CN116089086A - Rail transit energy saving method, device, equipment and storage medium - Google Patents
Rail transit energy saving method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN116089086A CN116089086A CN202310084061.XA CN202310084061A CN116089086A CN 116089086 A CN116089086 A CN 116089086A CN 202310084061 A CN202310084061 A CN 202310084061A CN 116089086 A CN116089086 A CN 116089086A
- Authority
- CN
- China
- Prior art keywords
- data
- equipment
- energy
- saving
- rail transit
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5072—Grid computing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Computing Systems (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The embodiment of the invention discloses a rail transit energy-saving method, a device, equipment and a storage medium. In addition, the embodiment of the invention calculates the equipment data in real time by using the streaming calculation and persists the result into the database, thereby fully playing the calculation capability of the edge node and further improving the calculation efficiency. The embodiment of the invention can improve the calculation efficiency of the energy-saving system and solve the technical problem of low calculation efficiency of the energy-saving system in the prior art.
Description
Technical Field
The embodiment of the application relates to the field of rail transit, in particular to a rail transit energy-saving method, a device, equipment and a storage medium.
Background
At present, the rapid development of the rail transit technology greatly facilitates the life of people. However, along with the continuous expansion of the track traffic lines, the power consumption of the track traffic system is increasingly increased, and how to reduce the power consumption of the track traffic system becomes the focus of current research. In the prior art, an energy-saving system is generally arranged in a rail transit system to reduce the power consumption of the rail transit system, however, the existing energy-saving system is generally arranged in a centralized mode, the data transmission efficiency is low, and the energy-saving efficiency of the energy-saving system is low.
In summary, how to improve the energy saving efficiency of the energy saving system is a technical problem to be solved.
Disclosure of Invention
The embodiment of the invention provides a rail transit energy-saving method, a device, equipment and a storage medium, which solve the technical problem of low calculation efficiency of an energy-saving system in the prior art.
In a first aspect, an embodiment of the present invention provides a rail traffic energy saving method, which is applicable to an edge node arranged in a rail traffic system, and includes the following steps:
accessing to the track traffic equipment of the target station, receiving equipment data uploaded by the track traffic equipment, and simultaneously acquiring passenger flow data of the target station and environment data of the target station;
carrying out stream calculation on the equipment data, determining the power consumption data of each track traffic equipment within a preset time length, and storing the equipment data, the passenger flow data, the environment data and the power consumption data into a database;
inputting equipment data, passenger flow data, environment data and power consumption data in a database into an energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data, and an energy-saving control measure of a target station is obtained;
and controlling the track traffic equipment in the target station according to the energy-saving control measure.
In a second aspect, an embodiment of the present invention provides a rail transit energy saving device, which is applicable to an edge node arranged in a rail transit system, and includes:
the data acquisition module is used for receiving equipment data uploaded by the track traffic equipment after being accessed to the track traffic equipment of the target station, and simultaneously acquiring passenger flow data of the target station and environment data of the target station;
the flow calculation module is used for carrying out flow calculation on the equipment data, determining the power consumption data of each track traffic equipment within a preset time length, and storing the equipment data, the passenger flow data, the environment data and the power consumption data into the database;
the energy-saving control system comprises a power consumption control module, a target station and a power consumption control module, wherein the power consumption control module is used for inputting equipment data, passenger flow data, environment data and power consumption data in a database into an energy-saving application so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data to obtain energy-saving control measures of the target station;
and the equipment control module is used for controlling the track traffic equipment in the target station according to the energy-saving control measure.
In a third aspect, an embodiment of the present invention provides a rail transit energy-saving apparatus, including a processor and a memory;
the memory is used for storing the computer program and transmitting the computer program to the processor;
the processor is configured to execute a rail transit energy saving method according to the first aspect according to instructions in the computer program.
In a fourth aspect, embodiments of the present invention provide a storage medium storing computer executable instructions which, when executed by a computer processor, are adapted to carry out a rail transit energy saving method as described in the first aspect.
