CN116559684A - Large-scale battery energy storage power station running state monitoring and evaluating system - Google Patents
Large-scale battery energy storage power station running state monitoring and evaluating system Download PDFInfo
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- 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
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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Abstract
The invention relates to the technical field of battery energy storage power stations, and particularly discloses a large-scale battery energy storage power station operation state monitoring and evaluating system, which comprises the following components: the invention comprehensively analyzes the discharge quality evaluation coefficient corresponding to the energy storage battery, overcomes the defect of low attention to a discharge object of the energy storage battery in the prior art, further ensures the accuracy of the corresponding discharge quality analysis of the energy storage battery, improves the operation efficiency of the energy storage battery to a certain extent, analyzes the operation safety of the energy storage battery, ensures the accuracy of the analysis of the health evaluation coefficient of the energy storage battery and improves the charge and discharge efficiency of the battery energy storage power station to a certain extent.
Description
Technical Field
The invention relates to the technical field of battery energy storage power stations, in particular to a large-scale battery energy storage power station operation state monitoring and evaluating system.
Background
Along with development of science and technology, the development of various industries has more and more requirements for electricity, meanwhile, more battery energy storage power stations are in front of people to meet the requirements for electricity, in the normal operation process of the battery energy storage power stations, energy storage batteries are core components of the battery energy storage power stations, healthy operation of the energy storage batteries is a key of normal operation of the battery energy storage power stations, if healthy operation of the energy storage batteries cannot be guaranteed, on one hand, the charge and discharge efficiency of the energy storage batteries is reduced, and then the efficiency of the battery energy storage power stations is influenced, the related benefits of the battery energy storage power stations are reduced to a certain extent, on the other hand, the operation safety of the energy storage batteries is difficult to guarantee, and then the safety of related workers is difficult to guarantee, so that the health of the energy storage batteries needs to be assessed.
The existing health evaluation of the energy storage battery can meet the current requirements to a certain extent, but has certain defects, and the specific appearance of the method is as follows: (1) The existing health assessment of the energy storage battery has low attention to a discharge object to which the energy storage battery belongs when the energy storage battery discharges, and the related information of the discharge object to which the energy storage battery belongs reflects the stability and the loss rate of the energy storage battery in the corresponding discharge process to a certain extent.
(2) The prior art has low attention to the operation safety of the energy storage battery, the temperature of the energy storage battery and the emitted noise reflect the operation safety and the operation quality of the energy storage battery, on one hand, the operation safety of the energy storage battery cannot be guaranteed due to the neglect of the prior art, the phenomena of overhigh temperature and loud noise of the energy storage battery are easy to occur, meanwhile, certain harm is caused to the environment, on the other hand, the accuracy of the analysis of the health evaluation coefficient of the energy storage battery is influenced, the charge and discharge efficiency of a battery energy storage power station is reduced to a certain extent, and the related benefits of the battery energy storage power station are influenced.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a large-scale battery energy storage power station operation state monitoring and evaluating system which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: a system for monitoring and evaluating the operating state of a large-scale battery energy storage power station, comprising: and the energy storage power station monitoring module is used for monitoring each energy storage battery in the energy storage power station.
The energy storage battery charging quality evaluation module is used for extracting the operation parameters and the actual charging quantity corresponding to each charging of each energy storage battery from the energy storage battery operation background, and further analyzing the charging quality evaluation coefficients corresponding to each energy storage battery.
The energy storage battery discharge quality evaluation module is used for extracting the actual discharge quantity and the operation parameters corresponding to each discharge of each energy storage battery from the energy storage battery operation background, acquiring the actual receiving quantity and the receiving parameters corresponding to the discharge object of each discharge of each energy storage battery, and further analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery.
The energy storage battery operation safety analysis module is used for acquiring operation parameters of each energy storage battery at each test time point, wherein the operation parameters comprise box body temperature and sound decibels, and analyzing operation safety coefficients of each energy storage battery at each test time point.
The energy storage battery appearance defect analysis module is used for acquiring appearance images of all the energy storage batteries at all the test time points from monitoring in the energy storage power station, and further analyzing appearance damage coefficients of all the energy storage batteries at all the test time points.
And the energy storage battery health state evaluation module is used for analyzing health evaluation coefficients corresponding to the energy storage batteries.
And the early warning terminal is used for carrying out corresponding early warning based on the operation safety coefficient corresponding to each energy storage battery at each test time point, the appearance damage coefficient of each energy storage battery at each test time point and the health evaluation coefficient corresponding to each energy storage battery.
And the cloud database is used for storing the expected charge quantity corresponding to each charge of each energy storage battery and storing the gray value range of the crack corresponding to the energy storage battery.
As a preferred embodiment, the operating parameters include a charging current and a charging voltage corresponding to each detection time point.
As a preferred embodiment, the operation parameters include a discharge current and a discharge voltage corresponding to each discharge time point, and the reception parameters include a reception current and a reception voltage for each reception time point.
