CN117406104A - Monitoring method, device, equipment and storage medium for cell data of energy storage power station - Google Patents
Monitoring method, device, equipment and storage medium for cell data of energy storage power station Download PDFInfo
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- CN117406104A CN117406104A CN202311169475.9A CN202311169475A CN117406104A CN 117406104 A CN117406104 A CN 117406104A CN 202311169475 A CN202311169475 A CN 202311169475A CN 117406104 A CN117406104 A CN 117406104A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 38
- 238000004146 energy storage Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000012360 testing method Methods 0.000 claims abstract description 117
- 238000007405 data analysis Methods 0.000 claims abstract description 60
- 238000007599 discharging Methods 0.000 claims abstract description 60
- 238000000540 analysis of variance Methods 0.000 claims abstract description 29
- 230000002159 abnormal effect Effects 0.000 claims abstract description 23
- 238000001514 detection method Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 12
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- 230000005856 abnormality Effects 0.000 claims description 5
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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- 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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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Abstract
The invention discloses a method, a device, equipment and a storage medium for monitoring cell data of an energy storage power station, wherein the method comprises the following steps: acquiring charging voltage data of each cell device in a battery cluster in an energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state; establishing a battery cell voltage data analysis of variance hypothesis test, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing charging voltage data or discharging voltage data of each battery cell device in the battery cluster; when the test result of the analysis of variance assumption test of the cell voltage data is accepted, monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal; and when judging that the test result of the analysis of variance hypothesis test of the cell voltage data is refused, monitoring that the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster is abnormal.
Description
Technical Field
The invention relates to the technical field of energy storage power stations, in particular to a method, a device, equipment and a storage medium for monitoring cell data of an energy storage power station.
Background
There are a large number of electrochemical cell devices in electrochemical energy storage power stations. In the daily operation process of the energy storage power station, the difference condition between the voltage values of the electric cores needs to be paid attention to. In the case of normal operation, the voltage data between the cells of the same energy storage unit should be at the same level.
The current common index difference level monitoring mode between the battery cells is to monitor the highest voltage and the lowest voltage under the same battery cluster and the corresponding battery cell equipment numbers, then display the highest voltage and the lowest voltage in the battery cluster in an operation and maintenance management informatization system of an energy storage power station in a numerical value or graph form, and an operation and maintenance manager judges the balance condition between the battery cells in the appointed battery cluster by observing the two groups of numerical values of the highest voltage and the lowest voltage in the battery cluster. This approach requires experience from the operation and maintenance manager to determine the core related index balance.
In addition, the number of the observation indexes can be reduced by automatically observing the form of data discrete degree parameters such as the voltage range, standard deviation or discrete rate in the battery cluster, so that the manual efficiency is improved, but the related indexes still need to judge whether the index values are normal or not by the experience of operation and maintenance personnel, so that whether the specific discrete degree is within a reasonable range or not is judged.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for monitoring cell data of an energy storage power station, so as to solve the technical problem of judging the balance condition among cells in a specified battery cluster.
The embodiment of the invention provides a method for monitoring cell data of an energy storage power station, which comprises the following steps:
acquiring charging voltage data of each cell device in a battery cluster in an energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state;
establishing a battery cell voltage data analysis of variance hypothesis test, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing charging voltage data or discharging voltage data of each battery cell device in the battery cluster;
when the test result of the analysis of variance assumption test of the cell voltage data is accepted, monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal;
and when judging that the test result of the analysis of variance hypothesis test of the cell voltage data is refused, monitoring that the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster is abnormal.
Preferably, using the charging voltage data or the discharging voltage data of each cell device in the battery cluster, determining whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected includes:
calculating inter-group mean square and intra-group mean square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster, and calculating F statistics of all the cell devices in the battery cluster according to the inter-group mean square and intra-group mean square of all the cell devices in the battery cluster;
and judging whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing F statistics of all cell devices in the battery cluster.
