Energy Internet of Things data processing system and method based on industrial cloud platform

Abstract

The present invention discloses an energy Internet of Things data processing system and method based on an industrial cloud platform, which belongs to the field of energy data processing technology. The present invention obtains all energy conversion stages in the energy supply process, classifies all devices based on each energy conversion stage, and marks different types of devices with different colors to obtain a labeled energy Internet of Things topological relationship diagram; obtains the operation data of the device through a sensor network, and the weather data of the location of different types of devices, performs equipment abnormality analysis, and obtains abnormality analysis results of different types of devices in different energy conversion stages; imports the abnormality analysis results of different types of equipment into the equipment maintenance path analysis strategy to perform equipment maintenance path analysis, and displays the equipment maintenance path in the labeled energy Internet of Things topological relationship diagram. The present invention helps enterprises quickly retrieve equipment abnormalities in the energy Internet of Things and generate maintenance paths.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy data processing, and specifically to an energy Internet of Things data processing system and method based on an industrial cloud platform. Background Art

[0002] With the rapid development of intelligence in the energy industry, the massive data generated by real-time monitoring of the operating status of energy equipment and energy consumption in the Energy Internet of Things requires industrial cloud platforms to collect, transmit, store and analyze the Energy Internet of Things data to help enterprises achieve intelligent and refined energy management. Existing technologies often focus on abnormal processing of power energy monitoring data, or research on how to analyze business data in the Energy Internet of Things. The Energy Internet of Things involves many stages of energy conversion, such as from energy supply to energy storage, from energy storage to energy use. Some energy equipment in these stages will generate a lot of data. A method is needed to monitor abnormalities of energy equipment in stages to help enterprises quickly retrieve abnormal energy equipment.

[0003] For example, a Chinese patent with authorization announcement number CN111143482B discloses a business data processing method for the energy Internet of Things, including: receiving classification information of any business data input by a user through a business interface, as well as a calculation formula for the business data corresponding to the business data classification information and a model hierarchy of the business data; responding to the first operation instruction of the user through the business interface to establish a connection between the business data classification information and the calculation formula of the business data and the model hierarchy, and obtaining a business relationship model of the business data, wherein the business relationship model is a model that establishes associations between each classified business data through a calculation formula and a model hierarchy; storing the business relationship model in a preset relational database, wherein the relational database includes business relationship models corresponding to a variety of business data. Effectively organize and transform the business data of the energy Internet of Things to be able to perceive energy enterprises and energy systems in all aspects, and accelerate the optimization of energy utilization efficiency and energy transformation.

[0004] At the same time, for example, in a Chinese patent with application publication number CN116757870A, a smart energy monitoring data processing method and system for an energy Internet of Things is provided, which relates to the field of data processing technology. In this invention, the first bound device set corresponding to each Internet of Things gateway device is updated to output the second bound device set corresponding to each Internet of Things gateway device. For each piece of electric energy monitoring data, the electric energy monitoring data and each other electric energy monitoring data are calculated to output the data similarity between the electric energy monitoring data and each other electric energy monitoring data. For each piece of electric energy monitoring data, based on the data similarity between the electric energy monitoring data and each other electric energy monitoring data, the electric energy monitoring data is subjected to data anomaly analysis processing to output the corresponding anomaly analysis result. Based on the above method, the reliability of data anomaly analysis can be improved.

[0005] The above patents all have the problem raised by this background technology: they do not take into account that the energy Internet of Things involves many stages of energy conversion, such as from energy supply to energy storage, and from energy storage to energy use. Some energy equipment in these stages will generate a lot of data, and these data will have an impact on energy equipment at different stages; in order to solve these problems, this application designs an energy Internet of Things data processing system and method based on an industrial cloud platform. Summary of the invention

[0006] In view of the shortcomings of the prior art, the embodiments of the present invention propose an energy Internet of Things data processing system and method based on an industrial cloud platform, which can perform targeted analysis on the data generated by some energy equipment in the stages from energy supply to energy storage to energy use.