As a preferred scheme, the method for analyzing the charge quality evaluation coefficient corresponding to each energy storage battery specifically comprises the following steps: extracting charging current I corresponding to each detection time point of each charge of each energy storage battery from operation parameters corresponding to each charge of each energy storage battery im,p And a charging voltage U im,p Where i is denoted as the number of each energy storage battery, i=1, 2,..n, m is denoted as the number of each charge, m=1, 2,..l, p is denoted as the number of each detection time point, p=1, 2,..q.
According to a predefined safety current interval corresponding to the energy storage battery, and obtaining a safety current lower limit value I corresponding to the energy storage battery from the safety current interval Lower part(s) And a safety upper limit value I Upper part Analyzing the charging current coincidence coefficient corresponding to each charging of each energy storage batteryWherein I' is expressed as a preset allowable current error.
Screening the maximum charging current corresponding to each charging of each energy storage battery from the charging current corresponding to each charging of each energy storage battery at each detection time pointAnd minimum charging current->Analyzing charging current deviation coefficient corresponding to each charging of each energy storage battery>Wherein I is im,p+1 The charging current corresponding to the (p+1) th detection time point is represented by the mth charging of the ith energy storage battery, q is represented by the number of detection time points, and I' is represented by the allowable error between the preset maximum charging current and the preset minimum charging current, lambda 1 、λ 2 The weight coefficients respectively correspond to the deviation between the preset maximum charging current and the preset minimum charging current and the integral error of the charging current.
Comparing the charging current coincidence coefficient corresponding to each charge of each energy storage battery with a preset charging current coincidence coefficient threshold value, if the charging current coincidence coefficient corresponding to a certain charge of a certain energy storage battery is greater than or equal to the charging current coincidence coefficient threshold value, marking the charge as current normal charge, further obtaining each normal current charge of each energy storage battery, and counting the times CI of the current normal charge of each energy storage battery i 。
Counting the charging corresponding to each energy storage batteryTotal number of electric circuits CS i Analyzing the charging current quality coefficient corresponding to each energy storage batteryWhere l is denoted as the number of charges.
Analyzing the quality coefficient of the charging voltage corresponding to each energy storage battery according to the charging voltage corresponding to each detection time point of each charging to which each energy storage battery belongs
Extracting predicted charge quantity Q' corresponding to each charge of each energy storage battery from cloud database im According to the actual charge quantity Q corresponding to each charge of each energy storage battery im Further analyzing the charging electric quantity coincidence coefficient corresponding to each charging of each energy storage batteryWhere e is denoted as a natural constant.
Analyzing the charge quality evaluation coefficients corresponding to the energy storage batteriesWherein gamma is 1 、γ 2 、γ 3 Respectively representing the preset charging current quality, charging voltage quality and charging electric quantity to accord with corresponding duty ratio factors.
As a preferable scheme, the charging voltage quality coefficient corresponding to each energy storage battery comprises the following specific steps: analyzing a charging voltage evaluation index corresponding to each charging of each energy storage battery according to the charging voltage corresponding to each charging of each energy storage battery at each detection time pointWhere U' represents a preset safety voltage.
Obtaining the maximum charging voltage of each charge of each energy storage battery according to the charging voltage corresponding to each charge of each energy storage battery at each detection time pointAnd minimum charging voltage>
Screening the maximum charge voltage evaluation index corresponding to each energy storage battery based on the charge voltage evaluation index corresponding to each charge to which each energy storage battery belongsAnd a minimum charge voltage evaluation index->
The method is consistent with the analysis method of each normal current charging of each energy storage battery, each normal voltage charging of each energy storage battery is analyzed, and the frequency CY of each energy storage battery corresponding to the normal voltage charging is counted i 。
Analyzing the quality coefficient of the charging voltage corresponding to each energy storage batteryWherein U 'is a preset allowable voltage error, D' is a preset allowable charging voltage evaluation index error, χ 1 、χ 2 、χ 3 、χ 4 Respectively corresponding weight factors of preset voltage evaluation, voltage deviation, voltage evaluation error and normal voltage charging times.
As a preferable scheme, the method for analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery specifically comprises the following steps: analyzing the discharge current quality coefficient xi corresponding to each energy storage battery in accordance with the charge current quality coefficient corresponding to each energy storage battery i 。
Analyzing the discharge voltage quality coefficient zeta corresponding to each energy storage battery in accordance with the charge voltage quality coefficient corresponding to each energy storage battery i 。
Connection corresponding to each discharge of each energy storage batteryExtracting the receiving current IJ of the discharge object corresponding to each discharge of each energy storage battery at each receiving time point from the receiving parameters ihx And a receiving voltage UJ ihx Where h is the number of each discharge, h=1, 2,..g, where x is denoted as the number of each reception time point, x=1, 2,..y.
Analyzing the received current voltage stability coefficient of the discharge object corresponding to each discharge of each energy storage batteryWhere y is the number of receive time points, delta 1 、δ 2 The correction factors are respectively corresponding to preset current stability and voltage stability.