Preferably, calculating the inter-group mean square and the intra-group mean square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster includes:
calculating the inter-group square sum and the intra-group square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster;
calculating the degree of freedom between groups and the degree of freedom in groups of all the battery cell devices in the battery cluster by using the square between groups and the square in groups of all the battery cell devices in the battery cluster;
and calculating the inter-group mean square of all the cell devices in the battery cluster according to the inter-group square sum of the cell devices in the battery cluster and the inter-group degree of freedom, and calculating the intra-group mean square of all the cell devices in the battery cluster according to the intra-group square sum of the cell devices in the battery cluster.
Preferably, using the F statistics of all the cell devices in the battery cluster, determining whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected includes:
when F statistics of all the battery cell devices in the battery cluster are larger than a preset threshold, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused;
when the F statistics of all the battery cell devices in the battery cluster is not greater than a preset threshold, acquiring probability values of all the battery cell devices in the battery cluster by querying an F distribution probability statistics table, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused when the probability values are not greater than a significance level value preset by a user, and judging that the test result of the battery cell voltage data analysis of variance hypothesis test is accepted when the probability values are greater than the significance level value preset by the user.
Preferably, after monitoring that there is an abnormality in the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster, the method further includes:
obtaining N battery cell equipment groups comprising a plurality of battery cell equipment by carrying out average division processing on all battery cell equipment in the battery cluster, and respectively obtaining charging voltage data of each battery cell equipment in each battery cell equipment group in a first time period in a charging state or discharging voltage data in each battery cell equipment in a second time period in a discharging state;
establishing a battery cell voltage data analysis of variance hypothesis test for each battery cell equipment group, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is refused or not by utilizing charging voltage data or discharging voltage data of each battery cell equipment in the battery cell equipment group;
when the test result of the electrical core voltage data analysis of variance hypothesis test is judged to be refused, further judging whether the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is two or three, and searching for abnormal electrical core devices in the electrical core device group when the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is judged to be two or three.
Preferably, when the number of the battery cell devices in the battery cell device group for which the test result of the analysis of variance assumption test of the battery cell voltage data is determined to be rejected is two or three, searching for the abnormal battery cell devices in the battery cell device group includes:
subtracting the charging voltage data or discharging voltage data of each cell device in the cell device group with the refused checking result of the cell voltage data analysis of variance hypothesis checking from the charging voltage data or discharging voltage data of the normal cell device respectively to obtain a charging voltage data difference value or a discharging voltage data difference value of each cell device and the normal cell device, and selecting at least one cell device from the two or three cell devices as an abnormal cell device in the cell device group according to the charging voltage data difference value or the discharging voltage data difference value.
Preferably, the method further comprises:
and when the detection result of the electrical core voltage data analysis of variance hypothesis detection is judged to be refused and the number of the electrical core devices in the electrical core device group is judged to be more than three, continuing to perform electrical core voltage data analysis of variance hypothesis detection processing on all the electrical core devices in the electrical core device group of which the detection result of the electrical core voltage data analysis of variance hypothesis detection is refused until abnormal electrical core devices are found.
The invention also provides a device for monitoring the cell data of the energy storage power station, which comprises the following steps:
the acquisition module is used for acquiring charging voltage data of each cell device in the battery cluster in the energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state;
the establishing and judging module is used for establishing the analysis of variance hypothesis test of the cell voltage data and judging whether the test result of the analysis of variance hypothesis test of the established cell voltage data is accepted or rejected by utilizing the charge voltage data or the discharge voltage data of each cell device in the battery cluster;
the monitoring module is used for monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be accepted, and monitoring that the charging voltage data or the discharging voltage data of at least one cell device in the battery cluster is abnormal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be refused.
The invention also provides an electronic device, comprising: a memory; a processor; a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement a method of monitoring energy storage plant cell data.
The present invention also provides a computer-readable storage medium having a computer program stored thereon; the computer program is executed by a processor to implement a method for monitoring cell data of an energy storage power station.
The method has the advantages that whether the voltage data of the cell equipment in the appointed battery cluster are at the same level is monitored by establishing the analysis of variance assumption test of the voltage data of the cell, so that the time for identifying abnormal cell equipment is shortened, a large amount of manpower resources are saved, and the accuracy is improved.