[0007] According to a first aspect of an embodiment of the present invention, a method for processing energy Internet of Things data based on an industrial cloud platform is provided, which includes the following specific steps:

[0008] S1. Obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and simultaneously obtain the energy Internet of Things topological relationship diagram, and mark the colors according to the types of devices in the energy Internet of Things topological relationship diagram to obtain the marked energy Internet of Things topological relationship diagram, wherein the energy conversion stages include: energy supply stage, energy storage stage and energy use stage; the types of devices include energy supply equipment, energy storage equipment and energy use equipment;

[0009] S2, obtaining the operation data of each category of equipment in the energy Internet of Things and the weather data of the location of each category of equipment through the sensor network;

[0010] S3, substituting the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the energy conversion stage equipment abnormality analysis strategy to perform equipment abnormality analysis in each energy conversion stage, and obtaining abnormality analysis results of all categories of equipment in the energy conversion stage;

[0011] S4. Import the abnormal analysis results of each category of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the labeled energy Internet of Things topology diagram.

[0012] According to an embodiment of the present invention, the energy conversion stage equipment abnormality analysis strategy in S3 includes the following specific contents:

[0013] S31, substituting the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply anomaly analysis sub-strategy to perform an anomaly analysis of the energy supply equipment in the energy supply stage;

[0014] S32, substituting the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage anomaly analysis sub-strategy to perform an anomaly analysis of the energy storage devices in the energy storage stage;

[0015] S33, substituting the operating data of all energy-consuming devices in the energy use phase and the weather data of the location of each energy-consuming device into the energy use anomaly analysis sub-strategy to perform an anomaly analysis of the energy-consuming devices in the energy use phase.

[0016] According to one embodiment of the present invention, the specific steps of the energy supply anomaly analysis sub-strategy in S31 are as follows:

[0017] S311, obtaining the operating data of all energy supply equipment in the energy supply stage at n moments and the weather data of the location where each energy supply equipment is located; the operating data of the energy supply equipment includes: the power output value and the equipment temperature of the energy supply equipment at n moments, and the weather data of the location where each energy supply equipment is located includes the ambient temperature of the location where each energy supply equipment is located at n moments;

[0018] S312: Calculate the abnormal value of each energy supply device at the jth moment Where P j , Tg j is the power output value and equipment temperature of the energy supply equipment at the jth moment, Tg min , Tg max They are the minimum and maximum device temperatures for normal operation of the energy supply equipment, GT j is the ambient temperature of the location of the energy supply equipment at the jth moment, where j is any one of 1 to n;

[0019] S313. Taking the energy supply device abnormality value of each energy supply device at the j-th moment as the energy supply device abnormality analysis result of each energy supply device at the j-th moment.

[0020] According to one embodiment of the present invention, the specific steps of the energy storage abnormality analysis sub-strategy in S32 are:

[0021] S321, obtaining the operating data of all energy storage devices in the energy storage stage and the weather data of the location where each energy storage device is located, wherein the operating data of the energy storage device includes the power value and device temperature of the energy storage device, and the weather data of the location where each energy storage device is located includes the ambient temperature of the location where each energy storage device is located;

[0022] S322, calculating the abnormal value of each energy storage device at the jth moment where e j , Tc j is the power value and device temperature of the energy storage device at the jth moment, Tc min , Tc max are the minimum and maximum device temperatures for normal operation of the energy storage device, CT j is the ambient temperature of the location of the energy storage device at the jth moment, where j is any one of 1 to n;

[0023] S323. Taking the energy storage device abnormality value of each energy storage device at the j-th moment as the energy storage device abnormality analysis result of each energy storage device at the j-th moment.

[0024] According to an embodiment of the present invention, the energy usage anomaly analysis sub-strategy in S33 includes the following specific steps:

[0025] S331, obtaining the operating data of all energy-consuming devices during the energy use phase and the weather data of the location where each energy-consuming device is located; the operating data of the energy-consuming devices includes the operating time, power output value, and device temperature of the energy-consuming devices, and the weather data of the location where each energy-consuming device is located includes the ambient temperature of the location where each energy-consuming device is located;

[0026] S332. Calculate the abnormal value of each energy-consuming device at the jth moment where yt j 、yp j 、Ty j is the operating time, power output value, and equipment temperature of the energy-consuming equipment at the jth moment, Ty min 、Ty max They are the lowest and highest equipment temperatures for normal operation of energy-consuming equipment, YT jis the ambient temperature of the location of the energy-consuming equipment at the jth moment, where j is any one of 1 to n;

[0027] S333. Taking the energy-consuming device abnormal value of each energy-consuming device at the j-th moment as the energy-consuming device abnormality analysis result of each energy-consuming device at the j-th moment.

