CN116111677B - Background monitoring data processing method and system applied to energy storage field - Google Patents

Background monitoring data processing method and system applied to energy storage field Download PDF

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Publication number
CN116111677B
CN116111677B CN202310000865.7A CN202310000865A CN116111677B CN 116111677 B CN116111677 B CN 116111677B CN 202310000865 A CN202310000865 A CN 202310000865A CN 116111677 B CN116111677 B CN 116111677B
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energy storage
storage device
data
health
voltage
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CN116111677A (en
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姚茂法
吴鑫宇
陈熠
王江城
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Faroe Power Zhejiang Co ltd
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Faroe Power Zhejiang Co ltd
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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]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F13/00—Interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units
    • G06F13/38—Information transfer, e.g. on bus
    • G06F13/42—Bus transfer protocol, e.g. handshake; Synchronisation
    • G06F13/4282—Bus transfer protocol, e.g. handshake; Synchronisation on a serial bus, e.g. I2C bus, SPI bus

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Power Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

The application provides a background monitoring data processing method and a system applied to the energy storage field, which belong to the technical field of energy storage and specifically comprise the following steps: the bottom layer acquisition equipment acquires real-time operation data of the energy storage device and determines whether the real-time operation data is abnormal or not based on a set threshold value; the real-time operation data are communicated with a background acquisition module through a serial port, the background acquisition module gathers the real-time operation data to obtain summarized data, and the summarized data are forwarded to a monitoring front-end display module; the monitoring front-end display module performs feature extraction on the summarized data and obtains waveform features and amplitude values to determine the fault type of the energy storage device; based on the amplitude of the summarized data, the health evaluation result is obtained by constructing a health evaluation model of the energy storage device, and the health evaluation result of the energy storage device and the summarized data are displayed, so that the running stability and reliability of the energy storage device are further improved.

Description

Background monitoring data processing method and system applied to energy storage field
Technical Field
The application belongs to the technical field of energy storage, and particularly relates to a background monitoring data processing method and system applied to the energy storage field.
Background
In order to realize the processing and display of the monitoring data of the energy storage system, the data acquisition device is arranged in an energy storage device management system in a micro-grid system of an authorized application patent and authorization bulletin number CN103475042B to collect the operation data of the lithium battery energy storage management subsystem; the data processor performs data processing on the acquired data; the data storage classifies the data and stores the classified data into different databases; the data display displays the device parameters and the running state of the energy storage device, so that the energy storage device is processed, but the following technical problems exist:
1. the collected abnormal data of the energy storage device are not considered to be screened, processed and reported, when the abnormality exists, if the analysis problem exists, a plurality of data are required to be carefully analyzed, meanwhile, a manual data calculation mode is adopted, high requirements are put forward on skills and experiences of personnel, time and labor are wasted, and timeliness accuracy is not ideal.
2. The health evaluation of the energy storage device is not considered according to the collected data of the energy storage device, the original equipment abnormality or fault information is set in the field equipment in a preset condition mode, abnormality processing and reporting are carried out according to a preset standard, so that a plurality of unknown fault problems cannot be found timely, a lot of precious time is delayed when the situation that the problems occur on the spot and then the problems are checked, if the screening and the processing of the faults can be carried out in advance according to the health setting, a large amount of time is saved, and unnecessary losses are avoided.
Aiming at the technical problems, the application provides a background monitoring data processing method and system applied to the energy storage field.
Disclosure of Invention
In order to achieve the purpose of the application, the application adopts the following technical scheme:
according to one aspect of the application, a background monitoring data processing method applied to the energy storage field is provided.