The actual discharge quantity corresponding to each discharge of each energy storage batteryAnd the actual received power to which the corresponding discharge object belongs +.>Analyzing discharge efficiency evaluation index corresponding to each discharge of each energy storage battery>
Analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage batteryWherein beta is 1 、β 2 、β 3 、β 4 Respectively expressed as preset discharge current quality, discharge voltage quality, receiving current voltage quality and discharge efficiency evaluation corresponding proportionality coefficients.
As a preferable scheme, the operation safety coefficient corresponding to each energy storage battery at each test time point is specifically analyzed by the following method: according to the box body temperature T of each energy storage battery at each test time point ir Sum sound decibel B ir Where r is expressed as the number of each test time point, r=1And 2.t. analyzing the operation safety coefficient corresponding to each energy storage battery at each test time pointWherein T 'and B' are the preset proper temperatures of the box body, and proper sound decibels and rho generated when the energy storage battery operates 1 、ρ 2 The safety influence factor is suitable for the preset box body temperature and the sound decibel.
As a preferred scheme, the analysis of the appearance damage coefficient of each energy storage battery at each test time point comprises the following specific steps: according to the appearance image of each energy storage battery at each test time, extracting the gray value range of the corresponding crack of the energy storage battery from the cloud database, analyzing each crack region corresponding to each energy storage battery at each test time point, acquiring the longest length of each energy storage battery in each crack region corresponding to each test time point, and marking the longest length as the length corresponding to each crack region corresponding to each energy storage battery at each test time pointWhere b is expressed as the number of each test time point, b=1, 2, c, f are denoted as the numbers of the respective crack regions, f=1, 2.
Counting the number SS of crack areas of each energy storage battery at each test time point ib Analyzing crack risk coefficients corresponding to each energy storage battery at each test time pointWherein SS' is the number of preset allowable fracture zones, alpha 1 、α 2 The preset fracture length and the preset proportion factors corresponding to the number of the fracture areas are respectively adopted.
Similarly, the corrosion risk coefficient XS of each energy storage battery at each test time point is analyzed ib 。
Comprehensively analyzing the appearance damage coefficient of each energy storage battery at each test time point
As a preferable solution, the analyzing the health evaluation coefficient corresponding to each energy storage battery specifically includes the following calculation formula:wherein t is the number of test time points, c is the number of test time points, τ 1 、τ 2 、τ 3 、τ 4 The method is characterized by respectively comprising preset duty ratio coefficients corresponding to charging quality, discharging quality, operation safety and appearance damage.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
(1) According to the invention, each energy storage battery in the energy storage power station is monitored in the energy storage power station monitoring module, so that a foundation is laid for analysis of appearance defects of the energy storage battery, the appearance of the energy storage battery is ensured to be in a normal category, the problem that appearance quality defects of the energy storage battery occur is avoided, and the normal operation of the energy storage battery is influenced.
(2) According to the invention, the charging quality evaluation coefficient of the energy storage battery is analyzed through the corresponding charging operation parameter and the actual charging amount of the energy storage battery in the charging quality evaluation module of the energy storage battery, so that the accuracy of the analysis of the charging process of the energy storage battery is ensured, and a foundation is laid for the analysis of the subsequent health evaluation coefficient of the energy storage battery.
(3) According to the invention, in the energy storage battery discharge quality evaluation module, not only are the operation parameters of the discharge of the energy storage battery analyzed, but also the actual received electric quantity and the actual received parameters of the discharge object of the energy storage battery are analyzed, so that the discharge quality evaluation coefficient corresponding to the energy storage battery is comprehensively analyzed, the defect of low attention to the discharge object of the energy storage battery in the prior art is overcome, the accuracy of the corresponding discharge quality analysis of the energy storage battery is further ensured, and therefore, powerful data support is provided for the analysis of the health evaluation index of the energy storage battery, and the operation efficiency of the energy storage battery is improved to a certain extent.
(4) According to the invention, the operation safety of the energy storage battery is analyzed through the box body temperature and the sound decibel of the energy storage battery in the operation safety analysis module of the energy storage battery, so that the phenomena of overhigh temperature and loud noise of the energy storage battery are avoided, meanwhile, the harm to the environment is reduced, the accuracy of analysis of the health evaluation coefficient of the energy storage battery is ensured, and the charge and discharge efficiency of the battery energy storage power station is improved to a certain extent.
(5) According to the invention, the image of the energy storage battery is obtained through monitoring in the energy storage power station in the energy storage battery appearance defect analysis module, so that the appearance defect coefficient of the energy storage battery is analyzed, and data support is provided for the analysis of the health evaluation coefficient of the energy storage battery.
(6) According to the invention, the health evaluation coefficient of the energy storage battery is comprehensively analyzed in the health state evaluation module of the energy storage battery, and the analysis dimension is more diversified, so that the accuracy and scientificity of the analysis result of the health evaluation coefficient of the energy storage battery are ensured.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic diagram of the module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a monitoring and evaluating system for operating states of a large-scale battery energy storage power station, which includes: the system comprises an energy storage power station monitoring module, an energy storage battery charging quality evaluation module, an energy storage battery discharging quality evaluation module, an energy storage battery operation safety analysis module, an energy storage battery appearance defect analysis module, an energy storage battery health state evaluation module, an early warning terminal and a cloud database.