[0028] According to one embodiment of the present invention, the specific content of S4 is as follows:

[0029] S41, obtaining abnormal analysis results of energy supply equipment, energy storage equipment, and energy consumption equipment at the jth moment;

[0030] S42, the equipment maintenance path analysis strategy includes: presetting an abnormal threshold value ΔG of energy supply equipment, an abnormal threshold value ΔC of energy storage equipment, and an abnormal threshold value ΔY of energy consumption equipment;

[0031] S43, obtaining the abnormal analysis result G of the energy supply equipment at the jth moment j >The number Q1 of all corresponding energy supply devices of ΔG and the positions of all corresponding energy supply devices in the annotated energy Internet of Things topology diagram;

[0032] S44. Obtain abnormal analysis result C of energy storage equipment at the jth moment j >The number Q2 of all corresponding energy storage devices of ΔC and the positions of all corresponding energy storage devices in the annotated energy Internet of Things topology diagram;

[0033] S45. Obtain abnormal analysis result Y of energy-consuming equipment at the jth moment j >The number Q3 of all corresponding energy-consuming devices of ΔY and the positions of all corresponding energy-consuming devices in the annotated energy Internet of Things topology diagram;

[0034] S46, any one of the Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices obtained in the above S43-S45 is selected as the starting device, and an equipment maintenance path sequence is created, wherein the equipment maintenance path sequence is used to store the paths found during the traversal process, and a traversed list is created at the same time to store the traversed devices, and the empty list initially contains only the starting device;

[0035] S47, obtaining the corresponding device with the shortest distance to the starting point device from the devices other than the starting point device, and taking the corresponding device with the shortest distance to the starting point device as the next traversal device;

[0036] S48, adding the next traversed device to the traversed list, and updating the device maintenance path sequence, recording the path from the starting device to the next traversed device;

[0037] S49, repeat steps S47-S48, take the next traversal device as the starting device, continue to obtain the corresponding device with the shortest distance to the starting device for traversal, until all Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices have been traversed, and execute S410;

[0038] S410. Output an updated equipment maintenance path sequence, and display the equipment maintenance path corresponding to the updated equipment maintenance path sequence in a labeled energy Internet of Things topology diagram.

[0039] According to a second aspect of an embodiment of the present invention, an energy Internet of Things data processing system based on an industrial cloud platform is provided, which specifically includes:

[0040] The device topology relationship acquisition module is used to obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and obtain the energy Internet of Things topology relationship diagram at the same time. In the energy Internet of Things topology relationship diagram, the color is marked according to the category of the device to obtain the marked energy Internet of Things topology relationship diagram, wherein the energy conversion stage includes: energy supply stage, energy storage stage and energy use stage; the categories of the equipment include energy supply equipment, energy storage equipment and energy use equipment;

[0041] The sensor data acquisition module is used to obtain the operating data of various types of equipment in the energy Internet of Things and the weather data of the locations where the various types of equipment are located through the sensor network;

[0042] The abnormality analysis module is used to substitute the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the abnormality analysis strategy of the equipment in the energy conversion stage to perform abnormality analysis of the equipment in each energy conversion stage, and obtain the abnormality analysis results of all categories of equipment in the energy conversion stage;

[0043] The equipment maintenance path analysis module is used to import the abnormal analysis results of various types of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the annotated energy Internet of Things topology diagram;

[0044] The control module is used to control the operation of each module.