A background monitoring data processing method applied to the energy storage field is characterized by comprising the following steps:
s11, acquiring real-time operation data of an energy storage device by bottom layer acquisition equipment, and transmitting the real-time operation data and an abnormal state to a monitoring server through a communication module when determining that the real-time operation data is abnormal based on a set threshold value;
s12, the real-time operation data are communicated with a background acquisition module through a serial port, the background acquisition module gathers the real-time operation data to obtain summarized data, and the summarized data are forwarded to a monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
s13, a monitoring front-end display module performs feature extraction on the summarized data and obtains waveform features and amplitude values, a prediction model based on a WOA-SVM algorithm is adopted to determine the fault type of the energy storage device, and the fault type and real-time operation data of the energy storage device are transmitted to a monitoring server when the fault type of the energy storage device is determined to be abnormal based on the fault type of the energy storage device;
and S14, based on the amplitude of the summarized data, the health degree evaluation of the energy storage device is achieved by constructing a health degree evaluation model of the energy storage device, a health degree evaluation result is obtained, and based on the monitoring front-end display module, the health degree evaluation result of the energy storage device and the summarized data are displayed.
When the real-time operation data is abnormal based on the set threshold value, the real-time operation data and the abnormal state are transmitted to the monitoring server through the communication module, so that early warning of faults is realized from the bottom layer acquisition equipment, the accuracy and the efficiency of fault judgment are further improved, and the operation stability of the energy storage device is promoted.
The fault type of the energy storage device is determined by further combining waveform characteristics and amplitude values of summarized data and adopting a prediction model based on a WOA-SVM algorithm, so that the judgment of faults from the angle of various data is further realized, the comprehensiveness and the accuracy of fault diagnosis are ensured, and meanwhile, the running stability of the energy storage device is also ensured.
Through the display of the health evaluation result, the accurate evaluation of the operation state of the energy storage device is realized, the occurrence of problems such as faults caused by the fact that the operation state of the energy storage device cannot be accurately mastered is avoided, and the stability and reliability of the final operation are ensured.
The real-time operation data comprise the voltage, the current and the temperature of the battery of the energy storage device, and the abnormal state comprises voltage abnormality, current abnormality and temperature abnormality.
The further technical scheme is that the communication message formats of the bottom layer acquisition equipment, the background acquisition module and the monitoring front end display module are uniformly in Modbus format, wherein the Modbus format comprises: the method comprises the steps of starting codes, functional codes, lengths, data areas, check areas and ending codes, wherein the check of the check areas is uniformly checked by using CRC 16.
The background acquisition module is used for acquiring the real-time operation data according to the data organization format of the point table by sending a data request message according to the preset point table, analyzing the real-time operation data according to the data organization format of the point table to obtain the summarized data, and storing the summarized data in a memory for summarization.
The further technical scheme is that the specific steps of determining the fault type of the energy storage device are as follows:
s21, acquiring waveform characteristics and amplitude values of the summarized data, wherein the waveform characteristics of the summarized data comprise curvature and slope of the summarized data, determining whether the energy storage device is abnormal or not based on the waveform characteristics of the summarized data, if yes, determining the fault type of the energy storage device based on the waveform characteristics of the summarized data, and if not, entering step S22;
s22, constructing an input set based on waveform characteristics and amplitude values of the energy storage device, and sending the input set into a prediction model based on a WOA-SVM algorithm to obtain a prediction result;
s23, determining the fault type of the energy storage device based on the prediction result.
A further technical solution is that the fault type includes: no fault, too high a charging environment temperature, short circuit of the battery, too low a battery capacity, and open circuit of the battery.
The further technical scheme is that the specific steps of constructing the health degree evaluation result are as follows:
s31, judging whether the voltage amplitude of the battery of the energy storage device is within a voltage threshold range of the battery of the energy storage device, if so, determining the voltage health of the battery of the energy storage device to be 1, and if not, determining the voltage health of the energy storage device based on the voltage amplitude of the battery of the energy storage device;
s32, judging whether the current amplitude of the battery of the energy storage device is within the current threshold range of the battery of the energy storage device, if so, determining the current health of the battery of the energy storage device to be 1, and if not, determining the current health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s33, judging whether the temperature amplitude of the battery of the energy storage device is within a temperature threshold range of the battery of the energy storage device, if so, determining the temperature health of the battery of the energy storage device to be 1, and if not, determining the temperature health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s34, determining a health evaluation result of the energy storage device based on the voltage health, the current health and the temperature health of the energy storage device.
