CN116316983A - Network point power monitoring method and device - Google Patents

Network point power monitoring method and device Download PDF

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Publication number
CN116316983A
CN116316983A CN202310278282.0A CN202310278282A CN116316983A CN 116316983 A CN116316983 A CN 116316983A CN 202310278282 A CN202310278282 A CN 202310278282A CN 116316983 A CN116316983 A CN 116316983A
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China
Prior art keywords
battery
business
point
current
grid point
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CN202310278282.0A
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Chinese (zh)
Inventor
王飞
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Industrial and Commercial Bank of China Ltd ICBC
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Industrial and Commercial Bank of China Ltd ICBC
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Priority to CN202310278282.0A priority Critical patent/CN116316983A/en
Publication of CN116316983A publication Critical patent/CN116316983A/en
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0029—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with safety or protection devices or circuits
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J9/00—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting
    • H02J9/04—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source
    • H02J9/06—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over, e.g. UPS systems

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the application provides a website power monitoring method and device, which can be used in the financial field, and the method comprises the following steps: the method comprises the steps that a sensor is additionally arranged at a battery end of a business website to collect real-time state information of the battery, and business processing information of the current business website is collected through a management system of the business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; obtaining predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition; the method and the device can early warn the abnormal situation of the battery at the business network in advance.