[0045] According to one embodiment of the present invention, the abnormality analysis module includes an energy supply device abnormality analysis unit, an energy storage device abnormality analysis unit, and an energy consumption device abnormality analysis unit;

[0046] The energy supply equipment abnormality analysis unit is used to substitute the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply abnormality analysis sub-strategy to perform abnormality analysis of energy supply equipment in the energy supply stage;

[0047] The energy storage device abnormality analysis unit is used to substitute the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage abnormality analysis sub-strategy to perform abnormality analysis of energy storage devices in the energy storage stage;

[0048] The energy-consuming equipment abnormality analysis unit is used to substitute the operating data of all energy-consuming equipment in the energy use stage and the weather data of the location of each energy-consuming equipment into the energy use abnormality analysis sub-strategy to perform abnormal analysis of energy-consuming equipment in the energy use stage.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention obtains all energy conversion stages in the energy supply process, classifies all devices based on each energy conversion stage, and marks different types of devices with different colors to obtain a labeled energy Internet of Things topology relationship diagram; obtains the operation data of the equipment through the sensor network, as well as the weather data of the locations of different types of equipment, performs equipment abnormality analysis, and obtains abnormality analysis results of different types of equipment in different energy conversion stages; imports the abnormality analysis results of different types of equipment into the equipment maintenance path analysis strategy to perform equipment maintenance path analysis, and displays the equipment maintenance path in the labeled energy Internet of Things topology relationship diagram. The present invention helps enterprises quickly retrieve equipment abnormalities in the energy Internet of Things and generate maintenance paths. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The following is a schematic diagram of a process flow of an energy Internet of Things data processing method based on an industrial cloud platform according to an embodiment of the present invention;

[0052] Figure 2 A schematic diagram of the architecture of an energy Internet of Things data processing system based on an industrial cloud platform according to an embodiment of the present invention is exemplarily shown. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0054] Example 1

[0055] Figure 1A schematic diagram of a process flow of an energy Internet of Things data processing method based on an industrial cloud platform according to an embodiment of the present invention is shown exemplarily. Figure 1 , an energy Internet of Things data processing method based on an industrial cloud platform includes the following specific steps:

[0056] S1. Obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and simultaneously obtain the energy Internet of Things topological relationship diagram, and mark the colors according to the types of devices in the energy Internet of Things topological relationship diagram to obtain the marked energy Internet of Things topological relationship diagram, wherein the energy conversion stages include: energy supply stage, energy storage stage and energy use stage; the types of devices include energy supply equipment, energy storage equipment and energy use equipment;

[0057] According to one embodiment of the present invention, all energy conversion stages in the energy supply process are obtained in step S1, wherein the energy conversion stage includes the whole process from energy generation to final use, so the energy conversion stage can be divided into an energy supply stage, an energy storage stage and an energy use stage. In the energy Internet of Things, each stage corresponds to each category of equipment. For example, the equipment in the energy supply stage is an energy supply equipment, which is a equipment used to convert energy into usable energy. The function of the energy supply equipment is to convert raw energy, such as fossil fuels, solar energy, wind energy, etc., into electrical energy or other forms of usable energy for subsequent use. The energy supply equipment can be a wind turbine, a solar photovoltaic panel, etc.;

[0058] According to one embodiment of the present invention, the device in the energy storage stage in step S1 is an energy storage device, which is used to store the energy generated by the energy supply device in the energy supply stage so as to release it when needed. The energy storage device stores energy when there is an excess supply of energy and releases energy when there is an insufficient supply of energy, thereby balancing energy supply and demand; for example, lead-acid batteries, lithium-ion batteries, and sodium-ion batteries are all common energy storage devices;

[0059] According to one embodiment of the present invention, the equipment in the energy use stage in step S1 is energy-consuming equipment, which is equipment or facilities used to consume energy in industrial production processes or in daily life. These energy-consuming equipment usually converts the electrical energy, thermal energy, etc. provided by the energy supply equipment in the energy supply stage into mechanical energy, light energy, etc. to meet production or life needs. For example, various mechanical equipment in industrial production, such as machine tools, conveying equipment, presses, etc., which require electrical drive, are all electrical equipment in the energy use stage.

[0060] S2, obtaining the operation data of each category of equipment in the energy Internet of Things and the weather data of the location of each category of equipment through the sensor network;

[0061] S3, substituting the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the energy conversion stage equipment abnormality analysis strategy to perform equipment abnormality analysis in each energy conversion stage, and obtaining abnormality analysis results of all categories of equipment in the energy conversion stage;

[0062] S4. Import the abnormal analysis results of each category of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the labeled energy Internet of Things topology diagram.

