Methods, devices, computer equipment and storage media for fault detection of energy storage equipment

Abstract

This application relates to a method, apparatus, computer equipment, and storage medium for fault detection of energy storage devices. This application determines whether the energy storage device experiences output power fluctuations. If output power fluctuations occur, the number of fluctuations is counted. Based on the cumulative number of output power fluctuations, the accuracy of fault detection is improved, and the method is objective and accurate. Output power fluctuation faults can be detected using control software, reducing investment costs.

Description

Technical Field

[0001] This application relates to the field of energy storage equipment technology, and in particular to a method, apparatus, computer equipment and storage medium for fault detection of energy storage equipment. Background Technology

[0002] A common fault in energy storage equipment operation is output power fluctuation caused by load or battery failure. When the energy storage equipment enters an output power fluctuation condition, periodic oscillations occur between the energy storage equipment and the electrical equipment, generating strong voltage fluctuations, which can even cause serious damage to both the energy storage equipment and the electrical equipment in severe cases. Therefore, timely and accurate determination of whether output power fluctuations occur in energy storage equipment is of great significance for ensuring the safe and stable operation of both energy storage equipment and electrical equipment.

[0003] Currently, the main method for determining whether an energy storage device is experiencing output power fluctuations is by observing the stability of the energy storage device and the electrical equipment. This method protects against sudden output power fluctuations by blowing fuses. Therefore, it is necessary to develop a more accurate and reliable method for determining energy storage device faults. Summary of the Invention

[0004] Based on this, a method, apparatus, computer equipment, and storage medium for fault detection of energy storage devices are provided to solve the technical problem that the current method of judging whether the output power of an energy storage device has fluctuated depends on observing the stability of the operation of the energy storage device and the electrical equipment, which lacks objectivity and accuracy. The method enables accurate judgment of the output power fluctuation of the energy storage device through control software.

[0005] On the one hand, a fault detection method for energy storage equipment is provided, the method comprising:

[0006] To determine whether the energy storage device has experienced output power fluctuations, if the energy storage device has experienced output power fluctuations, the cumulative number of consecutive output power fluctuations will be counted during the second monitoring period.

[0007] The fluctuation levels of the output power fluctuations of the energy storage device are set to include high-risk, medium-risk, and low-risk levels. The fault types of the energy storage device are set to include shutdown fault, maintenance-pending fault, and observation-pending fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-pending fault, and the observation-pending fault corresponds to the low-risk level.

[0008] When the cumulative number of consecutive output power fluctuations counted during the second monitoring period exceeds the first threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be high-risk, and an early warning message for the energy storage device to be shut down is issued.

[0009] When the cumulative number of consecutive output power fluctuations counted during the second monitoring period is less than the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be low-risk, and an early warning message is issued that the energy storage device is a fault requiring maintenance.

[0010] When the cumulative number of consecutive output power fluctuations counted during the second monitoring period is between the first threshold and the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be medium-risk, and an early warning message for the energy storage device to be observed for fault is issued.

[0011] In one embodiment, determining whether the energy storage device experiences output power fluctuations includes:

[0012] Real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data to determine whether the energy storage device experiences sudden data changes;

[0013] In response to a sudden data change in the energy storage device, the output power of the energy storage device and its corresponding output voltage and current data are acquired during the first monitoring time period to obtain the fluctuation segment monitoring data.

[0014] Based on the monitoring data of the fluctuation segment, determine whether there is an output power fluctuation during the first monitoring period. If there is an output power fluctuation, count the number of output power fluctuations during the second monitoring period.

[0015] If the number of fluctuations during the second monitoring period exceeds the fluctuation threshold, it is determined that the energy storage device has experienced output power fluctuations; otherwise, it is determined that the energy storage device has not experienced output power fluctuations.

[0016] In one embodiment, the real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data, and the determination of whether the energy storage device has experienced a data mutation, includes:

[0017] The output power of the energy storage device and its corresponding output voltage and current data are obtained at the first moment and used as the first monitoring data;

[0018] The output power of the energy storage device at the second moment and its corresponding output voltage and current data are obtained as the second monitoring data;

[0019] Based on the difference between the second monitoring data and the first monitoring data, it is determined whether the energy storage device has experienced a data mutation.

[0020] If the difference between the output power of the energy storage device at the first moment and the output power at the second moment is greater than the power mutation threshold, and the difference between the output voltage of the energy storage device at the first moment and the output voltage at the second moment is greater than the voltage mutation threshold, and the difference between the output current of the energy storage device at the first moment and the output current at the second moment is greater than the current mutation threshold, then it is determined that the energy storage device has experienced a data mutation; otherwise, it is determined that the energy storage device has not experienced a data mutation.

[0021] In one embodiment, the energy storage device fault detection method further includes:

[0022] A first evaluation weight is determined based on the first monitoring data, and a first health evaluation model is constructed based on the first monitoring data and the first evaluation weight. In response to the determination that the energy storage device has not experienced a data mutation, the first health evaluation model is used to evaluate the health of the energy storage device.

[0023] In response to the determination that the energy storage device has experienced a data mutation, the first evaluation weight is updated to form a second evaluation weight, and a second health evaluation model is constructed based on the second monitoring data and the second evaluation weight. The health of the energy storage device is then evaluated using the second health evaluation model.

[0024] In response to the energy storage device's health status being greater than or equal to a first health threshold, the energy storage device is controlled according to a first control strategy;

[0025] In response to the energy storage device's health status being less than a first health threshold, the energy storage device is controlled according to a second control strategy, an isolation flag is set for the energy storage device, and several consecutive risk assessments are performed.

