A distributed energy storage equipment monitoring system based on big data

Abstract

The present invention relates to the technical field of energy storage device monitoring, and specifically discloses a distributed energy storage device monitoring system based on big data, wherein the system comprises: a data monitoring module, comprising a data acquisition unit and an image acquisition unit, wherein the data acquisition unit is used to acquire operating parameter data and environmental information data of the energy storage device; a data calculation unit is used to calculate an operating state risk value of the energy storage device in a discharge operation, and then an analysis and comparison unit is used to compare the operating state risk value in combination with a preset operating state risk value threshold, and the operating state of the energy storage device is analyzed according to the comparison result; since the operating state risk value of the energy storage device is calculated by combining an environmental impact coefficient and an equipment damage coefficient, the calculation result is closer to the real data, so the operating state of the energy storage device is analyzed and determined by the data, which can accurately reflect the operating state of the energy storage device, thereby improving the accuracy of the detection result.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage equipment monitoring, and in particular to a distributed energy storage equipment monitoring system based on big data. Background Art

[0002] Distributed energy storage equipment refers to energy storage equipment that is installed in various locations, usually close to the point of power demand. These devices can store electrical energy in different forms and release it when needed to meet energy demand.

[0003] The most common energy storage device in our lives is the lithium-ion battery, which is widely used in electric vehicles and distributed energy storage systems. Lithium-ion batteries have the advantages of high energy density, long cycle life and fast charging and discharging speeds. During use, lithium-ion batteries will be monitored in real time through a monitoring system. The monitoring system can promptly understand the operating status and health of the equipment to ensure the safe, stable and efficient operation of the energy storage system.

[0004] When existing monitoring systems perform real-time monitoring of various parameters of lithium-ion batteries, the data they monitor is based on data from different environmental conditions and different aging states of the equipment. There is a certain deviation from the real data under the actual operating state of the lithium-ion battery. Analyzing and judging the operating state of the lithium-ion battery based on this data may lead to incorrect judgments on the operating state of the lithium-ion battery, thereby affecting the accuracy of the monitoring results and increasing operation and maintenance costs. Summary of the Invention

[0005] The purpose of the present invention is to provide a distributed energy storage equipment monitoring system based on big data to solve the following technical problems:

[0006] How to ensure accurate judgment of the operating status of lithium-ion batteries.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A distributed energy storage equipment monitoring system based on big data, the system comprising:

[0009] A data monitoring module includes a data acquisition unit and an image acquisition unit, wherein the data acquisition unit is used to collect operating parameter data and environmental information data of the energy storage device;

[0010] The image acquisition unit is used to capture the appearance image of the energy storage device;

[0011] an identification and recording module for identifying data in the appearance image provided by the image acquisition module and recording the data together with the operating parameter data and the environmental information data;

[0012] A data processing module, comprising a data calculation unit and an analysis and comparison unit, wherein the data calculation unit is used to first calculate the environmental impact coefficient and the equipment damage coefficient based on the data recorded in the identification and recording module, and then combine the two to calculate the operating state risk value of the energy storage device during the discharge operation;

[0013] The analysis and comparison unit is used to compare the preset operating state risk value threshold with the operating state risk value of the energy storage device during the discharge operation, and analyze the operating state of the energy storage device according to the comparison result;

[0014] An early warning and evaluation module, comprising an early warning unit and an evaluation unit, wherein the early warning unit is configured to issue an early warning when determining that the operating state of the energy storage device is poor;

[0015] The evaluation unit is used to predict the performance change trend of the energy storage device based on big data and past data analysis when it is judged that the operating status of the energy storage device is good.

[0016] Furthermore, the operating parameter data recorded in the identification and recording module includes voltage intensity, current size and energy storage device temperature, the environmental information data recorded in the identification and recording module includes ambient temperature, humidity and floating matter content in the air, and the appearance image data recorded in the identification and recording module includes the damaged area, corroded area and stained area of ​​the energy storage device.