Drawings
FIG. 1 is a flow chart of a method for monitoring cell data of an energy storage power station;
FIG. 2 is a schematic diagram of a monitoring device for cell data of an energy storage power station according to the present invention;
FIG. 3 is a flow chart of a method for monitoring cell data of an energy storage power station provided by the invention;
fig. 4 is a flow chart of the electrical core data analysis of variance hypothesis test provided by the invention.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In the following description, suffixes such as "module", "part" or "unit" for representing elements are used only for facilitating the description of the present invention, and have no particular meaning in themselves. Thus, "module," "component," or "unit" may be used in combination.
Fig. 1 is a flowchart of a method for monitoring cell data of an energy storage power station according to the present invention, where, as shown in fig. 1, the method may include:
step S101: acquiring charging voltage data of each cell device in a battery cluster in an energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state;
step S102: establishing a battery cell voltage data analysis of variance hypothesis test, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing charging voltage data or discharging voltage data of each battery cell device in the battery cluster;
step S103: when the test result of the analysis of variance assumption test of the cell voltage data is accepted, monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal;
step S104: and when judging that the test result of the analysis of variance hypothesis test of the cell voltage data is refused, monitoring that the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster is abnormal.
Specifically, using the charging voltage data or the discharging voltage data of each cell device in the battery cluster, determining whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected includes: calculating inter-group mean square and intra-group mean square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster, and calculating F statistics of all the cell devices in the battery cluster according to the inter-group mean square and intra-group mean square of all the cell devices in the battery cluster; and judging whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing F statistics of all cell devices in the battery cluster.
Further, calculating the inter-group mean square and intra-group mean square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster comprises: calculating the inter-group square sum and the intra-group square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster; calculating the degree of freedom between groups and the degree of freedom in groups of all the battery cell devices in the battery cluster by using the square between groups and the square in groups of all the battery cell devices in the battery cluster; and calculating the inter-group mean square of all the cell devices in the battery cluster according to the inter-group square sum of the cell devices in the battery cluster and the inter-group degree of freedom, and calculating the intra-group mean square of all the cell devices in the battery cluster according to the intra-group square sum of the cell devices in the battery cluster.
Further, using the F statistics of all the cell devices in the battery cluster, determining whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected includes: when F statistics of all the battery cell devices in the battery cluster are larger than a preset threshold, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused; when the F statistics of all the battery cell devices in the battery cluster is not greater than a preset threshold, acquiring probability values of all the battery cell devices in the battery cluster by querying an F distribution probability statistics table, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused when the probability values are not greater than a significance level value preset by a user, and judging that the test result of the battery cell voltage data analysis of variance hypothesis test is accepted when the probability values are greater than the significance level value preset by the user.
After monitoring that the charging voltage data or the discharging voltage data of at least one cell device in the battery cluster is abnormal, the embodiment of the invention further comprises the following steps: obtaining N battery cell equipment groups comprising a plurality of battery cell equipment by carrying out average division processing on all battery cell equipment in the battery cluster, and respectively obtaining charging voltage data of each battery cell equipment in each battery cell equipment group in a first time period in a charging state or discharging voltage data in each battery cell equipment in a second time period in a discharging state; establishing a battery cell voltage data analysis of variance hypothesis test for each battery cell equipment group, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is refused or not by utilizing charging voltage data or discharging voltage data of each battery cell equipment in the battery cell equipment group; when the test result of the electrical core voltage data analysis of variance hypothesis test is judged to be refused, further judging whether the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is two or three, and searching for abnormal electrical core devices in the electrical core device group when the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is judged to be two or three.
When the number of the battery cell devices in the battery cell device group, of which the test results of the battery cell voltage data analysis of variance hypothesis test are refused, is two or three, searching the abnormal battery cell devices in the battery cell device group comprises: subtracting the charging voltage data or discharging voltage data of each cell device in the cell device group with the refused checking result of the cell voltage data analysis of variance hypothesis checking from the charging voltage data or discharging voltage data of the normal cell device respectively to obtain a charging voltage data difference value or a discharging voltage data difference value of each cell device and the normal cell device, and selecting at least one cell device from the two or three cell devices as an abnormal cell device in the cell device group according to the charging voltage data difference value or the discharging voltage data difference value.
