Intelligent inspection method and system for energy storage cloud platform

Abstract

The invention discloses an intelligent inspection method and system for an energy storage cloud platform, and aims to solve the problems of high operation and maintenance cost, inaccurate data and low inspection efficiency of energy storage equipment. The intelligent inspection method comprises the following steps: collecting an energy storage equipment model and operation data, setting a threshold parameter according to the equipment model, analyzing the operation data, and constructing a database in combination with the threshold parameter; creating an intelligent inspection scheme in the energy storage cloud platform; executing intelligent inspection according to the intelligent inspection scheme to obtain an inspection result; searching a solution corresponding to a keyword in a database according to the keyword in the inspection result; and executing the solution to obtain an execution result. According to the mode, the follow-up judgment of the operation condition of the energy storage equipment and the problem processing have the basis, corresponding solutions can be accurately matched according to the specific operation conditions of different equipment, and the efficiency and the accuracy of dealing with various conditions of the equipment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage management, and in particular to an intelligent inspection method and system for an energy storage cloud platform. Background Art

[0002] With the rapid development of electrochemical energy storage technology, distributed energy storage and centralized energy storage projects are being deployed at an accelerated pace across the country. However, due to the scattered and remote locations of energy storage equipment, the operation and maintenance of energy storage equipment has brought huge challenges. Traditional manual inspection methods have many disadvantages, such as large amounts of data, low abnormal recognition rates, and difficulty in judging key data, which lead to low inspection efficiency, high operation and maintenance costs, and huge human resource investment. In addition, manual inspections also have problems such as human operational errors and inaccurate data records, which cannot meet the actual needs of energy storage equipment operation and maintenance.

[0003] On the other hand, the information channels between power grid enterprises, owners, related industry chain manufacturers, financial institutions and governments are not smooth, and there is a serious "information island" phenomenon, which urgently needs information services and operation services. The lack of effective information sharing and coordination mechanisms among the various entities has led to low decision-making efficiency and low resource utilization. The problems that restrict industrial development are becoming increasingly prominent. It is urgent to establish an efficient and intelligent energy storage equipment operation and maintenance management system to reduce operation and maintenance costs, improve the safety and reliability of on-site operation of energy storage equipment, and promote the healthy development of the energy storage industry. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent inspection method and system for an energy storage cloud platform, aiming to solve the problems of high operation and maintenance cost of energy storage equipment, inaccurate data and low inspection efficiency.

[0005] To solve the above problems, a first aspect of the present invention provides an intelligent inspection method for an energy storage cloud platform, the intelligent inspection method comprising the steps of:

[0006] Collect energy storage device models and operating data, set threshold parameters according to the device models, analyze the operating data and build a database based on the threshold parameters;

[0007] Create intelligent inspection solutions in the energy storage cloud platform;

[0008] Perform intelligent inspection according to the intelligent inspection plan and obtain the inspection results;

[0009] According to the keywords in the inspection results, searching the database for solutions corresponding to the keywords;

[0010] Execute the solution and obtain an execution result.

[0011] Preferably, the analyzing the operating data and constructing a database in combination with the threshold parameters comprises:

[0012] Comparing the operating data with the threshold parameter to obtain a comparison result;

[0013] Issue equipment alarms or warnings based on the comparison results;

[0014] Determine the processing plan according to the equipment alarm or warning, and build a database based on the processing plan.

[0015] Preferably, the intelligent inspection method further includes: generating historical data according to the execution result, and updating the database based on the historical data.

[0016] Preferably, performing intelligent inspection according to the intelligent inspection scheme includes:

[0017] According to the preset timing cycle, the selected intelligent inspection plan is executed regularly and the inspection results are output.

[0018] Preferably, the preset timing cycle includes a daily inspection cycle, a weekly inspection cycle and a monthly inspection cycle.