[0017] Furthermore, the calculation process of the data calculation unit includes:

[0018] By formula Calculate the equipment damage coefficient at the i-th time point ;

[0019] Among them, i is a data collection at a fixed time interval, is the apparent damaged area of ​​the energy storage device at the i-th time point during the discharge operation, is the surface corrosion area of ​​the energy storage device at the i-th time point during the discharge operation, is the pollution area of ​​the energy storage equipment at the i-th time point during the discharge operation, is the surface area of ​​the energy storage device, The odor impact function is obtained based on the test results of the influence of different odor data around the energy storage device on the device damage coefficient. is the odor data of the energy storage device at the i-th time point during the discharge operation, is the error influence coefficient, which is set based on empirical fitting.

[0020] Furthermore, the calculation process of the data calculation unit also includes:

[0021] By formula Calculate the environmental impact coefficient at the i-th time point ;

[0022] in, is the ambient temperature of the energy storage device at the i-th time point during the discharge operation, is the preset standard ambient temperature, for The standard value of is the ambient humidity of the energy storage device at the i-th time point during the discharge operation, is the preset ambient humidity, is the content of floating matter in the air at the i-th time point during the discharge operation of the energy storage device, The preset floating matter content in the air.

[0023] Furthermore, the calculation process of the data calculation unit also includes:

[0024] By formula Calculate the operating status risk value of the energy storage device at the i-th time point during the discharge operation ;

[0025] in, is the current of the energy storage device at the i-th time point during the discharge operation, The standard current size preset for energy storage equipment, for The standard value of is the voltage intensity of the energy storage device at the i-th time point during the discharge operation, The voltage intensity preset for the energy storage device, is the operating temperature of the energy storage device at the i-th time point during the discharge operation, The preset operating temperature for the energy storage device, and 2 is the weight coefficient.

[0026] Furthermore, the analysis process of the analysis and comparison unit includes:

[0027] By calculating the operating state risk value of the energy storage device at the i-th time point in the discharge operation Compared with the preset operating status risk value threshold Make a comparison;

[0028] like ,The system judges that the operation risk value at this time point is low, indicating that the operation status of the energy storage device is good, and predicts the performance change trend of the energy storage device through the evaluation unit;

[0029] like ,The system determines that the operation risk value at this time point is high, indicating that the operating status of the energy storage equipment is poor, and issues an early warning through the early warning unit to remind the operation and maintenance personnel to inspect and repair the energy storage equipment in time.

[0030] Furthermore, the evaluation process of the evaluation unit includes:

[0031] First, by the formula Calculate the total risk value of the operating status of the energy storage equipment during discharge operation ;

[0032] And through the formula Calculate the total value of the equipment damage coefficient of the energy storage equipment during discharge operation ;

[0033] Finally, the formula Calculate the future performance change index of energy storage equipment ;

[0034] in, is the total number of data collection times of the energy storage device during the discharge operation, Any use in the working history of the energy storage device, is the total number of times the energy storage device has been used in its working history. is the total risk value of the operating status of the energy storage device when it is used for the ath time in its working history, For all The average value of is the total value of the equipment damage coefficient when the energy storage equipment is used for the ath time in its working history, For all The average value of and 2 is the weight coefficient.

[0035] Furthermore, the assessment process of the assessment unit also includes;

[0036] By using the energy storage equipment future performance change index Compared with the preset performance change index threshold Make a comparison;

[0037] like ,The system judges that the future performance change index of the energy storage equipment is small, ,which indicates that the future operation state of the energy storage equipment ,will be stable and the future operation performance will not be affected;

[0038] like ,The system judges that the future performance change index of the energy storage equipment is large, ,which indicates that the future operating state stability of the energy storage equipment is poor, ,and the future operating performance will be affected.