The embodiment of the invention also comprises the following steps: and when the detection result of the electrical core voltage data analysis of variance hypothesis detection is judged to be refused and the number of the electrical core devices in the electrical core device group is judged to be more than three, continuing to perform electrical core voltage data analysis of variance hypothesis detection processing on all the electrical core devices in the electrical core device group of which the detection result of the electrical core voltage data analysis of variance hypothesis detection is refused until abnormal electrical core devices are found.
Fig. 2 is a schematic diagram of a monitoring device for cell data of an energy storage power station according to the present invention, as shown in fig. 2, including: the acquisition module is used for acquiring charging voltage data of each cell device in the battery cluster in the energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state; the establishing and judging module is used for establishing the analysis of variance hypothesis test of the cell voltage data and judging whether the test result of the analysis of variance hypothesis test of the established cell voltage data is accepted or rejected by utilizing the charge voltage data or the discharge voltage data of each cell device in the battery cluster; the monitoring module is used for monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be accepted, and monitoring that the charging voltage data or the discharging voltage data of at least one cell device in the battery cluster is abnormal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be refused.
The embodiment of the invention provides electronic equipment, which comprises: a memory; a processor; a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement a method of monitoring energy storage plant cell data.
Embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon; the computer program is executed by a processor to implement a method for monitoring cell data of an energy storage power station.
Analysis of variance (ANOVA), also known as "variance analysis," is a method of testing for the significance of differences between two or more sets of data samples. The purpose of the analysis of variance is to verify whether the average number of each group is the same hypothesis testing method. The premise of analysis of variance requires that the data set follow a positive-going distribution. The voltage data set of the battery cells is verified to follow a positive distribution during successive charge or discharge state periods of the battery cluster.
For each cell device in the same battery cluster, if enough cell voltage time series data can be obtained for a past period of time, it can be found whether each cell voltage data is at the same level for a past period of complete charge/discharge time by performing a hypothesis test based on "analysis of variance". However, if it is found that the voltage data of each cell associated in a certain battery cluster is not at the same level, only one round of analysis of variance cannot tell which specific cell device has an abnormality, so that it is necessary to detect the number of the cell device not at the same level as other cells by applying the analysis of variance hypothesis test multiple times. The method for identifying the problem cell is realized by reducing the participation quantity of telecommunication equipment in the analysis of variance hypothesis test model, wherein the method is divided into two groups of data according to the serial numbers of the cell equipment, and the analysis of variance hypothesis test is carried out again on the cell data in each group. For the group with problems, the equipartition is continued until the analysis of variance hypothesis test model between 2 and 3 telecommunication devices is subdivided, so that the device number of the problem cell can be identified.
Fig. 3 is a flowchart of a method for monitoring cell data of an energy storage power station provided by the present invention, as shown in fig. 3, including:
1. acquiring data: there is a need to obtain voltage data from an energy storage power station monitoring system for cell devices associated with a given battery cluster over a period of continuous and complete charge/discharge time period over a period of time.
2. An analysis of variance hypothesis test was established as shown in fig. 4.
2.1 set confidence level 1- α, default value of 1- α is 95% (α is "significance level", i.e., the threshold for judging a small probability event).
2.2, establishing a primary assumption H0-the voltage data of all the battery cell devices are consistent:
H0:V cell-1 ＝V cell-2 ＝...＝V cell-n
2.3 creating alternative hypothesis H1-at least one cell voltage data is inconsistent.
2.4 calculating inter-group mean square MSB and intra-group mean square MSE of all cell devices of the battery cluster
1) First, the sum of squares between groups SS is calculated M Sum and intra-group sum of squares SS E :
Wherein V is cell-i[t] Representing voltage data of the battery cell equipment i at the moment t; v (V) ave-i Representing the average value of voltage data of the battery cell equipment i in a specified time period; v (V) AVE Representing the total average of all cell device voltage datasets over a specified period of time.
