CN116014850A - Energy storage battery control optimization method and device and electronic equipment - Google Patents
Energy storage battery control optimization method and device and electronic equipment Download PDFInfo
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Abstract
The invention discloses an energy storage battery control optimization method, an energy storage battery control optimization device and electronic equipment, wherein the method comprises the following steps: acquiring data information of each battery module in all battery clusters in a target battery system; analyzing the data information to obtain battery state parameters; comparing the battery state parameter with a preset alarm threshold; when the battery state parameter exceeds a preset alarm threshold value, rechecking and checking the battery state parameter; and carrying out error adjustment on the target battery system according to the rechecking and checking result. When the bottom layer battery module generates a data threshold value line crossing alarm condition, the authenticity of the alarm data is judged through rechecking and checking, and the alarm data is adjusted and repaired in a targeted mode according to the checking result, so that the deviation of the system control precision and the accuracy and the abnormal system operation caused by the error of the data acquisition of the bottom terminal are reduced.
Description
Technical Field
The invention relates to the field of energy storage application, in particular to an energy storage battery control optimization method and device and electronic equipment.
Background
Along with the large-scale system entering the engineering application stage, how to ensure the safe operation level of the system, improve the control precision of the system and ensure the accuracy of the automatic action of the system is a difficult problem faced by the engineering application stage and the operation stage. In the energy storage engineering application, the state of the battery system is usually collected, processed and controlled by BMS dispersed in the battery module, and the control reliability and accuracy of the system are difficult to reach the expected target due to the influence of the factors of the system, on one hand, the system is influenced by the single operation and control main body of the BMS, and parameter data cannot be rechecked and checked by the system; on the other hand, due to the restriction of a large number of sensors and electrical connection points in the module, the reliability and the precision of data acquisition cannot be ensured, and the acquired data is deviated and interrupted.
Disclosure of Invention
In view of the above, the embodiment of the invention provides an energy storage battery control optimization method to solve the problems of poor control reliability and poor accuracy of an energy storage battery system in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the embodiment of the invention provides an energy storage battery control optimization method, which comprises the following steps:
acquiring data information of each battery module in all battery clusters in a target battery system, wherein the data information is data for representing a plurality of operation parameters of the battery modules;
analyzing the data information to obtain battery state parameters;
comparing the battery state parameter with a preset alarm threshold;
when the battery state parameter exceeds the preset alarm threshold, checking the battery state parameter;
and carrying out error adjustment on the target battery system according to the rechecking and checking result.
Optionally, the rechecking checking the battery state parameter includes:
re-acquiring the data information of each battery module in all battery clusters in the target battery system as rechecking data;
and verifying the battery state parameters based on the rechecking data to generate a rechecking verification result.
Optionally, the verifying the battery state parameter based on the rechecking data generates a rechecking verification result, including:
analyzing the rechecking data to obtain battery rechecking parameters;
comparing the battery rechecking parameter with the battery state parameter;
when the battery rechecking parameter is different from the battery state parameter, the rechecking verification result shows that an error exists in the target battery system.
Optionally, when there is no error in the result of checking the battery state parameter based on the rechecking data, the checking the battery state parameter further includes:
acquiring historical data information of each battery module in all battery clusters in the target battery system;
and verifying the battery state parameters based on the historical data information to generate a rechecking verification result.
Optionally, the verifying the battery state parameter based on the historical data information generates a rechecking result, including:
obtaining a historical development curve of each state parameter of each battery module based on the historical data information;
predicting the data of the current state parameters according to the change trend of the historical development curve to obtain predicted parameter data;
comparing the predicted parameter data with the battery state parameters;
and when the predicted parameter data is different from the battery state parameter, checking and checking results to obtain errors in the target battery system.
Optionally, the rechecking checking the battery state parameter includes:
extracting parameter information of different battery modules connected in series in the same battery cluster from the battery state parameters for longitudinal comparison;
extracting parameter information of battery modules in adjacent battery clusters from the battery state parameters for transverse comparison;
when the longitudinal comparison result and/or the transverse comparison result are different, the rechecking verification result is that an error exists in the target battery system.