[0039] Beneficial effects of the present invention:

[0040] (1) The present invention calculates the operating status risk value of the energy storage device during the discharge operation through a data calculation unit, and then compares it with a preset operating status risk value threshold through an analysis and comparison unit, and analyzes the operating status of the energy storage device based on the comparison result. Since the operating status risk value of the energy storage device is calculated by combining the environmental impact coefficient and the equipment damage coefficient, the calculation result is closer to the real data. Therefore, the operating status of the energy storage device is analyzed and determined by the data, which can accurately reflect the operating status of the energy storage device, thereby improving the accuracy of the detection result.

[0041] (2) The present invention can calculate the operating status risk value of the energy storage device during the discharge operation by combining the environmental impact coefficient, the equipment damage coefficient and the operating parameter data. By setting it in this way, when combining the two sets of impact coefficients, the operating status risk value of the energy storage device during the discharge operation can be accurately calculated, and the calculation result is closer to the real data, thereby improving the accuracy of the judgment of the operating status of the energy storage device, avoiding the deviation between the operating parameter data and the real data, resulting in an erroneous judgment on the operating status of the energy storage device, and ensuring the accuracy of the monitoring results.

[0042] (3) The present invention calculates the operating state risk value of the energy storage device at the i-th time point during the discharge operation. Compared with the preset operating status risk value threshold For comparison, since the operating status risk value of the energy storage device at the i-th time point during the discharge operation is calculated by combining the environmental impact coefficient and the equipment damage coefficient, the authenticity and accuracy of the data are relatively high, and an accurate judgment can be made on the operating status of the energy storage device, avoiding the error in the operating status of the energy storage device due to a certain deviation between the collected data and the actual data, thereby improving the accuracy of the monitoring results.

[0043] (4) The present invention uses the future performance change index of the energy storage device to Compared with the preset performance change index threshold By comparing the performance of the energy storage equipment, the size of the future performance change index can be judged, and the stability of the future operating status of the energy storage equipment can be predicted based on the judgment results. Through such settings, the system can formulate a scientific and reasonable maintenance plan based on the data, and perform preventive maintenance in advance before the equipment performance begins to decline or failure may occur, which can effectively reduce unplanned downtime and avoid damage to the energy storage equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The present invention will be further described below with reference to the accompanying drawings.

[0045] Figure 1This is a schematic block diagram of a distributed energy storage device monitoring system based on big data in the present invention; DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0047] See also Figure 1 As shown, in one embodiment, the present application provides a distributed energy storage device monitoring system based on big data, the system comprising:

[0048] A data monitoring module includes a data acquisition unit and an image acquisition unit, wherein the data acquisition unit is used to collect operating parameter data and environmental information data of the energy storage device;

[0049] The image acquisition unit is used to capture the appearance image of the energy storage device;

[0050] an identification and recording module for identifying data in the appearance image provided by the image acquisition module and recording the data together with the operating parameter data and the environmental information data;

[0051] A data processing module, comprising a data calculation unit and an analysis and comparison unit, wherein the data calculation unit is used to first calculate the environmental impact coefficient and the equipment damage coefficient based on the data recorded in the identification and recording module, and then combine the two to calculate the operating state risk value of the energy storage device during the discharge operation;

[0052] The analysis and comparison unit is used to compare the preset operating state risk value threshold with the operating state risk value of the energy storage device during the discharge operation, and analyze the operating state of the energy storage device according to the comparison result;

[0053] An early warning and evaluation module, comprising an early warning unit and an evaluation unit, wherein the early warning unit is configured to issue an early warning when determining that the operating state of the energy storage device is poor;

[0054] The evaluation unit is used to predict the performance change trend of the energy storage device based on big data and past data analysis when judging that the operating status of the energy storage device is good;

[0055] Through the above technical solution, this embodiment provides a data monitoring module, the internal data acquisition unit and image acquisition unit of which can collect the operating parameter data and environmental information data of the energy storage device during the discharge operation, and take a picture of the appearance image of the energy storage device. Then, the recognition and recording module will recognize the data in the appearance image and record the data together with the operating parameter data and environmental information data. After that, the data calculation unit will calculate the operating status risk value of the energy storage device during the discharge operation based on the data recorded in the recognition and recording module. After the calculation is completed, the analysis and comparison unit will compare it with the preset operating status risk value threshold, and analyze the operating status of the energy storage device based on the comparison result. When it is judged that the operating status of the energy storage device is poor, the system will issue an early warning through the early warning unit to remind the operation and maintenance personnel to carry out maintenance in time. When it is judged that the operating status of the energy storage device is good, the system will predict the performance change trend of the energy storage device based on big data and past data analysis.