In the foregoing, the embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for energy saving of rail transit, where after a rail transit device is connected to an edge node, stream computation is performed on device data reported by the rail transit device, so as to determine power consumption data of the rail transit device. And then inputting the equipment data, the passenger flow data, the environment data and the power consumption data into the energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data to obtain an energy-saving control measure of the target station, and finally controlling the rail transit equipment in the target station according to the energy-saving control measure, thereby reducing the power consumption of the target station. According to the embodiment of the invention, the edge nodes are arranged in the track traffic system, and the edge nodes can be connected with the track traffic equipment of the target site, so that the distance between the application and the equipment is reduced, the condition of data loss caused by network problems is reduced, and meanwhile, the data transmission speed is improved. In addition, the embodiment of the invention calculates the equipment data in real time by using the streaming calculation and persists the result into the database, thereby fully playing the calculation capability of the edge node and further improving the calculation efficiency. The embodiment of the invention can improve the calculation efficiency of the energy-saving system and solve the technical problem of low calculation efficiency of the energy-saving system in the prior art.
Drawings
Fig. 1 is a schematic flow chart of a rail transit energy-saving method according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a rail transit energy-saving system according to an embodiment of the present invention.
Fig. 3 is a working schematic diagram of a rail transit energy-saving system provided by an embodiment of the invention.
Fig. 4 is a schematic structural diagram of another rail transit energy-saving system according to an embodiment of the present invention.
Fig. 5 is a working schematic diagram of another rail transit energy-saving system according to an embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a rail transit energy-saving device according to an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a rail transit energy-saving device according to an embodiment of the present invention.
Detailed Description
The following description and the drawings illustrate specific embodiments of the application sufficiently to enable those skilled in the art to practice them. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in, or substituted for, those of others. The scope of the embodiments of the present application encompasses the full ambit of the claims, as well as all available equivalents of the claims. Embodiments may be referred to herein, individually or collectively, by the term "invention" merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed. Various embodiments are described herein in a progressive manner, each embodiment focusing on differences from other embodiments, and identical and similar parts between the various embodiments are sufficient to be seen with each other. The structures, products and the like disclosed in the embodiments correspond to the parts disclosed in the embodiments, so that the description is relatively simple, and the relevant parts refer to the description of the method parts.
As shown in fig. 1, fig. 1 is a flowchart of a track traffic energy saving method according to an embodiment of the present invention. The rail transit energy-saving method provided by the embodiment of the invention is suitable for the edge nodes arranged in the rail transit system, wherein the edge nodes are service platforms constructed on one side close to objects or data sources, provide storage, calculation, network and other resources, sink part of key service applications to the edge of an access network, provide a nearest application technical means nearby, can reduce the width and time delay loss caused by network transmission and multistage forwarding, generate faster network application response, and meet the requirements of various industries in the aspects of real-time service, application intelligence, security, privacy protection and the like. In this embodiment, each station on the track traffic line is provided with a corresponding edge node, and the method includes the following steps:
and 101, accessing track traffic equipment of a target station, receiving equipment data uploaded by the track traffic equipment, and simultaneously acquiring passenger flow data of the target station and environment data of the target station.
In this embodiment, first, the edge node needs to access the track traffic equipment of the target station, where the track traffic equipment is equipment required by each station on the track traffic line in the operation process, for example, the track traffic equipment includes air conditioning system equipment, water pump system equipment, lighting system equipment, wind power system equipment, and the like. After the rail transit equipment is accessed to the edge node, the self equipment data is reported to the edge node, and the edge node receives the equipment data uploaded by the rail transit equipment. In one embodiment, as shown in fig. 2, the edge node includes an application layer, a data processing layer and a data transmission layer, the edge node uses a device access unit to access the track traffic device of the target station, and after the track traffic device is accessed, the device access unit is reported with device data of the edge node, wherein the device data includes device information of the track traffic device and operation information of the track traffic device. After receiving the device data uploaded by the track traffic device, the device access unit uploads the device data of the track traffic device to the data reporting unit so that the subsequent data reporting unit can report the device data of the track traffic device.