Description

Network point power monitoring method and device
Technical Field
The application relates to the field of power management and also can be used in the field of finance, in particular to a network point power monitoring method and device.
Background
Robot process automation (Robotic process automation, RPA for short) is a software technology that can easily create, deploy and manage software robots, simulate human behavior, interact with digital systems and software, and automatically execute process tasks according to rules. The software robot can work like a human, automate regular operations based on rules, and complete work with high repeatability and fixed business logic, such as automatic repeated mail reading work, mass file and report generation work, file checking work and the like.
In the prior art, the monitoring of the batteries at the business network points is not advanced enough, the normal operation of the business network points is influenced when the batteries are abnormal, and the operation stability of the business network points cannot be ensured without corresponding treatment measures for the abnormal batteries.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a grid point power monitoring method and device, which can early warn the abnormal situation of a business grid point battery in advance.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a method for monitoring grid power, including:
the method comprises the steps that a sensor is additionally arranged at a battery end of a business website to collect real-time state information of the battery, and business processing information of the current business website is collected through a management system of the business website;
determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point;
and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
Further, the method for collecting the real-time state information of the battery by additionally arranging a sensor at the battery end of the business website comprises the following steps:
the real-time load information and the real-time voltage information of the battery are collected by additionally arranging a sensor at the UPS battery host end of a business website.
Further, the service processing information of the current business website includes: at least one of current network point equipment operation quantity, current network point equipment operation ratio and current network point waiting traffic quantity.
Further, the determining the network point business handling prediction data and the network point equipment operation prediction data according to the business processing information of the current business network point includes:
determining the operation prediction data of the network point equipment according to the current network point equipment operation quantity, the current network point equipment operation duty ratio and the current network point to-be-processed traffic quantity;
and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
Further, the performing the power early warning operation according to the predicted data of the current grid point battery condition includes:
triggering abnormal battery early warning through an RPA technology when the predicted data of the current network point battery condition exceeds a threshold value;
and analyzing the change rate of the acquired data in a set period, and determining the problem point causing the battery abnormality.
Further, the determining a problem point causing abnormality of the battery includes:
if the determined problem point belongs to the battery, starting the standby battery to access the power system through the RPA technology, and judging whether the standby battery is still abnormal or not again, wherein a plurality of groups or a plurality of types of standby batteries can be arranged, and determining which group or which type of standby battery is started according to the difference value of the prediction data and the threshold value;
if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager through an RPA technology, and a corresponding device regulation strategy is determined according to the difference value between the battery condition prediction data and the threshold value and the network point device condition.
In a second aspect, the present application provides a grid point power monitoring apparatus, comprising:
the information acquisition module is used for acquiring real-time state information of the battery by additionally arranging a sensor at the battery end of the business website and acquiring service processing information of the current business website by a management system of the business website;
the data analysis module is used for determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point;
and the power early warning module is used for obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business transaction predicted data and the data change trend of the grid point equipment running predicted data, and executing power early warning operation according to the predicted data of the current grid point battery condition.
Further, the data analysis module includes:
the network point equipment operation prediction data determining unit is used for determining network point equipment operation prediction data according to the current network point equipment operation quantity, the current network point equipment operation duty ratio and the current network point to-be-processed traffic;
the network site business handling prediction data determining unit is used for determining network site business handling prediction data according to the current network site waiting business volume and the current network site contemporaneous historical business handling total volume.
Further, the power early warning module includes:
the RPA automatic early warning unit is used for triggering abnormal battery early warning through an RPA technology when the predicted data of the current network point battery condition exceeds a threshold value;
and the abnormality analysis unit is used for analyzing the change rate of the acquired data in a set period and determining a problem point causing battery abnormality.
Further, the abnormality analysis unit includes:
the battery abnormality processing subunit is used for starting the standby battery to access the power system through the RPA technology if the determined problem point belongs to the battery, and re-judging whether the standby battery is still abnormal, wherein a plurality of groups or a plurality of types of standby batteries can be arranged, and which group or which type of standby battery is started is determined according to the difference value between the predicted data and the threshold value;
and the business abnormality processing subunit is used for sending an early warning to a website manager through an RPA technology if the determined problem point belongs to the website to-do business, and determining a corresponding equipment regulation strategy according to the difference value between the battery condition prediction data and the threshold value and the website equipment condition.
