CN114007149B - Monitoring method, device, system, storage medium and processor of power system - Google Patents
Monitoring method, device, system, storage medium and processor of power system Download PDFInfo
- Publication number
- CN114007149B CN114007149B CN202111285343.3A CN202111285343A CN114007149B CN 114007149 B CN114007149 B CN 114007149B CN 202111285343 A CN202111285343 A CN 202111285343A CN 114007149 B CN114007149 B CN 114007149B
- Authority
- CN
- China
- Prior art keywords
- data
- power system
- cloud server
- uploading
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 64
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000013135 deep learning Methods 0.000 claims abstract description 14
- 238000003062 neural network model Methods 0.000 claims abstract description 12
- 238000004891 communication Methods 0.000 claims description 46
- 238000005516 engineering process Methods 0.000 claims description 38
- 230000005540 biological transmission Effects 0.000 claims description 15
- 238000004128 high performance liquid chromatography Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000012806 monitoring device Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 7
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 230000000694 effects Effects 0.000 description 10
- 238000012545 processing Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000009295 sperm incapacitation Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/30—Arrangements in telecontrol or telemetry systems using a wired architecture
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/40—Arrangements in telecontrol or telemetry systems using a wireless architecture
- H04Q2209/47—Arrangements in telecontrol or telemetry systems using a wireless architecture using RFID associated with sensors
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Computer Security & Cryptography (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses a monitoring method, a device, a system, a storage medium and a processor of an electric power system. Wherein the method comprises the following steps: acquiring multiple sets of power system data, wherein the multiple sets of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; uploading a plurality of groups of power system data to a cloud server in real time; and inputting a plurality of groups of electric power data into an electric power system monitoring model and outputting the running state of a target electric power system, wherein the electric power system monitoring model is a neural network model obtained by deep learning based on a plurality of groups of sample data of the target electric power system. The intelligent power system operation state monitoring system solves the technical problem that the operation state monitoring of the power system is not intelligent.
Description
Technical Field
The invention relates to the field of electricity protection, in particular to a monitoring method, a device, a system, a storage medium and a processor of an electric power system.
Background
The outdoor large-scale activity power supply ensures that the sensitive users on the scene are more in types and huge in quantity, such as lights, sounds, screens and the like. The sensitive load characteristics of the parts are special, and the problems of power quality such as voltage fluctuation, current harmonic waves and the like can be caused, and the operation characteristics of the field guarantee equipment and the success and failure of the guarantee are directly related. Therefore, this puts higher demands on the safeguarding work of the power system, and the operation characteristics of the equipment and the load need to be monitored as soon as possible when an electric energy quality event occurs in the safeguarding process. However, the large data volume, wide distribution range and many aspects of monitoring are generated by the power system depending on the outdoor large-scale activities, and the requirement of high-speed reaction to the electric energy quality event in the power supply guarantee work cannot be met by relying on manual analysis work on mass data.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a monitoring method, a device, a system, a storage medium and a processor for an electric power system, which are used for at least solving the technical problem of incapacitation of monitoring the running state of the electric power system.
According to an aspect of an embodiment of the present invention, there is provided a monitoring method of an electric power system, including: acquiring multiple sets of power system data, wherein the multiple sets of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; uploading the multiple groups of power system data to a cloud server in real time; and inputting the multiple groups of power data into a power system monitoring model, and outputting the running state of the target power system, wherein the power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target power system.
Optionally, uploading the plurality of sets of power system data to a cloud server in real time includes: deploying an edge processor on a data acquisition side of the target power system, wherein the edge processor is used for performing edge calculation; preprocessing the plurality of sets of power system data using the edge processor; and uploading the preprocessed multiple groups of power system data to the cloud server in real time.
Optionally, the edge processor is disposed at a data acquisition side of the target power system, comprising: disposing a plurality of the edge processors on a plurality of data acquisition sides of the power system, respectively, wherein the data acquisition device comprises at least one of the following: the sensor and the electricity-keeping terminal equipment; and accessing a plurality of edge processors and the cloud server into a distributed network, wherein the cloud server and any one of the edge processors are a node in the distributed network.