[0063] According to an embodiment of the present invention, the energy conversion stage equipment abnormality analysis strategy in S3 includes the following specific contents:

[0064] S31, substituting the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply anomaly analysis sub-strategy to perform an anomaly analysis of the energy supply equipment in the energy supply stage;

[0065] S32, substituting the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage anomaly analysis sub-strategy to perform an anomaly analysis of the energy storage devices in the energy storage stage;

[0066] S33, substituting the operating data of all energy-consuming devices in the energy use phase and the weather data of the location of each energy-consuming device into the energy use anomaly analysis sub-strategy to perform an anomaly analysis of the energy-consuming devices in the energy use phase.

[0067] According to one embodiment of the present invention, the specific steps of the energy supply anomaly analysis sub-strategy in S31 are as follows:

[0068] S311, obtaining the operating data of all energy supply equipment in the energy supply stage at n moments and the weather data of the location where each energy supply equipment is located; the operating data of the energy supply equipment includes: the power output value and the equipment temperature of the energy supply equipment at n moments, and the weather data of the location where each energy supply equipment is located includes the ambient temperature of the location where each energy supply equipment is located at n moments;

[0069] S312: Calculate the abnormal value of each energy supply device at the jth moment Where P j , Tg j is the power output value and equipment temperature of the energy supply equipment at the jth moment, Tg min , Tg max They are the minimum and maximum device temperatures for normal operation of the energy supply equipment, GT j is the ambient temperature of the location of the energy supply equipment at the jth moment, where j is any one of 1 to n;

[0070] S313. Taking the energy supply device abnormality value of each energy supply device at the j-th moment as the energy supply device abnormality analysis result of each energy supply device at the j-th moment.

[0071] According to one embodiment of the present invention, the specific steps of the energy storage abnormality analysis sub-strategy in S32 are:

[0072] S321, obtaining the operating data of all energy storage devices in the energy storage stage and the weather data of the location where each energy storage device is located, wherein the operating data of the energy storage device includes the power value and device temperature of the energy storage device, and the weather data of the location where each energy storage device is located includes the ambient temperature of the location where each energy storage device is located;

[0073] S322, calculating the abnormal value of each energy storage device at the jth moment where e j , Tc j is the power value and device temperature of the energy storage device at the jth moment, Tc min , Tc max are the minimum and maximum device temperatures for normal operation of the energy storage device, CT j is the ambient temperature of the location of the energy storage device at the jth moment, where j is any one of 1 to n;

[0074] S323. Taking the energy storage device abnormality value of each energy storage device at the j-th moment as the energy storage device abnormality analysis result of each energy storage device at the j-th moment.

[0075] According to an embodiment of the present invention, the energy usage anomaly analysis sub-strategy in S33 includes the following specific steps:

[0076] S331, obtaining the operating data of all energy-consuming devices during the energy use phase and the weather data of the location where each energy-consuming device is located; the operating data of the energy-consuming devices includes the operating time, power output value, and device temperature of the energy-consuming devices, and the weather data of the location where each energy-consuming device is located includes the ambient temperature of the location where each energy-consuming device is located;

[0077] S332. Calculate the abnormal value of each energy-consuming device at the jth moment where yt j 、yp j 、Ty j is the operating time, power output value, and equipment temperature of the energy-consuming equipment at the jth moment, Ty min 、Ty max They are the lowest and highest equipment temperatures for normal operation of energy-consuming equipment, YT jis the ambient temperature of the location of the energy-consuming equipment at the jth moment, where j is any one of 1 to n;

[0078] S333. Taking the energy-consuming device abnormal value of each energy-consuming device at the j-th moment as the energy-consuming device abnormality analysis result of each energy-consuming device at the j-th moment.

[0079] According to one embodiment of the present invention, the specific content of S4 is as follows:

[0080] S41, obtaining abnormal analysis results of energy supply equipment, energy storage equipment, and energy consumption equipment at the jth moment;

[0081] S42, the equipment maintenance path analysis strategy includes: presetting an abnormal threshold value ΔG of energy supply equipment, an abnormal threshold value ΔC of energy storage equipment, and an abnormal threshold value ΔY of energy consumption equipment. It should be noted that the abnormal threshold values ​​of each category of equipment are set by those skilled in the art according to actual needs;

[0082] S43, obtaining the abnormal analysis result G of the energy supply equipment at the jth moment j >The number Q1 of all corresponding energy supply devices of ΔG and the positions of all corresponding energy supply devices in the annotated energy Internet of Things topology diagram;