Optionally, the performing error adjustment on the target battery system according to the result of the rechecking verification includes:
when the result of the rechecking and checking is that the error exists in the target battery system, judging an error source according to the rechecking and checking process;
and carrying out error adjustment on the target battery system according to the error source.
The embodiment of the invention also provides an energy storage battery control optimizing device, which comprises the following steps:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring data information of each battery module in all battery clusters in a target battery system, wherein the data information is data for representing a plurality of operation parameters of the battery modules;
the analysis module is used for analyzing the data information to obtain battery state parameters;
the comparison module is used for comparing the battery state parameter with a preset alarm threshold value;
the verification module is used for rechecking and verifying the battery state parameters when the battery state parameters exceed the preset alarm threshold;
and the adjusting module is used for adjusting the error of the target battery system according to the rechecking and checking result.
The embodiment of the invention also provides electronic equipment, which comprises:
the energy storage battery control optimizing method comprises the steps of storing a storage battery, storing computer instructions in the storage, and executing the computer instructions by the processor, so that the energy storage battery control optimizing method is executed.
The embodiment of the invention also provides a computer readable storage medium which stores computer instructions for causing a computer to execute the energy storage battery control optimization method provided by the embodiment of the invention.
The technical scheme of the invention has the following advantages:
the invention provides an energy storage battery control optimization method, which is characterized in that data information of each battery module in all battery clusters in a target battery system is obtained, wherein the data information is data for representing a plurality of operation parameters of the battery modules; analyzing the data information to obtain battery state parameters; comparing the battery state parameter with a preset alarm threshold; when the battery state parameter exceeds a preset alarm threshold value, rechecking and checking the battery state parameter; and carrying out error adjustment on the target battery system according to the rechecking and checking result. When the bottom layer battery module generates a data threshold value line crossing alarm condition, the authenticity of the alarm data is judged through rechecking and checking, and the alarm data is adjusted and repaired in a targeted mode according to the checking result, so that the deviation of the system control precision and the accuracy and the abnormal system operation caused by the error of the data acquisition of the bottom terminal are reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an energy storage battery control optimization method in an embodiment of the invention;
FIG. 2 is a flow chart of re-acquiring data information for review verification according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for verifying battery status parameters based on review data to generate a result of review verification in accordance with an embodiment of the present invention;
FIG. 4 is a flow chart of a review check according to historical data information in an embodiment of the invention;
FIG. 5 is a flow chart of checking by prediction according to an embodiment of the present invention;
FIG. 6 is a flow chart of checking the transverse-longitudinal comparison in accordance with an embodiment of the present invention;
FIG. 7 is a flowchart of performing error adjustment on a target battery system according to a result of rechecking verification in accordance with an embodiment of the invention;
FIG. 8 is a schematic diagram of an energy storage battery control optimizing device according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. 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.
According to an embodiment of the present invention, there is provided an energy storage battery control optimization method embodiment, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different from that herein.
In this embodiment, an energy storage battery control optimization method is provided, which may be used in the above terminal device, such as a computer, as shown in fig. 1, and includes the following steps:
step S1: and acquiring data information of each battery module in all battery clusters in the target battery system, wherein the data information is data for representing a plurality of operation parameters of the battery modules. Specifically, the process of obtaining the data information includes: collecting battery data of each battery module; classifying the battery data according to the parameter types; and coding and protocol conversion are carried out on the classified battery data, so that data information which can be identified by the target battery system is generated.
Step S2: and analyzing the data information to obtain the battery state parameters. Specifically, the data information is analyzed and calculated, and the voltage, current, resistance, temperature, SOC, SOH and other battery parameters of the battery are synthesized from the data information, so that the operation and the health state of the battery can be reflected through the parameters.
Step S3: and comparing the battery state parameter with a preset alarm threshold. Specifically, abnormal data can be found and timely alarmed through comparison, so that timely error adjustment is facilitated.
Step S4: and when the battery state parameter exceeds a preset alarm threshold, checking the battery state parameter. Specifically, whether the abnormal data with the alarm is true or not can be judged through rechecking and checking, so that the deviation of the system control precision and the accuracy and the abnormal operation of the energy storage system caused by the error of the data collected by the bottom terminal are reduced. Meanwhile, through the rechecking and checking process, data support can be provided for subsequent error adjustment.