When equipment data reported by rail traffic equipment is received, the edge node needs to acquire passenger flow data of a target station and environment data of the target station at the same time. As shown in fig. 2, the weather application and the passenger flow application are set on the application layer of the edge node, where the weather application is used to obtain environmental data, and the passenger flow application is used to obtain passenger flow data, and the edge node can obtain the environmental data and passenger flow data of the target station through the weather application and the passenger flow application, and the environmental data includes current air temperature data and humidity data of the target station.
After the equipment data are acquired, the edge node further performs streaming calculation on the equipment data, so that the equipment data from different rail transit equipment are analyzed in real time, and the power consumption data of each rail transit equipment in a preset time length are calculated. The device data is processed through the stream computing, so that the response speed of the system can be improved, the network bandwidth cost and the storage cost are saved, the system safety is improved, and the like. In fig. 2, after the data reporting unit reports the device data to the streaming computing unit, the streaming computing unit may calculate the power consumption data of the rail transit device corresponding to the device data within a preset time period, where the preset time period may be set according to actual needs, for example, the preset time period may be set to 20 minutes or 30 minutes, and in this embodiment, the preset time period is not specifically limited.
After calculating the power consumption data of each rail transit device, the edge node further stores the device data, the passenger flow data, the environment data and the power consumption data into a database for persistence. For example, in fig. 2, the data reporting unit sends the device data, the passenger flow data and the environment data to the data collecting unit, and the flow calculating unit sends the power consumption data to the data collecting unit after calculating the power consumption data, and the data collecting unit sends the device data, the passenger flow data, the environment data and the power consumption data to the data distributed persistence unit for storage.
And step 103, inputting the equipment data, the passenger flow data, the environment data and the power consumption data in the database into the energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data, and an energy-saving control measure of the target station is obtained.
And then, the edge node starts an energy-saving application, and inputs equipment data, passenger flow data, environment data and power consumption data in a database into the energy-saving application, wherein the energy-saving application can call a pre-trained energy-saving algorithm model to comprehensively analyze the equipment data, the passenger flow data, the environment data and the power consumption data to obtain energy-saving control measures of the target station, and the energy-saving control measures comprise energy-saving control means corresponding to different rail transit equipment in the target station so as to reduce the overall power consumption of the target station. For example, in the early peak period of the target station, when the energy-saving algorithm model determines that the current passenger flow volume in the target station is relatively large, the energy-saving algorithm model can adjust the number of starting air conditioners and the temperature of the air conditioners according to the air temperature data and the humidity data in the environment data, so that energy-saving control measures of the target station are generated.
And 104, controlling the track traffic equipment in the target station according to the energy-saving control measure.
After the energy-saving control measures of the target station are obtained, the edge node can carry out linkage control on the track traffic equipment in the target station according to the energy-saving control measures, so that the power consumption of the target station is reduced. As shown in fig. 2, the energy-saving algorithm model sends the energy-saving control measure to the device control unit, and the device control unit generates a control instruction of the rail transit device according to the energy-saving control measure and sends the control instruction to the control sending unit, and the control sending unit further sends the control instruction to the rail transit device to realize control of the rail transit device, and the specific process is shown in fig. 3.
In the above, the embodiment of the invention provides a track traffic energy-saving method, after the track traffic equipment is connected to the edge node, the equipment data reported by the track traffic equipment is subjected to stream calculation, and the power consumption data of the track traffic equipment is determined. And then inputting the equipment data, the passenger flow data, the environment data and the power consumption data into the energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data to obtain an energy-saving control measure of the target station, and finally controlling the rail transit equipment in the target station according to the energy-saving control measure, thereby reducing the power consumption of the target station. According to the embodiment of the invention, the edge nodes are arranged in the track traffic system, and the edge nodes can be connected with the track traffic equipment of the target site, so that the distance between the application and the equipment is reduced, the condition of data loss caused by network problems is reduced, and meanwhile, the data transmission speed is improved. In addition, the embodiment of the invention calculates the equipment data in real time by using the streaming calculation and persists the result into the database, thereby fully playing the calculation capability of the edge node and further improving the calculation efficiency. The embodiment of the invention can improve the calculation efficiency of the energy-saving system and solve the technical problem of low calculation efficiency of the energy-saving system in the prior art.