According to a further technical scheme, according to the absolute value of the difference between the voltage amplitude of the battery of the energy storage device and the voltage threshold value closest to the voltage amplitude, the voltage defect degree of the energy storage device is built according to the ratio of the voltage deviation value to the voltage threshold value closest to the voltage amplitude, if the voltage defect degree of the energy storage device is larger than 1, the voltage health degree of the energy storage device is 0, and if the voltage defect degree of the energy storage device is smaller than or equal to 1, the difference between 1 and the voltage defect degree is used as the voltage health degree of the energy storage device.
The further technical scheme is that the calculation formula of the health degree evaluation result is as follows:
wherein J V 、J I 、J T Respectively the voltage health degree, the current health degree and the temperature health degree of the energy storage device, K 1 、K 2 、K 3 Is constant and K 1 >K 2 >K 3 ,K 1 +K 2 +K 3 ＝1。
On the other hand, the application provides a background monitoring data processing system applied to the energy storage field, which adopts the background monitoring data processing method applied to the energy storage field and comprises bottom layer acquisition equipment, a background acquisition module and a monitoring front end display module;
the bottom layer acquisition equipment is responsible for acquiring real-time operation data of the energy storage device, and transmitting the real-time operation data and an abnormal state to the monitoring server through the communication module when the real-time operation data are abnormal based on a set threshold value, and communicating the real-time operation data with the background acquisition module through the serial port;
the background acquisition module is responsible for summarizing the real-time operation data to obtain summarized data, and forwarding the summarized data to the monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
the monitoring front-end display module is responsible for carrying out feature extraction on the summarized data and obtaining waveform features and amplitude values, adopts a prediction model based on a WOA-SVM algorithm to determine the fault type of the energy storage device, and transmits the fault type and real-time operation data of the energy storage device to a monitoring server when the fault type of the energy storage device is determined to be abnormal; based on the amplitude of the summarized data, the health evaluation of the energy storage device is achieved by constructing a health evaluation model of the energy storage device, a health evaluation result is obtained, and based on the monitoring front-end display module, the health evaluation result of the energy storage device and the summarized data are displayed.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a flow chart of a background monitoring data processing method applied to the energy storage field according to embodiment 1;
fig. 2 is a frame diagram of a background monitoring data processing system applied to the energy storage field in embodiment 2.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus detailed descriptions thereof will be omitted.
The terms "a," "an," "the," and "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. in addition to the listed elements/components/etc.
Example 1
In order to solve the above-mentioned problems, according to one aspect of the present application, as shown in fig. 1, a background monitoring data processing method applied to an energy storage field is provided, which is characterized in that the method specifically includes:
s11, acquiring real-time operation data of an energy storage device by bottom layer acquisition equipment, and transmitting the real-time operation data and an abnormal state to a monitoring server through a communication module when determining that the real-time operation data is abnormal based on a set threshold value;
specifically, the bottom layer acquisition equipment acquires various remote signals such as voltage, current, temperature and the like of the field battery, telemetry data are used for monitoring the working state of the battery, capacity evaluation, health degree evaluation and the like, remote control and remote adjustment such as charging and discharging, balancing and the like can be performed, and errors such as over-charging, over-discharging, high temperature and the like of the battery can be produced through preset settings, and corresponding alarms are generated.