2) Secondly, calculating the degree of freedom df between groups m Degree of freedom df in group e ：
df m ＝n-1
df e ＝n×(T-1)
Wherein n represents the number of the battery cell devices; t represents the number of consecutive samples of the cell device voltage over a specified period of time.
3) And finally calculating the MSB of the inter-group mean square and the MSE of the intra-group mean square.
2.5 calculating F statistics:
2.6 judging based on the F statistic value:
if F statistic > 1: the original hypothesis is directly rejected.
If F statistic is less than or equal to 1: the p-value (probability value) is calculated by the following formula, the corresponding physical meaning being the probability that the voltage levels of all the cell devices are identical during the selected charge/discharge time period.
Wherein F represents F statistic; n1, n2 represent the degrees of freedom of the dataset, n1>0, n2>0, and are integers.
2.7 comparing P and α to determine if the original hypothesis is accepted: if P > alpha, the original assumption is not refused, and all the cell voltage data under the selected battery cluster can be considered to be always on the same horizontal line in the selected complete charge/discharge time period; if P.ltoreq.α, the original assumption is rejected that the voltage data of at least one cell device is not on the same horizontal line as the other cells during the selected complete charge/discharge period.
3. And judging according to the hypothesis test result:
-not rejecting the original hypothesis: and judging that the voltage data of each cell device in the range of the selected cell device associated with the designated battery cluster has no abnormal condition.
-reject the original hypothesis: and (3) abnormal voltage data of the cell equipment exists in the range of the cell equipment selected by the appointed battery cluster.
4. And (3) continuously establishing 'cell voltage data analysis of variance hypothesis test' based on the step (2) in the range of the cell equipment for finding the voltage data abnormality of the cell equipment until the number of the cell equipment participating in the analysis of variance hypothesis test is reduced to 2 or 3, so that the range of the cell equipment for finding the voltage abnormality can be reduced to the minimum.
5. Finally, the average value of the voltage data of the 2 battery cells can be compared with the voltage data of the battery cells which are ascertained to be normal, so that the voltage data of which battery cell is larger or smaller than the normal voltage value can be determined.
The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, and thus do not limit the scope of the claims of the present invention. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the present invention shall fall within the scope of the appended claims.
Claims (10)
1. The method for monitoring the cell data of the energy storage power station is characterized by comprising the following steps of:
acquiring charging voltage data of each cell device in a battery cluster in an energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state;
establishing a battery cell voltage data analysis of variance hypothesis test, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing charging voltage data or discharging voltage data of each battery cell device in the battery cluster;
when the test result of the analysis of variance assumption test of the cell voltage data is accepted, monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal;
and when judging that the test result of the analysis of variance hypothesis test of the cell voltage data is refused, monitoring that the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster is abnormal.
2. The method of claim 1, wherein determining whether the test result of the cell voltage data anova hypothesis test is accepted or rejected using the charge voltage data or the discharge voltage data for each cell device in the battery cluster comprises:
calculating inter-group mean square and intra-group mean square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster, and calculating F statistics of all the cell devices in the battery cluster according to the inter-group mean square and intra-group mean square of all the cell devices in the battery cluster;
and judging whether the test result of the cell voltage data analysis of variance hypothesis test is accepted or rejected by utilizing F statistics of all cell devices in the battery cluster.
3. The method of claim 2, wherein calculating inter-group mean and intra-group mean for all cell devices in the battery cluster using the charge voltage data or the discharge voltage data for each cell device in the battery cluster comprises:
calculating the inter-group square sum and the intra-group square of all the cell devices in the battery cluster by using the charging voltage data or the discharging voltage data of each cell device in the battery cluster;
calculating the degree of freedom between groups and the degree of freedom in groups of all the battery cell devices in the battery cluster by using the square between groups and the square in groups of all the battery cell devices in the battery cluster;
and calculating the inter-group mean square of all the cell devices in the battery cluster according to the inter-group square sum of the cell devices in the battery cluster and the inter-group degree of freedom, and calculating the intra-group mean square of all the cell devices in the battery cluster according to the intra-group square sum of the cell devices in the battery cluster.