On the basis of the embodiment, the energy-saving application also calculates an energy-saving result according to the energy-saving control measure and visualizes the device data, the power consumption data and the energy-saving result.
In one embodiment, after the energy saving algorithm model obtains the energy saving control measure, the energy saving method can further calculate the power consumption value which can be saved by the target station after the track traffic equipment is controlled according to the energy saving control measure, so as to obtain an energy saving result. For example, the energy-saving control measures comprise the number of air conditioners required to be closed and the power required to be regulated by the light, the energy-saving application calculates the difference value of the power consumption of the target station relative to the power consumption before regulation according to the number of closed air conditioners and the power regulated by the light, so that an energy-saving result is obtained, and then the energy-saving application can further visually display the equipment data, the power consumption data and the energy-saving result, so that a user can know the running condition and the energy-saving condition of the rail transit equipment.
On the basis of the above embodiment, the method further comprises:
and determining the running state of the rail transit equipment according to the equipment data, generating alarm information when the running state is abnormal, and sending the alarm information to the energy-saving application for visualization.
In one embodiment, after receiving the device data reported by the rail transit devices, the edge node further determines an operation state of each rail transit device according to the device data, generates alarm information when the operation state of the rail transit device is abnormal, and sends the alarm information to the energy-saving application for visualization, so that a user can timely learn and process the abnormal rail transit device. As shown in fig. 2, the edge node further includes an equipment alarm application, the data reporting unit sends the equipment data to the equipment alarm application, and after receiving the equipment data, the equipment alarm application compares the received equipment data of each rail transit equipment with the rated equipment data of each rail transit equipment stored in advance, for example, compares the current data and the voltage data of the rail transit equipment with the rated current data and the rated voltage data respectively, so as to determine whether the rail transit equipment is abnormal. If yes, generating alarm information and sending the alarm information to the energy-saving application for visualization.
On the basis of the above embodiment, the method further comprises:
uploading the equipment data to the cloud so that the cloud updates the equipment digital model corresponding to the rail transit equipment according to the equipment data, wherein the equipment digital model is built in the cloud in advance, and each rail transit equipment corresponds to one equipment digital model.
In one embodiment, a device digital model corresponding to each accessed rail traffic device is also created on the cloud end, and the cloud end defines the device digital model through three dimensions of device attributes, services and events. The device attributes are information and states describing the operation of the rail transit device, such as the operation temperature and the operation state of the air conditioner. The service is used for receiving parameters for controlling the input and output of the rail transit equipment, for example, when the brightness of the lamplight needs to be adjusted, the lamplight is adjusted by sending an instruction for adjusting the brightness of the lamplight to the input parameters of the equipment digital model corresponding to the lamplight. The event is information actively reported to the cloud when the rail transit equipment operates. Including, for example, device data, alarm information, fault information, etc.
And after receiving the device data reported by the rail transit device, the edge node further sends the device data to the cloud end, so that the cloud end updates a device data model corresponding to the rail transit device according to the device data. For example, after the data acquisition unit in fig. 3 acquires the device data, the device data may be further sent to the cloud, so that the cloud updates the device data model. In addition, when the data reporting unit reports the device data, the device data needs to be converted into a format corresponding to the digital device model and then reported to the data acquisition unit. For example, when the data reporting unit reports the device data, the reporting process adopts the message subscription and release modes of the MQTT to conduct data interaction. For the Topic of the MQTT, a unified definition generation mode exists, and after the device data model is defined in the process, the Topic with the unified format is generated as follows:
obtaining device data Topic: znjn/$ { deviceKey }/$ { deviceName }/device/get
Wherein, $ { deviceKey } and $ { deviceName } correspond to the unique device id and device name in the created device digital model, respectively, and the message content is the content defined for the device in the device digital model. The data acquisition unit can acquire the device data in the data reporting unit from the MQTT and persist the device data into the database.