S12, the real-time operation data are communicated with a background acquisition module through a serial port, the background acquisition module gathers the real-time operation data to obtain summarized data, and the summarized data are forwarded to a monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
specifically, the background acquisition module mainly collects and gathers various data of the bottom acquisition device, analyzes and gathers the data according to a preset point table, sends the data request message according to the data organization format of the point table, and stores the data in the memory, forwards the data to the monitoring front-end display module through websocket protocol in TCP protocol of Ethernet, executes instructions of charging and discharging, balancing, power limiting and the like sent by the monitoring front-end display module through websocket protocol, forwards the message of the bottom acquisition data sent through the serial port to the monitoring front-end display module for processing through websocket protocol, and one background acquisition module supports acquisition of a plurality of data of various bottom acquisition devices, provides a unified and unique interface for the monitoring front-end display module, reduces complexity of the monitoring front-end display module, and because the bottom acquisition device only communicates with the background acquisition module, does not directly reduce attack to the device, and also can effectively increase security of the attack device by using two different protocols for communication with the bottom acquisition device and the monitoring front-end display module respectively.
Specifically, the background acquisition module comprises a data processing module, a strategy execution module, a front-end communication module and an equipment communication module:
1. the data processing module is used for converting Modbus protocol messages sent by the bottom acquisition equipment through a serial port into multiple bytes through left shifting of single byte data according to the number of bytes of the data according to a format agreed by a point table, then carrying out bit or operation on the multiple bytes of single byte data and the rest single byte data to form shaping data, converting floating point type multiplying power into real data according to the data type in the point table, converting the real data into websocket protocol messages, and sending the websocket protocol messages to the monitoring front-end display module for data display, and analyzing problems
2. And the strategy executing module executes some strategy instructions sent by the monitoring front-end display module, such as sending oscilloscope data at fixed time, wherein the strategy starting message contains data sending intervals and data point table numbers, and then the strategy executing module receives the specified data according to the specified time intervals and sends the data to the monitoring front-end display module for oscillography.
3. The front-end communication module is communicated with the monitoring front-end display module, determines the action type to be executed according to the function code specified by the protocol, shifts left to multiple bytes according to the number of bytes of data according to the data area specified by the protocol, and then carries out bit or operation with the rest single-byte data to obtain the data.
4. And the equipment communication module is used for communicating with the bottom layer acquisition equipment and forwarding the message.
S13, a monitoring front-end display module performs feature extraction on the summarized data and obtains waveform features and amplitude values, a prediction model based on a WOA-SVM algorithm is adopted to determine the fault type of the energy storage device, and the fault type and real-time operation data of the energy storage device are transmitted to a monitoring server when the fault type of the energy storage device is determined to be abnormal based on the fault type of the energy storage device;
specifically, the monitoring front end display module is in communication with the background acquisition module and is used for displaying real-time data, historical data, equipment operation logs, equipment point list issuing, equipment timing, alarm display, software oscilloscopes, data modification, data storage and other functions in the bottom acquisition equipment sent from the background acquisition module, and the monitoring front end display module is mainly divided into a communication module, a real-time data display module, a historical data display module, a log display module, a software oscilloscopes module and an instruction issuing module.
1. The communication module is used for communicating with the background acquisition module through a network, receiving a message of the background acquisition module, determining the action type to be executed according to a function code specified by a protocol, shifting left to be multi-byte according to the number of data bytes in a data area specified by the protocol, and then carrying out bit or operation on the multi-byte data and the rest single-byte data to obtain data such as voltage, current, temperature, oscillograph waveform and the like.
2. And the real-time data display module displays the real-time data such as voltage, current, temperature and the like of the equipment point table acquired from the background acquisition module and provides the functions of setting and modifying the power grid frequency, rated voltage, rated current, charging and discharging and the like of the bottom equipment.
3. The historical data display module is used for displaying data of the voltage, the current, the temperature and the like of the bottom layer acquisition equipment stored in the bottom layer acquisition equipment when the fault occurs when the battery voltage exceeds the preset upper limit or is lower than the preset lower limit or the temperature is higher than the preset upper limit or the temperature is lower than the preset lower limit or the current is higher than the preset upper limit and the like when the bottom layer equipment acquired from the background acquisition module is in a preset fault
4. The log display module is used for displaying various operational anomalies such as failure in setting the upper limit and the lower limit of various data alarms such as voltage, current and the like of the bottom layer acquisition equipment obtained from the background acquisition module, judging whether the setting is successful or not by a mode of re-reading the data after setting, and judging whether the anomalies occur or not, and various log files such as upgrading, restarting, shutting down, restoring factory settings, setting point tables and the like.