Optionally, uploading the multiple sets of power system data to a cloud server in real time, further includes: dividing a plurality of groups of power system data into first data, second data and third data according to the type of equipment generating the plurality of groups of power system data; adopting URLLC service in a 5G communication technology to upload the first data to the cloud server in real time; uploading the second data to the cloud server by adopting a blockchain encryption communication technology; and uploading the third data to the cloud server by adopting an HPLC electronic carrier communication technology.
Optionally, uploading the second data to the cloud server using a blockchain encryption communication technology includes: establishing connection between target equipment and an Ethernet Geth node, wherein the target equipment is equipment for generating the second data; acquiring equipment information of the second equipment; sending the equipment information to the Geth node, triggering the intelligent contract of the Geth node, and performing node consensus authentication of the equipment information; transmitting the second data to the Geth node if the device information authentication is passed; the Geth node uploads the second data to the cloud server.
Optionally, after outputting the operation state of the target power system, the method further includes: judging whether the running state of the target power system is normal or not; and under the condition that the running state of the target power system is abnormal, carrying out alarm prompt.
According to another aspect of the embodiment of the present invention, there is also provided a monitoring device for an electric power system, including: the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a plurality of groups of power system data, the plurality of groups of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; the uploading module is used for uploading the multiple groups of power system data to the cloud server in real time; and the output module is used for inputting the multiple groups of electric power data into an electric power system monitoring model and outputting the running state of the target electric power system, wherein the electric power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target electric power system.
According to still another aspect of the embodiment of the present invention, there is also provided a monitoring system of an electric power system, including: the system comprises a data acquisition device, an edge calculation device, a data transmission device and a cloud server, wherein the data acquisition device is used for acquiring a plurality of groups of power system data, the plurality of groups of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; the data transmission device is used for uploading the multiple groups of power system data to the cloud server in real time by adopting URLLC service in a 5G communication technology; the cloud server is used for inputting the multiple groups of power data into a power system monitoring model and outputting the running state of the target power system, wherein the power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target power system.
Optionally, the system further comprises: the edge computing device is deployed beside the data acquisition device and is used for preprocessing the plurality of groups of power system data.
According to still another aspect of the embodiments of the present invention, there is further provided a computer readable storage medium, where the computer readable storage medium includes a stored program, and when the program runs, the device in which the computer readable storage medium is controlled to execute the power system monitoring method according to any one of the foregoing methods.
According to still another aspect of the embodiment of the present invention, there is further provided a processor, where the processor is configured to execute a program, where the program executes any one of the above power system monitoring methods.
In the embodiment of the invention, a mode of acquiring a plurality of groups of power system data generated by a target power system is adopted, the plurality of groups of power system data are uploaded to a cloud server in real time and are input into a power system monitoring model obtained through deep learning, and the running state of the target power system is output, so that the purpose of monitoring the running state of the target power system in real time is achieved, the technical effect of intelligently monitoring the running state of the power system is realized, and the technical problem of incapacity of monitoring the running state of the power system is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
Fig. 1 is a schematic flow chart of a method for monitoring an electric power system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a communication mode of a monitoring system according to an alternative embodiment of the present invention;
fig. 3 is a block diagram of a monitoring device of an electric power system according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
First, partial terms or terminology appearing in the course of describing the embodiments of the application are applicable to the following explanation:
URLLC, ultra-high reliability Low latency communication service (URLLC for short), is supported by the 5G new radio standard.
The Ethernet Geth node is used for realizing communication with other clients through Geth nodes in order to realize functions of signing, broadcasting transaction, intelligent contract interaction and the like for a blockchain client used for communication with a blockchain.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a method of monitoring a power system, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical sequence is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than what is shown herein.
Fig. 1 is a flow chart of a method for monitoring an electric power system according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
Step S102, a plurality of groups of power system data are acquired, wherein the plurality of groups of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data, and power-saving terminal equipment data. Alternatively, the target power system may be a power system for supporting outdoor large-scale activities, including, for example, lights, sounds, screens, and power supply networks for supplying power thereto, and the like. The sensor data may be deployed alongside the target power system for monitoring data of specific characteristics of the target power system, for example, may be used to monitor load access conditions, component temperatures, communication status, etc. in the target power system. The electricity-protecting terminal equipment is professional monitoring equipment for guaranteeing the power supply stability of the target power system.