[0019] Preferably, the intelligent inspection method further includes:

[0020] Set up multiple intelligent inspection plans;

[0021] Intelligent inspections are performed separately according to multiple intelligent inspection schemes to obtain intelligent inspection reports.

[0022] Another aspect of the present invention provides an intelligent inspection system for an energy storage cloud platform, the intelligent inspection system comprising:

[0023] Data construction module: used to collect energy storage equipment models and operating data, set threshold parameters according to equipment models, analyze operating data and construct a database in combination with the threshold parameters;

[0024] Intelligent inspection plan creation module: used to create intelligent inspection plans in the energy storage cloud platform;

[0025] Intelligent inspection execution module: used to execute intelligent inspection according to the intelligent inspection plan and obtain the inspection results;

[0026] Solution execution module: used to search for solutions corresponding to the keywords in the database according to the keywords in the inspection results; execute the solutions to obtain execution results.

[0027] Preferably, the data construction module includes:

[0028] Data acquisition unit: used to collect energy storage equipment model and operation data;

[0029] Analysis unit: used to compare the operation data with the threshold parameter to obtain a comparison result; and issue an equipment alarm or warning according to the comparison result;

[0030] Database unit: used to determine the processing plan according to the equipment alarm or warning, and build a database based on the processing plan.

[0031] Preferably, the analysis unit comprises:

[0032] Data analysis subunit: used to collect the execution results obtained by the solution execution module and generate historical data, and update the database based on the historical data.

[0033] Preferably, the intelligent inspection system further includes:

[0034] Energy storage monitoring module: used to comprehensively monitor the operating status of the energy storage equipment and transmit the monitoring results to the data construction module.

[0035] By collecting the model and operation data of energy storage equipment, setting threshold parameters according to the equipment model, comparing the operation data with the threshold, issuing equipment alarms or warnings, and then determining the treatment plan based on this, a database is built. This method provides a basis for subsequent judgments on the operating status of energy storage equipment and handling problems, and can accurately match corresponding solutions to the specific operating conditions of different equipment, improving the efficiency and accuracy of dealing with various conditions of the equipment. Historical data is generated based on the execution results, and the database is updated based on these historical data. This enables the database to keep pace with the times, and continuously improve with the actual execution situation and changes in the operation of the equipment, improving the timeliness and practicality of the information in the database, so that when dealing with similar problems in the future, more practical solutions can be used as a reference. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of an intelligent inspection method according to an embodiment of the present invention;

[0037] Figure 2 is a schematic diagram of the composition of an intelligent inspection system according to another embodiment of the present invention;

[0038] Figure 3 is a schematic diagram of a data construction module in an intelligent inspection system according to another embodiment of the present invention;

[0039] Figure 4 It is a schematic diagram of an analysis unit in an intelligent inspection system according to yet another embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0041] Combination Figure 1 The embodiment of the present invention provides an intelligent inspection method for an energy storage cloud platform, the intelligent inspection method comprising the steps of:

[0042] S1. Collect the model and operation data of energy storage equipment, set threshold parameters according to the equipment model, analyze the operation data and build a database in combination with the threshold parameters. Collect relevant information and operation data of various types of energy storage equipment. According to the model of energy storage equipment, set corresponding threshold parameters based on the performance standards and safety requirements of the equipment. These threshold parameters are used to evaluate whether the equipment is operating normally. The collected operation data needs to be carefully analyzed, and various factors such as the equipment model, use environment, and workload should be considered during the analysis. Through analysis, identify abnormal patterns or potential problems in the operation of the equipment, combine the results of the analysis with the previously set threshold parameters, and build a database. This database not only records the operating status of the equipment, but also contains key information such as equipment model and threshold parameters, providing strong data support for the maintenance, upgrade and decision support of energy storage equipment. When any abnormal operation data occurs, the relevant information of the model of equipment can be quickly located, providing an accurate and comprehensive data basis for subsequent alarms, early warnings, and the formulation of treatment plans, improving the efficiency and accuracy of problem response.