5. The instruction issuing module is used for timing the equipment, taking the local time as the standard time, issuing the time according to the format of time of year, month, day, time of second and millisecond, issuing the point table to the background acquisition module according to the binary system of the point table file and the like, and issuing the point table to the bottom layer equipment by the background acquisition module
6. The software oscilloscope module is used for generating coordinates according to time sequence, X-axis and Y-axis data values and drawing each coordinate into a curve through straight line connection, and comprises a module for displaying the real-time data of the curve and temporarily displaying the curve, wherein the curve is specified to be hidden and not drawn, the display range of the X-axis and the Y-axis is changed to scale and offset the curve, the abnormal equipment data such as abrupt change and steep change of the slope of the curve can be seen simply and intuitively in a graph curvature change mode, the curve is flattened, the slope of the curve can be seen in a related manner through the offset of the coordinates of each data point of a single curve, the slope of the curve such as voltage and current can be seen in a related manner, the temperature slope is steep at the same time, the battery charge and discharge abnormality is described, the manual calculation amount and the error rate are reduced, the identification rate of unknown errors are improved, a large amount of manpower is saved, the requirement on operation staff is reduced, the coordinate values of each point forming the curve can be clicked, the curve is also checked, the color change of the single-click curve is marked, all curve coordinate points to be needed to be intercepted are determined through selecting initial coordinates and ending coordinates, and the data point to be intercepted, and data of the curve interception and data are stored.
And S14, based on the amplitude of the summarized data, the health degree evaluation of the energy storage device is achieved by constructing a health degree evaluation model of the energy storage device, a health degree evaluation result is obtained, and based on the monitoring front-end display module, the health degree evaluation result of the energy storage device and the summarized data are displayed.
When the real-time operation data is abnormal based on the set threshold value, the real-time operation data and the abnormal state are transmitted to the monitoring server through the communication module, so that early warning of faults is realized from the bottom layer acquisition equipment, the accuracy and the efficiency of fault judgment are further improved, and the operation stability of the energy storage device is promoted.
The fault type of the energy storage device is determined by further combining waveform characteristics and amplitude values of summarized data and adopting a prediction model based on a WOA-SVM algorithm, so that the judgment of faults from the angle of various data is further realized, the comprehensiveness and the accuracy of fault diagnosis are ensured, and meanwhile, the running stability of the energy storage device is also ensured.
Through the display of the health evaluation result, the accurate evaluation of the operation state of the energy storage device is realized, the occurrence of problems such as faults caused by the fact that the operation state of the energy storage device cannot be accurately mastered is avoided, and the stability and reliability of the final operation are ensured.
In another possible embodiment, the real-time operation data includes voltage, current, temperature of a battery of the energy storage device, and the abnormal state includes voltage abnormality, current abnormality, temperature abnormality.
In another possible embodiment, the communication message formats of the bottom layer collection device and the background collection module, and the background collection module and the monitoring front end display module uniformly adopt a Modbus format, where the Modbus format includes: the method comprises the steps of starting codes, functional codes, lengths, data areas, check areas and ending codes, wherein the check of the check areas is uniformly checked by using CRC 16.
The method comprises the steps of sending a data request to be displayed to a background acquisition module by a monitoring front end display module, wherein the format is a start code, a function code, a message length, a data area, a check area and an end code, the check is unified by CRC16, after receiving a message, the background acquisition module converts the function code into a communication function code agreed with a background acquisition device, re-checks the communication function code, sends the message to the background acquisition device, after the background acquisition device acquires corresponding data, multiplying power of the real data, performing AND operation by 0xFF, acquiring single bytes, repeating AND operation by right shift operation and 0xFF, converting the multi-byte data into a plurality of single-byte data, transmitting the start code, the data return code, the message length, the single-byte data, the check and the end code to the background acquisition module, firstly performing CRC16 check on the message to ensure that the message is correct and interference is not generated, converting the function code into the communication function code agreed with the background acquisition module and the monitoring front end, re-checking the message, sending the message to the monitoring front end to the corresponding data, performing AND operation by 0xFF, obtaining the single-byte data, and then displaying the multi-byte data to the left byte data according to the data area, and displaying the single-byte data in a left byte area.