Step S104, uploading a plurality of groups of power system data to the cloud server in real time. For a large-scale outdoor power system, the generated data volume is very huge, the data processing is difficult to be performed locally, and meanwhile, due to the limitation of the environment scene of the activity, large-scale reliable computing equipment or servers cannot be deployed nearby the local area, so that the technical problem can be solved by uploading the data to the cloud server in real time, and the proper preservation of the power system data is realized.
And S106, inputting a plurality of groups of electric power data into an electric power system monitoring model and outputting the running state of the target electric power system, wherein the electric power system monitoring model is a neural network model obtained by deep learning based on a plurality of groups of sample data of the target electric power system.
It should be noted that the power system monitoring model may be trained in advance and stored in the cloud server, and may be directly invoked when needed. Because the data volume of the target power system is huge, mining and analyzing the data of the power system by adopting a manual or automatic mode is time-consuming and labor-consuming, and the accuracy cannot be ensured. Therefore, the embodiment proposes to process the power system data by adopting the power system monitoring model trained based on the deep learning neural network model, and outputting the running state of the power system by the model. Alternatively, the model may be trained from sample data of the target power system. The sample data can be multiple groups of sample data collected on site after the power supply site of the outdoor large-scale activity is built with a power system, and the sample data comprise manual marks for identifying the running state of the power system in each group of sample data. In addition, the sample data can be sample data of other power systems similar to the target power system, and the sample data of the similar power system can be used for providing more ready sample data for training of a model, so that the efficiency of model training is improved.
Through the steps, the mode of acquiring the multiple groups of power system data generated by the target power system is adopted, the multiple groups of power system data are uploaded to the cloud server in real time and are input into the power system monitoring model obtained through deep learning, the running state of the target power system is output, the purpose of monitoring the running state of the target power system in real time is achieved, the technical effect of intelligently monitoring the running state of the power system is achieved, and the technical problem that the running state monitoring of the power system is not intelligent is solved.
As an optional embodiment, the uploading of the multiple sets of power system data to the cloud server in real time may be performed by: deploying an edge processor on a data acquisition side of a target power system, wherein the edge processor is used for performing edge calculation; preprocessing a plurality of sets of power system data using an edge processor; and uploading the preprocessed multiple groups of power system data to the cloud server in real time.
As an alternative embodiment, the edge processors may be deployed on the data acquisition side of the target power system, where the edge processors may be deployed on multiple data acquisition sides of the power system, respectively, where the data acquisition device includes at least one of: the sensor and the electricity-keeping terminal equipment; and then accessing a plurality of edge processors and a cloud server into the distributed network, wherein the cloud server and any one of the edge processors are a node in the distributed network. By adopting a network layout mode of a distributed network, the stability of the power monitoring system can be improved, and the effect of global monitoring is prevented from being influenced when a single node breaks down.
As an optional embodiment, the uploading of the multiple sets of power system data to the cloud server in real time may further adopt the following manner: dividing a plurality of groups of power system data into first data, second data and third data according to the type of equipment generating the plurality of groups of power system data; the first data is uploaded to a cloud server in real time by adopting URLLC service in a 5G communication technology; uploading the second data to a cloud server by adopting a blockchain encryption communication technology; and uploading the third data to a cloud server by adopting an HPLC electronic carrier communication technology.
For the power security scene, various power equipment sources can appear on the power security scene, different equipment possibly belong to different individuals or units, the types of equipment are also various, and the unified power data transmission technology can not meet different requirements sometimes well. The execution scene of the power guarantee may be indoor, square or outdoor, and the power equipment required to be guaranteed in different scenes is necessarily different, and the data processing requirements of different power equipment are also necessarily different. For example, the electric equipment can include, but is not limited to, broadcasting vehicles, lighting systems, electric equipment in confidential places and the like, and in the scenes of indoor or urban squares and the like, the electric equipment can be connected with power through an urban power supply system, but in the field places, since no mature power pipeline exists in the environment, other power connection modes are needed for the electric equipment, and the data transmission modes which can be selected for the electric equipment are also necessarily influenced by the differences.
Optionally, the technical problem can be solved by classifying the data generated by the power equipment in the power system according to the scene and the requirement, and then uploading the data of different types to the cloud server in a data transmission mode meeting the requirement. Specifically, the types of the power system data may include first data, second data and third data, where the first data is data with highest aging demand level, and data that needs to be transmitted in a fastest manner; the second data is the data with highest security requirement level, and the data is required to be transmitted in the safest mode; the third data is more general data, which is less demanding in terms of timeliness and confidentiality and can be transmitted in a more economical manner.