[0056] With such a configuration, the data calculation unit calculates the operating state risk value of the energy storage device during the discharge operation, and then the analysis and comparison unit compares it with a preset operating state risk value threshold. The operating state of the energy storage device is analyzed based on the comparison result. Since the operating state risk value of the energy storage device is calculated by combining the environmental impact coefficient and the equipment damage coefficient, the calculation result is closer to the real data. Therefore, the operating state of the energy storage device can be analyzed and determined by using this data to accurately reflect the operating state of the energy storage device, thereby improving the accuracy of the detection result.

[0057] It should be noted that the recognition and recording module is a trained neural network model, and the training process of the neural network model is an existing technology and will not be described in detail here.

[0058] The operating parameter data recorded in the recognition and recording module includes voltage intensity, current magnitude, and energy storage device temperature; the environmental information data recorded in the recognition and recording module includes ambient temperature, humidity, and floating matter content in the air; and the appearance image data recorded in the recognition and recording module includes the damaged area, corroded area, and stained area of ​​the energy storage device;

[0059] Through the above technical solution, this embodiment provides environmental information data, including ambient temperature, humidity, and the amount of floating matter in the air. Using this data, the data calculation unit can calculate the environmental impact coefficient. Furthermore, the equipment damage coefficient can be calculated based on the damaged area, corrosion area, and stain area of ​​the energy storage device. By combining the environmental impact coefficient and the equipment damage coefficient with the operating parameter data, the operating status risk value of the energy storage device during the discharge operation can be calculated. By combining these two sets of impact coefficients, the operating status risk value of the energy storage device during the discharge operation can be accurately calculated, making the calculated result closer to the actual data, thereby improving the accuracy of the determination of the operating status of the energy storage device, avoiding erroneous determinations of the operating status of the energy storage device due to deviations between the operating parameter data and the actual data, and ensuring the accuracy of the monitoring results.

[0060] The calculation process of the data calculation unit includes:

[0061] By formula Calculate the equipment damage coefficient at the i-th time point ;

[0062] Among them, i is a data collection at a fixed time interval, is the apparent damaged area of ​​the energy storage device at the i-th time point during the discharge operation, is the surface corrosion area of ​​the energy storage device at the i-th time point during the discharge operation, is the pollution area of ​​the energy storage equipment at the i-th time point during the discharge operation, is the surface area of ​​the energy storage device, The odor impact function is obtained based on the test results of the influence of different odor data around the energy storage device on the device damage coefficient. is the odor data of the energy storage device at the i-th time point during the discharge operation, is the error influence coefficient, which is set based on empirical fitting;

[0063] Through the above technical solution, this embodiment provides the equipment damage coefficient at the i-th time point: , can be obtained by formula Calculations show that, clearly, the larger the external damage area, external corrosion area, and contaminated area of ​​the energy storage device at the i-th time point during the discharge operation, the greater the device damage coefficient at the i-th time point, indicating that the device is significantly damaged at that time point. External damage may mean that the internal structure of the energy storage device has also been damaged to a certain extent, which may lead to a reduction in the device's energy storage and release efficiency, thereby affecting the performance of the energy storage device. In addition, the damaged appearance may expose more internal components, making these components more susceptible to external environmental influences such as moisture and dust, thereby increasing the risk of equipment failure.

[0064] On the contrary, the smaller the external damage area, external corrosion area, and contaminated area of ​​the energy storage device at the i-th time point during the discharge operation, the smaller the device damage coefficient at the i-th time point, indicating that the equipment is not damaged at this time point. By calculating the device damage coefficient at the i-th time point, the accuracy of the subsequent calculation of the operating status risk value of the energy storage device at the i-th time point during the discharge operation can be improved, thereby improving the accuracy of the judgment of the operating status of the energy storage device.