In another possible embodiment, the background collection module sends a data request message according to a preset point table, analyzes the real-time operation data according to a data organization format of the point table to obtain the summarized data, and stores the summarized data in a memory for summarization.
In another possible embodiment, the specific steps of determining the fault type of the energy storage device are:
s21, acquiring waveform characteristics and amplitude values of the summarized data, wherein the waveform characteristics of the summarized data comprise curvature and slope of the summarized data, determining whether the energy storage device is abnormal or not based on the waveform characteristics of the summarized data, if yes, determining the fault type of the energy storage device based on the waveform characteristics of the summarized data, and if not, entering step S22;
s22, constructing an input set based on waveform characteristics and amplitude values of the energy storage device, and sending the input set into a prediction model based on a WOA-SVM algorithm to obtain a prediction result;
s23, determining the fault type of the energy storage device based on the prediction result.
In another possible embodiment, the fault type includes: no fault, too high a charging environment temperature, short circuit of the battery, too low a battery capacity, and open circuit of the battery.
In another possible embodiment, the specific steps of constructing the health degree evaluation result are as follows:
s31, judging whether the voltage amplitude of the battery of the energy storage device is within a voltage threshold range of the battery of the energy storage device, if so, determining the voltage health of the battery of the energy storage device to be 1, and if not, determining the voltage health of the energy storage device based on the voltage amplitude of the battery of the energy storage device;
s32, judging whether the current amplitude of the battery of the energy storage device is within the current threshold range of the battery of the energy storage device, if so, determining the current health of the battery of the energy storage device to be 1, and if not, determining the current health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s33, judging whether the temperature amplitude of the battery of the energy storage device is within a temperature threshold range of the battery of the energy storage device, if so, determining the temperature health of the battery of the energy storage device to be 1, and if not, determining the temperature health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s34, determining a health evaluation result of the energy storage device based on the voltage health, the current health and the temperature health of the energy storage device.
In another possible embodiment, according to the absolute value of the difference between the voltage amplitude of the battery of the energy storage device and the voltage threshold value closest to the voltage amplitude, the voltage defect degree of the energy storage device is constructed according to the ratio of the voltage deviation value and the voltage threshold value closest to the voltage amplitude, if the voltage defect degree of the energy storage device is greater than 1, the voltage health degree of the energy storage device is 0, and if the voltage defect degree of the energy storage device is less than or equal to 1, the difference between 1 and the voltage defect degree is taken as the voltage health degree of the energy storage device.
For example, if the voltage amplitude of the battery is 2V and the voltage threshold is 3-4V, the voltage threshold closest to the voltage amplitude is 3V, the voltage deviation value is 1V, the voltage defect is 0.33, and the voltage defect is 1-0.33=0.67.
Specifically, for example, according to the absolute value of the difference between the current amplitude of the battery of the energy storage device and the current threshold value closest to the current amplitude, the current defect degree of the energy storage device is constructed according to the ratio of the current deviation value to the current threshold value closest to the current amplitude, if the current defect degree of the energy storage device is greater than 1, the current health degree of the energy storage device is 0, and if the current defect degree of the energy storage device is less than or equal to 1, the difference between 1 and the current defect degree is taken as the current health degree of the energy storage device.
Specifically, for example, according to the absolute value of the difference between the temperature amplitude of the battery of the energy storage device and the temperature threshold value closest to the temperature amplitude as the temperature deviation value, the temperature defect degree of the energy storage device is constructed according to the ratio of the temperature deviation value to the temperature threshold value closest to the temperature amplitude, if the temperature defect degree of the energy storage device is greater than 1, the temperature health degree of the energy storage device is 0, and if the temperature defect degree of the energy storage device is less than or equal to 1, the difference between 1 and the temperature defect degree is taken as the temperature health degree of the energy storage device.