Step S5: and carrying out error adjustment on the target battery system according to the rechecking and checking result. Specifically, the targeted adjustment is performed according to the rechecking and checking result, so that the optimization is more accurate, the precision is higher, and the running reliability of the target battery system is improved.
Through the steps S1 to S5, when the bottom battery module generates a data threshold crossing alarm, the method for optimizing the energy storage battery control according to the embodiment of the invention judges the authenticity of the alarm data through checking, and adjusts and repairs the alarm data according to the checking result in a targeted manner, thereby reducing the deviation of the system control precision and accuracy and the abnormal system operation caused by the error of the data acquisition of the bottom terminal.
Specifically, in an embodiment, step S4 described above, as shown in fig. 2, specifically includes the following steps:
step S411: and re-acquiring the data information of each battery module in all battery clusters in the target battery system as rechecking data.
Step S412: and checking the battery state parameters based on the rechecking data to generate a rechecking checking result.
Specifically, whether the target battery system operates normally can be judged by re-acquiring data to perform rechecking and checking, and when the target battery system operates normally, the results of the two data are consistent; if the results are different, an error exists in the target battery system, and the error may be caused by the failure of the operation state.
Specifically, in an embodiment, step S412 described above, as shown in fig. 3, specifically includes the following steps:
step S4121: and analyzing the rechecking data to obtain the battery rechecking parameters.
Step S4122: and comparing the battery rechecking parameter with the battery state parameter.
Step S4123: when the battery rechecking parameter is different from the battery state parameter, the rechecking verification result shows that an error exists in the target battery system.
Specifically, the consistency of the analysis and calculation process is ensured by re-acquiring the data and the same analysis and calculation mode, so that the comparison result has higher reliability, and whether the operation error is caused by the fault of the target battery system is more reasonably reflected.
Specifically, in an embodiment, step S4 described above, as shown in fig. 4, specifically includes the following steps:
step S421: historical data information of each battery module in all battery clusters in the target battery system is obtained.
Step S422: and verifying the battery state parameters based on the historical data information to generate a rechecking verification result.
Specifically, by analyzing the historical data information, the current parameter can be predicted according to the change trend, and because the historical data information is generated in the same condition as the current environment, the current battery state parameter generating the alarm is checked through the prediction result, the authenticity of the battery state parameter generating the alarm can be accurately judged, and the possibility of misjudgment is reduced.
Specifically, in one embodiment, the step S422 described above, as shown in fig. 5, specifically includes the following steps:
step S4221: and obtaining a historical development curve of each state parameter of each battery module based on the historical data information.
Step S4222: and predicting the data of the current state parameters according to the change trend of the historical development curve to obtain predicted parameter data. Specifically, the current state data can be predicted through a curve trend prediction algorithm model in the prior art, so that the method has higher accuracy.
Step S4223: and comparing the predicted parameter data with the battery state parameters. Specifically, by comparison, whether the difference exists between the predicted parameter data and the battery state parameter or not can be obviously reflected.
Step S4224: when the predicted parameter data is different from the battery state parameter, the rechecking and checking result shows that an error exists in the target battery system.
Specifically, the authenticity of the battery state parameter with the alarm can be accurately judged in a prediction comparison mode.
Specifically, the historical data information can further include a historical warning threshold, and the current preset warning threshold is checked by generating a historical warning development curve for the historical warning threshold to judge whether the current preset warning threshold is reasonable or not.
Specifically, in an embodiment, step S4 described above, as shown in fig. 6, specifically includes the following steps:
step S431: parameter information of different battery modules connected in series in the same battery cluster is extracted from the battery state parameters for longitudinal comparison. Specifically, whether calculation errors caused by different working conditions exist or not can be judged by a longitudinal comparison method.
Step S432: and extracting parameter information of battery modules in adjacent battery clusters from the battery state parameters for transverse comparison. Specifically, whether a threshold setting error caused by working condition change exists or not can be judged by a transverse comparison mode.
Step S433: when the longitudinal comparison result and/or the transverse comparison result are different, the rechecking and checking result is that an error exists in the target battery system.