In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the grid point power monitoring method when executing the program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the grid point power monitoring method.
In a fifth aspect, the present application provides a computer program product comprising computer programs/instructions which when executed by a processor implement the steps of the grid point power monitoring method.
According to the technical scheme, the application provides a network point power monitoring method and device, a sensor is additionally arranged at a battery end of a business network point to collect real-time state information of a battery, and a management system of the business network point is used for collecting service processing information of the current business network point; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for monitoring grid power in an embodiment of the present application;
FIG. 2 is a second flow chart of a method for monitoring grid power according to an embodiment of the present disclosure;
FIG. 3 is a third flow chart of a method for monitoring grid power according to an embodiment of the present disclosure;
FIG. 4 is a flowchart of a method for monitoring grid power according to an embodiment of the present disclosure;
FIG. 5 is one of the block diagrams of the grid point power monitoring device in the embodiment of the present application;
FIG. 6 is a second block diagram of a grid point power monitoring device in an embodiment of the present application;
FIG. 7 is a third block diagram of a grid point power monitoring device in an embodiment of the present application;
FIG. 8 is a fourth block diagram of a grid point power monitoring device in an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The data acquisition, storage, use, processing and the like in the technical scheme meet the relevant regulations of national laws and regulations.
In consideration of the problems existing in the prior art, the application provides a website power monitoring method and device, wherein a sensor is additionally arranged at a battery end of a business website to collect real-time state information of a battery, and a management system of the business website is used for collecting business processing information of the current business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
In order to early warn of abnormal business grid-point batteries, the application provides an embodiment of a grid-point power monitoring method, referring to fig. 1, wherein the grid-point power monitoring method specifically comprises the following steps:
step S101: the real-time state information of the battery is acquired by additionally arranging a sensor at the battery end of the business website, and the service processing information of the current business website is acquired by a management system of the business website.
Optionally, in the present application, the source of information collected by the sensor is a UPS host, and besides the battery, a node is a UPS host, so that key information such as real-time load and voltage can be collected from the operating parameters of the UPS host.
Optionally, in this application, the service processing information includes: current mesh point device operation amount, current mesh point device operation ratio, current mesh point pending (numbered) traffic.
Step S102: and determining the battery running condition according to the battery real-time state information and the battery original physical value, and determining network point service handling prediction data and network point equipment running prediction data according to the service processing information of the current business network point.
Alternatively, in the present application, battery operating conditions, such as battery load level, battery used duty cycle.
Optionally, in the present application, the operation prediction data of the mesh point device may be determined according to the current mesh point device operation amount, the current mesh point device operation ratio, and the current mesh point to-be-processed traffic; and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
Step S103: and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
It will be appreciated that the battery is typically in a charged state, and there is a discharge of electrical energy in the event of a mains outage. The method and the device can obtain the predicted data of the current network point battery condition based on the change trend of the predicted data according to the battery operation condition, network point business handling predicted data and network point equipment operation predicted data.
When the predicted data of the network point battery condition exceeds a threshold value, triggering battery abnormality early warning through an RPA technology, analyzing the change rate of each item of collected data in a period, and determining a problem point causing battery abnormality.
As can be seen from the above description, the method for monitoring the grid point power according to the embodiments of the present application can collect real-time status information of the battery by adding a sensor at the battery end of the business grid point, and collect service processing information of the current business grid point through the management system of the business grid point; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
In an embodiment of the method for monitoring grid power of the present application, the collecting real-time status information of the battery by adding a sensor at a battery end of a business grid includes:
the real-time load information and the real-time voltage information of the battery are collected by additionally arranging a sensor at the UPS battery host end of a business website.
In an embodiment of the method for monitoring grid power of the present application, the service processing information of the current business grid includes: at least one of current network point equipment operation quantity, current network point equipment operation ratio and current network point waiting traffic quantity.
In an embodiment of the method for monitoring grid power of the present application, referring to fig. 2, the step S102 may further specifically include the following:
step S201: and determining the running prediction data of the network point equipment according to the running amount of the current network point equipment, the running duty ratio of the current network point equipment and the traffic volume to be processed of the current network point.
Step S202: and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
Alternatively, in the present application, battery operating conditions, such as battery load level, battery used duty cycle.
Optionally, in the present application, the operation prediction data of the mesh point device may be determined according to the current mesh point device operation amount, the current mesh point device operation ratio, and the current mesh point to-be-processed traffic; and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
In an embodiment of the method for monitoring grid power of the present application, referring to fig. 3, the step S103 may further specifically include the following:
step S301: when the predicted data of the current network point battery condition exceeds a threshold value, triggering battery abnormality early warning through an RPA technology.
Step S302: and analyzing the change rate of the acquired data in a set period, and determining the problem point causing the battery abnormality.
In an embodiment of the method for monitoring grid power of the present application, referring to fig. 4, the step S302 may further specifically include the following:
step S401: if the determined problem point belongs to the battery, starting the standby battery to access the power system through the RPA technology, and judging whether the standby battery is still abnormal or not again, wherein a plurality of groups or a plurality of types of standby batteries can be arranged, and determining which group or which type of standby battery is started according to the difference value of the prediction data and the threshold value.
Step S402: if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager through an RPA technology, and a corresponding device regulation strategy is determined according to the difference value between the battery condition prediction data and the threshold value and the network point device condition.
In order to early warn about abnormal business grid point batteries, the application provides an embodiment of a grid point power monitoring device for implementing all or part of the grid point power monitoring method, referring to fig. 5, the grid point power monitoring device specifically includes the following contents:
the information acquisition module 10 is used for acquiring real-time state information of the battery by additionally arranging a sensor at the battery end of the business website and acquiring service processing information of the current business website by a management system of the business website.
The data analysis module 20 is configured to determine a battery running condition according to the battery real-time status information and the battery original physical value, and determine site service transaction prediction data and site equipment running prediction data according to the service processing information of the current business site.
And the power early warning module 30 is configured to obtain predicted data of a current grid point battery condition according to the battery running condition, the grid point business transaction predicted data and a data change trend of the grid point equipment running predicted data, and execute power early warning operation according to the predicted data of the current grid point battery condition.
As can be seen from the above description, the website power monitoring device provided in the embodiment of the present application can collect real-time status information of a battery by adding a sensor at a battery end of a business website, and collect service processing information of the current business website through a management system of the business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
In an embodiment of the grid power monitoring apparatus of the present application, referring to fig. 6, the data analysis module 20 includes:
the mesh point device operation prediction data determining unit 21 is configured to determine mesh point device operation prediction data according to the current mesh point device operation amount, the current mesh point device operation ratio, and the current mesh point pending traffic.
The website service transaction prediction data determining unit 22 is configured to determine website service transaction prediction data according to the current website pending traffic volume and the current website contemporaneous historical service transaction total volume.
In an embodiment of the grid point power monitoring apparatus of the present application, referring to fig. 7, the power early warning module 30 includes:
and the RPA automatic early warning unit 31 is used for triggering abnormal battery early warning through an RPA technology when the predicted data of the current network point battery condition exceeds a threshold value.
An abnormality analysis unit 32 for analyzing the rate of change of the collected data in a set period and determining a problem point that causes abnormality of the battery.
In an embodiment of the grid power monitoring apparatus of the present application, referring to fig. 8, the anomaly analysis unit 32 includes:
and the battery abnormality processing subunit 321 is configured to start the backup battery to access the power system through the RPA technology if the determined problem point belongs to the battery itself, and re-determine whether the backup battery is still abnormal, where multiple groups or multiple types of backup batteries can be set, and determine which group or which type of backup battery is started according to the difference value between the prediction data and the threshold value.
And the business anomaly processing subunit 322 is configured to send an early warning to the website administrator end through the RPA technology if the determined problem point belongs to the website to-do business, and determine a corresponding device regulation policy according to the difference value between the battery condition prediction data and the threshold value and the website device condition.
In order to early warn of abnormal batteries of business network points in advance from a hardware aspect, the application provides an embodiment of an electronic device for implementing all or part of contents in the network point power monitoring method, wherein the electronic device specifically comprises the following contents:
a processor (processor), a memory (memory), a communication interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete communication with each other through the bus; the communication interface is used for realizing information transmission between the network point power monitoring device and related equipment such as a core service system, a user terminal, a related database and the like; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, etc., and the embodiment is not limited thereto. In this embodiment, the logic controller may refer to an embodiment of the method for monitoring grid power in the embodiment and an embodiment of the device for monitoring grid power, and the contents thereof are incorporated herein, and the repetition is omitted.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Wherein, intelligent wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical applications, part of the method for monitoring the grid power may be performed on the electronic device side as described above, or all operations may be performed in the client device. Specifically, the selection may be made according to the processing capability of the client device, and restrictions of the use scenario of the user. The present application is not limited in this regard. If all operations are performed in the client device, the client device may further include a processor.