Further, the first data may include, but is not limited to, live broadcast signals or data of power equipment which is extremely important in power security activities, and must be uploaded in real time at a high speed, so that the server can complete data processing as soon as possible; the second data may include, but is not limited to, data related to privacy of a user of the on-site power equipment, or data of a special object, such as a power system arrangement of a place involving national or military confidentiality, and the security requirement on the power system data is high, but the data cannot be uploaded at ordinary times, but the data needs to be uploaded from the site to a cloud server for power guarantee, and such data may be divided into the second data; the third data may be data generated by a power device accessing the city power line.
For the three data, the following different data transmission modes can be adopted: adopting URLLC service in a 5G communication technology to upload the first data to the cloud server in real time; uploading the second data to the cloud server by adopting a blockchain encryption communication technology; and uploading the third data to the cloud server by adopting an HPLC electronic carrier communication technology. Wherein URLLC is a communication service with ultra-high reliability and low time delay in the 5G standard, so that timeliness of data transmission can be ensured to the greatest extent. The block chain encryption communication technology can ensure the reliability of data transmission and avoid the leakage of sensitive information. HPLC is short for broadband power line carrier technology, has the characteristics of large bandwidth and high transmission rate, and can be suitable for data transmission of power equipment connected with urban power lines.
Optionally, data other than the three data may be transmitted by using a 4G communication technology, and the data is uploaded to the cloud server. The 4G communication technology is more mature and has lower cost, the 5G communication technology, the blockchain encryption communication technology and the HPLC communication technology have the advantages, and an operation and maintenance person can flexibly select the combination of the plurality of communication technologies according to the specific situation of power supply activities. Fig. 2 is a schematic diagram of a communication manner of a monitoring system according to an alternative embodiment of the present invention, as shown in fig. 2, the data of the monitoring terminal may be uploaded to a cloud server, and a 4G and 5G hybrid networking may be further selected, and in combination with a blockchain encryption communication technology and an HPLC technology, the data of multiple types of monitoring terminals may be selected to use a suitable data transmission path. For example, for a sensor with small data volume, the data can be uploaded to the cloud server in a 4G communication mode, and for a more precise professional electricity-protecting device with mass data generation, the data is uploaded to the cloud server in a 5G communication mode for subsequent analysis.
As an alternative embodiment, the second data is uploaded to the cloud server by using the blockchain encryption communication technology, which may be as follows: establishing connection between target equipment and an Ethernet Geth node, wherein the target equipment is equipment for generating second data; acquiring equipment information of the second equipment; sending equipment information to Geth nodes, triggering an intelligent contract of Geth nodes, and performing node consensus authentication of the equipment information; transmitting the second data to the Geth node under the condition that the equipment information authentication is passed; and Geth, uploading the second data to the cloud server by the node. In the above-mentioned alternative embodiment, the intelligent contract of Geth nodes is used to authenticate the device information of the target device, so as to realize the authentication of the target device, and the data of the target device is encrypted and uploaded by the blockchain technology on the basis of the authentication, so that the security of the data transmission of the target device is ensured.
As an alternative embodiment, after outputting the operation state of the target power system, it may also be determined whether the operation state of the target power system is normal; and when the running state of the target power system is abnormal, carrying out alarm prompt.
Example 2
According to an embodiment of the present invention, there is further provided a monitoring device for an electric power system for implementing the above-mentioned monitoring method for an electric power system, and fig. 3 is a block diagram of a structure of the monitoring device for an electric power system according to an embodiment of the present invention, as shown in the drawing, the monitoring device 30 for an electric power system includes: the acquisition module 32, the upload module 34 and the output module 36 are described below with respect to the monitoring device 30 of the power system.
An acquiring module 32, configured to acquire a plurality of sets of power system data, where the plurality of sets of power system data are data generated by a target power system, and the power system data include at least one of: sensor data and electricity-retaining terminal equipment data;
The uploading module 34 is connected to the acquiring module 32, and is configured to upload the multiple sets of power system data to the cloud server in real time;
The output module 36 is connected to the uploading module 34, and is configured to input a plurality of sets of power data into a power system monitoring model, and output an operation state of a target power system, where the power system monitoring model is a neural network model obtained by performing deep learning based on a plurality of sets of sample data of the target power system.