[0065] The calculation process of the data calculation unit also includes:

[0066] By formula Calculate the environmental impact coefficient at the i-th time point ;

[0067] in, is the ambient temperature of the energy storage device at the i-th time point during the discharge operation, is the preset standard ambient temperature, for The standard value can be set based on the allowable error fitting in the empirical data. is the ambient humidity of the energy storage device at the i-th time point during the discharge operation, is the preset ambient humidity, is the content of floating matter in the air at the i-th time point during the discharge operation of the energy storage device, The preset floating matter content in the air;

[0068] Through the above technical solution, this embodiment provides the environmental impact coefficient at the i-th time point , can be obtained by formula Calculations show that, obviously, the greater the difference between the ambient temperature at the i-th time point during the energy storage device's discharge operation and the preset temperature, and the greater the ambient humidity and the floating matter content in the air, the greater the environmental impact coefficient at the i-th time point. Since the ambient temperature, humidity, and floating matter in the air all affect the operating status of the energy storage device, after calculating the environmental impact coefficient at the i-th time point, combining this data with the subsequent calculation of the operating status risk value of the energy storage device at the i-th time point during the discharge operation can improve the accuracy of the calculation results, making the calculation results closer to the actual data, thereby improving the accuracy of the judgment of the operating status of the energy storage device.

[0069] The calculation process of the data calculation unit also includes:

[0070] By formula Calculate the operating status risk value of the energy storage device at the i-th time point during the discharge operation ;

[0071] in, is the current of the energy storage device at the i-th time point during the discharge operation, The standard current size preset for energy storage equipment, for The standard value of can be set based on the allowable error fitting in the empirical data. is the voltage intensity of the energy storage device at the i-th time point during the discharge operation, The voltage intensity preset for the energy storage device, is the operating temperature of the energy storage device at the i-th time point during the discharge operation, The preset operating temperature for the energy storage device, and 2 is the weight coefficient, which can be set based on empirical fitting;

[0072] Through the above technical solution, this embodiment provides the operating state risk value of the energy storage device at the i-th time point during the discharge operation. , can be obtained by formula Calculations show that, obviously, when the current magnitude of the energy storage device at the i-th time point during the discharge operation differs greatly from the preset current magnitude, and the higher the voltage intensity and operating temperature of the energy storage device at the i-th time point during the discharge operation, the higher the operating status risk value of the energy storage device at the i-th time point during the discharge operation. Moreover, after combining the environmental impact coefficient and the equipment damage coefficient, the authenticity and accuracy of the calculation results can be improved, thereby providing strong data support for the subsequent judgment of the operating status of the energy storage device and ensuring the accuracy of the monitoring and judgment results.

[0073] The analysis process of the analysis and comparison unit includes:

[0074] By calculating the operating state risk value of the energy storage device at the i-th time point in the discharge operation Compared with the preset operating status risk value threshold Make a comparison;

[0075] like ,The system judges that the operation risk value at this time point is low, indicating that the operation status of the energy storage device is good, and predicts the performance change trend of the energy storage device through the evaluation unit;

[0076] like The system determines that the operation risk value at this point in time is high, indicating that the operating status of the energy storage equipment is poor, and issues an early warning through the early warning unit to remind the operation and maintenance personnel to inspect and repair the energy storage equipment in a timely manner;

[0077] Through the above technical solution, this embodiment calculates the operating state risk value of the energy storage device at the i-th time point during the discharge operation. Compared with the preset operating status risk value threshold Comparison is performed. Since the operating status risk value of the energy storage device at the i-th time point during the discharge operation is calculated by combining the environmental impact coefficient and the equipment damage coefficient, the authenticity and accuracy of this data are high, and an accurate judgment can be made on the operating status of the energy storage device. This avoids the possibility of making incorrect judgments on the operating status of the energy storage device due to a certain deviation between the collected data and the actual data, thereby improving the accuracy of the monitoring results.