The client device may have a communication module (i.e. a communication unit) and may be connected to a remote server in a communication manner, so as to implement data transmission with the server. The server may include a server on the side of the task scheduling center, and in other implementations may include a server of an intermediate platform, such as a server of a third party server platform having a communication link with the task scheduling center server. The server may include a single computer device, a server cluster formed by a plurality of servers, or a server structure of a distributed device.
Fig. 9 is a schematic block diagram of a system configuration of an electronic device 9600 of an embodiment of the present application. As shown in fig. 9, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 9 is exemplary; other types of structures may also be used in addition to or in place of the structures to implement telecommunications functions or other functions.
In one embodiment, the grid point power monitoring method functionality may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:
step S101: the real-time state information of the battery is acquired by additionally arranging a sensor at the battery end of the business website, and the service processing information of the current business website is acquired by a management system of the business website.
Step S102: and determining the battery running condition according to the battery real-time state information and the battery original physical value, and determining network point service handling prediction data and network point equipment running prediction data according to the service processing information of the current business network point.
Step S103: and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
As can be seen from the above description, in the electronic device provided in the embodiment of the present application, a sensor is added at a battery end of a business website to collect real-time status information of a battery, and a management system of the business website collects service processing information of a current business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
In another embodiment, the grid power monitoring device may be configured separately from the cpu 9100, for example, the grid power monitoring device may be configured as a chip connected to the cpu 9100, and the grid power monitoring method function is implemented by control of the cpu.
As shown in fig. 9, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 need not include all of the components shown in fig. 9; in addition, the electronic device 9600 may further include components not shown in fig. 9, and reference may be made to the related art.
As shown in fig. 9, the central processor 9100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 9100 receives inputs and controls the operation of the various components of the electronic device 9600.
The memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 9100 can execute the program stored in the memory 9140 to realize information storage or processing, and the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.
The memory 9140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, etc. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 storing application programs and function programs or a flow for executing operations of the electronic device 9600 by the central processor 9100.
The memory 9140 may also include a data store 9143, the data store 9143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. A communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, as in the case of conventional mobile communication terminals.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and to receive audio input from the microphone 9132 to implement usual telecommunications functions. The audio processor 9130 can include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100 so that sound can be recorded locally through the microphone 9132 and sound stored locally can be played through the speaker 9131.
The embodiments of the present application further provide a computer readable storage medium capable of implementing all the steps in the method for monitoring grid point power in which the execution subject is a server or a client in the above embodiments, where the computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps in the method for monitoring grid point power in which the execution subject is a server or a client in the above embodiments, for example, the processor implements the following steps when executing the computer program:
step S101: the real-time state information of the battery is acquired by additionally arranging a sensor at the battery end of the business website, and the service processing information of the current business website is acquired by a management system of the business website.
Step S102: and determining the battery running condition according to the battery real-time state information and the battery original physical value, and determining network point service handling prediction data and network point equipment running prediction data according to the service processing information of the current business network point.
Step S103: and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
As can be seen from the above description, the computer readable storage medium provided in the embodiments of the present application collects real-time status information of a battery by adding a sensor at a battery end of a business website, and collects service processing information of a current business website through a management system of the business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
The embodiments of the present application further provide a computer program product capable of implementing all the steps in the method for monitoring grid point power in which the execution subject is a server or a client in the above embodiments, where the computer program/instructions implement the steps of the method for monitoring grid point power when executed by a processor, for example, the computer program/instructions implement the steps of:
step S101: the real-time state information of the battery is acquired by additionally arranging a sensor at the battery end of the business website, and the service processing information of the current business website is acquired by a management system of the business website.
Step S102: and determining the battery running condition according to the battery real-time state information and the battery original physical value, and determining network point service handling prediction data and network point equipment running prediction data according to the service processing information of the current business network point.
Step S103: and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
As can be seen from the above description, the computer program product provided in the embodiments of the present application collects real-time status information of the battery by adding a sensor at the battery end of the business website, and collects service processing information of the current business website by the management system of the business website; determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point; and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition, so that abnormal business grid point batteries can be early warned.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.