Specifically, the authenticity and rationality of the alarm data can be judged through transverse comparison and longitudinal comparison, and meanwhile, the battery module in which battery cluster the error originates from can be checked according to the comparison result, so that support is provided for the subsequent error adjustment process.
Specifically, in one embodiment, step S5 described above, as shown in fig. 7, specifically includes the following steps:
step S51: and when the result of the rechecking and checking is that the error exists in the target battery system, judging the error source according to the rechecking and checking process.
Step S52: and performing error adjustment on the target battery system according to the error source. Specifically, the generation position of the error can be clearly known through the rechecking and checking process, and when the system has a fault problem or the error is caused by a working condition fault problem, the error adjustment can be performed by starting a fault removal execution program; when errors caused by numerical setting problems can be corrected and repaired by staff.
Specifically, by judging the error source and performing targeted adjustment, the system can provide convenience for the adjustment work of staff, effectively improve the control precision of the system, improve the data accuracy and ensure that the system operates more reliably.
In this embodiment, there is also provided an energy storage battery control optimization system, including: a battery module level data acquisition terminal; the battery cluster data summarizing and calculating unit; a spacer layer data aggregation and forwarding unit; and the station control layer monitoring module. An independent energy storage interval is formed by combining an energy storage converter PCS and one or more battery clusters electrically connected with the PCS in the system, and each interval forms an independent network access station control network layer to form a complete communication network of the whole system.
Battery module level data acquisition terminal: in the system, a single battery module in each battery cluster is used as a data acquisition minimum unit, a data acquisition circuit and an acquisition element are arranged in the module, a data acquisition module is arranged at the outlet of the module, and classification, coding, collection and protocol conversion of data are completed to form a data source which can be identified by the system.
Battery cluster-level data total sum calculating unit BMS: the data acquisition and operation device is arranged by taking the battery cluster as a unit, has the functions of acquisition, identification and data storage, can synthesize and calculate all original data according to a certain algorithm, generates battery parameters such as voltage, current, resistance, temperature, SOC, SOH and the like of the battery, reflects the working and health state of the battery, and carries out abnormal alarm according to the threshold value of each parameter.
Spacer layer data summarizing and forwarding unit: in order to ensure the collection and transmission of different information, a protocol converter and a convergence switch are generally configured in the link, and the information of each unit is converged and collected and then uploaded to a station control layer information collection system.
Station control layer monitoring module: the highest data management unit of the energy storage power station is used for completing information acquisition, storage, operation processing, control and execution of the whole station through each layer of communication network, and is an automatic control center of the energy storage power station.
The energy storage battery safety control optimizing process comprises the following steps:
1. when the original data information in the energy storage battery module is summarized and transmitted by the module-level data acquisition terminal and then uploaded to the battery cluster-level BMS, various parameters capable of reflecting battery state information are generated through BMS operation processing and then uploaded to the spacer layer data summarizing and forwarding unit, the spacer layer data summarizing and forwarding unit and other spacer layer equipment information are sent to the station control layer monitoring module, meanwhile, the BMS carries out vector comparison on the generated battery parameter information and a manual preset threshold value, and the BMS starts alarming on out-of-limit parameters and reports the alarming to the station control level monitoring system through a network channel.
2. After receiving the out-of-limit alarm of the related parameter of a certain battery module reported by the battery cluster, the station control level monitoring system immediately starts a parameter rechecking and checking program:
1) The monitoring system issues a control command to the alarm BMS end, opens a BMS data transmission channel, and reports original data of the alarm module to the monitoring system in a direct-picking and direct-sending mode through a bypass.
2) The monitoring system transfers the original data to operation processing, and the battery parameters of the alarm module are regenerated by operation according to the same calculation strategy as the BMS.
3) The monitoring system carries out recheck examination on the regenerated battery parameters and the battery parameters uploaded by the BMS so as to judge the running state and calculation errors of the BMS.