On the basis of the above embodiment, before accessing the track traffic device of the target station, the method further includes:
step 1001, extracting training set data of the energy-saving algorithm model from a database, and sending the training set data to a cloud end so that the cloud end trains the energy-saving algorithm model according to the training set data to obtain a trained energy-saving algorithm model.
In one embodiment, the edge node further needs to extract training set data of the energy-saving algorithm model from the database before accessing the rail transit device of the target station, where the training set data user may be stored in the database in advance, or the edge node extracts the training set data from the data stored in the database history. As shown in fig. 4, the edge node further includes an edge data extraction application, where after the edge data extraction application extracts the training set data from the data distributed persistence unit, the training set data is further sent to the cloud, and the algorithm model training unit in the cloud trains the energy-saving algorithm model according to the training set data to obtain a trained energy-saving algorithm model. In another embodiment, during the operation of the subsequent edge node, the edge data extraction application may further extract data from the data distributed persistence unit, after the data is formatted by the data formatting unit, the formatted data is stored in the cloud end at regular time by the cloud edge message application, and the data analysis unit in the cloud end performs big data analysis on the data, or the edge data extraction application may send the data to a pre-designated destination, for example, a designated database or message middleware. Meanwhile, the data distributed persistence unit of the edge node can clear the data which is synchronized to the cloud, so that the edge node is guaranteed to have enough storage space, and meanwhile, the application can be guaranteed to run with the best performance.
Step 1002, receiving a trained energy-saving algorithm model issued by a cloud.
After the cloud end completes the training of the energy-saving algorithm model, the trained energy-saving algorithm model is issued to the edge node, so that the edge node can generate energy-saving control measures according to the energy-saving algorithm model later, as shown in fig. 5.
On the basis of the above embodiment, the method further comprises:
and receiving modification information of the digital model of the target equipment issued by the cloud, and controlling the track traffic equipment corresponding to the digital model of the target equipment according to the modification information.
In one embodiment, as shown in fig. 4, the cloud end further includes an equipment management unit, and the equipment management unit can also control the accessed rail transit equipment. Specifically, the device management unit may input a control instruction into the corresponding digital model of the target device according to the content of controlling the rail transit device as required, and modify the running state of the digital model of the target device to obtain modification information of the digital model of the target device. And then the device management unit issues the modification information to the device control unit of the edge node, so that the device control unit of the edge node controls the rail transit device corresponding to the digital model of the target device according to the modification information, as shown in fig. 5. Specifically, after the device control unit obtains modification information (Json) of a digital model of the target device from the cloud, the device control unit sends the content and the MQTT to the corresponding device control Topic, and the control issuing unit changes the state of the rail transit device after subscribing the device control Topic to obtain the control content, so as to achieve the purpose of controlling the device, wherein the format of the device control Topic is as follows:
device control Topic: the \znjn/$ { deviceKey }/$ { deviceName }/device/upload.
On the basis of the above embodiment, the method further comprises:
and receiving application management information issued by the cloud, and managing the energy-saving application according to the application management information.
In one embodiment, as shown in fig. 4, the cloud end further includes an application management unit, where the application management unit can manage the energy-saving application in the edge node, and when the cloud end needs to manage and control the energy-saving application, the cloud end can issue application management information to the edge node, where the application management information includes content for controlling and managing the application, so that the edge node manages the energy-saving application according to the application management information. Specifically, the cloud can manage the life cycle of each application in the edge node, including deployment, start, stop, deletion, version update, and the like of the application, in addition, the application management unit can also generate an application arrangement policy, the edge node executes the application according to the application arrangement policy, and the cloud can dynamically adjust resources and the like required by the application operation in a cloud-edge cooperative manner. In addition, in fig. 4, the cloud end is further provided with an application operation and maintenance monitoring unit, which can monitor the running state of the application and maintain the application in the running process of the application.
In the embodiment of the invention, the edge nodes are arranged in the rail transit system and can be connected with the rail transit equipment of the target station, so that the distance between the application and the equipment is reduced, the condition of data loss caused by network problems is reduced, and the data transmission speed is improved. In addition, the embodiment of the invention calculates the equipment data in real time by using the streaming calculation and persists the result into the database, thereby fully playing the calculation capability of the edge node and further improving the calculation efficiency. The embodiment of the invention can improve the calculation efficiency of the energy-saving system and solve the technical problem of low calculation efficiency of the energy-saving system in the prior art.