[0083] S44. Obtain abnormal analysis result C of energy storage equipment at the jth moment j >The number Q2 of all corresponding energy storage devices of ΔC and the positions of all corresponding energy storage devices in the annotated energy Internet of Things topology diagram;

[0084] S45. Obtain abnormal analysis result Y of energy-consuming equipment at the jth moment j >The number Q3 of all corresponding energy-consuming devices of ΔY and the positions of all corresponding energy-consuming devices in the annotated energy Internet of Things topology diagram;

[0085] S46, any one of the Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices obtained in the above S43-S45 is selected as the starting device, and an equipment maintenance path sequence is created, wherein the equipment maintenance path sequence is used to store the paths found during the traversal process, and a traversed list is created at the same time to store the traversed devices, and the empty list initially contains only the starting device;

[0086] S47, obtaining the corresponding device with the shortest distance to the starting point device from the devices other than the starting point device, and taking the corresponding device with the shortest distance to the starting point device as the next traversal device;

[0087] S48, adding the next traversed device to the traversed list, and updating the device maintenance path sequence, recording the path from the starting device to the next traversed device;

[0088] S49, repeat steps S47-S48, take the next traversal device as the starting device, continue to obtain the corresponding device with the shortest distance to the starting device for traversal, until all Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices have been traversed, and execute S410;

[0089] S410. Output an updated equipment maintenance path sequence, and display the equipment maintenance path corresponding to the updated equipment maintenance path sequence in a labeled energy Internet of Things topology diagram.

[0090] Example 2

[0091] Figure 2 The schematic diagram of the energy Internet of Things data processing system architecture based on the industrial cloud platform according to an embodiment of the present invention is shown as an example. Figure 2 As shown in the figure, the energy Internet of Things data processing system based on the industrial cloud platform specifically includes:

[0092] The device topology relationship acquisition module is used to obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and obtain the energy Internet of Things topology relationship diagram at the same time. In the energy Internet of Things topology relationship diagram, the color is marked according to the category of the device to obtain the marked energy Internet of Things topology relationship diagram, wherein the energy conversion stage includes: energy supply stage, energy storage stage and energy use stage; the categories of the equipment include energy supply equipment, energy storage equipment and energy use equipment;

[0093] The sensor data acquisition module is used to obtain the operating data of various types of equipment in the energy Internet of Things and the weather data of the locations where the various types of equipment are located through the sensor network;

[0094] The abnormality analysis module is used to substitute the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the abnormality analysis strategy of the equipment in the energy conversion stage to perform abnormality analysis of the equipment in each energy conversion stage, and obtain the abnormality analysis results of all categories of equipment in the energy conversion stage;

[0095] The equipment maintenance path analysis module is used to import the abnormal analysis results of various types of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the annotated energy Internet of Things topology diagram;

[0096] The control module is used to control the operation of each module.

[0097] According to one embodiment of the present invention, the abnormality analysis module includes an energy supply device abnormality analysis unit, an energy storage device abnormality analysis unit, and an energy consumption device abnormality analysis unit;

[0098] The energy supply equipment abnormality analysis unit is used to substitute the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply abnormality analysis sub-strategy to perform abnormality analysis of energy supply equipment in the energy supply stage;

[0099] The energy storage device abnormality analysis unit is used to substitute the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage abnormality analysis sub-strategy to perform abnormality analysis of energy storage devices in the energy storage stage;

[0100] The energy-consuming equipment abnormality analysis unit is used to substitute the operating data of all energy-consuming equipment in the energy use stage and the weather data of the location of each energy-consuming equipment into the energy use abnormality analysis sub-strategy to perform abnormal analysis of energy-consuming equipment in the energy use stage.