4) When the BMS is normal through the rechecking, the system goes into an alarm parameter checking subroutine:
a) The monitoring system invokes the historical data of the alarm parameters to form a historical development curve;
b) Other related parameter data of the alarm module are called to form a history curve;
c) In the same working condition, judging the authenticity of the alarm parameters through the variation trend of the same module associated parameters;
d) The monitoring system selects the same and related parameter information of different serial battery modules in the same battery cluster, eliminates calculation errors caused by different working conditions by a longitudinal comparison method, and judges the authenticity of alarm data;
e) The monitoring system selects the same parameter or related parameter information in the adjacent battery clusters of the battery clusters where the alarm module is positioned, and respectively and transversely compares the same parameter or related parameter information with the alarm module information, so as to eliminate threshold setting errors caused by working condition changes and check the rationality of the alarm information;
3. after the authenticity of the alarm information is judged through the review and verification program of the alarm information, the monitoring system determines to start a fault removal execution program or to transfer to an error manual correction and restoration process according to the result.
Specifically, the system provided by the embodiment of the invention increases the verification and rechecking of the acquired data of the BMS system on the basis of optimizing the architecture of the data acquisition, operation and uploading of the battery system commonly used at present, and greatly reduces the background operation amount and the verification and rechecking amount by introducing the concepts of hierarchical data operation and hierarchical management. After the data threshold value line crossing alarm occurs at the bottom layer, the monitoring background is triggered to start an original basic data line crossing sending and upper system level multiple correlation path and parameter rechecking checking program, the system carries out vector comparison of horizontal and longitudinal multi-azimuth correlated data while carrying out basic data secondary calculation generation, and the authenticity of the alarm data is judged through secondary rechecking checking of a third party system, so that deviation of system control precision and accuracy rate and abnormal operation of an energy storage system caused by errors of data acquisition of a bottom terminal are reduced.
The embodiment also provides an energy storage battery control optimizing device, which is used for realizing the embodiment and the preferred implementation manner, and the description is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides an energy storage battery control optimizing device, as shown in fig. 8, including:
the acquiring module 101 is configured to acquire data information of each battery module in all battery clusters in the target battery system, where the data information is data for representing a plurality of operation parameters of the battery modules, and details refer to the description related to step S1 in the foregoing method embodiment, which is not repeated herein.
The analysis module 102 is configured to analyze the data information to obtain the battery state parameter, and details refer to the description related to step S2 in the above method embodiment, which is not described herein.
The comparison module 103 is configured to compare the battery state parameter with a preset alarm threshold, and details refer to the related description of step S3 in the foregoing method embodiment, which is not described herein again.
The verification module 104 is configured to perform a recheck verification on the battery state parameter when the battery state parameter exceeds the preset alarm threshold, and details refer to the related description of step S4 in the foregoing method embodiment, which is not described herein.
The adjustment module 105 is configured to perform error adjustment on the target battery system according to the result of the rechecking verification, and details refer to the related description of step S5 in the foregoing method embodiment, which is not described herein again.
The energy storage battery control optimizing means in this embodiment is presented in the form of functional units, where units refer to ASIC circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above described functionality.
Further functional descriptions of the above respective modules are the same as those of the above corresponding embodiments, and are not repeated here.
There is also provided in accordance with an embodiment of the present invention, an electronic device, as shown in fig. 9, which may include a processor 901 and a memory 902, wherein the processor 901 and the memory 902 may be connected via a bus or otherwise, as exemplified by the bus connection in fig. 9.
The processor 901 may be a central processing unit (Central Processing Unit, CPU). The processor 901 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory 902 is used as a non-transitory computer readable storage medium for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the methods in the method embodiments of the present invention. The processor 901 executes various functional applications of the processor and data processing, i.e., implements the methods in the above-described method embodiments, by running non-transitory software programs, instructions, and modules stored in the memory 902.
The memory 902 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created by the processor 901, and the like. In addition, the memory 902 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 902 optionally includes memory remotely located relative to processor 901, which may be connected to processor 901 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 902 that, when executed by the processor 901, perform the methods of the method embodiments described above.
The specific details of the electronic device may be correspondingly understood by referring to the corresponding related descriptions and effects in the above method embodiments, which are not repeated herein.