Here, the above-mentioned obtaining module 32, uploading module 34 and outputting module 36 correspond to steps S102 to S106 in embodiment 1, and the three modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in embodiment 1.
Example 3
Embodiments of the present invention may provide a computer device, optionally in this embodiment, the computer device may be located in at least one network device of a plurality of network devices of a computer network. The computer device includes a memory and a processor.
The memory may be used to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for monitoring a power system in the embodiments of the present invention, and the processor executes the software programs and modules stored in the memory, thereby executing various functional applications and data processing, that is, implementing the method for monitoring a power system described above. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located relative to the processor, which may be connected to the computer terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may call the information and the application program stored in the memory through the transmission device to perform the following steps: acquiring multiple sets of power system data, wherein the multiple sets of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; uploading a plurality of groups of power system data to a cloud server in real time; and inputting a plurality of groups of electric power data into an electric power system monitoring model and outputting the running state of a target electric power system, wherein the electric power system monitoring model is a neural network model obtained by deep learning based on a plurality of groups of sample data of the target electric power system.
Optionally, the above processor may further execute program code for: uploading the multiple groups of power system data to the cloud server in real time comprises: deploying an edge processor on a data acquisition side of a target power system, wherein the edge processor is used for performing edge calculation; preprocessing a plurality of sets of power system data using an edge processor; and uploading the preprocessed multiple groups of power system data to the cloud server in real time.
Optionally, the above processor may further execute program code for: an edge processor is deployed at a data acquisition side of a target power system, comprising: disposing a plurality of edge processors on a plurality of data acquisition sides of the power system, respectively, wherein the data acquisition device comprises at least one of the following: the sensor and the electricity-keeping terminal equipment; and accessing the plurality of edge processors and the cloud server into a distributed network, wherein the cloud server and any one of the edge processors are a node in the distributed network.
Optionally, the above processor may further execute program code for: uploading the multiple groups of power system data to the cloud server in real time, and further comprising: dividing a plurality of groups of power system data into first data, second data and third data according to the type of equipment generating the plurality of groups of power system data; the first data is uploaded to a cloud server in real time by adopting URLLC service in a 5G communication technology; uploading the second data to a cloud server by adopting a blockchain encryption communication technology; and uploading the third data to a cloud server by adopting an HPLC electronic carrier communication technology.
Optionally, the above processor may further execute program code for: uploading the second data to the cloud server using a blockchain encryption communication technique, comprising: establishing connection between target equipment and an Ethernet Geth node, wherein the target equipment is equipment for generating second data; acquiring equipment information of the second equipment; sending equipment information to Geth nodes, triggering an intelligent contract of Geth nodes, and performing node consensus authentication of the equipment information; transmitting the second data to the Geth node under the condition that the equipment information authentication is passed; and Geth, uploading the second data to the cloud server by the node.
Optionally, the above processor may further execute program code for: after outputting the operation state of the target power system, the method further includes: judging whether the running state of the target power system is normal or not; and when the running state of the target power system is abnormal, carrying out alarm prompt.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing a terminal device to execute in association with hardware, the program may be stored in a computer readable storage medium, and the storage medium may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.
Example 4
Embodiments of the present invention also provide a computer-readable storage medium. Alternatively, in the present embodiment, the computer-readable storage medium may be used to store the program code executed by the monitoring method of the electric power system provided in the embodiment 1.