As shown in fig. 6, fig. 6 is a schematic structural diagram of an energy-saving device for rail transit, provided in an embodiment of the present invention, where the device is suitable for an edge node arranged in a rail transit system, and includes:
the data acquisition module 201 is configured to receive equipment data uploaded by the rail traffic equipment after accessing the rail traffic equipment of the target station, and simultaneously acquire passenger flow data of the target station and environmental data of the target station;
the streaming computing module 202 is configured to perform streaming computing on the device data, determine power consumption data of each rail transit device within a preset time period, and store the device data, the passenger flow data, the environment data and the power consumption data into a database;
the power consumption control module 203 is configured to input device data, passenger flow data, environment data and power consumption data in the database into the energy-saving application, so that the energy-saving application invokes a pre-trained energy-saving algorithm model to analyze the device data, the passenger flow data, the environment data and the power consumption data, and obtain an energy-saving control measure of the target station;
and the equipment control module 204 is used for controlling the track traffic equipment in the target station according to the energy-saving control measure.
On the basis of the embodiment, the energy-saving application also calculates an energy-saving result according to the energy-saving control measure and visualizes the device data, the power consumption data and the energy-saving result.
On the basis of the above embodiment, the method further comprises:
and the alarm module is used for determining the running state of the rail transit equipment according to the equipment data, generating alarm information when the running state is abnormal, and sending the alarm information to the energy-saving application for visualization.
On the basis of the above embodiment, the method further comprises:
the digital model updating module is used for uploading the equipment data to the cloud so that the cloud updates the equipment digital model corresponding to the rail transit equipment according to the equipment data, the equipment digital model is built in the cloud in advance, and each rail transit equipment corresponds to one equipment digital model.
On the basis of the above embodiment, the method further comprises:
the training set acquisition module is used for acquiring training set data of the energy-saving algorithm model, transmitting the training set data into the cloud end so that the cloud end trains the energy-saving algorithm model according to the training set data to obtain a trained energy-saving algorithm model,
the model receiving module is used for receiving the trained energy-saving algorithm model issued by the cloud.
On the basis of the above embodiment, the method further comprises:
the target equipment control module is used for receiving the modification information of the digital model of the target equipment issued by the cloud and controlling the track traffic equipment corresponding to the digital model of the target equipment according to the modification information.
On the basis of the above embodiment, the method further comprises:
and the application management module is used for receiving the application management information issued by the cloud and managing the energy-saving application according to the application management information.
The present embodiment also provides a track traffic energy-saving device, as shown in fig. 7, where the track traffic energy-saving device 30 includes a processor 300 and a memory 301;
the memory 301 is used for storing a computer program 302 and transmitting the computer program 302 to the processor;
the processor 300 is configured to perform the steps of one of the track traffic energy saving method embodiments described above according to instructions in the computer program 302.
Illustratively, the computer program 302 may be partitioned into one or more modules/units that are stored in the memory 301 and executed by the processor 300 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 302 in the rail transit energy saving device 30.
The track traffic energy saving device 30 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud application, etc. The rail transit energy saving device 30 may include, but is not limited to, a processor 300, a memory 301. It will be appreciated by those skilled in the art that fig. 7 is merely an example of the rail transit energy conservation device 30 and is not intended to be limiting of the rail transit energy conservation device 30, and may include more or fewer components than illustrated, or may combine certain components, or different components, e.g., the rail transit energy conservation device 30 may also include input and output devices, network access devices, buses, etc.
The processor 300 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 301 may be an internal storage unit of the track traffic energy saving device 30, for example, a hard disk or a memory of the track traffic energy saving device 30. The memory 301 may also be an external storage device of the track traffic energy saving device 30, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the track traffic energy saving device 30. Further, the memory 301 may also include both an internal storage unit and an external storage device of the track traffic energy saving device 30. The memory 301 is used for storing the computer program and other programs and data required by the rail transit energy saving device 30. The memory 301 may also be used to temporarily store data that has been output or is to be output.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., 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 an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of 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.