[0101] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0102] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0104] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0107] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0108] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The energy Internet of Things data processing method based on the industrial cloud platform is characterized by: It includes the following specific steps: S1. Obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and simultaneously obtain the energy Internet of Things topological relationship diagram, and mark the colors according to the types of devices in the energy Internet of Things topological relationship diagram to obtain the marked energy Internet of Things topological relationship diagram, wherein the energy conversion stages include: energy supply stage, energy storage stage and energy use stage; the types of devices include energy supply equipment, energy storage equipment and energy use equipment; S2, obtaining the operation data of each category of equipment in the energy Internet of Things and the weather data of the location of each category of equipment through the sensor network; S3, substituting the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the energy conversion stage equipment abnormality analysis strategy to perform equipment abnormality analysis in each energy conversion stage, and obtaining abnormality analysis results of all categories of equipment in the energy conversion stage; S4. Import the abnormal analysis results of each category of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the annotated energy Internet of Things topology relationship diagram; The energy conversion stage equipment abnormality analysis strategy in S3 includes the following specific contents: S31, substituting the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply anomaly analysis sub-strategy to perform an anomaly analysis of the energy supply equipment in the energy supply stage; S32, substituting the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage anomaly analysis sub-strategy to perform an anomaly analysis of the energy storage devices in the energy storage stage; S33, substituting the operation data of all energy-consuming devices in the energy use stage and the weather data of the location of each energy-consuming device into the energy use anomaly analysis sub-strategy to perform an anomaly analysis of the energy-consuming devices in the energy use stage; The specific steps of the energy supply anomaly analysis sub-strategy in S31 are as follows: S311, obtaining the operating data of all energy supply equipment in the energy supply stage at n moments and the weather data of the location where each energy supply equipment is located; the operating data of the energy supply equipment includes: the power output value and the equipment temperature of the energy supply equipment at n moments, and the weather data of the location where each energy supply equipment is located includes the ambient temperature of the location where each energy supply equipment is located at n moments; S312: Calculate the abnormal value of each energy supply device at the jth moment Where P j , Tg j is the power output value and equipment temperature of the energy supply equipment at the jth moment, Tg min , Tg max They are the minimum and maximum device temperatures for normal operation of the energy supply equipment, GT j is the ambient temperature of the location of the energy supply equipment at the jth moment, where j is any one of 1 to n; S313, taking the energy supply device abnormality value of each energy supply device at the jth moment as the energy supply device abnormality analysis result of each energy supply device at the jth moment; The specific steps of the energy storage abnormality analysis sub-strategy in S32 are: S321, obtaining the operating data of all energy storage devices in the energy storage stage and the weather data of the location where each energy storage device is located, wherein the operating data of the energy storage device includes the power value and device temperature of the energy storage device, and the weather data of the location where each energy storage device is located includes the ambient temperature of the location where each energy storage device is located; S322, calculating the abnormal value of each energy storage device at the jth moment where e j , Tc j is the power value and device temperature of the energy storage device at the jth moment, Tc min , Tc max are the minimum and maximum device temperatures for normal operation of the energy storage device, CT j is the ambient temperature of the location of the energy storage device at the jth moment, where j is any one of 1 to n; S323, taking the energy storage device abnormal value of each energy storage device at the jth moment as the energy storage device abnormality analysis result of each energy storage device at the jth moment; The energy usage anomaly analysis sub-strategy in S33 includes the following specific steps: S331, obtaining the operating data of all energy-consuming devices during the energy use phase and the weather data of the location where each energy-consuming device is located; the operating data of the energy-consuming devices includes the operating time, power output value, and device temperature of the energy-consuming devices, and the weather data of the location where each energy-consuming device is located includes the ambient temperature of the location where each energy-consuming device is located; S332. Calculate the abnormal value of each energy-consuming device at the jth moment where yt j 、yp j 、Ty j is the operating time, power output value, and equipment temperature of the energy-consuming equipment at the jth moment, Ty min 、Ty max They are the lowest and highest equipment temperatures for normal operation of energy-consuming equipment, YT j is the ambient temperature of the location of the energy-consuming equipment at the jth moment, where j is any one of 1 to n; S333, taking the energy-consuming device abnormal value of each energy-consuming device at the jth moment as the energy-consuming device abnormality analysis result of each energy-consuming device at the jth moment; The specific contents of S4 are as follows: S41, obtaining abnormal analysis results of energy supply equipment, energy storage equipment and energy consumption equipment at the jth moment; S42, the equipment maintenance path analysis strategy includes: presetting an abnormal threshold value ΔG of energy supply equipment, an abnormal threshold value ΔC of energy storage equipment and an abnormal threshold value ΔY of energy consumption equipment; S43, obtaining the abnormal analysis result G of the energy supply equipment at the jth moment j >The number Q1 of all corresponding energy supply devices of ΔG and the positions of all corresponding energy supply devices in the annotated energy Internet of Things topology diagram; S44. Obtain abnormal analysis result C of energy storage equipment at the jth moment j >The number Q2 of all corresponding energy storage devices of ΔC and the positions of all corresponding energy storage devices in the annotated energy Internet of Things topology diagram; S45. Obtain abnormal analysis result Y of energy-consuming equipment at the jth moment j >The number Q3 of all corresponding energy-consuming devices of ΔY and the positions of all corresponding energy-consuming devices in the annotated energy Internet of Things topology diagram; S46, any one of the Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices obtained in the above S43-S45 is selected as the starting device, and an equipment maintenance path sequence is created, wherein the equipment maintenance path sequence is used to store the paths found during the traversal process, and a traversed list is created at the same time to store the traversed devices, and the empty list initially contains only the starting device; S47, obtaining the corresponding device with the shortest distance to the starting point device from the devices other than the starting point device, and taking the corresponding device with the shortest distance to the starting point device as the next traversal device; S48, adding the next traversed device to the traversed list, and updating the device maintenance path sequence, recording the path from the starting device to the next traversed device; S49, repeat steps S47-S48, take the next traversal device as the starting device, continue to obtain the corresponding device with the shortest distance to the starting device for traversal, until all Q1 energy supply devices, Q2 energy storage devices and Q3 energy consumption devices have been traversed, and execute S410; S410. Output an updated equipment maintenance path sequence, and display the equipment maintenance path corresponding to the updated equipment maintenance path sequence in a labeled energy Internet of Things topology diagram.