The energy storage power station monitoring module is connected with the energy storage battery appearance defect analysis module, the energy storage battery charging quality assessment module, the energy storage battery discharging quality assessment module, the energy storage battery operation safety analysis module and the energy storage battery appearance defect analysis module are all connected with the energy storage battery health state assessment module, the early warning terminal is respectively connected with the energy storage battery operation safety analysis module, the energy storage battery appearance defect analysis module and the energy storage battery health state assessment module, and the cloud database is respectively connected with the energy storage battery charging quality assessment module and the energy storage battery appearance defect analysis module.
The energy storage power station monitoring module is used for monitoring each energy storage battery in the energy storage power station.
It should be noted that, each energy storage battery in the energy storage power station is monitored by using a camera.
According to the invention, each energy storage battery in the energy storage power station is monitored in the energy storage power station monitoring module, so that a foundation is laid for analysis of appearance defects of the energy storage battery, the appearance of the energy storage battery is ensured to be in a normal category, the problem that appearance quality defects of the energy storage battery occur is avoided, and the normal operation of the energy storage battery is influenced.
The energy storage battery charging quality evaluation module is used for extracting operation parameters and actual charging amounts corresponding to the charging of each energy storage battery from the energy storage battery operation background, and further analyzing charging quality evaluation coefficients corresponding to each energy storage battery.
In a specific embodiment of the present invention, the operation parameters include a charging current and a charging voltage corresponding to each detection time point.
In a specific embodiment of the present invention, the method for analyzing the charge quality evaluation coefficient corresponding to each energy storage battery includes: extracting charging current I corresponding to each detection time point of each charge of each energy storage battery from operation parameters corresponding to each charge of each energy storage battery im,p And a charging voltage U im,p Where i is denoted as the number of each energy storage battery, i=1, 2, n, m is denoted as the number of each charge, m=1, 2, l, p is denoted as each testNumber of time points, p=1, 2,..q.
According to a predefined safety current interval corresponding to the energy storage battery, and obtaining a safety current lower limit value I corresponding to the energy storage battery from the safety current interval Lower part(s) And a safety upper limit value I Upper part Analyzing the charging current coincidence coefficient corresponding to each charging of each energy storage batteryWherein I' is expressed as a preset allowable current error.
Screening the maximum charging current corresponding to each charging of each energy storage battery from the charging current corresponding to each charging of each energy storage battery at each detection time pointAnd minimum charging current->Analyzing charging current deviation coefficient corresponding to each charging of each energy storage battery>Wherein I is im,p+1 The charging current corresponding to the (p+1) th detection time point is represented by the mth charging of the ith energy storage battery, q is represented by the number of detection time points, and I' is represented by the allowable error between the preset maximum charging current and the preset minimum charging current, lambda 1 、λ 2 The weight coefficients respectively correspond to the deviation between the preset maximum charging current and the preset minimum charging current and the integral error of the charging current.
Comparing the charging current coincidence coefficient corresponding to each charge of each energy storage battery with a preset charging current coincidence coefficient threshold value, if the charging current coincidence coefficient corresponding to a certain charge of a certain energy storage battery is greater than or equal to the charging current coincidence coefficient threshold value, marking the charge as current normal charge, further obtaining each normal current charge of each energy storage battery, and counting the times CI of the current normal charge of each energy storage battery i 。
Counting the total charging times CS corresponding to each energy storage battery i Analyzing the charging current quality coefficient corresponding to each energy storage batteryWhere l is denoted as the number of charges.
Analyzing the quality coefficient of the charging voltage corresponding to each energy storage battery according to the charging voltage corresponding to each detection time point of each charging to which each energy storage battery belongs
Extracting predicted charge quantity Q' corresponding to each charge of each energy storage battery from cloud database im According to the actual charge quantity Q corresponding to each charge of each energy storage battery im Further analyzing the charging electric quantity coincidence coefficient corresponding to each charging of each energy storage batteryWhere e is denoted as a natural constant.
Analyzing the charge quality evaluation coefficients corresponding to the energy storage batteriesWherein gamma is 1 、γ 2 、γ 3 Respectively representing the preset charging current quality, charging voltage quality and charging electric quantity to accord with corresponding duty ratio factors.
In a specific embodiment of the present invention, the charging voltage quality coefficient corresponding to each energy storage battery is specifically: analyzing a charging voltage evaluation index corresponding to each charging of each energy storage battery according to the charging voltage corresponding to each charging of each energy storage battery at each detection time pointWhere U' represents a preset safety voltage.