In another possible embodiment, the calculation formula of the health degree evaluation result is:
wherein J V 、J I 、J T Respectively the voltage health degree, the current health degree and the temperature health degree of the energy storage device, K 1 、K 2 、K 3 Is constant and K 1 >K 2 >K 3 ,K 1 +K 2 +K 3 ＝1。
Example 2
As shown in fig. 2, the application provides a background monitoring data processing system applied to the energy storage field, which adopts the background monitoring data processing method applied to the energy storage field and comprises bottom layer acquisition equipment, a background acquisition module and a monitoring front end display module;
the bottom layer acquisition equipment is responsible for acquiring real-time operation data of the energy storage device, and transmitting the real-time operation data and an abnormal state to the monitoring server through the communication module when the real-time operation data are abnormal based on a set threshold value, and communicating the real-time operation data with the background acquisition module through the serial port;
the background acquisition module is responsible for summarizing the real-time operation data to obtain summarized data, and forwarding the summarized data to the monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
the monitoring front-end display module is responsible for carrying out feature extraction on the summarized data and obtaining waveform features and amplitude values, adopts a prediction model based on a WOA-SVM algorithm to determine the fault type of the energy storage device, and transmits the fault type and real-time operation data of the energy storage device to a monitoring server when the fault type of the energy storage device is determined to be abnormal; based on the amplitude of the summarized data, the health evaluation of the energy storage device is achieved by constructing a health evaluation model of the energy storage device, a health evaluation result is obtained, and based on the monitoring front-end display module, the health evaluation result of the energy storage device and the summarized data are displayed.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other manners as well. The system embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored on a computer readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a U-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 capable of storing program codes.
With the above-described preferred embodiments according to the present application as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present application. The technical scope of the present application is not limited to the description, but must be determined according to the scope of claims.

Claims (5)

1. A background monitoring data processing method applied to the energy storage field is characterized by comprising the following steps:
s11, acquiring real-time operation data of an energy storage device by bottom layer acquisition equipment, and transmitting the real-time operation data and an abnormal state to a monitoring server through a communication module when determining that the real-time operation data is abnormal based on a set threshold value;
s12, the real-time operation data are communicated with a background acquisition module through a serial port, the background acquisition module gathers the real-time operation data to obtain summarized data, and the summarized data are forwarded to a monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
s13, a monitoring front-end display module performs feature extraction on the summarized data and obtains waveform features and amplitude values, a prediction model based on a WOA-SVM algorithm is adopted based on the waveform features and the amplitude values of the summarized data, the fault type of the energy storage device is determined, and when the fault type of the energy storage device is determined to be abnormal based on the fault type of the energy storage device, the fault type and real-time operation data of the energy storage device are transmitted to a monitoring server;
the specific steps of determining the fault type of the energy storage device are as follows:
s21, acquiring waveform characteristics and amplitude values of the summarized data, wherein the waveform characteristics of the summarized data comprise curvature and slope of the summarized data, determining whether the energy storage device is abnormal or not based on the waveform characteristics of the summarized data, if yes, determining the fault type of the energy storage device based on the waveform characteristics of the summarized data, and if not, entering step S22;
s22, constructing an input set based on waveform characteristics and amplitude values of the energy storage device, and sending the input set into a prediction model based on a WOA-SVM algorithm to obtain a prediction result;
s23, determining the fault type of the energy storage device based on the prediction result;
the fault types include: no fault, too high temperature of charging environment, short circuit of battery, too low battery capacity and open circuit of battery;
s14, based on the amplitude of the summarized data, a health degree evaluation model of the energy storage device is constructed, health degree evaluation results are obtained by evaluating the health degree of the energy storage device, and the health degree evaluation results and the summarized data of the energy storage device are displayed based on the monitoring front-end display module;