Alternatively, in this embodiment, the above-mentioned computer-readable storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: acquiring multiple sets of power system data, wherein the multiple sets of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data; uploading a plurality of groups of power system data to a cloud server in real time; and inputting a plurality of groups of electric power data into an electric power system monitoring model and outputting the running state of a target electric power system, wherein the electric power system monitoring model is a neural network model obtained by deep learning based on a plurality of groups of sample data of the target electric power system.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: uploading the multiple groups of power system data to the cloud server in real time comprises: deploying an edge processor on a data acquisition side of a target power system, wherein the edge processor is used for performing edge calculation; preprocessing a plurality of sets of power system data using an edge processor; and uploading the preprocessed multiple groups of power system data to the cloud server in real time.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: an edge processor is deployed at a data acquisition side of a target power system, comprising: disposing a plurality of edge processors on a plurality of data acquisition sides of the power system, respectively, wherein the data acquisition device comprises at least one of the following: the sensor and the electricity-keeping terminal equipment; and accessing the plurality of edge processors and the cloud server into a distributed network, wherein the cloud server and any one of the edge processors are a node in the distributed network.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: uploading the multiple groups of power system data to the cloud server in real time, and further comprising: dividing a plurality of groups of power system data into first data, second data and third data according to the type of equipment generating the plurality of groups of power system data; the first data is uploaded to a cloud server in real time by adopting URLLC service in a 5G communication technology; uploading the second data to a cloud server by adopting a blockchain encryption communication technology; and uploading the third data to a cloud server by adopting an HPLC electronic carrier communication technology.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: uploading the second data to the cloud server using a blockchain encryption communication technique, comprising: establishing connection between target equipment and an Ethernet Geth node, wherein the target equipment is equipment for generating second data; acquiring equipment information of the second equipment; sending equipment information to Geth nodes, triggering an intelligent contract of Geth nodes, and performing node consensus authentication of the equipment information; transmitting the second data to the Geth node under the condition that the equipment information authentication is passed; and Geth, uploading the second data to the cloud server by the node.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: after outputting the operation state of the target power system, the method further includes: judging whether the running state of the target power system is normal or not; and when the running state of the target power system is abnormal, carrying out alarm prompt.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of units may be a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (8)
1. A method of monitoring an electrical power system, comprising:
acquiring multiple sets of power system data, wherein the multiple sets of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data;
uploading the multiple groups of power system data to a cloud server in real time;
inputting the multiple groups of power data into a power system monitoring model and outputting the running state of the target power system, wherein the power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target power system;
uploading the plurality of groups of power system data to a cloud server in real time comprises:
deploying an edge processor on a data acquisition side of the target power system, wherein the edge processor is used for performing edge calculation;
Preprocessing the plurality of sets of power system data using the edge processor;
Uploading the preprocessed multiple groups of power system data to the cloud server in real time;
uploading the multiple groups of power system data to a cloud server in real time, and further comprising:
dividing a plurality of groups of power system data into first data, second data and third data according to the type of equipment generating the plurality of groups of power system data;
Adopting URLLC service in a 5G communication technology to upload the first data to the cloud server in real time;
Uploading the second data to the cloud server by adopting a blockchain encryption communication technology;
and uploading the third data to the cloud server by adopting an HPLC electronic carrier communication technology.
2. The method of claim 1, wherein the edge processor is deployed at a data acquisition side of the target power system, comprising:
Disposing a plurality of the edge processors on a plurality of data acquisition sides of the power system, respectively, wherein the data acquisition device comprises at least one of the following: the sensor and the electricity-keeping terminal equipment;
And accessing a plurality of edge processors and the cloud server into a distributed network, wherein the cloud server and any one of the edge processors are a node in the distributed network.
3. The method of claim 1, wherein uploading the second data to the cloud server using a blockchain encryption communication technique comprises:
establishing connection between target equipment and an Ethernet Geth node, wherein the target equipment is equipment for generating the second data;
acquiring equipment information of the target equipment;
sending the equipment information to the Geth node, triggering the intelligent contract of the Geth node, and performing node consensus authentication of the equipment information;
Transmitting the second data to the Geth node if the device information authentication is passed;
the Geth node uploads the second data to the cloud server.
4. The method of claim 1, further comprising, after outputting the operational state of the target power system:
Judging whether the running state of the target power system is normal or not;
and under the condition that the running state of the target power system is abnormal, carrying out alarm prompt.
5. A monitoring device for an electrical power system, comprising:
The system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a plurality of groups of power system data, the plurality of groups of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data;
The uploading module is used for uploading the multiple groups of power system data to the cloud server in real time;
the output module is used for inputting the multiple groups of power data into a power system monitoring model and outputting the running state of the target power system, wherein the power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target power system;
The uploading module is further configured to deploy an edge processor on a data acquisition side of the target power system, where the edge processor is configured to perform edge calculation; preprocessing the plurality of sets of power system data using the edge processor; uploading the preprocessed multiple groups of power system data to the cloud server in real time;
The uploading module is further used for dividing the multiple groups of power system data into first data, second data and third data according to the type of equipment for generating the multiple groups of power system data; adopting URLLC service in a 5G communication technology to upload the first data to the cloud server in real time; uploading the second data to the cloud server by adopting a blockchain encryption communication technology; and uploading the third data to the cloud server by adopting an HPLC electronic carrier communication technology.