[0026] If the feedback results of the continuous risk assessment of the energy storage device are all normal, the health of the energy storage device is reassessed using the first health evaluation model. If the health of the energy storage device is greater than or equal to the second health threshold, the isolation label is removed from the energy storage device.

[0027] In one embodiment, the step of acquiring the output power and corresponding output voltage and current data of the energy storage device during a first monitoring period in response to a data mutation in the energy storage device, and obtaining the fluctuation segment monitoring data, includes:

[0028] In response to a sudden data change, the first monitoring period is divided into multiple consecutive fluctuation confirmation periods.

[0029] According to the order of the fluctuation confirmation time period, the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI are obtained in each fluctuation confirmation time period. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power.

[0030] The minimum output power (MinPow), the maximum output power (MaxPow), the minimum output voltage (MinV), the minimum output current (MinI), the maximum output voltage (MaxV), and the maximum output current (MaxI) obtained within each fluctuation confirmation period are used as fluctuation segment monitoring data.

[0031] In one embodiment, the step of determining whether an output power fluctuation occurs within the first monitoring time period based on the fluctuation segment monitoring data, and if an output power fluctuation occurs, counting the number of output power fluctuations within the second monitoring time period, further includes:

[0032] When the change in output power during the target fluctuation confirmation period is less than or equal to the output power change ratio threshold, it is determined that the output power has not fluctuated during the target fluctuation confirmation period. The change in output power is expressed as: (MaxPow-MinPow) / (MaxPow+MinPow).

[0033] When the change in output power during the target fluctuation confirmation period is greater than the output power change ratio threshold, it is determined whether the difference between the maximum output voltage and the minimum output voltage is less than the output voltage change threshold and whether the difference between the maximum output current and the minimum output current is less than the output current change threshold during the target fluctuation confirmation period.

[0034] If so, it is determined that the output power did not fluctuate once during the target fluctuation confirmation period; otherwise, it is determined that the output power fluctuated once during the target fluctuation confirmation period.

[0035] In response to the determination that no fluctuation occurs within the target fluctuation confirmation period, a second fluctuation judgment is performed within the fluctuation confirmation period following the target fluctuation confirmation period. This fluctuation judgment is repeated in a loop. If a fluctuation occurs within the first monitoring period, the next step is executed. If no fluctuation occurs within the first monitoring period, the process ends.

[0036] In response to the determination that a fluctuation occurs within the target fluctuation confirmation period, output power fluctuation is judged during the second monitoring period after the target fluctuation confirmation period, and the cumulative number of output power fluctuations occurring during the second monitoring period is counted.

[0037] In one embodiment, the counting of the cumulative number of output power fluctuations occurring during the second monitoring time period includes:

[0038] The second monitoring period is divided into multiple consecutive fluctuation statistical periods.

[0039] The cumulative fluctuation count is set to a default value of one. In each fluctuation statistics period, it is determined whether there is an output power fluctuation. If there is an output power fluctuation, the cumulative fluctuation count is incremented by one. If there is no output power fluctuation, the cumulative fluctuation count is decremented by one.

[0040] The cumulative number of fluctuations is taken as the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0041] On the other hand, a fault detection device for an energy storage device is provided, the device comprising:

[0042] The power fluctuation judgment module is used to determine whether the energy storage device has experienced output power fluctuation. In response to the energy storage device experiencing output power fluctuation, the module counts the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0043] The hazard level management module is used to set the fluctuation level of the output power fluctuation of the energy storage device, including high-risk level, medium-risk level and low-risk level, and to set the fault type of the energy storage device, including shutdown fault, maintenance-awaited fault and observation fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-awaited fault, and the observation fault corresponds to the low-risk level.

[0044] The cumulative fluctuation count module is used to count the cumulative number of consecutive output power fluctuations during the second monitoring period in response to the output power fluctuation of the energy storage device.

[0045] The fault diagnosis and early warning module is used to determine that the output power fluctuation level of the energy storage device is high-risk when the cumulative number of consecutive output power fluctuations counted during the second monitoring period exceeds a first threshold, and to issue an early warning message that the energy storage device is experiencing a shutdown fault; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is less than a second threshold, the module determines that the output power fluctuation level of the energy storage device is low-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring maintenance; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is between the first threshold and the second threshold, the module determines that the output power fluctuation level of the energy storage device is medium-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring observation.

[0046] In another aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the energy storage device fault detection method.

[0047] In another aspect, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the energy storage device fault detection method.

[0048] The aforementioned output power fluctuation judgment method, device, computer equipment, and storage medium improve the accuracy of energy storage device fault judgment by judging whether the energy storage device has output power fluctuation. If output power fluctuation occurs, the number of output power fluctuations is counted. Based on the counted cumulative number of output power fluctuations, the accuracy of energy storage device fault judgment is improved. Moreover, it has objectivity and accuracy. The output power fluctuation fault of energy storage device can be judged by control software, reducing investment costs. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a fault detection method for an energy storage device in one embodiment of this application;

[0051] Figure 2 This is a structural block diagram of an energy storage device fault detection device in one embodiment of this application;

[0052] Figure 3This is an internal structural diagram of a computer device in one embodiment of this application. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] To address the aforementioned issues, this invention presents a novel method for detecting faults in energy storage devices. The overall approach to judging output power fluctuations is as follows: under steady-state output voltage conditions, if the percentage of continuous output power fluctuations exceeds a certain value, it is judged as an output power fluctuation; under dynamic speed regulation of output voltage conditions, no output power fluctuation judgment is performed; the distinction between steady-state output voltage and dynamic output voltage is based on the rate of change of output voltage.

[0055] In one embodiment, such as Figure 1 As shown, a fault detection method for energy storage equipment is provided, including the following steps:

[0056] Step S1: Determine whether the energy storage device has experienced output power fluctuations. If the energy storage device has experienced output power fluctuations, count the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0057] Step S2: Set the fluctuation level of the output power fluctuation of the energy storage device to include high-risk level, medium-risk level and low-risk level; set the fault type of the energy storage device to include shutdown fault, maintenance-awaited fault and observation fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-awaited fault, and the observation fault corresponds to the low-risk level.

[0058] Step S3: When the cumulative number of consecutive output power fluctuations counted during the second monitoring time period exceeds the first threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be high-risk, and an early warning message for the energy storage device to be shut down is issued.

[0059] Step S4: When the cumulative number of consecutive output power fluctuations counted during the second monitoring period is less than the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be low-risk, and an early warning message is issued that the energy storage device is a fault requiring maintenance.

[0060] Step S5: When the cumulative number of consecutive output power fluctuations counted during the second monitoring period is between the first threshold and the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be medium-risk, and an early warning message is issued that the energy storage device is a fault to be observed.

[0061] The fluctuation levels based on different output power fluctuations can reasonably indicate the fault status of energy storage devices. Moreover, judging the fluctuation level of output power fluctuations based on the cumulative number of consecutive output power fluctuations can reduce the impact of occasional output power fluctuations. The fluctuation level of output power fluctuations of energy storage devices can be accurately assessed based on the frequency of output power fluctuations, thus accurately reflecting the fault status of energy storage devices.

[0062] The determination of whether the energy storage device experiences output power fluctuations includes:

[0063] Real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data to determine whether the energy storage device experiences sudden data changes;

[0064] In response to a sudden data change in the energy storage device, the output power of the energy storage device and its corresponding output voltage and current data are acquired during the first monitoring time period to obtain the fluctuation segment monitoring data.

[0065] Based on the monitoring data of the fluctuation segment, determine whether there is an output power fluctuation during the first monitoring period. If there is an output power fluctuation, count the number of output power fluctuations during the second monitoring period.

[0066] If the number of fluctuations during the second monitoring period exceeds the fluctuation threshold, it is determined that the energy storage device has experienced output power fluctuations; otherwise, it is determined that the energy storage device has not experienced output power fluctuations.

[0067] Specifically, by first determining whether there are sudden changes in the output power of the energy storage device and its corresponding output voltage and current data, and then further determining whether there are output power fluctuations when data changes occur, and if output power fluctuations occur, the number of output power fluctuations is counted. Based on the cumulative number of output power fluctuations, it is determined whether the energy storage device has experienced output power fluctuations. This can improve the accuracy of energy storage device fault diagnosis and is objective and accurate. The output power fluctuation faults of energy storage devices can be diagnosed through control software, reducing investment costs.

[0068] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" and "second" may explicitly or implicitly include one or more of the aforementioned features. The first monitoring time period is preferably 1 minute, the second monitoring time period is preferably 3 minutes, and the fluctuation threshold number is preferably 6 times. That is, when a data mutation is detected in the energy storage device, monitoring data for the fluctuation segment is acquired within the following 1 minute. If no output power fluctuation occurs within this 1 minute, it indicates that the data mutation is an occasional occurrence. If an output power fluctuation occurs within this 1 minute, the number of output power fluctuations is counted within the following 3 minutes. If the number of output power fluctuations counted within 3 minutes is greater than 6, it is determined that the energy storage device has experienced output power fluctuation; otherwise, it is determined that the energy storage device has not experienced output power fluctuation. The first monitoring time period, the second monitoring time period, and the fluctuation threshold number can be adjusted according to actual circumstances and are not limited here.

[0069] The real-time monitoring of the energy storage device's output power and its corresponding output voltage and current data, and the determination of whether the energy storage device has experienced a data mutation, includes:

[0070] The output power of the energy storage device and its corresponding output voltage and current data are obtained at the first moment and used as the first monitoring data;

[0071] The output power of the energy storage device at the second moment and its corresponding output voltage and current data are obtained as the second monitoring data;

[0072] Based on the difference between the second monitoring data and the first monitoring data, it is determined whether the energy storage device has experienced a data mutation.

[0073] If the difference between the output power of the energy storage device at the first moment and the output power at the second moment is greater than the power mutation threshold, and the difference between the output voltage of the energy storage device at the first moment and the output voltage at the second moment is greater than the voltage mutation threshold, and the difference between the output current of the energy storage device at the first moment and the output current at the second moment is greater than the current mutation threshold, then it is determined that the energy storage device has experienced a data mutation; otherwise, it is determined that the energy storage device has not experienced a data mutation.

[0074] The first and second moments represent different points in time along the time axis. Preferably, the first and second moments are spaced one to ten minutes apart, indicating that the detection determines whether a data mutation has occurred in the energy storage device within this one- to ten-minute interval. The power mutation threshold is preferably one-tenth of the average power of the energy storage device during power transmission, and the voltage mutation threshold is preferably one-tenth of the average voltage of the energy storage device during power transmission. Setting the power mutation threshold in this way can effectively monitor whether a data mutation has occurred. The first moment, the second moment, the power mutation threshold, and the voltage mutation threshold can be adjusted according to actual conditions and are not limited here.

[0075] In this embodiment, the energy storage device fault detection method further includes:

[0076] A first evaluation weight is determined based on the first monitoring data, and a first health evaluation model is constructed based on the first monitoring data and the first evaluation weight. In response to the determination that the energy storage device has not experienced a data mutation, the first health evaluation model is used to evaluate the health of the energy storage device.

[0077] In response to the determination that the energy storage device has experienced a data mutation, the first evaluation weight is updated to form a second evaluation weight, and a second health evaluation model is constructed based on the second monitoring data and the second evaluation weight. The health of the energy storage device is then evaluated using the second health evaluation model.

[0078] In response to the energy storage device's health status being greater than or equal to a first health threshold, the energy storage device is controlled according to a first control strategy;

[0079] In response to the energy storage device's health status being less than a first health threshold, the energy storage device is controlled according to a second control strategy, an isolation flag is set for the energy storage device, and several consecutive risk assessments are performed.

[0080] If the feedback results of the continuous risk assessment of the energy storage device are all normal, the health of the energy storage device is reassessed using the first health evaluation model. If the health of the energy storage device is greater than or equal to the second health threshold, the isolation label is removed from the energy storage device.

[0081] The first and second evaluation weights are weight arrays corresponding to the factors affecting the transmission capacity of the energy storage device. These factors include the average transmission delay D of the transmission line, transmission stability V, energy consumption Q of the transmission line resistance, and the control and regulation efficiency C of the energy storage device. The first evaluation weight includes weights Wd, Wv, Wq, and Wc corresponding to the average transmission delay D, transmission stability V, energy consumption Q of the transmission line resistance, and the control and regulation efficiency C of the energy storage device, respectively. The second evaluation weight includes weights Wd, Wv, Wq, and Wc corresponding to the average transmission delay D, transmission stability V, energy consumption Q of the transmission line resistance, and the control and regulation efficiency C of the energy storage device, respectively. The weights Wd', Wv', Wq', and Wc' for the energy consumption Q due to road resistance and the control and regulation efficiency C of the energy storage device differ between the first and second evaluation weights. This is because the first monitoring data changes under different operating conditions, and different combinations of monitoring data produce different effects. Therefore, different evaluation weights are set for different combinations of monitoring data to reflect their different effects. When the first monitoring data changes to the second monitoring data, the first evaluation weight also needs to be adjusted accordingly to the second evaluation weight, thus enabling different health evaluation models to be formed based on the monitoring data and evaluation weights. When the first monitoring data changes to the second monitoring data, the health evaluation model also changes from the first to the second health evaluation model, reflecting the different effects produced by the energy storage device.

[0082] The first health assessment model is H1=Wd*(1-D)+Wv*V+Wq*(1-Q)+Wc*C, and the second health assessment model is H2=Wd'*(1-D)+Wv'*V+Wq'*(1-Q)+Wc'*C, where D represents the average transmission delay of the transmission line, V represents the transmission stability, Q represents the energy consumption of the transmission line resistance, C represents the control and regulation efficiency of the energy storage device, Wd represents the first weight corresponding to the average transmission delay of the transmission line, Wv represents the first weight corresponding to the transmission efficiency of the transformer, Wq represents the first weight corresponding to the energy consumption of the grid resistance, Wc represents the first weight corresponding to the control and regulation efficiency of the energy storage device, Wd' represents the second weight corresponding to the average transmission delay of the transmission line, Wv' represents the second weight corresponding to the transmission efficiency of the transformer, Wq' represents the second weight corresponding to the energy consumption of the grid resistance, and Wc' represents the second weight corresponding to the control and regulation efficiency of the energy storage device.

[0083] The first and second health thresholds can be adjusted according to the actual situation, and are not limited here.

[0084] The first control strategy is a power transmission control method suitable for energy storage devices with high health levels, while the second control strategy is a power transmission control method suitable for energy storage devices with low health levels. The difference between the first and second control strategies lies in the different control parameters such as power transmission and duration for energy storage devices with different health levels.

[0085] In this embodiment, the step of acquiring the output power and corresponding output voltage and current data of the energy storage device during the first monitoring time period in response to a data mutation in the energy storage device, and obtaining the fluctuation segment monitoring data, includes:

[0086] In response to a sudden data change, the first monitoring period is divided into multiple consecutive fluctuation confirmation periods.

[0087] According to the order of the fluctuation confirmation time period, the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI are obtained in each fluctuation confirmation time period. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power.

[0088] The minimum output power (MinPow), the maximum output power (MaxPow), the minimum output voltage (MinV), the minimum output current (MinI), the maximum output voltage (MaxV), and the maximum output current (MaxI) obtained within each fluctuation confirmation period are used as fluctuation segment monitoring data.

[0089] In this embodiment, the step of determining whether output power fluctuation occurs within the first monitoring time period based on the fluctuation segment monitoring data, and counting the number of output power fluctuations within the second monitoring time period if output power fluctuation occurs, further includes:

[0090] When the change in output power during the target fluctuation confirmation period is less than or equal to the output power change ratio threshold, it is determined that the output power has not fluctuated during the target fluctuation confirmation period. The change in output power is expressed as: (MaxPow-MinPow) / (MaxPow+MinPow).

[0091] When the change in output power during the target fluctuation confirmation period is greater than the output power change ratio threshold, it is determined whether the difference between the maximum output voltage and the minimum output voltage is less than the output voltage change threshold and whether the difference between the maximum output current and the minimum output current is less than the output current change threshold during the target fluctuation confirmation period.

[0092] If so, it is determined that the output power did not fluctuate once during the target fluctuation confirmation period; otherwise, it is determined that the output power fluctuated once during the target fluctuation confirmation period.

[0093] In response to the determination that no fluctuation occurs within the target fluctuation confirmation period, a second fluctuation judgment is performed within the fluctuation confirmation period following the target fluctuation confirmation period. This fluctuation judgment is repeated in a loop. If a fluctuation occurs within the first monitoring period, the next step is executed. If no fluctuation occurs within the first monitoring period, the process ends.

[0094] In response to the determination that a fluctuation occurs within the target fluctuation confirmation period, output power fluctuation is judged during the second monitoring period after the target fluctuation confirmation period, and the cumulative number of output power fluctuations occurring during the second monitoring period is counted.

[0095] Understandably, within the target fluctuation confirmation period (1 minute), the minimum and maximum values ​​of the output power Pow (MinPow and MaxPow), as well as the corresponding output voltages MinV and MaxV, are detected. If the change in output power (MaxPow - MinPow) / (MaxPow + MinPow) > 10% (output power change threshold), and simultaneously |MaxV - MinV| < 5000 volts (output voltage change threshold) and |MaxI - MinI| < 200 amps (output current change threshold), then a fluctuation in output power is considered to have occurred. If |MaxV - MinV| > 5000 volts (output voltage change threshold) and |MaxI - MinI| > 200 amps (output current change threshold), then it is considered to be in dynamic fine-tuning, and no fluctuation judgment is made. Once a fluctuation is detected, a second fluctuation judgment is immediately performed; and so on.

[0096] In this embodiment, the counting of cumulative output power fluctuations occurring during the second monitoring time period includes:

[0097] The second monitoring period is divided into multiple consecutive fluctuation statistical periods.

[0098] The cumulative fluctuation count is set to a default value of one. In each fluctuation statistics period, it is determined whether there is an output power fluctuation. If there is an output power fluctuation, the cumulative fluctuation count is incremented by one. If there is no output power fluctuation, the cumulative fluctuation count is decremented by one.

[0099] The cumulative number of fluctuations is taken as the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0100] Understandably, after each fluctuation, an output power fluctuation confirmation timer is initiated. Within the second monitoring period (3 minutes), if the number of fluctuations exceeds the fluctuation threshold (4 times), an output power fluctuation is considered to have occurred, and an output power fluctuation warning message is output. If the number of fluctuations does not reach the fluctuation threshold (4 times) within the second monitoring period, then within each fluctuation statistics time (1 minute), if no fluctuation occurs, the cumulative fluctuation count is decremented by 1. When the next fluctuation occurs, the output power fluctuation confirmation timer is restarted, and the current cumulative fluctuation count is incremented by 1.

[0101] In this embodiment, determining whether output power fluctuations occur within each fluctuation statistical time period includes:

[0102] Within the target fluctuation statistical period, obtain the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power.

[0103] When the change in output power (MaxPow-MinPow) / (MaxPow+MinPow) within the target fluctuation statistical period is greater than the output power change ratio threshold, and when |MaxV-MinV| is less than the output voltage change threshold and |MaxI-MinI| is less than the output current change threshold within the target fluctuation statistical period, it is determined that output power fluctuation has occurred within the target fluctuation statistical period; otherwise, it is determined that no output power fluctuation has occurred within the target fluctuation statistical period.

[0104] The above-mentioned method for judging output power fluctuations first determines whether there are sudden changes in the output power of the energy storage device and its corresponding output voltage and current data. If a sudden change occurs, it further determines whether there is an output power fluctuation. If there is an output power fluctuation, the number of output power fluctuations is counted. Based on the cumulative number of output power fluctuations, it is determined whether the energy storage device has experienced an output power fluctuation. This method can improve the accuracy of judging energy storage device faults and has objectivity and accuracy. The output power fluctuation faults of energy storage devices can be judged through control software, reducing investment costs.

[0105] In one embodiment, such as Figure 2 As shown, a fault detection device for energy storage equipment is provided, comprising:

[0106] The power fluctuation judgment module is used to determine whether the energy storage device has experienced output power fluctuation. In response to the energy storage device experiencing output power fluctuation, the module counts the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0107] The hazard level management module is used to set the fluctuation level of the output power fluctuation of the energy storage device, including high-risk level, medium-risk level and low-risk level, and to set the fault type of the energy storage device, including shutdown fault, maintenance-awaited fault and observation fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-awaited fault, and the observation fault corresponds to the low-risk level.

[0108] The cumulative fluctuation count module is used to count the cumulative number of consecutive output power fluctuations during the second monitoring period in response to the output power fluctuation of the energy storage device.

[0109] The fault diagnosis and early warning module is used to determine that the output power fluctuation level of the energy storage device is high-risk when the cumulative number of consecutive output power fluctuations counted during the second monitoring period exceeds a first threshold, and to issue an early warning message that the energy storage device is experiencing a shutdown fault; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is less than a second threshold, the module determines that the output power fluctuation level of the energy storage device is low-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring maintenance; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is between the first threshold and the second threshold, the module determines that the output power fluctuation level of the energy storage device is medium-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring observation.

[0110] In this embodiment, determining whether the energy storage device experiences output power fluctuations includes:

[0111] Real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data to determine whether the energy storage device experiences sudden data changes;

[0112] In response to a sudden data change in the energy storage device, the output power of the energy storage device and its corresponding output voltage and current data are acquired during the first monitoring time period to obtain the fluctuation segment monitoring data.

[0113] Based on the monitoring data of the fluctuation segment, determine whether there is an output power fluctuation during the first monitoring period. If there is an output power fluctuation, count the number of output power fluctuations during the second monitoring period.

[0114] If the number of fluctuations during the second monitoring period exceeds the fluctuation threshold, it is determined that the energy storage device has experienced output power fluctuations; otherwise, it is determined that the energy storage device has not experienced output power fluctuations.

[0115] In this embodiment, the real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data, and the determination of whether the energy storage device has experienced a data mutation, includes:

[0116] The output power of the energy storage device and its corresponding output voltage and current data are obtained at the first moment and used as the first monitoring data;

[0117] The output power of the energy storage device at the second moment and its corresponding output voltage and current data are obtained as the second monitoring data;

[0118] Based on the difference between the second monitoring data and the first monitoring data, it is determined whether the energy storage device has experienced a data mutation.

[0119] If the difference between the output power of the energy storage device at the first moment and the output power at the second moment is greater than the power mutation threshold, and the difference between the output voltage of the energy storage device at the first moment and the output voltage at the second moment is greater than the voltage mutation threshold, and the difference between the output current of the energy storage device at the first moment and the output current at the second moment is greater than the current mutation threshold, then it is determined that the energy storage device has experienced a data mutation; otherwise, it is determined that the energy storage device has not experienced a data mutation.

[0120] like Figure 2 As shown, in this embodiment, the energy storage device fault detection device further includes a health assessment module, which is used for:

[0121] A first evaluation weight is determined based on the first monitoring data, and a first health evaluation model is constructed based on the first monitoring data and the first evaluation weight. In response to the determination that the energy storage device has not experienced a data mutation, the first health evaluation model is used to evaluate the health of the energy storage device.

[0122] In response to the determination that the energy storage device has experienced a data mutation, the first evaluation weight is updated to form a second evaluation weight, and a second health evaluation model is constructed based on the second monitoring data and the second evaluation weight. The health of the energy storage device is then evaluated using the second health evaluation model.

[0123] In response to the energy storage device's health status being greater than or equal to a first health threshold, the energy storage device is controlled according to a first control strategy;

[0124] In response to the energy storage device's health status being less than a first health threshold, the energy storage device is controlled according to a second control strategy, an isolation flag is set for the energy storage device, and several consecutive risk assessments are performed.

[0125] If the feedback results of the continuous risk assessment of the energy storage device are all normal, the health of the energy storage device is reassessed using the first health evaluation model. If the health of the energy storage device is greater than or equal to the second health threshold, the isolation label is removed from the energy storage device.

[0126] In this embodiment, the step of acquiring the output power and corresponding output voltage and current data of the energy storage device during the first monitoring time period in response to a data mutation in the energy storage device, and obtaining the fluctuation segment monitoring data, includes:

[0127] In response to a sudden data change, the first monitoring period is divided into multiple consecutive fluctuation confirmation periods.

[0128] According to the order of the fluctuation confirmation time period, the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI are obtained in each fluctuation confirmation time period. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power.

[0129] The minimum output power (MinPow), the maximum output power (MaxPow), the minimum output voltage (MinV), the minimum output current (MinI), the maximum output voltage (MaxV), and the maximum output current (MaxI) obtained within each fluctuation confirmation period are used as fluctuation segment monitoring data.

[0130] In this embodiment, the step of determining whether output power fluctuation occurs within the first monitoring time period based on the fluctuation segment monitoring data, and counting the number of output power fluctuations within the second monitoring time period if output power fluctuation occurs, further includes:

[0131] When the change in output power during the target fluctuation confirmation period is less than or equal to the output power change ratio threshold, it is determined that the output power has not fluctuated during the target fluctuation confirmation period. The change in output power is expressed as: (MaxPow-MinPow) / (MaxPow+MinPow).

[0132] When the change in output power during the target fluctuation confirmation period is greater than the output power change ratio threshold, it is determined whether the difference between the maximum output voltage and the minimum output voltage is less than the output voltage change threshold and whether the difference between the maximum output current and the minimum output current is less than the output current change threshold during the target fluctuation confirmation period.

[0133] If so, it is determined that the output power did not fluctuate once during the target fluctuation confirmation period; otherwise, it is determined that the output power fluctuated once during the target fluctuation confirmation period.

[0134] In response to the determination that no fluctuation occurs within the target fluctuation confirmation period, a second fluctuation judgment is performed within the fluctuation confirmation period following the target fluctuation confirmation period. This fluctuation judgment is repeated in a loop. If a fluctuation occurs within the first monitoring period, the next step is executed. If no fluctuation occurs within the first monitoring period, the process ends.

[0135] In response to the determination that a fluctuation occurs within the target fluctuation confirmation period, output power fluctuation is judged during the second monitoring period after the target fluctuation confirmation period, and the cumulative number of output power fluctuations occurring during the second monitoring period is counted.

[0136] In this embodiment, the counting of cumulative output power fluctuations occurring during the second monitoring time period includes:

[0137] The second monitoring period is divided into multiple consecutive fluctuation statistical periods.

[0138] The cumulative fluctuation count is set to a default value of one. In each fluctuation statistics period, it is determined whether there is an output power fluctuation. If there is an output power fluctuation, the cumulative fluctuation count is incremented by one. If there is no output power fluctuation, the cumulative fluctuation count is decremented by one.

[0139] The cumulative number of fluctuations is taken as the cumulative number of consecutive output power fluctuations during the second monitoring period.

[0140] In this embodiment, determining whether output power fluctuations occur within each fluctuation statistical time period includes:

[0141] Within the target fluctuation statistical period, obtain the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power.

[0142] When the change in output power (MaxPow-MinPow) / (MaxPow+MinPow) within the target fluctuation statistical period is greater than the output power change ratio threshold, and when |MaxV-MinV| is less than the output voltage change threshold and |MaxI-MinI| is less than the output current change threshold within the target fluctuation statistical period, it is determined that output power fluctuation has occurred within the target fluctuation statistical period; otherwise, it is determined that no output power fluctuation has occurred within the target fluctuation statistical period.

[0143] In the aforementioned output power fluctuation judgment device, it first judges whether there is a sudden change in the output power of the energy storage device and its corresponding output voltage and current data. When a sudden change occurs, it further judges whether there is an output power fluctuation. If there is an output power fluctuation, it counts the number of output power fluctuations. Based on the counted cumulative number of output power fluctuations, it determines whether the energy storage device has an output power fluctuation. This can improve the accuracy of energy storage device fault judgment and has objectivity and accuracy. The output power fluctuation fault of the energy storage device can be judged by the control software, reducing the investment cost.

[0144] Specific limitations regarding the output power fluctuation detection device can be found in the limitations of the output power fluctuation detection method described above, and will not be repeated here. Each module in the aforementioned output power fluctuation detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0145] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the energy storage device fault detection method.

[0146] For specific limitations on the steps implemented when a computer program is executed by a processor, please refer to the limitations on the method for judging output power fluctuations mentioned above, which will not be repeated here.

[0147] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores output power fluctuation judgment data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a fault detection method for energy storage devices.

[0148] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0149] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the energy storage device fault detection method.

[0150] For specific limitations on the steps a processor takes when executing a computer program, please refer to the limitations on the method for judging output power fluctuations mentioned above, which will not be repeated here.

[0151] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the energy storage device fault detection method.

[0152] For specific limitations on the steps implemented when a computer program is executed by a processor, please refer to the limitations on the method for judging output power fluctuations mentioned above, which will not be repeated here.

[0153] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0154] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for fault detection in energy storage equipment, characterized in that, include: To determine whether the energy storage device has experienced output power fluctuations, if the energy storage device has experienced output power fluctuations, the cumulative number of consecutive output power fluctuations will be counted during the second monitoring period. The fluctuation levels of the output power fluctuations of the energy storage device are set to include high-risk, medium-risk, and low-risk levels. The fault types of the energy storage device are set to include shutdown fault, maintenance-pending fault, and observation-pending fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-pending fault, and the observation-pending fault corresponds to the low-risk level. When the cumulative number of consecutive output power fluctuations exceeds a first threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be high-risk, and an early warning message indicating that the energy storage device is experiencing a shutdown failure is issued. When the cumulative number of consecutive output power fluctuations is less than the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be low-risk, and an early warning message is issued that the energy storage device is a fault requiring maintenance. When the cumulative number of consecutive output power fluctuations is between the first threshold and the second threshold, the fluctuation level of the output power fluctuation of the energy storage device is determined to be medium risk level, and an early warning message is issued that the energy storage device is a fault to be observed. The determination of whether the energy storage device experiences output power fluctuations includes: real-time monitoring of the output power of the energy storage device and its corresponding output voltage and current data, and determining whether the energy storage device experiences data abrupt changes; The real-time monitoring of the energy storage device's output power and its corresponding output voltage and current data, and the determination of whether the energy storage device has experienced a data mutation, includes: The output power of the energy storage device and its corresponding output voltage and current data are obtained at the first moment and used as the first monitoring data; The output power of the energy storage device at the second moment and its corresponding output voltage and current data are obtained as the second monitoring data; Based on the difference between the second monitoring data and the first monitoring data, it is determined whether the energy storage device has experienced a data mutation. The energy storage device fault detection method further includes: A first evaluation weight is determined based on the first monitoring data, and a first health evaluation model is constructed based on the first monitoring data and the first evaluation weight. In response to the determination that the energy storage device has not experienced a data mutation, the first health evaluation model is used to evaluate the health of the energy storage device. In response to the determination that the energy storage device has experienced a data mutation, the first evaluation weight is updated to form a second evaluation weight, and a second health evaluation model is constructed based on the second monitoring data and the second evaluation weight. The health of the energy storage device is then evaluated using the second health evaluation model. In response to the energy storage device's health status being greater than or equal to a first health threshold, the energy storage device is controlled according to a first control strategy; In response to the energy storage device's health status being less than a first health threshold, the energy storage device is controlled according to a second control strategy, an isolation flag is set for the energy storage device, and several consecutive risk assessments are performed. If the feedback results of the continuous risk assessment of the energy storage device are all normal, the health of the energy storage device is reassessed using the first health evaluation model. If the health of the energy storage device is greater than or equal to the second health threshold, the isolation label is removed from the energy storage device.

2. The energy storage device fault detection method according to claim 1, characterized in that, The determination of whether the energy storage device experiences output power fluctuations includes: In response to a sudden data change in the energy storage device, the output power of the energy storage device and its corresponding output voltage and current data are acquired during the first monitoring time period to obtain the fluctuation segment monitoring data. Based on the monitoring data of the fluctuation segment, determine whether there is an output power fluctuation during the first monitoring period. If there is an output power fluctuation, count the number of output power fluctuations during the second monitoring period. If the number of fluctuations during the second monitoring period exceeds the fluctuation threshold, it is determined that the energy storage device has experienced output power fluctuations; otherwise, it is determined that the energy storage device has not experienced output power fluctuations.

3. The energy storage device fault detection method according to claim 2, characterized in that, The real-time monitoring of the energy storage device's output power and corresponding output voltage and current data, and the determination of whether the energy storage device has experienced a data mutation, includes: If the difference between the output power of the energy storage device at the first moment and the output power at the second moment is greater than the power mutation threshold, and the difference between the output voltage of the energy storage device at the first moment and the output voltage at the second moment is greater than the voltage mutation threshold, and the difference between the output current of the energy storage device at the first moment and the output current at the second moment is greater than the current mutation threshold, then it is determined that the energy storage device has experienced a data mutation; otherwise, it is determined that the energy storage device has not experienced a data mutation.

4. The energy storage device fault detection method according to claim 2, characterized in that, In response to a sudden data change in the energy storage device, the system acquires the output power and corresponding output voltage and current data of the energy storage device during the first monitoring time period to obtain the fluctuation segment monitoring data, including: In response to a sudden data change, the first monitoring period is divided into multiple consecutive fluctuation confirmation periods. According to the order of the fluctuation confirmation time period, the minimum output power MinPow, the maximum output power MaxPow, the minimum output voltage MinV, the minimum output current MinI, the maximum output voltage MaxV, and the maximum output current MaxI are obtained in each fluctuation confirmation time period. Among them, the minimum output voltage MinV and the minimum output current MinI are the voltage and current corresponding to the minimum output power, and the maximum output voltage and the maximum output current MaxI are the voltage and current corresponding to the maximum output power. The minimum output power (MinPow), the maximum output power (MaxPow), the minimum output voltage (MinV), the minimum output current (MinI), the maximum output voltage (MaxV), and the maximum output current (MaxI) obtained within each fluctuation confirmation period are used as fluctuation segment monitoring data.

5. The energy storage device fault detection method according to claim 4, characterized in that, The step of determining whether output power fluctuations occur within the first monitoring time period based on the fluctuation segment monitoring data, and if output power fluctuations occur, counting the number of output power fluctuations within the second monitoring time period, further includes: When the change in output power during the target fluctuation confirmation period is less than or equal to the output power change ratio threshold, it is determined that the output power has not fluctuated during the target fluctuation confirmation period. The change in output power is expressed as: (MaxPow-MinPow) / (MaxPow+MinPow). When the change in output power during the target fluctuation confirmation period is greater than the output power change ratio threshold, it is determined whether the difference between the maximum output voltage and the minimum output voltage is less than the output voltage change threshold and whether the difference between the maximum output current and the minimum output current is less than the output current change threshold during the target fluctuation confirmation period. If so, it is determined that the output power did not fluctuate once during the target fluctuation confirmation period; otherwise, it is determined that the output power fluctuated once during the target fluctuation confirmation period. In response to the determination that no fluctuation occurs within the target fluctuation confirmation period, a second fluctuation judgment is performed within the fluctuation confirmation period following the target fluctuation confirmation period. This fluctuation judgment is repeated in a loop. If a fluctuation occurs within the first monitoring period, the next step is executed. If no fluctuation occurs within the first monitoring period, the process ends. In response to the determination that a fluctuation occurs within the target fluctuation confirmation period, output power fluctuation is judged during the second monitoring period after the target fluctuation confirmation period, and the cumulative number of output power fluctuations occurring during the second monitoring period is counted.

6. The energy storage device fault detection method according to claim 5, characterized in that, The statistics on the cumulative number of output power fluctuations that occurred during the second monitoring period include: The second monitoring period is divided into multiple consecutive fluctuation statistical periods. The cumulative fluctuation count is set to a default value of one. In each fluctuation statistics period, it is determined whether there is an output power fluctuation. If there is an output power fluctuation, the cumulative fluctuation count is incremented by one. If there is no output power fluctuation, the cumulative fluctuation count is decremented by one. The cumulative number of fluctuations is taken as the cumulative number of consecutive output power fluctuations during the second monitoring period.

7. A fault detection device for energy storage equipment, characterized in that, The apparatus for implementing the energy storage device fault detection method according to any one of claims 1 to 6, the apparatus comprising: The power fluctuation judgment module is used to determine whether the energy storage device has experienced output power fluctuation. In response to the energy storage device experiencing output power fluctuation, the module counts the cumulative number of consecutive output power fluctuations during the second monitoring period. The hazard level management module is used to set the fluctuation level of the output power fluctuation of the energy storage device, including high-risk level, medium-risk level and low-risk level, and to set the fault type of the energy storage device, including shutdown fault, maintenance-awaited fault and observation fault. The shutdown fault corresponds to the high-risk level, the medium-risk level corresponds to the maintenance-awaited fault, and the observation fault corresponds to the low-risk level. The cumulative fluctuation count module is used to count the cumulative number of consecutive output power fluctuations during the second monitoring period in response to the output power fluctuation of the energy storage device. The fault diagnosis and early warning module is used to determine that the output power fluctuation level of the energy storage device is high-risk when the cumulative number of consecutive output power fluctuations counted during the second monitoring period exceeds a first threshold, and to issue an early warning message that the energy storage device is experiencing a shutdown fault; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is less than a second threshold, the module determines that the output power fluctuation level of the energy storage device is low-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring maintenance; when the cumulative number of consecutive output power fluctuations counted during the second monitoring period is between the first threshold and the second threshold, the module determines that the output power fluctuation level of the energy storage device is medium-risk, and to issue an early warning message that the energy storage device is experiencing a fault requiring observation.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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