Corresponding to each detection time point according to each charging of each energy storage batteryThe charging voltage obtains the maximum charging voltage of each charging of each energy storage batteryAnd minimum charging voltage>
Screening the maximum charge voltage evaluation index corresponding to each energy storage battery based on the charge voltage evaluation index corresponding to each charge to which each energy storage battery belongsAnd a minimum charge voltage evaluation index->
The method is consistent with the analysis method of each normal current charging of each energy storage battery, each normal voltage charging of each energy storage battery is analyzed, and the frequency CY of each energy storage battery corresponding to the normal voltage charging is counted i 。
Analyzing the quality coefficient of the charging voltage corresponding to each energy storage batteryWherein U 'is a preset allowable voltage error, D' is a preset allowable charging voltage evaluation index error, χ 1 、χ 2 、χ 3 、χ 4 Respectively corresponding weight factors of preset voltage evaluation, voltage deviation, voltage evaluation error and normal voltage charging times.
According to the invention, the charging quality evaluation coefficient of the energy storage battery is analyzed through the corresponding charging operation parameter and the actual charging amount of the energy storage battery in the charging quality evaluation module of the energy storage battery, so that the accuracy of the analysis of the charging process of the energy storage battery is ensured, and a foundation is laid for the analysis of the subsequent health evaluation coefficient of the energy storage battery.
The energy storage battery discharge quality evaluation module is used for extracting the actual discharge quantity and the operation parameters corresponding to each discharge of each energy storage battery from the energy storage battery operation background, acquiring the actual receiving quantity and the receiving parameters corresponding to the discharge object of each discharge of each energy storage battery, and further analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery.
In a specific embodiment of the present invention, the operation parameters include a discharge current and a discharge voltage corresponding to each discharge time point, and the reception parameters include a reception current and a reception voltage for each reception time point.
In a specific embodiment of the present invention, the method for analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery includes: analyzing the discharge current quality coefficient xi corresponding to each energy storage battery in accordance with the charge current quality coefficient corresponding to each energy storage battery i 。
Analyzing the discharge voltage quality coefficient zeta corresponding to each energy storage battery in accordance with the charge voltage quality coefficient corresponding to each energy storage battery i 。
Extracting the receiving current IJ of the discharge object corresponding to each discharge of each energy storage battery at each receiving time point from the receiving parameters corresponding to each discharge of each energy storage battery ihx And a receiving voltage UJ ihx Where h is the number of each discharge, h=1, 2,..g, where x is denoted as the number of each reception time point, x=1, 2,..y.
Analyzing the received current voltage stability coefficient of the discharge object corresponding to each discharge of each energy storage batteryWhere y is the number of receive time points, delta 1 、δ 2 The correction factors are respectively corresponding to preset current stability and voltage stability.
The actual discharge quantity corresponding to each discharge of each energy storage batteryAnd the actual received power to which the corresponding discharge object belongs +.>Analyzing discharge efficiency evaluation index corresponding to each discharge of each energy storage battery>
Analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage batteryWherein beta is 1 、β 2 、β 3 、β 4 Respectively expressed as preset discharge current quality, discharge voltage quality, receiving current voltage quality and discharge efficiency evaluation corresponding proportionality coefficients.
According to the invention, in the energy storage battery discharge quality evaluation module, not only are the operation parameters of the discharge of the energy storage battery analyzed, but also the actual received electric quantity and the actual received parameters of the discharge object of the energy storage battery are analyzed, so that the discharge quality evaluation coefficient corresponding to the energy storage battery is comprehensively analyzed, the defect of low attention to the discharge object of the energy storage battery in the prior art is overcome, the accuracy of the corresponding discharge quality analysis of the energy storage battery is further ensured, and therefore, powerful data support is provided for the analysis of the health evaluation index of the energy storage battery, and the operation efficiency of the energy storage battery is improved to a certain extent.
The energy storage battery operation safety analysis module is used for acquiring operation parameters of each energy storage battery at each test time point, wherein the operation parameters comprise box body temperature and sound decibels, and analyzing operation safety coefficients of each energy storage battery at each test time point.
It should be noted that, the temperature sensor and the sound sensor are used for monitoring the energy storage batteries, so as to obtain the operation parameters of each energy storage battery at each test time point.
In a specific embodiment of the present invention, the operation safety coefficient corresponding to each energy storage battery at each test time point is specifically analyzed by: according to the box body temperature T of each energy storage battery at each test time point ir Sum sound decibel B ir Where r is expressed as the number of each test time point, r=1, 2., where, t is the number of times, analyzing operation safety coefficients of each energy storage battery corresponding to each test time pointWherein T 'and B' are the preset proper temperatures of the box body, and proper sound decibels and rho generated when the energy storage battery operates 1 、ρ 2 The safety influence factor is suitable for the preset box body temperature and the sound decibel.
According to the invention, the operation safety of the energy storage battery is analyzed through the box body temperature and the sound decibel of the energy storage battery in the operation safety analysis module of the energy storage battery, so that the phenomena of overhigh temperature and loud noise of the energy storage battery are avoided, meanwhile, the harm to the environment is reduced, the accuracy of analysis of the health evaluation coefficient of the energy storage battery is ensured, and the charge and discharge efficiency of the battery energy storage power station is improved to a certain extent.
The energy storage battery appearance defect analysis module is used for acquiring appearance images of all the energy storage batteries at all the test time points from monitoring in the energy storage power station, and further analyzing appearance damage coefficients of all the energy storage batteries at all the test time points.