2. An energy Internet of Things data processing system based on an industrial cloud platform, which is implemented based on the energy Internet of Things data processing method based on an industrial cloud platform as claimed in claim 1, characterized in that: Specifically include: The device topology relationship acquisition module is used to obtain all energy conversion stages in the energy supply process, classify the devices in the energy Internet of Things based on each energy conversion stage, and obtain the energy Internet of Things topology relationship diagram at the same time. In the energy Internet of Things topology relationship diagram, the color is marked according to the category of the device to obtain the marked energy Internet of Things topology relationship diagram, wherein the energy conversion stage includes: energy supply stage, energy storage stage and energy use stage; the categories of the equipment include energy supply equipment, energy storage equipment and energy use equipment; The sensor data acquisition module is used to obtain the operating data of various types of equipment in the energy Internet of Things and the weather data of the locations where the various types of equipment are located through the sensor network; The abnormality analysis module is used to substitute the operation data of each category of equipment in each energy conversion stage and the weather data of the location of each category of equipment into the abnormality analysis strategy of the equipment in the energy conversion stage to perform abnormality analysis of the equipment in each energy conversion stage, and obtain the abnormality analysis results of all categories of equipment in the energy conversion stage; The equipment maintenance path analysis module is used to import the abnormal analysis results of various types of equipment in the energy conversion stage into the equipment maintenance path analysis strategy to analyze the equipment maintenance path, and display the equipment maintenance path in the annotated energy Internet of Things topology diagram; The control module is used to control the operation of each module.

3. The energy Internet of Things data processing system based on the industrial cloud platform as described in claim 2 is characterized in that: The abnormality analysis module includes an energy supply device abnormality analysis unit, an energy storage device abnormality analysis unit, and an energy consumption device abnormality analysis unit; The energy supply equipment abnormality analysis unit is used to substitute the operation data of all energy supply equipment in the energy supply stage and the weather data of the location of each energy supply equipment into the energy supply abnormality analysis sub-strategy to perform abnormality analysis of energy supply equipment in the energy supply stage; The energy storage device abnormality analysis unit is used to substitute the operating data of all energy storage devices in the energy storage stage and the weather data of the location of each energy storage device into the energy storage abnormality analysis sub-strategy to perform abnormality analysis of energy storage devices in the energy storage stage; The energy-consuming equipment abnormality analysis unit is used to substitute the operating data of all energy-consuming equipment in the energy use stage and the weather data of the location of each energy-consuming equipment into the energy use abnormality analysis sub-strategy to perform abnormal analysis of energy-consuming equipment in the energy use stage.

Images