateway 302, and the end computing gateway 302 is communicatively connected to the energy consumption data collection device 303 via a 5G network, wherein:

[0130] The cloud platform 301 is used for:

[0131] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0132] receiving the first energy usage data sent by the end computing gateway;

[0133] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0134] Based on the data parsing plug-in, convert the first energy usage data into a data format to obtain second energy usage data in a target data format;

[0135] The end computing gateway 302 is used to:

[0136] Receiving a data collection instruction sent by the cloud platform;

[0137] In response to the data collection instruction, sending a request message for requesting to report energy consumption data to the energy consumption data collection device;

[0138] receiving raw data reported by the energy consumption data collection device, and performing data preprocessing operations based on the raw data to determine the first energy consumption data;

[0139] The first energy consumption data is sent to the cloud platform.

[0140] Optionally, data communication can be carried out between the end computing gateway and the energy consumption data collection device via MQTT. MQTT can provide real-time and reliable message services for connected remote devices with minimal code and limited bandwidth.

[0141] Optionally, the cloud platform can push data to the user terminal in real time via WebSocket.

[0142] WebSocket is a full-duplex communication protocol over a single TCP connection. It simplifies data exchange between clients and servers, allowing servers to proactively push data to clients. With the WebSocket API, browsers and servers only need to complete a single handshake to establish a persistent connection and enable bidirectional data transfer.

[0143] Optionally, the end computing gateway and the cloud platform can communicate through the 5G network, and the large bandwidth and low latency characteristics of 5G can ensure the real-time and accuracy of data collection.

[0144] The energy consumption data processing system provided by the present invention can obtain a data parsing plug-in for parsing the first energy consumption data based on the device type identification of the energy consumption data acquisition device, and then based on the data parsing plug-in, it can convert the data format of the first energy consumption data to obtain the second energy consumption data. The second energy consumption data has a target data format, and the data processed by the data parsing plug-in has a specified data format, which can ensure that the data on the cloud platform is standardized and unified and easy to statistically analyze.

[0145] Figure 4 Schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the energy usage data processing method, for example, the method includes:

[0146] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0147] receiving the first energy usage data sent by the end computing gateway;

[0148] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0149] Based on the data parsing plug-in, data format conversion is performed on the first energy usage data to obtain second energy usage data in a target data format.

[0150] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0151] In another aspect, the present invention further provides a computer program product, comprising a computer program. The computer program may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the energy usage data processing method provided by each of the above methods, the method comprising:

[0152] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0153] receiving the first energy usage data sent by the end computing gateway;

[0154] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0155] Based on the data parsing plug-in, data format conversion is performed on the first energy usage data to obtain second energy usage data in a target data format.

[0156] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for processing energy usage data provided by the above methods is implemented, the method comprising:

[0157] Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data;

[0158] receiving the first energy usage data sent by the end computing gateway;

[0159] Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data;

[0160] Based on the data parsing plug-in, data format conversion is performed on the first energy usage data to obtain second energy usage data in a target data format.

[0161] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0162] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for processing energy consumption data, characterized in that: include: Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data; receiving the first energy usage data sent by the end computing gateway; Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data; Based on the data parsing plug-in, convert the first energy usage data into a data format to obtain second energy usage data in a target data format; The acquiring, based on the device type identifier of the energy consumption data collection device, a data parsing plug-in for parsing the first energy consumption data includes: Based on a data parsing plug-in table and the device type identifier, obtaining a data parsing plug-in corresponding to the device type identifier, wherein the data parsing plug-in table is used to represent a mapping relationship between the device type identifier and the data parsing plug-in; Before acquiring the data parsing plug-in corresponding to the device type identifier based on the data parsing plug-in table and the device type identifier, the method further includes: displaying a plurality of labels in a first data format; receiving a first input from a user, wherein the first input is used to select a first tag matching a data format of the first energy usage data from among the multiple tags in the first data format; In response to the first input, determining a data format of the first energy usage data based on a first data format corresponding to the first tag; Displays labels for multiple data format conversion instructions; receiving a second input from a user, where the second input is used to select a second tag from among the multiple data format conversion instruction tags, and the data format conversion instruction corresponding to the second tag is used to convert the data format of the first energy usage data; In response to the second input, generating the data parsing plug-in based on the data format conversion instruction corresponding to the second tag; Based on the device type identifier and the data parsing plug-in, the data parsing plug-in table is updated.