[0078] It should be noted that the above preset operating status risk value threshold It can be set based on experience fitting.

[0079] The evaluation process of the evaluation unit includes:

[0080] First, by the formula Calculate the total risk value of the operating status of the energy storage equipment during discharge operation ;

[0081] And through the formula Calculate the total value of the equipment damage coefficient of the energy storage equipment during discharge operation ;

[0082] Finally, the formula Calculate the future performance change index of energy storage equipment ;

[0083] in, is the total number of data collection times of the energy storage device during the discharge operation, Any use in the working history of the energy storage device, is the total number of times the energy storage device has been used in its working history. is the total risk value of the operating status of the energy storage device when it is used for the ath time in its working history, For all The average value of is the total value of the equipment damage coefficient when the energy storage equipment is used for the ath time in its working history, For all The average value of and 2 is the weight coefficient, which can be set based on empirical fitting;

[0084] Through the above technical solution, this embodiment provides the energy storage device future performance change index , can be obtained by formula Calculated, where the formula The dispersion coefficient of the total risk value in the working history of the energy storage equipment can be calculated. This data can reflect the risk value fluctuation of the energy storage equipment in the historical working process. The formula The dispersion coefficient of the equipment damage coefficient in the working history of the energy storage equipment can be calculated. This data can reflect the fluctuation of the equipment damage coefficient of the energy storage equipment in the historical working process. By combining the two sets of data of the energy storage equipment in the historical working process, the future performance change index of the energy storage equipment can be calculated, thereby judging the risk of the future operation of the energy storage equipment. The system can formulate a scientific and reasonable maintenance plan based on the data, and perform preventive maintenance in advance before the equipment performance begins to decline or failure may occur, which can effectively reduce unplanned downtime and avoid damage to the energy storage equipment.

[0085] The assessment process for the assessment unit also includes;

[0086] By using the energy storage equipment future performance change index Compared with the preset performance change index threshold Make a comparison;

[0087] like ,The system judges that the future performance change index of the energy storage equipment is small, ,which indicates that the future operation state of the energy storage equipment ,will be stable and the future operation performance will not be affected;

[0088] like ,The system judges that the future performance change index of the energy storage equipment is large, which means that the future operating state stability of the energy storage equipment is poor and the future operating performance will be affected;

[0089] Through the above technical solution, this implementation will be carried out by the energy storage equipment future performance change index Compared with the preset performance change index threshold By comparing the performance of the energy storage equipment, the magnitude of the future performance change index can be judged, and the stability of the energy storage equipment's future operating status can be predicted based on the judgment results. With this setting, the system can formulate a scientific and reasonable maintenance plan based on this data. Before the equipment performance begins to decline or failure may occur, preventive maintenance can be carried out in advance, which can effectively reduce unplanned downtime and avoid damage to the energy storage equipment.

[0090] It should be noted that the above performance change index threshold It can be set based on experience fitting.