[0043] S2. Create an intelligent inspection plan in the energy storage cloud platform. Create an intelligent inspection plan based on inspection requirements. Multiple intelligent inspection plans can be set at the same time, and different inspection plans can be selected for intelligent inspection according to different user needs and business needs. Creating an intelligent inspection plan in the cloud platform can achieve remote control without geographical restrictions. After the intelligent inspection plan is created, it is also convenient to store, call, and subsequently optimize and update the plan, which facilitates the execution and management of intelligent inspections.

[0044] S3. Perform intelligent inspection according to the intelligent inspection plan and obtain the inspection results. When performing intelligent inspection, the operation data of the energy storage equipment designed in the intelligent inspection plan is obtained, and the obtained operation data is compared with the preset parameters in the database to obtain the current operation status of the energy storage equipment and obtain the inspection results. This can more comprehensively reflect the operation status of the equipment, determine whether the current operation of the energy storage equipment is in a normal state, and predict potential risks, providing a basis for taking measures in advance and effectively avoiding sudden equipment failures.

[0045] S4. Search for solutions to the corresponding keywords in the database based on the keywords in the inspection results. The database stores a large number of solutions that have been summarized through practice and experience. Searching for relevant solutions in the database based on the keywords in the inspection results can quickly locate the problems in the current inspection process and accurately obtain solutions, saving operation and maintenance time, improving the timeliness of fault handling, reducing equipment downtime and the probability of damage, and thus ensuring the stable operation of energy storage equipment.

[0046] S5. Execute the solution and obtain the execution result. When the corresponding solution is found in the database, the cloud platform automatically executes the relevant operations in the solution, monitors the execution status in real time and records it, and compares the operating data of the energy storage equipment during and after the execution with the threshold parameters in the database to determine the effectiveness of the solution. Further analysis can be performed based on the execution results to optimize the solution or try other alternative solutions, forming a closed-loop operation and maintenance system that is constantly updated and improved.

[0047] It should be noted that the collection of energy storage equipment model information can be obtained through various channels such as identification of energy storage equipment and registration information when energy storage equipment is connected to the cloud platform; when collecting energy storage equipment operation data, it covers the voltage, current, temperature, power capacity, charge and discharge power of energy storage equipment and other aspects of data, and can also include environmental data of energy storage equipment operation, such as ambient temperature, humidity and other information. When setting threshold parameters according to the equipment model, for example, for a certain type of lithium-ion energy storage battery, its normal operating temperature range may be set to 20℃-40℃, and the threshold parameters are determined according to its material properties, heat dissipation design and other factors. When analyzing the operation data, these real-time acquired data are compared with the corresponding threshold parameters one by one. If a certain data is found to exceed the threshold range, it is necessary to record relevant information, such as the time when the data exceeds the threshold, the magnitude of the excess, etc. By integrating a large number of such analysis results and corresponding equipment models, threshold parameters and other information, a large and orderly database is constructed.

[0048] In a preferred case, analyzing the operating data and building a database in combination with the threshold parameters includes: comparing the operating data with the threshold parameters to obtain a comparison result; issuing an equipment alarm or warning based on the comparison result; determining a processing plan based on the equipment alarm or warning, and building a database based on the processing plan. When the comparison result exceeds the threshold or an abnormality occurs, an alarm or warning is issued in a timely manner, and the corresponding processing plan is matched from a pre-set processing plan library based on information such as the equipment model and the type of abnormality. The processing plan is summarized after a lot of practical experience and technical research, including detailed processing steps for different faults, required tools and materials, and possible professional fields of technical personnel involved. For example, for an overheating alarm of a charging module of a certain type of energy storage device, the processing plan may include the steps of stopping the charging operation first, checking whether the cooling fan is operating normally, cleaning the heat sink dust, and using an infrared thermometer to detect the temperature distribution of each component inside the module. When energy storage equipment encounters similar problems, it can directly call the processing plan to respond quickly, reducing the time for troubleshooting and processing. As new alarms and warnings continue to appear and processing experience accumulates, the database will continue to be enriched and improved, so that the operation and maintenance capabilities of the entire energy storage system will continue to improve.