the specific steps of constructing the health evaluation result are as follows:
s31, judging whether the voltage amplitude of the battery of the energy storage device is within a voltage threshold range of the battery of the energy storage device, if so, determining the voltage health of the battery of the energy storage device to be 1, and if not, determining the voltage health of the energy storage device based on the voltage amplitude of the battery of the energy storage device;
s32, judging whether the current amplitude of the battery of the energy storage device is within the current threshold range of the battery of the energy storage device, if so, determining the current health of the battery of the energy storage device to be 1, and if not, determining the current health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s33, judging whether the temperature amplitude of the battery of the energy storage device is within a temperature threshold range of the battery of the energy storage device, if so, determining the temperature health of the battery of the energy storage device to be 1, and if not, determining the temperature health of the energy storage device based on the current amplitude of the battery of the energy storage device;
s34, determining a health evaluation result of the energy storage device based on the voltage health, the current health and the temperature health of the energy storage device;
according to the absolute value of the difference value between the voltage amplitude of the battery of the energy storage device and the voltage threshold value closest to the voltage amplitude, the voltage defect degree of the energy storage device is built according to the ratio of the voltage deviation value to the voltage threshold value closest to the voltage amplitude, if the voltage defect degree of the energy storage device is larger than 1, the voltage health degree of the energy storage device is 0, and if the voltage defect degree of the energy storage device is smaller than or equal to 1, the difference value between 1 and the voltage defect degree is taken as the voltage health degree of the energy storage device;
the calculation formula of the health degree evaluation result is as follows:wherein J V 、J I 、J T Respectively the voltage health degree, the current health degree and the temperature health degree of the energy storage device, K 1 、K 2 、K 3 Is constant and K 1 >K 2 >K 3 ,K 1 +K 2 +K 3 =1。
2. The background monitoring data processing method according to claim 1, wherein the real-time operation data includes voltage, current, temperature of a battery of the energy storage device, and the abnormal state includes voltage abnormality, current abnormality, temperature abnormality.
3. The method for processing background monitoring data according to claim 1, wherein communication message formats of the bottom layer collection device and the background collection module, and communication message formats of the background collection module and the monitoring front end display module are uniformly in a Modbus format, wherein the Modbus format comprises: the method comprises the steps of starting codes, functional codes, lengths, data areas, check areas and ending codes, wherein the check of the check areas is uniformly checked by using CRC 16.
4. The background monitoring data processing method according to claim 1, wherein the background collection module obtains the summarized data by sending a data request message according to a preset point table, analyzing the real-time operation data according to a data organization format of the point table, and storing the summarized data in a memory for summarization.
5. A background monitoring data processing system applied to the energy storage field, which adopts the background monitoring data processing method applied to the energy storage field according to any one of claims 1-4, and comprises bottom layer acquisition equipment, a background acquisition module and a monitoring front end display module;
the bottom layer acquisition equipment is responsible for acquiring real-time operation data of the energy storage device, and transmitting the real-time operation data and an abnormal state to the monitoring server through the communication module when the real-time operation data are abnormal based on a set threshold value, and communicating the real-time operation data with the background acquisition module through the serial port;
the background acquisition module is responsible for summarizing the real-time operation data to obtain summarized data, and forwarding the summarized data to the monitoring front-end display module according to websocket protocol in TCP protocol passing through Ethernet;
the monitoring front-end display module is responsible for carrying out feature extraction on the summarized data and obtaining waveform features and amplitude values, adopts a prediction model based on a WOA-SVM algorithm to determine the fault type of the energy storage device, and transmits the fault type and real-time operation data of the energy storage device to a monitoring server when the fault type of the energy storage device is determined to be abnormal; based on the amplitude of the summarized data, the health evaluation of the energy storage device is achieved by constructing a health evaluation model of the energy storage device, a health evaluation result is obtained, and based on the monitoring front-end display module, the health evaluation result of the energy storage device and the summarized data are displayed.
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