6. A monitoring system for an electrical power system, comprising: the system comprises a data acquisition device, an edge calculation device, a data transmission device and a cloud server, wherein,
The data acquisition device is used for acquiring a plurality of groups of power system data, wherein the plurality of groups of power system data are data generated by a target power system, and the power system data comprise at least one of the following: sensor data and electricity-retaining terminal equipment data;
The data transmission device is used for uploading the multiple groups of power system data to the cloud server in real time by adopting URLLC service in a 5G communication technology;
The cloud server is used for inputting the multiple groups of power data into a power system monitoring model and outputting the running state of the target power system, wherein the power system monitoring model is a neural network model obtained by deep learning based on multiple groups of sample data of the target power system.
7. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run controls a device in which the computer readable storage medium is located to perform the power system monitoring method according to any one of claims 1 to 5.
8. A processor for running a program, wherein the program when run performs the power system monitoring method of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111285343.3A CN114007149B (en) | 2021-11-01 | 2021-11-01 | Monitoring method, device, system, storage medium and processor of power system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111285343.3A CN114007149B (en) | 2021-11-01 | 2021-11-01 | Monitoring method, device, system, storage medium and processor of power system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114007149A CN114007149A (en) | 2022-02-01 |
| CN114007149B true CN114007149B (en) | 2024-04-30 |
Family
ID=79926245
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111285343.3A Active CN114007149B (en) | 2021-11-01 | 2021-11-01 | Monitoring method, device, system, storage medium and processor of power system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114007149B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113984896A (en) * | 2021-11-01 | 2022-01-28 | 国网北京市电力公司 | Method and device for determining defect size of grounding electrode of transmission tower |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109188153A (en) * | 2018-10-22 | 2019-01-11 | 平顶山学院 | A kind of high-tension switch gear three-dimensional panorama intelligent condition monitoring system |
| CN110401262A (en) * | 2019-06-17 | 2019-11-01 | 北京许继电气有限公司 | GIS device state intelligent monitoring system and method based on edge calculations technology |
| CN110690699A (en) * | 2019-07-30 | 2020-01-14 | 国网浙江省电力有限公司嘉兴供电公司 | Transformer substation intelligent detection system based on ubiquitous power Internet of things |
| CN111313549A (en) * | 2020-02-24 | 2020-06-19 | 国网北京市电力公司 | Flood light stock power supply system based on ubiquitous Internet of things and monitoring method |
| CN111404914A (en) * | 2020-03-11 | 2020-07-10 | 南京邮电大学 | Ubiquitous power Internet of things terminal safety protection method under specific attack scene |
| CN111710122A (en) * | 2020-04-30 | 2020-09-25 | 国网天津市电力公司 | Safe power utilization management system based on ubiquitous power Internet of things |
| CN111741073A (en) * | 2020-05-27 | 2020-10-02 | 北京智芯微电子科技有限公司 | Electric power data transmission system based on 5G communication network |
| CN111857015A (en) * | 2020-08-06 | 2020-10-30 | 山东科宏电子科技有限公司 | Power transmission and transformation cloud intelligent controller |
| CN112464295A (en) * | 2020-12-14 | 2021-03-09 | 国网辽宁省电力有限公司抚顺供电公司 | Communication maintenance safety device based on electric power edge gateway equipment |
| KR102248727B1 (en) * | 2019-12-13 | 2021-05-06 | 주식회사 두두원 | Multi-protocol iot gateway for energy management |
| CN113532621A (en) * | 2021-07-13 | 2021-10-22 | 国网浙江省电力有限公司 | Power cable monitoring and analyzing system and method based on edge calculation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200225655A1 (en) * | 2016-05-09 | 2020-07-16 | Strong Force Iot Portfolio 2016, Llc | Methods, systems, kits and apparatuses for monitoring and managing industrial settings in an industrial internet of things data collection environment |
-
2021