[0049] When performing intelligent inspections, the cloud platform retrieves and analyzes data according to the intelligent inspection plan. For example, in the inspection plan, the voltage and temperature of a certain energy storage device are set to be tested every 10 minutes. The cloud platform will obtain the voltage and temperature data within the corresponding time interval and compare it with the threshold in the database. The inspection results include not only a simple judgment of whether the data is normal, but also an analysis of the data change trend. For example, if it is found that the temperature of a certain device has continued to rise slowly in the past few hours, although it has not exceeded the threshold, this trend information will also be recorded in the inspection results. In this way, the inspection process is more rigorous and can more comprehensively reflect the operating status of the equipment.

[0050] Keywords in the inspection results can be information such as device name, fault type, abnormal data name, etc. For example, if the inspection result shows that the energy storage device has "abnormal charging power", then "abnormal charging power" is the keyword. At this time, the database is searched for solutions with corresponding keywords. These solutions may include adjusting the specific values ​​of charging parameters, steps to check whether the charging line connection is loose, and prompting the charging module model that may need to be replaced.

[0051] In a preferred case, after executing the solution and obtaining the execution result, historical data can also be generated according to the execution result, and the database can be updated based on the historical data. The execution result includes a variety of information, such as the changes in various parameters during the execution of the solution, the final recovery of the equipment, whether new anomalies occur during the execution, etc. For example, after executing the solution to adjust the voltage threshold of the energy storage device, the voltage change curve before and after the adjustment, the time for the equipment to run stably under the new threshold, whether other related parameters (such as current, power, etc.) are affected, etc. are recorded as historical data. When updating the database based on these historical data, the details of this execution will be compared and analyzed with the previous processing records of the same type of equipment. If some special circumstances or new lessons are found during this execution, this information will be added to the corresponding processing plan or equipment operation data reference materials in the database. In this way, the database can continuously adapt to the actual operation changes of the equipment and the accumulation of operation and maintenance experience, ensuring that the information in the database is always the latest, most accurate, and most comprehensive, improving the success rate of fault diagnosis and processing in subsequent operation and maintenance work, and also helping to discover potential common problems or new risk points of the equipment, providing data support for the optimization and upgrading of the equipment.

[0052] In a preferred case, performing intelligent inspection according to the intelligent inspection scheme includes: regularly executing the selected intelligent inspection scheme according to a preset timing cycle, and outputting the inspection result. Regularly executing the intelligent inspection scheme through a preset inspection cycle. Preferably, the preset timing cycle includes a daily inspection cycle, a weekly inspection cycle, and a monthly inspection cycle.

[0053] During the daily inspection cycle, a comprehensive inspection of key energy storage equipment is initiated at a fixed time every day. The inspection items cover the basic electrical parameters (voltage, current, power, etc.), physical status (temperature, appearance integrity, etc.) and key safety indicators (leakage detection, fire and explosion prevention monitoring, etc.) of the equipment. For example, for the core battery pack of a large lithium-ion energy storage power station, the daily inspection will check the voltage consistency of each battery module in detail. If it is found that the voltage of a module is significantly lower than that of other modules, it may indicate that the module has an internal short circuit or aging problem. Timely discovery can avoid the overall performance of the battery pack from deteriorating or even causing serious consequences such as fire.

[0054] During the weekly inspection cycle, in-depth inspections are conducted on auxiliary equipment on specific working days of each week. Taking the cooling system as an example, in addition to checking the operating status, water flow rate, water temperature and other basic parameters of the cooling water pump, the cooling pipes are also inspected for sealing, and the blades of the cooling fans are inspected for cleanliness and balance. For the monitoring system, data calibration tests are conducted to ensure that the data collected by each sensor is accurately transmitted to the cloud platform and correctly presented on the display interface. This ensures the continuous and stable operation of the auxiliary equipment and provides a good environment and data support for the normal operation of the energy storage equipment.