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 this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in whole or in part 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, an application, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media in which computer programs can be stored.
The embodiment of the invention also provides a storage medium containing computer executable instructions, which when executed by a computer processor, are used for executing a rail transit energy saving method, the method is applicable to edge nodes arranged in a rail transit system, and comprises the following steps:
accessing to the track traffic equipment of the target station, receiving equipment data uploaded by the track traffic equipment, and simultaneously acquiring passenger flow data of the target station and environment data of the target station;
carrying out stream calculation on the equipment data, determining the power consumption data of each track traffic equipment within a preset time length, and storing the equipment data, the passenger flow data, the environment data and the power consumption data into a database;
inputting equipment data, passenger flow data, environment data and power consumption data in a database into an energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data, and an energy-saving control measure of a target station is obtained;
and controlling the track traffic equipment in the target station according to the energy-saving control measure.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the embodiments of the present invention are not limited to the particular embodiments described herein, but are capable of numerous obvious changes, rearrangements and substitutions without departing from the scope of the embodiments of the present invention. Therefore, while the embodiments of the present invention have been described in connection with the above embodiments, the embodiments of the present invention are not limited to the above embodiments, but may include many other equivalent embodiments without departing from the spirit of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A rail transit energy saving method, characterized in that the method is applicable to edge nodes arranged in a rail transit system, comprising the steps of:
accessing to rail transit equipment of a target station, receiving equipment data uploaded by the rail transit equipment, and simultaneously acquiring passenger flow data of the target station and environment data of the target station;
performing stream calculation on the equipment data, determining the power consumption data of each track traffic equipment within a preset time length, and storing the equipment data, the passenger flow data, the environment data and the power consumption data into a database;
inputting the equipment data, the passenger flow data, the environment data and the power consumption data in the database into an energy-saving application, so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data, and energy-saving control measures of the target station are obtained;
and controlling the track traffic equipment in the target station according to the energy-saving control measure.
2. The rail transit energy saving method of claim 1, wherein the energy saving application further calculates an energy saving result based on the energy saving control measure and visualizes the device data, the power consumption data, and the energy saving result.
3. The rail transit energy saving method of claim 1, further comprising:
and determining the running state of the rail transit equipment according to the equipment data, generating alarm information when the running state is abnormal, and sending the alarm information to the energy-saving application for visualization.
4. The rail transit energy saving method of claim 1, further comprising:
uploading the equipment data to a cloud end, so that the cloud end updates an equipment digital model corresponding to the rail transit equipment according to the equipment data, wherein the equipment digital model is built in the cloud end in advance, and each rail transit equipment corresponds to one equipment digital model.
5. The energy saving method for rail transit of claim 4, further comprising, before said accessing the rail transit device of the target station:
acquiring training set data of the energy-saving algorithm model, transmitting the training set data to the cloud end so that the cloud end trains the energy-saving algorithm model according to the training set data to obtain a trained energy-saving algorithm model,
and receiving the trained energy-saving algorithm model issued by the cloud.
6. The rail transit energy saving method of claim 4, further comprising:
and receiving modification information of the digital model of the target equipment issued by the cloud, and controlling track traffic equipment corresponding to the digital model of the target equipment according to the modification information.
7. The rail transit energy saving method of claim 4, further comprising:
and receiving application management information issued by the cloud, and managing the energy-saving application according to the application management information.
8. A rail transit energy saving device, the device being adapted for an edge node arranged in a rail transit system, comprising:
the data acquisition module is used for receiving equipment data uploaded by the track traffic equipment after being accessed to the track traffic equipment of the target station, and simultaneously acquiring passenger flow data of the target station and environment data of the target station;
the stream computing module is used for carrying out stream computation on the equipment data, determining the power consumption data of each track traffic equipment within a preset time length, and storing the equipment data, the passenger flow data, the environment data and the power consumption data into a database;
the power consumption control module is used for inputting the equipment data, the passenger flow data, the environment data and the power consumption data in the database into an energy-saving application so that the energy-saving application calls a pre-trained energy-saving algorithm model to analyze the equipment data, the passenger flow data, the environment data and the power consumption data to obtain energy-saving control measures of the target station;
and the equipment control module is used for controlling the track traffic equipment in the target station according to the energy-saving control measure.