[0091] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A distributed energy storage equipment monitoring system based on big data, characterized in that: The system comprises: A data monitoring module, including a data acquisition unit and an image acquisition unit, wherein the data acquisition unit is used to collect operating parameter data and environmental information data of the energy storage device; The image acquisition unit is used to capture the appearance image of the energy storage device; An identification and recording module, used to identify data in the appearance image provided by the image acquisition module, and record the data together with the operating parameter data and the environmental information data; The data processing module includes a data calculation unit and an analysis and comparison unit, wherein the data calculation unit is used to first calculate the environmental impact coefficient and the equipment damage coefficient according to the data recorded in the identification and recording module, and combine the two to calculate the operating state risk value of the energy storage device in the discharge operation; The analysis and comparison unit is used to compare the preset operating state risk value threshold with the operating state risk value of the energy storage device in the discharge operation, and analyze the operating state of the energy storage device according to the comparison result; An early warning evaluation module, comprising an early warning unit and an evaluation unit, wherein the early warning unit is used to issue an early warning when it is determined that the operating state of the energy storage device is poor; The evaluation unit is used to predict the performance change trend of the energy storage device based on big data and past data analysis when judging that the operating state of the energy storage device is good; The operating parameter data recorded in the identification and recording module include voltage intensity, current size and energy storage device temperature; the environmental information data recorded in the identification and recording module include environmental temperature, humidity and floating matter content in the air; the appearance image data recorded in the identification and recording module include the damaged area, corroded area and stained area of ​​the energy storage device; The calculation process of the data calculation unit includes: By formula Calculate the equipment damage coefficient at the i-th time point ; Where i is a data collection at a fixed time interval, is the apparent damaged area of ​​the energy storage device at the i-th time point during the discharge operation, is the surface corrosion area of ​​the energy storage device at the i-th time point during the discharge operation, is the pollution area of ​​the energy storage equipment at the i-th time point during the discharge operation, is the surface area of ​​the energy storage device, The odor impact function is obtained based on the test results according to the influence of different odor data around the energy storage device on the damage coefficient of the device. is the odor data of the energy storage device at the i-th time point during the discharge operation, is the error influence coefficient, which is set according to empirical fitting; The calculation process of the data calculation unit also includes: By formula Calculate the environmental impact coefficient at the i-th time point ; in, is the ambient temperature of the energy storage device at the i-th time point during the discharge operation, is the preset standard ambient temperature. for The standard value of is the ambient humidity of the energy storage device at the i-th time point during the discharge operation, is the preset ambient humidity, is the floating matter content in the air at the i-th time point during the discharge operation of the energy storage device, The preset floating matter content in the air; The calculation process of the data calculation unit also includes: By formula Calculate the operating status risk value of the energy storage device at the i-th time point during the discharge operation ; in, is the current of the energy storage device at the i-th time point during the discharge operation, The standard current size preset for energy storage equipment, for The standard value of is the voltage intensity of the energy storage device at the i-th time point during the discharge operation, The voltage intensity preset for the energy storage device, is the operating temperature of the energy storage device at the i-th time point during the discharge operation, The preset operating temperature for the energy storage device, and is the weight coefficient; The analysis process of the analysis and comparison unit includes: By calculating the operating status risk value of the energy storage device at the i-th time point in the discharge operation Compared with the preset operating status risk value threshold Make a comparison; like ,The system determines that the operation risk value at this time point is low, indicating that the operation status of the energy storage device is good, and predicts the performance change trend of the energy storage device through the evaluation unit; like , the system determines that the operation risk value at this time point is high, indicating that the operation status of the energy storage equipment is poor, and issues an early warning through the early warning unit to remind the operation and maintenance personnel to inspect and repair the energy storage equipment in time; The evaluation process of the evaluation unit includes: First, by the formula Calculate the total risk value of the operating status of the energy storage equipment during the discharge operation ; And through the formula Calculate the total value of the equipment damage coefficient of the energy storage equipment during the discharge operation ; Finally, the formula Calculate the future performance change index of energy storage equipment ; in, is the total number of data collection times of the energy storage device during the discharge operation, Any use in the working history of the energy storage device. is the total number of times the energy storage device has been used in its working history. is the total risk value of the operating status of the energy storage device when it is used for the ath time in its working history, For all The average value of is the total value of the equipment damage coefficient when the energy storage equipment is used for the ath time in its working history, For all The average value of and is the weight coefficient.

2. According to a distributed energy storage device monitoring system based on big data according to claim 1, it is characterized in that: The assessment process of the assessment unit also includes; By using the energy storage device future performance change index With the preset performance change index threshold Make a comparison; like ,The system judges that the future performance change index of the energy storage equipment is small, which means that the future operation state of the energy storage equipment will be stable and the future operation performance will not be affected; like ,The system judges that the future performance change index of the energy storage equipment is large, which means that the future operating state stability of the energy storage equipment is poor and the future operating performance will be affected.

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