[0055] Under the monthly inspection cycle, a comprehensive performance evaluation of the entire energy storage system is conducted at the end of each month. By accurately measuring the capacity of the energy storage battery, the capacity decay rate is calculated by comparing the data of the previous month, and the health of the battery is evaluated. At the same time, the energy conversion efficiency of the entire energy storage system is comprehensively tested, and the efficiency of the entire process from power input to energy storage equipment to power output is analyzed to identify possible energy loss links and formulate improvement measures. The advantage of this inspection arrangement covering different cycles of days, weeks, and months is that it comprehensively monitors the operating status of energy storage equipment from micro to macro, from short-term to long-term, and promptly discovers various problems from minor fault hazards to overall performance changes, ensuring the long-term stable and efficient operation of the energy storage system.

[0056] In a preferred case, multiple intelligent inspection schemes can also be set in the intelligent inspection method of the present invention; intelligent inspections are performed according to multiple intelligent inspection schemes to obtain intelligent inspection reports. By setting multiple inspection schemes at the same time, different inspection schemes can be selected for intelligent inspection according to different user needs and business needs. At the same time, multiple intelligent inspection schemes can be set to inspect the energy storage equipment from different angles and depths. For example, a basic inspection scheme mainly focuses on the basic operating parameters and safety indicators of the equipment, such as the voltage, current, temperature, leakage detection mentioned above, which is suitable for daily rapid screening. A deep inspection scheme will conduct detailed inspections on the internal structure and key components of the equipment, such as the plate condition of the energy storage battery, electrolyte composition analysis, and component performance testing of the charging and discharging control circuit. This scheme needs to be carried out when the equipment is shut down or running at low load, and is generally performed once a quarter or half a year. There are also special inspection schemes that inspect specific equipment problems or environmental factors, such as special inspections of the heat dissipation system of the energy storage equipment before the arrival of the high temperature season, and special evaluations of the lightning protection measures of the equipment in areas prone to lightning. This method can provide a comprehensive and in-depth understanding of the operating status of energy storage equipment, provide a detailed and reliable basis for formulating accurate operation and maintenance strategies and equipment upgrade and transformation plans, improve the overall management level and inspection efficiency of the energy storage system, and reduce operation and maintenance costs.

[0057] Combination Figures 2 to 4The embodiment of the present invention further provides an intelligent inspection system for an energy storage cloud platform, the intelligent inspection system comprising:

[0058] Data construction module: used to collect energy storage equipment models and operating data, set threshold parameters according to equipment models, analyze operating data and build a database based on threshold parameters;

[0059] Intelligent inspection plan creation module: used to create intelligent inspection plans in the energy storage cloud platform;

[0060] Intelligent inspection execution module: used to execute intelligent inspection according to the intelligent inspection plan and obtain the inspection results;

[0061] Solution execution module: used to search for solutions corresponding to keywords in the database according to the keywords in the inspection results; execute the solutions and obtain the execution results.

[0062] In a preferred case, the data building module includes:

[0063] Data acquisition unit: used to collect energy storage equipment model and operation data;

[0064] Analysis unit: used to compare the operating data with the threshold parameters to obtain the comparison result; and to issue equipment alarms or early warnings based on the comparison result;

[0065] Database unit: used to determine the processing plan according to the equipment alarm or warning, and build a database based on the processing plan.

[0066] In a preferred embodiment, the analysis unit comprises:

[0067] Data analysis subunit: used to collect the execution results obtained by the solution execution module and generate historical data, and update the database based on the historical data.

[0068] The processes of each module and unit in the intelligent inspection system of the energy storage cloud platform in this embodiment of the present invention are the same as the steps in the intelligent inspection method of the energy storage cloud platform provided in the above embodiment of the present invention, and their repeated description is omitted here.