It will be appreciated by those skilled in the art that implementing all or part of the above-described methods in the embodiments may be implemented by a computer program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, and the program may include the steps of the embodiments of the above-described methods when executed. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. The energy storage battery control optimization method is characterized by comprising the following steps of:
acquiring data information of each battery module in all battery clusters in a target battery system, wherein the data information is data for representing a plurality of operation parameters of the battery modules;
analyzing the data information to obtain battery state parameters;
comparing the battery state parameter with a preset alarm threshold;
when the battery state parameter exceeds the preset alarm threshold, checking the battery state parameter;
and carrying out error adjustment on the target battery system according to the rechecking and checking result.
2. The energy storage battery control optimization method of claim 1, wherein the rechecking of the battery state parameter comprises:
re-acquiring the data information of each battery module in all battery clusters in the target battery system as rechecking data;
and verifying the battery state parameters based on the rechecking data to generate a rechecking verification result.
3. The energy storage battery control optimization method according to claim 2, wherein the verifying the battery state parameter based on the rechecking data generates a rechecking verification result, comprising:
analyzing the rechecking data to obtain battery rechecking parameters;
comparing the battery rechecking parameter with the battery state parameter;
when the battery rechecking parameter is different from the battery state parameter, the rechecking verification result shows that an error exists in the target battery system.
4. The energy storage battery control optimization method according to claim 2, wherein when there is no error in the result of checking the battery state parameter based on the rechecking data, the rechecking the battery state parameter further includes:
acquiring historical data information of each battery module in all battery clusters in the target battery system;
and verifying the battery state parameters based on the historical data information to generate a rechecking verification result.
5. The energy storage battery control optimization method of claim 4, wherein the verifying the battery state parameter based on the historical data information generates a rechecking verification result, comprising:
obtaining a historical development curve of each state parameter of each battery module based on the historical data information;
predicting the data of the current state parameters according to the change trend of the historical development curve to obtain predicted parameter data;
comparing the predicted parameter data with the battery state parameters;
and when the predicted parameter data is different from the battery state parameter, checking and checking results to obtain errors in the target battery system.
6. The energy storage battery control optimization method of claim 4, wherein the rechecking the battery state parameter further comprises:
extracting parameter information of different battery modules connected in series in the same battery cluster from the battery state parameters for longitudinal comparison;
extracting parameter information of battery modules in adjacent battery clusters from the battery state parameters for transverse comparison;
when the longitudinal comparison result and/or the transverse comparison result are different, the rechecking verification result is that an error exists in the target battery system.
7. The energy storage battery control optimization method according to claim 1, wherein the performing error adjustment on the target battery system according to the result of the rechecking check includes:
when the result of the rechecking and checking is that the error exists in the target battery system, judging an error source according to the rechecking and checking process;
and carrying out error adjustment on the target battery system according to the error source.
8. An energy storage battery control optimizing device, characterized by comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring data information of each battery module in all battery clusters in a target battery system, wherein the data information is data for representing a plurality of operation parameters of the battery modules;
the analysis module is used for analyzing the data information to obtain battery state parameters;
the comparison module is used for comparing the battery state parameter with a preset alarm threshold value;
the verification module is used for rechecking and verifying the battery state parameters when the battery state parameters exceed the preset alarm threshold;
and the adjusting module is used for adjusting the error of the target battery system according to the rechecking and checking result.
9. An electronic device, comprising:
a memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the energy storage battery control optimization method of any one of claims 1-7.
10. A computer-readable storage medium storing computer instructions for causing a computer to execute the energy storage battery control optimization method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116885763A (en) * | 2023-09-07 | 2023-10-13 | 深圳市健网科技有限公司 | Energy management device and method suitable for distributed energy storage system |
| CN116923100A (en) * | 2023-09-19 | 2023-10-24 | 江西五十铃汽车有限公司 | Power battery pack repairing method and system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116885763A (en) * | 2023-09-07 | 2023-10-13 | 深圳市健网科技有限公司 | Energy management device and method suitable for distributed energy storage system |
| CN116885763B (en) * | 2023-09-07 | 2023-11-17 | 深圳市健网科技有限公司 | Energy management device and method suitable for distributed energy storage system |
| CN116923100A (en) * | 2023-09-19 | 2023-10-24 | 江西五十铃汽车有限公司 | Power battery pack repairing method and system |
| CN116923100B (en) * | 2023-09-19 | 2024-01-26 | 江西五十铃汽车有限公司 | Power battery pack repairing method and system |
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