In a specific embodiment of the present invention, the analysis of the appearance damage coefficient of each energy storage battery at each test time point includes the following specific steps: according to the appearance image of each energy storage battery at each test time, extracting the gray value range of the corresponding crack of the energy storage battery from the cloud database, analyzing each crack region corresponding to each energy storage battery at each test time point, acquiring the longest length of each energy storage battery in each crack region corresponding to each test time point, and marking the longest length as the length corresponding to each crack region corresponding to each energy storage battery at each test time pointWhere b is expressed as the number of each test time point, b=1, 2, c, f are denoted as the numbers of the respective crack regions, f=1, 2.
It should be noted that, each crack region corresponding to each energy storage battery at each test time point is analyzed, and the specific method is as follows: according to the appearance images of the energy storage batteries at the test time, the gray values of the energy storage batteries at the test time are obtained and compared with the gray value range of the cracks, if the gray value of the energy storage battery at the test time is between the gray value range of the cracks, the gray value is marked as the gray value of the cracks, the gray value of the cracks of the energy storage batteries at the test time is screened, the area of the gray value of the cracks of the energy storage batteries at the test time is obtained, the area of the gray value of the cracks of the energy storage batteries at the test time is marked as the crack area, and accordingly the crack area corresponding to the energy storage batteries at the test time is obtained.
Counting the number SS of crack areas of each energy storage battery at each test time point ib Analyzing crack risk coefficients corresponding to each energy storage battery at each test time pointWherein SS' is the number of preset allowable fracture zones, alpha 1 、α 2 The preset fracture length and the preset proportion factors corresponding to the number of the fracture areas are respectively adopted.
Similarly, the corrosion risk coefficient XS of each energy storage battery at each test time point is analyzed ib 。
Comprehensively analyzing the appearance damage coefficient of each energy storage battery at each test time point
According to the invention, the image of the energy storage battery is obtained through monitoring in the energy storage power station in the energy storage battery appearance defect analysis module, so that the appearance defect coefficient of the energy storage battery is analyzed, and data support is provided for the analysis of the health evaluation coefficient of the energy storage battery.
The energy storage battery health state evaluation module is used for analyzing health evaluation coefficients corresponding to the energy storage batteries.
In a specific embodiment of the present invention, the specific calculation formula for analyzing the health evaluation coefficient corresponding to each energy storage battery is:
wherein t is the number of test time points, c is the number of test time points, τ 1 、τ 2 、τ 3 、τ 4 The method is characterized by respectively comprising preset duty ratio coefficients corresponding to charging quality, discharging quality, operation safety and appearance damage.
According to the invention, the health evaluation coefficient of the energy storage battery is comprehensively analyzed in the health state evaluation module of the energy storage battery, and the analysis dimension is more diversified, so that the accuracy and scientificity of the analysis result of the health evaluation coefficient of the energy storage battery are ensured.
The early warning terminal is used for carrying out corresponding early warning based on the operation safety coefficient corresponding to each energy storage battery at each test time point, the appearance damage coefficient of each energy storage battery at each test time point and the health evaluation coefficient corresponding to each energy storage battery.
It should be noted that, based on the operation safety coefficient corresponding to each energy storage battery at each test time point, the appearance damage coefficient of each energy storage battery at each test time point, and the health evaluation coefficient corresponding to each energy storage battery, the specific method is as follows: comparing the operation safety coefficient corresponding to each energy storage battery at each test time point with a preset operation safety coefficient threshold value, if the operation safety coefficient corresponding to a certain energy storage battery at a certain test time point is smaller than the operation safety coefficient threshold value, transmitting the number of the energy storage battery to related management personnel at the test time point, carrying out operation safety abnormality early warning, and carrying out appearance damage early warning and health assessment abnormality early warning in the same way.
The cloud database is used for storing the expected charge quantity corresponding to each charge of each energy storage battery and storing the gray value range of the crack corresponding to the energy storage battery.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art of describing particular embodiments without departing from the structures of the invention or exceeding the scope of the invention as defined by the claims.
Claims (9)
1. The utility model provides a scale battery energy storage power station running state control evaluation system which characterized in that includes:
the energy storage power station monitoring module is used for monitoring each energy storage battery in the energy storage power station;
the energy storage battery charging quality evaluation module is used for extracting operation parameters and actual charging amounts corresponding to the charging of each energy storage battery from an energy storage battery operation background, and further analyzing charging quality evaluation coefficients corresponding to each energy storage battery;
the energy storage battery discharge quality evaluation module is used for extracting the actual discharge quantity and the operation parameters corresponding to each discharge of each energy storage battery from the energy storage battery operation background, acquiring the actual receiving quantity and the receiving parameters corresponding to the discharge object of each discharge of each energy storage battery, and further analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery;
the energy storage battery operation safety analysis module is used for acquiring operation parameters of each energy storage battery at each test time point, wherein the operation parameters comprise box body temperature and sound decibels, and analyzing operation safety coefficients of each energy storage battery at each test time point;
the energy storage battery appearance defect analysis module is used for acquiring appearance images of all the energy storage batteries at all the test time points from monitoring in the energy storage power station, and further analyzing appearance damage coefficients of all the energy storage batteries at all the test time points;
the energy storage battery health state evaluation module is used for analyzing health evaluation coefficients corresponding to the energy storage batteries;
the early warning terminal is used for carrying out corresponding early warning based on the operation safety coefficient corresponding to each energy storage battery at each test time point, the appearance damage coefficient of each energy storage battery at each test time point and the health evaluation coefficient corresponding to each energy storage battery;
and the cloud database is used for storing the expected charge quantity corresponding to each charge of each energy storage battery and storing the gray value range of the crack corresponding to the energy storage battery.
2. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 1, wherein: the operation parameters comprise charging current and charging voltage corresponding to each detection time point.
3. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 2, wherein: the operation parameters comprise discharge current and discharge voltage corresponding to each discharge time point, and the receiving parameters comprise receiving current and receiving voltage of each receiving time point.
4. A system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 3, wherein: the specific method for analyzing the charging quality evaluation coefficient corresponding to each energy storage battery comprises the following steps:
extracting charging current I corresponding to each detection time point of each charge of each energy storage battery from operation parameters corresponding to each charge of each energy storage battery im,p And a charging voltage U im,p Where i is denoted as the number of each energy storage battery, i=1, 2,..n, m is denoted as the number of each charge, m=1, 2,..l, p is denoted as the number of each detection time point, p=1, 2,..q;
according to a predefined safety current interval corresponding to the energy storage battery, and obtaining a safety current lower limit value I corresponding to the energy storage battery from the safety current interval Lower part(s) And a safety upper limit value I Upper part Analyzing the charging current coincidence coefficient corresponding to each charging of each energy storage batteryWherein I' represents a preset allowable current error;
screening the maximum charging current corresponding to each charging of each energy storage battery from the charging current corresponding to each charging of each energy storage battery at each detection time pointAnd minimum charging current->Analyzing charging current deviation coefficient corresponding to each charging of each energy storage battery>Wherein I is im,p+1 The charging current corresponding to the (p+1) th detection time point is represented by the mth charging of the ith energy storage battery, q is represented by the number of detection time points, and I' is represented by the allowable error between the preset maximum charging current and the preset minimum charging current, lambda 1 、λ 2 Respectively representing the deviation between the preset maximum charging current and the preset minimum charging current and the weight coefficients respectively corresponding to the overall errors of the charging currents;
comparing the charging current coincidence coefficient corresponding to each charge of each energy storage battery with a preset charging current coincidence coefficient threshold value, if the charging current coincidence coefficient corresponding to a certain charge of a certain energy storage battery is greater than or equal to the charging current coincidence coefficient threshold value, marking the charge as current normal charge, further obtaining each normal current charge of each energy storage battery, and counting the times CI of the current normal charge of each energy storage battery i ；
Counting the total charging times CS corresponding to each energy storage battery i Analyzing the charging current quality coefficient corresponding to each energy storage batteryWherein l is denoted as the number of charging times;
analyzing the quality coefficient of the charging voltage corresponding to each energy storage battery according to the charging voltage corresponding to each detection time point of each charging to which each energy storage battery belongs
Extracting predicted charge quantity Q' corresponding to each charge of each energy storage battery from cloud database im According to the corresponding charging of each energy storage batteryActual charge amount Q im Further analyzing the charging electric quantity coincidence coefficient corresponding to each charging of each energy storage batteryWherein e is represented as a natural constant;
analyzing the charge quality evaluation coefficients corresponding to the energy storage batteriesWherein gamma is 1 、γ 2 、γ 3 Respectively representing the preset charging current quality, charging voltage quality and charging electric quantity to accord with corresponding duty ratio factors.
5. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 4, wherein: the charging voltage quality coefficient corresponding to each energy storage battery comprises the following specific steps:
analyzing a charging voltage evaluation index corresponding to each charging of each energy storage battery according to the charging voltage corresponding to each charging of each energy storage battery at each detection time pointWherein U' represents a preset safety voltage;
obtaining the maximum charging voltage of each charge of each energy storage battery according to the charging voltage corresponding to each charge of each energy storage battery at each detection time pointAnd minimum charging voltage>
Screening the maximum charge voltage evaluation index corresponding to each energy storage battery based on the charge voltage evaluation index corresponding to each charge to which each energy storage battery belongsAnd a minimum charge voltage evaluation index->
The method is consistent with the analysis method of each normal current charging of each energy storage battery, each normal voltage charging of each energy storage battery is analyzed, and the frequency CY of each energy storage battery corresponding to the normal voltage charging is counted i ；
Analyzing the quality coefficient of the charging voltage corresponding to each energy storage batteryWherein U 'is a preset allowable voltage error, D' is a preset allowable charging voltage evaluation index error, χ 1 、χ 2 、χ 3 、χ 4 Respectively corresponding weight factors of preset voltage evaluation, voltage deviation, voltage evaluation error and normal voltage charging times.
6. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 4, wherein: the specific method for analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage battery comprises the following steps:
analyzing the discharge current quality coefficient xi corresponding to each energy storage battery in accordance with the charge current quality coefficient corresponding to each energy storage battery i ；
Analyzing the discharge voltage quality coefficient zeta corresponding to each energy storage battery in accordance with the charge voltage quality coefficient corresponding to each energy storage battery i ；
Extracting the receiving current IJ of the discharge object corresponding to each discharge of each energy storage battery at each receiving time point from the receiving parameters corresponding to each discharge of each energy storage battery ihx And a receiving voltage UJ ihx Where h is denoted as the number of each discharge, h=1, 2,..g, where x is denoted as the number of each reception time point, x=1, 2,..y;
analyzing the received current voltage stability coefficient of the discharge object corresponding to each discharge of each energy storage batteryWhere y is the number of receive time points, delta 1 、δ 2 Respectively setting correction factors corresponding to preset current stability and voltage stability;
the actual discharge quantity corresponding to each discharge of each energy storage batteryAnd the actual received power to which the corresponding discharge object belongs +.>Analyzing discharge efficiency evaluation index corresponding to each discharge of each energy storage battery>
Analyzing the comprehensive discharge quality evaluation coefficient corresponding to each energy storage batteryWherein beta is 1 、β 2 、β 3 、β 4 Respectively expressed as preset discharge current quality, discharge voltage quality, receiving current voltage quality and discharge efficiency evaluation corresponding proportionality coefficients.
7. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 1, wherein: the operation safety coefficient corresponding to each energy storage battery at each test time point is specifically analyzed by the following method:
according to the box body temperature T of each energy storage battery at each test time point ir Sum sound decibel B ir Wherein r represents the number of each test time point, r=1, 2,..and t, and analyzing the operation safety coefficient corresponding to each energy storage battery at each test time pointWherein T 'and B' are preset proper temperature and energy storage of the box bodyAppropriate sound decibels, ρ generated during battery operation 1 、ρ 2 The safety influence factor is suitable for the preset box body temperature and the sound decibel.
8. The system for monitoring and evaluating the operating state of a large-scale battery energy storage power station according to claim 7, wherein: the method for analyzing the appearance damage coefficient of each energy storage battery at each test time point comprises the following specific steps:
according to the appearance image of each energy storage battery at each test time, extracting the gray value range of the corresponding crack of the energy storage battery from the cloud database, analyzing each crack region corresponding to each energy storage battery at each test time point, acquiring the longest length of each energy storage battery in each crack region corresponding to each test time point, and marking the longest length as the length corresponding to each crack region corresponding to each energy storage battery at each test time pointWhere b is expressed as the number of each test time point, b=1, 2, c, f represents the number of each crack region, f=1, 2,. -%, d;
counting the number SS of crack areas of each energy storage battery at each test time point ib Analyzing crack risk coefficients corresponding to each energy storage battery at each test time pointWherein SS' is the number of preset allowable fracture zones, alpha 1 、α 2 The ratio factors are respectively corresponding to the preset crack length and the number of the crack areas;
similarly, the corrosion risk coefficient XS of each energy storage battery at each test time point is analyzed ib ；
Comprehensively analyzing the appearance damage coefficient of each energy storage battery at each test time point
9. According to claimThe system for monitoring and evaluating the operating state of a large-scale battery energy storage power station as claimed in claim 8, wherein the system is characterized in that: the specific calculation formula of the health evaluation coefficient corresponding to each energy storage battery is as follows:wherein t is the number of test time points, c is the number of test time points, τ 1 、τ 2 、τ 3 、τ 4 The method is characterized by respectively comprising preset duty ratio coefficients corresponding to charging quality, discharging quality, operation safety and appearance damage.
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| CN117081122A (en) * | 2023-10-16 | 2023-11-17 | 天津市普迅电力信息技术有限公司 | Running state analysis system based on distributed energy storage device |
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| CN117525692A (en) * | 2023-10-26 | 2024-02-06 | 苏州华骞时代新能源科技有限公司 | Control method and system of safe energy storage system |
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| CN117081122A (en) * | 2023-10-16 | 2023-11-17 | 天津市普迅电力信息技术有限公司 | Running state analysis system based on distributed energy storage device |
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| CN117525692A (en) * | 2023-10-26 | 2024-02-06 | 苏州华骞时代新能源科技有限公司 | Control method and system of safe energy storage system |
| CN117134506A (en) * | 2023-10-27 | 2023-11-28 | 广州能信数字科技有限公司 | Electric energy storage safety monitoring system based on power grid dispatching |
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| CN117233648A (en) * | 2023-11-14 | 2023-12-15 | 深圳市伟鹏世纪科技有限公司 | Outdoor operation intelligent early warning system suitable for energy storage power supply |
| CN117233648B (en) * | 2023-11-14 | 2024-01-23 | 深圳市伟鹏世纪科技有限公司 | Outdoor operation intelligent early warning system suitable for energy storage power supply |
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