[0069] The intelligent inspection system of the energy storage cloud platform also includes an energy storage monitoring module: it is used to comprehensively monitor the operating status of the energy storage equipment and transmit the monitoring results to the data construction module. The energy storage monitoring module uses multi-sensor fusion and real-time data transmission technology to conduct all-round and uninterrupted monitoring of energy storage equipment. It deploys various types of sensors, such as temperature sensors distributed in key heating parts of the equipment (battery modules, power conversion units, etc.) to monitor temperature changes in real time; current sensors are installed at key nodes of the circuit to accurately measure the current size and direction; voltage sensors monitor the various voltage levels of the equipment to ensure voltage stability; the data collected by these sensors are transmitted to the data construction module in real time through high-speed data transmission networks (such as industrial Ethernet, fiber optic communications, etc.).

[0070] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

Claims

1. An intelligent inspection method for an energy storage cloud platform, characterized in that: The intelligent inspection method comprises the steps of: Collect energy storage device models and operating data, set threshold parameters according to the device models, analyze the operating data and build a database based on the threshold parameters; Create intelligent inspection solutions in the energy storage cloud platform; Perform intelligent inspection according to the intelligent inspection plan and obtain the inspection results; According to the keywords in the inspection results, searching the database for solutions corresponding to the keywords; Execute the solution and obtain an execution result.

2. The intelligent inspection method according to claim 1, characterized in that: The analyzing the operation data and constructing a database in combination with the threshold parameters comprises: Comparing the operating data with the threshold parameter to obtain a comparison result; Issue equipment alarms or warnings based on the comparison results; Determine the processing plan according to the equipment alarm or warning, and build a database based on the processing plan.

3. The intelligent inspection method according to claim 2, characterized in that: The intelligent inspection method further includes: generating historical data according to the execution result, and updating a database based on the historical data.

4. The intelligent inspection method according to claim 3, characterized in that: The performing of intelligent inspection according to the intelligent inspection scheme includes: According to the preset timing cycle, the selected intelligent inspection plan is executed regularly and the inspection results are output.

5. The intelligent inspection method according to claim 4, characterized in that: The preset timing cycle includes a daily inspection cycle, a weekly inspection cycle and a monthly inspection cycle.

6. The intelligent inspection method according to claim 3, characterized in that: The intelligent inspection method further comprises: Set up multiple intelligent inspection plans; Intelligent inspections are performed separately according to multiple intelligent inspection schemes to obtain intelligent inspection reports.

7. An intelligent inspection system for an energy storage cloud platform, characterized in that: The intelligent inspection system comprises: Data construction module: used to collect energy storage equipment models and operating data, set threshold parameters according to equipment models, analyze operating data and construct a database in combination with the threshold parameters; Intelligent inspection plan creation module: used to create intelligent inspection plans in the energy storage cloud platform; Intelligent inspection execution module: used to execute intelligent inspection according to the intelligent inspection plan and obtain the inspection results; Solution execution module: used to search for solutions corresponding to the keywords in the database according to the keywords in the inspection results; execute the solutions to obtain execution results.

8. The intelligent inspection system according to claim 7, characterized in that: The data construction module includes: Data acquisition unit: used to collect energy storage equipment model and operation data; Analysis unit: used to compare the operation data with the threshold parameter to obtain a comparison result; and issue an equipment alarm or warning according to the comparison result; Database unit: used to determine the processing plan according to the equipment alarm or warning, and build a database based on the processing plan.

9. The intelligent inspection system according to claim 8, characterized in that: The analysis unit comprises: Data analysis subunit: used to collect the execution results obtained by the solution execution module and generate historical data, and update the database based on the historical data.

10. The intelligent inspection system according to claim 7, characterized in that: The intelligent inspection system also includes: Energy storage monitoring module: used to comprehensively monitor the operating status of the energy storage equipment and transmit the monitoring results to the data construction module.

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