4. The method of claim 2, wherein determining whether the test result of the cell voltage data anova hypothesis test is accepted or rejected using F statistics for all cell devices in the battery cluster comprises:
when F statistics of all the battery cell devices in the battery cluster are larger than a preset threshold, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused;
when the F statistics of all the battery cell devices in the battery cluster is not greater than a preset threshold, acquiring probability values of all the battery cell devices in the battery cluster by querying an F distribution probability statistics table, judging that the test result of the battery cell voltage data analysis of variance hypothesis test is refused when the probability values are not greater than a significance level value preset by a user, and judging that the test result of the battery cell voltage data analysis of variance hypothesis test is accepted when the probability values are greater than the significance level value preset by the user.
5. The method of claim 1, wherein after monitoring that there is an abnormality in the charge voltage data or the discharge voltage data of at least one cell device in the battery cluster, further comprising:
obtaining N battery cell equipment groups comprising a plurality of battery cell equipment by carrying out average division processing on all battery cell equipment in the battery cluster, and respectively obtaining charging voltage data of each battery cell equipment in each battery cell equipment group in a first time period in a charging state or discharging voltage data in each battery cell equipment in a second time period in a discharging state;
establishing a battery cell voltage data analysis of variance hypothesis test for each battery cell equipment group, and judging whether a test result of the established battery cell voltage data analysis of variance hypothesis test is refused or not by utilizing charging voltage data or discharging voltage data of each battery cell equipment in the battery cell equipment group;
when the test result of the electrical core voltage data analysis of variance hypothesis test is judged to be refused, further judging whether the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is two or three, and searching for abnormal electrical core devices in the electrical core device group when the number of electrical core devices in the electrical core device group of which the test result of the electrical core voltage data analysis of variance hypothesis test is refused is judged to be two or three.
6. The method of claim 5, wherein when the number of the cell devices in the cell device group for which the result of the analysis of variance hypothesis test of the cell voltage data is determined to be rejected is two or three, searching for the abnormal cell devices in the cell device group comprises:
subtracting the charging voltage data or discharging voltage data of each cell device in the cell device group with the refused checking result of the cell voltage data analysis of variance hypothesis checking from the charging voltage data or discharging voltage data of the normal cell device respectively to obtain a charging voltage data difference value or a discharging voltage data difference value of each cell device and the normal cell device, and selecting at least one cell device from the two or three cell devices as an abnormal cell device in the cell device group according to the charging voltage data difference value or the discharging voltage data difference value.
7. The method as recited in claim 6, further comprising:
and when the detection result of the electrical core voltage data analysis of variance hypothesis detection is judged to be refused and the number of the electrical core devices in the electrical core device group is judged to be more than three, continuing to perform electrical core voltage data analysis of variance hypothesis detection processing on all the electrical core devices in the electrical core device group of which the detection result of the electrical core voltage data analysis of variance hypothesis detection is refused until abnormal electrical core devices are found.
8. The utility model provides a monitoring devices of energy storage power station electricity core data which characterized in that includes:
the acquisition module is used for acquiring charging voltage data of each cell device in the battery cluster in the energy storage power station in a first time period in a charging state or discharging voltage data in a second time period in a discharging state;
the establishing and judging module is used for establishing the analysis of variance hypothesis test of the cell voltage data and judging whether the test result of the analysis of variance hypothesis test of the established cell voltage data is accepted or rejected by utilizing the charge voltage data or the discharge voltage data of each cell device in the battery cluster;
the monitoring module is used for monitoring that the charging voltage data or the discharging voltage data of all the cell devices in the battery cluster are normal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be accepted, and monitoring that the charging voltage data or the discharging voltage data of at least one cell device in the battery cluster is abnormal when the checking result of the cell voltage data analysis of variance hypothesis checking is judged to be refused.
9. An electronic device, comprising: a memory; a processor; a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon; the computer program being executed by a processor to implement the method of any of claims 1-7.
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