Claims (13)

1. A method for monitoring power at a grid site, the method comprising:
the method comprises the steps that a sensor is additionally arranged at a battery end of a business website to collect real-time state information of the battery, and business processing information of the current business website is collected through a management system of the business website;
determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point;
and obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business handling predicted data and the data change trend of the grid point equipment running predicted data, and executing electric power early warning operation according to the predicted data of the current grid point battery condition.
2. The method for monitoring power at a network site according to claim 1, wherein the step of adding a sensor at a battery end of a network site to collect real-time status information of the battery comprises:
the real-time load information and the real-time voltage information of the battery are collected by additionally arranging a sensor at the UPS battery host end of a business website.
3. The grid point power monitoring method according to claim 1, wherein the service processing information of the current business grid point includes: at least one of current network point equipment operation quantity, current network point equipment operation ratio and current network point waiting traffic quantity.
4. The method for monitoring grid point power according to claim 1, wherein determining grid point business transaction prediction data and grid point device operation prediction data according to the business processing information of the current business grid point comprises:
determining the operation prediction data of the network point equipment according to the current network point equipment operation quantity, the current network point equipment operation duty ratio and the current network point to-be-processed traffic quantity;
and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
5. The grid point power monitoring method according to claim 1, wherein the performing a power early warning operation according to the predicted data of the current grid point battery condition includes:
triggering abnormal battery early warning through an RPA technology when the predicted data of the current network point battery condition exceeds a threshold value;
and analyzing the change rate of the acquired data in a set period, and determining the problem point causing the battery abnormality.
6. The grid point power monitoring method according to claim 5, wherein the determining a problem point causing abnormality of the battery includes:
if the determined problem point belongs to the battery, starting the standby battery to access the power system through the RPA technology, and judging whether the standby battery is still abnormal or not again, wherein a plurality of groups or a plurality of types of standby batteries can be arranged, and determining which group or which type of standby battery is started according to the difference value of the prediction data and the threshold value;
if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager through an RPA technology, and a corresponding device regulation strategy is determined according to the difference value between the battery condition prediction data and the threshold value and the network point device condition.
7. A grid point power monitoring device, characterized by comprising:
the information acquisition module is used for acquiring real-time state information of the battery by additionally arranging a sensor at the battery end of the business website and acquiring service processing information of the current business website by a management system of the business website;
the data analysis module is used for determining the running condition of the battery according to the real-time state information of the battery and the original physical value of the battery, and determining network point business handling prediction data and network point equipment running prediction data according to the business processing information of the current business network point;
and the power early warning module is used for obtaining the predicted data of the current grid point battery condition according to the battery running condition, the grid point business transaction predicted data and the data change trend of the grid point equipment running predicted data, and executing power early warning operation according to the predicted data of the current grid point battery condition.
8. The grid point power monitoring device of claim 7, wherein the data analysis module comprises:
the network point equipment operation prediction data determining unit is used for determining network point equipment operation prediction data according to the current network point equipment operation quantity, the current network point equipment operation duty ratio and the current network point to-be-processed traffic;
the network site business handling prediction data determining unit is used for determining network site business handling prediction data according to the current network site waiting business volume and the current network site contemporaneous historical business handling total volume.
9. The grid point power monitoring device of claim 7, wherein the power early warning module comprises:
the RPA automatic early warning unit is used for triggering abnormal battery early warning through an RPA technology when the predicted data of the current network point battery condition exceeds a threshold value;
and the abnormality analysis unit is used for analyzing the change rate of the acquired data in a set period and determining a problem point causing battery abnormality.
10. The grid point power monitoring apparatus according to claim 9, wherein the abnormality analysis unit includes:
the battery abnormality processing subunit is used for starting the standby battery to access the power system through the RPA technology if the determined problem point belongs to the battery, and re-judging whether the standby battery is still abnormal, wherein a plurality of groups or a plurality of types of standby batteries can be arranged, and which group or which type of standby battery is started is determined according to the difference value between the predicted data and the threshold value;
and the business abnormality processing subunit is used for sending an early warning to a website manager through an RPA technology if the determined problem point belongs to the website to-do business, and determining a corresponding equipment regulation strategy according to the difference value between the battery condition prediction data and the threshold value and the website equipment condition.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the grid point power monitoring method of any one of claims 1 to 6 when the program is executed by the processor.
12. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of the grid point power monitoring method of any of claims 1 to 6.
13. A computer program product comprising computer programs/instructions which when executed by a processor implement the steps of the grid point power monitoring method of any one of claims 1 to 6.
CN202310278282.0A 2023-03-20 2023-03-20 Network point power monitoring method and device Pending CN116316983A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310278282.0A CN116316983A (en) 2023-03-20 2023-03-20 Network point power monitoring method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310278282.0A CN116316983A (en) 2023-03-20 2023-03-20 Network point power monitoring method and device

Publications (1)

Publication Number Publication Date
CN116316983A true CN116316983A (en) 2023-06-23

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310278282.0A Pending CN116316983A (en) 2023-03-20 2023-03-20 Network point power monitoring method and device

Country Status (1)

Country Link
CN (1) CN116316983A (en)

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