9. A rail transit energy saving device, characterized in that the rail transit energy saving device comprises a processor and a memory;
the memory is used for storing a computer program and transmitting the computer program to the processor;
the processor is configured to execute a rail transit energy saving method according to any one of claims 1-7 according to instructions in the computer program.
10. A storage medium storing computer executable instructions which, when executed by a computer processor, are for performing a rail transit energy saving method as claimed in any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310084061.XA CN116089086A (en) | 2023-01-13 | 2023-01-13 | Rail transit energy saving method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310084061.XA CN116089086A (en) | 2023-01-13 | 2023-01-13 | Rail transit energy saving method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116089086A true CN116089086A (en) | 2023-05-09 |
Family
ID=86206157
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310084061.XA Pending CN116089086A (en) | 2023-01-13 | 2023-01-13 | Rail transit energy saving method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116089086A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116700071A (en) * | 2023-05-18 | 2023-09-05 | 长沙穗城轨道交通有限公司 | Intelligent energy-saving control platform, method, electronic equipment and storage medium |
-
2023
- 2023-01-13 CN CN202310084061.XA patent/CN116089086A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116700071A (en) * | 2023-05-18 | 2023-09-05 | 长沙穗城轨道交通有限公司 | Intelligent energy-saving control platform, method, electronic equipment and storage medium |
| CN116700071B (en) * | 2023-05-18 | 2024-04-26 | 长沙穗城轨道交通有限公司 | Intelligent energy-saving control platform, method, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11513480B2 (en) | Method and device for automatically diagnosing and controlling apparatus in intelligent building | |
| CN105352542B (en) | A kind of current conversion station panorama condition monitoring system | |
| US10101244B2 (en) | Self-learning simulation environments | |
| CN113176948B (en) | Edge gateway, edge computing system and configuration method thereof | |
| CN109657003A (en) | A method of hardware data is directly accessed big data platform | |
| CN113179190B (en) | Edge controller, edge computing system and configuration method thereof | |
| CN106027328A (en) | Cluster monitoring method and system based on application container deployment | |
| CN109618301B (en) | Data processing method of wireless sensor network, readable storage medium and terminal | |
| CN103593274B (en) | A kind of method reaching to save power consumption according to computer cluster resource service condition dynamic switch machine | |
| CN116089086A (en) | Rail transit energy saving method, device, equipment and storage medium | |
| CN117240887B (en) | Wisdom thing networking energy management platform system | |
| WO2017008421A1 (en) | Method and device for controlling operational state of data center | |
| CN112907911A (en) | Intelligent anomaly identification and alarm algorithm based on equipment process data | |
| Weng et al. | AdaStorm: Resource efficient storm with adaptive configuration | |
| WO2023050930A1 (en) | Auxiliary control method and system for wind turbine generator set, and wind turbine generator set | |
| CN117221069A (en) | Management method and device based on micro-server architecture | |
| US20200133252A1 (en) | Systems and methods for monitoring performance of a building management system via log streams | |
| CN110647070A (en) | Power environment monitoring system for super-large-scale data center | |
| CN107783888A (en) | The method and device that a kind of server admin based on IPMI with data prediction function is realized | |
| US20200074213A1 (en) | Gpb algorithm based operation and maintenance multi-modal decision system prototype | |
| CN111416870B (en) | Industrial Internet of things system | |
| CN112654077B (en) | Energy-saving method and device, and computer storage medium | |
| CN112131069B (en) | Equipment operation monitoring method and system based on clustering | |
| Shuai et al. | Memtv: a research on multi-level edge computing model for traffic video processing | |
| CN110781125A (en) | Management method and system for complete cabinet super-fusion server |
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 |