2. The method for processing energy consumption data according to claim 1, characterized in that: Before receiving the first energy usage data sent by the end computing gateway, the method further includes: displaying a plurality of labels in a second data format; receiving a third input from a user, wherein the third input is used to select a third tag from the plurality of tags in the second data format that matches the data format of the original data of the energy consumption data acquisition device; In response to the third input, determining a data format of the raw data of the energy usage data collection device based on a second data format corresponding to the third tag; A label showing a plurality of data pre-processing instructions, wherein the data pre-processing instructions are used to perform pre-processing on raw data reported by the energy consumption data collection device; receiving a fourth input from a user, wherein the fourth input is used to select a fourth tag from among the tags of the plurality of data pre-processing instructions; In response to the fourth input, a data preprocessing instruction corresponding to the fourth tag is sent to the end computing gateway, where the data preprocessing instruction corresponding to the fourth tag is used to preprocess the original data reported by the energy consumption data collection device to obtain the first energy consumption data.

3. The method for processing energy consumption data according to any one of claims 1 to 2, characterized in that: The second energy usage data includes energy consumption data, device identification, enterprise identification, device geographic coordinates, and data collection timestamp. After performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain the second energy usage data in the target data format, the method further includes: Based on a target statistical method, performing statistical analysis on the plurality of second energy usage data to obtain energy usage statistical information; Sending the energy consumption statistical information to a user terminal; The target statistical method includes any one or more of the following statistical methods: a statistical method by equipment, a statistical method by enterprise, a statistical method by industry, or a statistical method by region.

4. The method for processing energy consumption data according to claim 3, characterized in that: The second energy usage data includes one or more energy consumption data. After performing data format conversion on the first energy usage data based on the data parsing plug-in to obtain second energy usage data in a target data format, the method further includes: Determining that the target energy consumption data is greater than a preset energy consumption value, sending a warning message to the user equipment, wherein the warning message is used to indicate that the target energy consumption data is greater than the preset energy consumption value; The target energy consumption data is any one of one or more energy consumption data.

5. A system for processing energy consumption data, characterized in that: include: A cloud platform, an end computing gateway, and an energy consumption data collection device, wherein the cloud platform is communicatively connected to the end computing gateway, and the end computing gateway is communicatively connected to the energy consumption data collection device via a 5G network, wherein: The cloud platform is used to: Sending a data collection instruction to the end computing gateway, wherein the data collection instruction is used to instruct the energy consumption data collection device to obtain first energy consumption data; receiving the first energy usage data sent by the end computing gateway; Based on the device type identifier of the energy usage data collection device, obtaining a data parsing plug-in for parsing the first energy usage data; Based on the data parsing plug-in, convert the first energy usage data into a data format to obtain second energy usage data in a target data format; The acquiring, based on the device type identifier of the energy consumption data collection device, a data parsing plug-in for parsing the first energy consumption data includes: Based on a data parsing plug-in table and the device type identifier, obtaining a data parsing plug-in corresponding to the device type identifier, wherein the data parsing plug-in table is used to represent a mapping relationship between the device type identifier and the data parsing plug-in; The cloud platform is also used to: Before acquiring the data parsing plug-in corresponding to the device type identifier based on the data parsing plug-in table and the device type identifier: displaying a plurality of labels in a first data format; receiving a first input from a user, wherein the first input is used to select a first tag matching a data format of the first energy usage data from among the multiple tags in the first data format; In response to the first input, determining a data format of the first energy usage data based on a first data format corresponding to the first tag; Displays labels for multiple data format conversion instructions; receiving a second input from a user, where the second input is used to select a second tag from among the multiple data format conversion instruction tags, and the data format conversion instruction corresponding to the second tag is used to convert the data format of the first energy usage data; In response to the second input, generating the data parsing plug-in based on the data format conversion instruction corresponding to the second tag; Based on the device type identifier and the data parsing plug-in, updating the data parsing plug-in table; The end computing gateway is used to: Receiving a data collection instruction sent by the cloud platform; In response to the data collection instruction, sending a request message for requesting to report energy consumption data to the energy consumption data collection device; receiving raw data reported by the energy consumption data collection device, and performing data preprocessing operations based on the raw data to determine the first energy consumption data; The first energy consumption data is sent to the cloud platform.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for processing energy usage data according to any one of claims 1 to 4 is implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for processing energy usage data according to any one of claims 1 to 4 is implemented.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for processing energy usage data according to any one of claims 1 to 4 is implemented.

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