- 2021-11-01 CN CN202111285343.3A patent/CN114007149B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109188153A (en) * | 2018-10-22 | 2019-01-11 | 平顶山学院 | A kind of high-tension switch gear three-dimensional panorama intelligent condition monitoring system |
| CN110401262A (en) * | 2019-06-17 | 2019-11-01 | 北京许继电气有限公司 | GIS device state intelligent monitoring system and method based on edge calculations technology |
| CN110690699A (en) * | 2019-07-30 | 2020-01-14 | 国网浙江省电力有限公司嘉兴供电公司 | Transformer substation intelligent detection system based on ubiquitous power Internet of things |
| KR102248727B1 (en) * | 2019-12-13 | 2021-05-06 | 주식회사 두두원 | Multi-protocol iot gateway for energy management |
| CN111313549A (en) * | 2020-02-24 | 2020-06-19 | 国网北京市电力公司 | Flood light stock power supply system based on ubiquitous Internet of things and monitoring method |
| CN111404914A (en) * | 2020-03-11 | 2020-07-10 | 南京邮电大学 | Ubiquitous power Internet of things terminal safety protection method under specific attack scene |
| CN111710122A (en) * | 2020-04-30 | 2020-09-25 | 国网天津市电力公司 | Safe power utilization management system based on ubiquitous power Internet of things |
| CN111741073A (en) * | 2020-05-27 | 2020-10-02 | 北京智芯微电子科技有限公司 | Electric power data transmission system based on 5G communication network |
| CN111857015A (en) * | 2020-08-06 | 2020-10-30 | 山东科宏电子科技有限公司 | Power transmission and transformation cloud intelligent controller |
| CN112464295A (en) * | 2020-12-14 | 2021-03-09 | 国网辽宁省电力有限公司抚顺供电公司 | Communication maintenance safety device based on electric power edge gateway equipment |
| CN113532621A (en) * | 2021-07-13 | 2021-10-22 | 国网浙江省电力有限公司 | Power cable monitoring and analyzing system and method based on edge calculation |
Non-Patent Citations (1)
| Title |
|---|
| 基于泛在电力物联网的换流站在线监测***优化综述;吕继伟;;电力工程技术;20191128(06);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114007149A (en) | 2022-02-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Abir et al. | Iot-enabled smart energy grid: Applications and challenges | |
| US11902318B2 (en) | Network visualization, intrusion detection, and network healing | |
| CN108989136B (en) | Business end-to-end performance monitoring method and device | |
| CN103916625A (en) | Video monitoring system and method based on cloud computing | |
| CN113656824B (en) | Intelligent terminal information safety interaction method of Internet of things based on block chain and IPFS technology | |
| Karabiyik et al. | Digital forensics for IoT and WSNS | |
| CN114422201B (en) | Network target range large-scale user remote access method and system | |
| CN110191105A (en) | OpenStack encrypted link realization method and system | |
| CN110209723A (en) | A kind of equipment information collection system based on Internet of Things big data | |
| Wang et al. | A centralized HIDS framework for private cloud | |
| CN114007149B (en) | Monitoring method, device, system, storage medium and processor of power system | |
| CN113507691B (en) | Information pushing system and method based on power distribution network cross-region service | |
| CN113703363A (en) | Plug-and-play method of intelligent edge computing gateway in power dispatching cloud | |
| CN115764984A (en) | Distributed photovoltaic grid-connected power generation operation system | |
| CN113241848B (en) | Comprehensive monitoring system for power distribution network | |
| CN104618320A (en) | Systems and methods for secure file transfers | |
| Soupionis et al. | Cyber-physical testbed—The impact of cyber attacks and the human factor | |
| CN108289041B (en) | Server information processing method and related device | |
| Sheba et al. | A new low‐cost and low‐power industrial internet of things infrastructure for effective integration of distributed and isolated systems with smart grids | |
| CN106254438B (en) | A kind of power distribution network CPS main website based on open communication | |
| CN106603624B (en) | Data mining system and implementation method thereof | |
| Albano et al. | A model with applications for data survivability in critical infrastructures | |
| Ali | Securing solar energy‐harvesting road‐side unit using an embedded cooperative‐hybrid intrusion detection system | |
| CN104144079B (en) | monitoring method and device for communication power supply | |
| CN114095193A (en) | Chip-level photovoltaic power station information security defense system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |