Fault detection method and apparatus for energy storage system, and computer device and storage medium

Abstract

The present application relates to a fault detection method and apparatus for an energy storage system, and a computer device and a storage medium. The method comprises: sampling a direct current of an energy storage system (S302); performing a fast Fourier transform on the direct current, so as to obtain a frequency spectrum corresponding to the direct current (S304); and when the frequency spectrum corresponding to the direct current is different from a reference standard frequency spectrum in a target frequency band, determining a fault condition of the energy storage system on the basis of a current change rate within the target frequency band (S306), wherein the reference standard frequency spectrum is a frequency spectrum corresponding to the direct current under the normal operation of the energy storage system. By means of the method, the false alarm rate of fault detection can be reduced.

Description

Fault detection method, device, computer equipment, and storage medium for energy storage system

[0001] This application claims priority to a domestic application filed with the Patent Office of China on March 27, 2024, with application number 202410362302.7 and invention name “Fault detection method, device, computer equipment, and storage medium for energy storage system,” the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the technical field of energy storage system fault detection, and in particular to a method, apparatus, computer equipment, and storage medium for energy storage system fault detection. Background Art

[0003] With the widespread application of renewable energy, the status of photovoltaic systems and energy storage systems in the power field has become increasingly prominent. Therefore, accurate fault detection is particularly important for the daily maintenance and normal operation of photovoltaic systems and energy storage systems.

[0004] Currently, fault detection for photovoltaic systems is relatively mature, with a low false alarm rate. However, fault detection for energy storage systems, due to their high voltage and high current characteristics, greatly increases the difficulty of detecting faults such as arcing, resulting in a significant increase in the risk of false alarms for energy storage systems.

[0005] Summary of the Invention

[0006] Based on this, it is necessary to provide a fault detection method, device, computer equipment, and storage medium for an energy storage system that can reduce the false alarm rate of fault detection in order to address the above technical problems.

[0007] In a first aspect, the present application provides a method for detecting a fault in an energy storage system, the method comprising:

[0008] Sampling the DC current of the energy storage system;

[0009] Perform fast Fourier transform on the DC current to obtain the spectrum corresponding to the DC current;

[0010] When the spectrum corresponding to the DC current differs from the reference standard spectrum in the target frequency band, the fault condition of the energy storage system is determined based on the current change rate within the target frequency band; the reference standard spectrum is the spectrum corresponding to the DC current under normal operation of the energy storage system.

[0011] In one embodiment, determining a fault condition of the energy storage system based on a current change rate within a target frequency band includes:

[0012] Determine whether the current change rate of the target frequency band is within a preset range; the preset range is used to represent the current change rate range when arcing occurs in the energy storage system;

[0013] When the current change rate in the target frequency band is within a preset range, it is determined that arcing occurs in the energy storage system.

[0014] In one embodiment, before determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0015] Obtain the maximum short-circuit current of the energy storage system and the maximum short-circuit time corresponding to the maximum short-circuit current;

[0016] The ratio of the maximum short-circuit current to the maximum short-circuit time is determined as an upper threshold value of the preset range.

[0017] In one embodiment, before determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0018] Obtain the maximum operating current of the energy storage system under normal operation and the duration of the maximum operating current; the maximum operating current is the maximum current that occurs when the energy storage system performs rapid power scheduling;

[0019] The ratio of the maximum operating current to the duration is determined as a lower threshold value of the preset range.

[0020] In one embodiment, after determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0021] When the current change rate in the target frequency band is not within a preset range, the DC current of the energy storage system is kept sampled.

[0022] In one embodiment, performing a fast Fourier transform on the DC current to obtain a spectrum corresponding to the DC current includes:

[0023] Extract the AC component of DC current;

[0024] Perform fast Fourier transform on the AC component to obtain the spectrum corresponding to the AC component;

[0025] The frequency spectrum corresponding to the AC component is determined as the frequency spectrum corresponding to the DC current.

[0026] In one embodiment, after obtaining the spectrum corresponding to the direct current, the method further includes:

[0027] When there is no difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band, the DC current of the energy storage system is kept sampled.

[0028] In one embodiment, determining whether a spectrum corresponding to the DC current differs from a reference standard spectrum in a target frequency band includes:

[0029] When the target current amplitude is greater than the preset current amplitude, determining that a spectrum corresponding to the DC current and a reference standard spectrum are different within a target frequency band;

[0030] The target current amplitude is the current amplitude of the spectrum corresponding to the DC current within the target frequency band, and the preset current amplitude is the current amplitude of the reference standard spectrum within the target frequency band.

[0031] In a second aspect, the present application further provides a fault detection device for an energy storage system, the device comprising:

[0032] A sampling module, used to sample the DC current of the energy storage system;

[0033] A processing module, used for performing fast Fourier transform on the DC current to obtain a frequency spectrum corresponding to the DC current;

[0034] The fault detection module is used to determine the fault condition of the energy storage system based on the current change rate within the target frequency band when the spectrum corresponding to the DC current differs from the reference standard spectrum in the target frequency band; the reference standard spectrum is the spectrum corresponding to the DC current under normal operation of the energy storage system.

[0035] In a third aspect, the present application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the above embodiment when executing the computer program.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method in the above embodiment are implemented.

[0037] The above-mentioned energy storage system fault detection method, device, computer equipment, and storage medium have at least the following beneficial effects:

[0038] By comparing the spectrum corresponding to the DC current with the reference standard spectrum and further analyzing the rate of change of the current within the target frequency band, the energy storage system can be inspected from multiple angles, accurately determining the fault condition of the energy storage system and improving the accuracy of fault detection. For both string and centralized energy storage systems, the above detection strategies can provide effective and reliable fault identification, thereby ensuring the safe and stable operation of the energy storage system. In practical applications, the timely detection and treatment of arcing faults can effectively prevent the fault from expanding, protect the safety of equipment and personnel, and improve the reliability and cost-effectiveness of the entire energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] FIG1 is a diagram illustrating an application environment of a method for detecting a fault in an energy storage system according to an embodiment;

[0041] FIG2 is a frequency spectrum curve diagram of an energy storage system during normal operation and arcing of an outlet line in one embodiment;

[0042] FIG3 is a schematic flow chart of a method for detecting a fault in an energy storage system according to an embodiment;

[0043] FIG4 is a flowchart illustrating steps for determining a fault condition of an energy storage system based on a current change rate within a target frequency band in one embodiment;

[0044] FIG5 is a schematic flow chart of the steps for determining the upper limit threshold of a preset range in one embodiment;

[0045] FIG6 is a schematic flow chart of the steps for determining the lower limit threshold of a preset range in one embodiment;

[0046] FIG7 is a flow chart illustrating the steps of performing a fast Fourier transform on a DC current to obtain a spectrum corresponding to the DC current in one embodiment;

[0047] FIG8 is a block diagram of a fault detection device for an energy storage system according to one embodiment;

[0048] FIG9 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0050] The energy storage system fault detection method provided in the embodiment of the present application can be applied in the application environment shown in Figure 1. Terminal 102 is connected to energy storage system 104, and terminal 102 samples the DC current of energy storage system 104; performs a fast Fourier transform on the DC current to obtain a spectrum corresponding to the DC current; and when there is a difference between the spectrum corresponding to the DC current and a reference standard spectrum in a target frequency band, terminal 102 determines the fault condition of energy storage system 104 based on the current change rate within the target frequency band; the reference standard spectrum is the spectrum corresponding to the DC current under normal operation of energy storage system 104. Terminal 102 can be, but is not limited to, various personal computers, laptop computers, etc.

[0051] As described in the background, there is currently a considerable amount of technical expertise in detecting faults such as arcing in photovoltaic systems, with a low false alarm rate and a long history of market adoption. Currently, arc detection in photovoltaic systems typically involves adding an arcing transformer to the MPPT (Maximum Power Point Tracking) branch. The branch current is typically around 30A, enabling high-resolution identification of arcing signatures. The current spectrum of a photovoltaic system experiencing arcing differs significantly from that during normal operation, with the discrepancy typically occurring in high-frequency bands such as 16kHz and 32kHz. Compared to photovoltaic systems, energy storage systems feature high voltage and high current, making fault detection more challenging. For example, as shown in Figure 2, curve S1 represents the spectrum of an energy storage system under normal operation, while curve S2 represents the spectrum of an energy storage system experiencing arcing. As can be seen from Figure 2, the arcing frequency is relatively low and concentrated around 1-4kHz. Harmonic components in the 1-4kHz range are very common in current, making them difficult to extract through software analysis. Therefore, compared to photovoltaic systems, the arcing frequency of energy storage systems is lower, leading to a higher risk of false alarms.

[0052] Based on the above reasons, in an exemplary embodiment, as shown in FIG3 , the present application provides a method for detecting a fault in an energy storage system, which is described by taking the method applied to the terminal 102 in FIG1 as an example, and includes the following steps S302 to S306 . In particular:

[0053] Step S302: sampling the direct current of the energy storage system.

[0054] Step S304 , performing fast Fourier transform on the direct current to obtain a frequency spectrum corresponding to the direct current.

[0055] The energy storage system may refer to a string energy storage system or a centralized energy storage system.

[0056] For example, a current sensor installed in the energy storage system is used to measure the DC current of the energy storage system during operation, and a fast Fourier transform is performed on the sampled DC current to obtain a frequency spectrum corresponding to the DC current.

[0057] Step S306 : If there is a difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band, a fault condition of the energy storage system is determined based on the current change rate in the target frequency band; the reference standard spectrum is the spectrum corresponding to the DC current under normal operation of the energy storage system.

[0058] The target frequency band may refer to any selected frequency band. Taking the energy storage system of the present application as an example, the target frequency band may specifically refer to the low frequency band of 1-4 kHz as shown in FIG. 2 .

[0059] Exemplarily, after obtaining the spectrum corresponding to the DC current sampled above, it is compared with the reference standard spectrum pre-stored in the terminal. For example, the two spectra can be judged to match by comparing whether the spectrum curve corresponding to the DC current in the target frequency band overlaps with the reference standard spectrum curve, or whether the degree of overlap is greater than a preset matching threshold. It is also possible to judge whether the two spectra match by comparing whether the current amplitude error corresponding to the two spectra in each sub-band of the target frequency band is less than a preset error. The above examples are for illustration only and are not limiting. When there is a difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band, it indicates that the energy storage system may have a fault such as arcing. In order to more accurately determine whether a fault has occurred and the specific fault condition, it is necessary to further analyze the current change rate in the target frequency band to determine the fault condition of the energy storage system. Specifically, the fault condition of the energy storage system can be judged by calculating the root mean square value, average value, peak value and other parameters of the current in the target frequency band, and analyzing the change trend and fluctuation of the current. For example, if the root mean square value of the current in the target frequency band increases significantly or the peak value increases sharply, it may indicate that a fault such as arcing has occurred in the energy storage system; if the average value of the current in the target frequency band shows periodic changes, it may indicate that there are problems with components such as inductors or capacitors in the energy storage system.

[0060] The above-mentioned fault detection method for energy storage systems, by comparing the spectrum corresponding to the DC current with the reference standard spectrum and further analyzing the current change rate within the target frequency band, can detect the energy storage system from multiple angles, accurately determine the fault condition of the energy storage system, and improve the accuracy of fault detection. For both string-type and centralized energy storage systems, the above-mentioned detection strategy can provide effective and reliable fault identification, thereby ensuring the safe and stable operation of the energy storage system. In practical applications, by promptly detecting and handling arcing faults, it is possible to effectively prevent the fault from expanding, protect the safety of equipment and personnel, and improve the reliability and economy of the entire energy storage system.

[0061] In an exemplary embodiment, as shown in FIG4 , determining a fault condition of the energy storage system based on the current change rate within the target frequency band includes:

[0062] Step S402 , determining whether the current change rate of the target frequency band is within a preset range; the preset range is used to represent the current change rate range when arcing occurs in the energy storage system.

[0063] Step S404 : When the current change rate in the target frequency band is within a preset range, it is determined that arcing occurs in the energy storage system.

[0064] Among them, the preset range refers to the range of the current change rate when arcing occurs in the energy storage system. Specifically, the range can be set according to the operating experience and actual situation of the energy storage system. Generally, the current change rate before and after the arcing can be statistically analyzed to obtain a more accurate preset range. In the actual implementation process, the DC current of the energy storage system can be monitored, and the current change rate within the target frequency band can be calculated, and then it can be determined whether the current change rate is within the preset range. If it is within the preset range, it can be determined that an arcing fault has occurred in the energy storage system. For example, suppose that in the process of monitoring the energy storage system, the current change rate within the target frequency band is analyzed and found. If its root mean square value increases significantly or the peak value increases sharply, and it is within the preset arcing current change rate range, it can be determined that an arcing fault has occurred in the energy storage system, and corresponding maintenance measures can be taken in time to ensure the normal operation of the energy storage system.

[0065] In this embodiment, by analyzing the current change rate within the target frequency band and comparing it with the current change rate range when arcing occurs in the energy storage system, it is determined whether it is within this range, so as to accurately determine whether an arcing fault has occurred. Even in complex operating environments, a high detection accuracy can be maintained, reducing the possibility of misjudgment.

[0066] In an exemplary embodiment, as shown in FIG5 , before determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0067] Step 502: Obtain the maximum short-circuit current of the energy storage system and the maximum short-circuit time corresponding to the maximum short-circuit current;

[0068] Step 504 : Determine the ratio of the maximum short-circuit current to the maximum short-circuit time as an upper threshold of a preset range.

[0069] Among them, taking the string energy storage system described in this application as an example, the maximum short-circuit current of the energy storage system may refer to the maximum short-circuit current when a single cluster of batteries in the energy storage system is short-circuited, and the maximum short-circuit time may refer to the time that the string energy storage system can withstand the above maximum short-circuit current.

[0070] For example, the maximum short-circuit current of the energy storage system and the maximum short-circuit time corresponding to the maximum short-circuit current can be directly pre-stored in the terminal. When setting a preset range, the values ​​can be directly retrieved from the terminal's memory and calculated to obtain the ratio of the maximum short-circuit current to the maximum short-circuit time, thereby determining the upper threshold of the preset range. For example, if the maximum short-circuit current during a single battery cluster short circuit is Isc-max and the maximum short-circuit time is t1, the upper threshold of the preset range can be determined as Isc-max / t1. Taking a 200kW machine power as an example, the calculated value is approximately 1500A / ms.

[0071] In this embodiment, by obtaining the energy storage system's maximum short-circuit current and the maximum short-circuit duration corresponding to that current, the upper threshold value ensures that it reflects the system's current rate of change under the most extreme short-circuit conditions. Using the ratio of maximum short-circuit current to maximum short-circuit duration as the upper threshold value not only considers the magnitude of the current but also the rate of current change, thereby more comprehensively reflecting the characteristics of arcing faults. This helps reduce misjudgments and missed detections, improves the accuracy and reliability of arcing fault detection, and provides solid technical support for the safe and stable operation of energy storage systems.

[0072] In an exemplary embodiment, as shown in FIG6 , before determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0073] Step S602: Acquire the maximum operating current of the energy storage system under normal operation and the duration of the maximum operating current; the maximum operating current is the maximum current that occurs when the energy storage system performs rapid power scheduling;

[0074] Step S604: Determine the ratio of the maximum operating current to the duration as the lower threshold of the preset range.

[0075] It should be noted that during the normal operation of the energy storage system, rapid power scheduling is required to meet the needs of the power system. Since the output power needs to be increased or decreased in a short period of time during rapid power scheduling, which leads to a short-term increase in the operating current, the maximum operating current of the energy storage system often appears during the power scheduling process.

[0076] For example, as described in the above embodiment, the maximum operating current and the duration of the maximum operating current can also be pre-simulated by the system, and the obtained data can be stored in the terminal. When setting the preset range, the data can be directly obtained from the terminal's memory and calculated to obtain the ratio of the maximum operating current to the duration, thereby determining the lower limit threshold of the preset range. For example, the maximum current during fast power scheduling is Iop-max, and the duration of this maximum current is t2. In this case, the lower limit threshold of the preset range can be determined as Iop-max / t2. Taking a 200kW machine power as an example, the maximum order of magnitude is approximately 20A / ms.

[0077] In this embodiment, by obtaining the maximum operating current and the duration of the energy storage system's normal operation, the lower threshold value is ensured to reflect the current change rate during normal power scheduling. Using the ratio of the maximum operating current to the duration as the lower threshold value not only considers the current magnitude but also the stability of current changes, thereby more comprehensively reflecting the characteristics of the energy storage system during normal operation. This also ensures data accuracy, enabling more accurate identification of arcing faults and improving detection accuracy and reliability.

[0078] In an exemplary embodiment, after determining whether the current change rate of the target frequency band is within a preset range, the method further includes:

[0079] When the current change rate in the target frequency band is not within the preset range, the DC current of the energy storage system is kept sampled.

[0080] In this embodiment, by resampling the DC current, the system can obtain the latest current data, thereby more accurately assessing the current operating status of the energy storage system. When the current rate of change is outside the preset range, it indicates that the energy storage system is not experiencing arcing. The current sampling process is then cyclically executed to achieve real-time monitoring of the energy storage system, enabling timely detection of arcing.

[0081] In an exemplary embodiment, as shown in FIG7 , a fast Fourier transform is performed on the DC current to obtain a spectrum corresponding to the DC current, including:

[0082] Step S702: extracting the AC component of the DC current.

[0083] Step S704: Perform fast Fourier transform on the AC component to obtain a frequency spectrum corresponding to the AC component.

[0084] Step S706: Determine the frequency spectrum corresponding to the AC component as the frequency spectrum corresponding to the DC current.

[0085] For example, it should be noted that there will be a certain AC component in the actual sampled DC current, and in power systems, faults such as arcing are usually caused by the AC component. Arcing faults are usually accompanied by rapid changes in current, and these changes are more obvious in the AC component. Therefore, in order to effectively detect arcing faults, it is often necessary to pay attention to the AC component of the DC current. By sampling the DC current and extracting the AC component to simplify the subsequent signal processing and analysis process, the AC component is further subjected to a fast Fourier transform to obtain the spectrum corresponding to the AC component, and the spectrum corresponding to the obtained AC component is determined as the spectrum corresponding to the DC current.

[0086] In this embodiment, by extracting the AC component from the DC current, the dynamic changes in the current can be more accurately reflected. In the power system, arc faults are often accompanied by rapid changes in current, and these changes are more obvious in the AC component. Therefore, focusing on the AC component helps to more accurately capture the characteristics of the arc fault. By performing a fast Fourier transform on the AC component to obtain its corresponding spectrum, the frequency characteristics of the current signal can be further revealed, and characteristics such as the increase in low-frequency components caused by the arc fault can be more clearly identified. Determining the spectrum corresponding to the AC component as the spectrum corresponding to the DC current helps to simplify the subsequent signal processing and analysis process. For example, the spectrum corresponding to the AC component can be directly compared with the reference standard spectrum, which not only improves the detection efficiency, but also reduces the possibility of misjudgment and missed judgment.

[0087] In an exemplary embodiment, after obtaining the spectrum corresponding to the direct current, the method further includes:

[0088] When there is no difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band, the DC current of the energy storage system is kept sampled.

[0089] In this embodiment, by continuously sampling and spectrum analyzing the DC current of the energy storage system, the operating status of the system can be monitored in real time. When it is found that there is no difference between the spectrum of the DC current and the reference standard spectrum within the target frequency band, it means that the system is currently in normal operation and no arcing fault has occurred. By cyclically executing the sampling steps, continuous monitoring of the state of the energy storage system can be achieved. Once a difference is found between the two spectra, that is, there may be signs of a fault, the system will immediately enter the fault detection process, thereby ensuring a rapid response and processing of potential faults. In addition, this cyclic sampling method also helps to reduce the possibility of misjudgment and missed judgment. Since the system status may change with time and changes in the operating environment, continuous sampling can provide more comprehensive and accurate system status information, thereby improving the accuracy and reliability of fault detection.

[0090] In an exemplary embodiment, determining whether a spectrum corresponding to the direct current differs from a reference standard spectrum in a target frequency band includes:

[0091] When the target current amplitude is greater than the preset current amplitude, determining that a spectrum corresponding to the DC current and a reference standard spectrum are different within a target frequency band;

[0092] The target current amplitude is the current amplitude of the spectrum corresponding to the DC current within the target frequency band, and the preset current amplitude is the current amplitude of the reference standard spectrum within the target frequency band.

[0093] In this embodiment, by comparing the target current amplitude and the preset current amplitude, it is possible to more accurately determine whether there is a difference in the spectrum. When the target current amplitude is greater than the preset current amplitude, it means that the intensity of the DC current in the target frequency band exceeds the reference standard, which often indicates a potential arcing phenomenon. In actual applications, it is only necessary to obtain the spectrum corresponding to the DC current and the current amplitude in the target frequency band, and then compare them with the corresponding values ​​in the reference standard spectrum. The judgment steps are simple and clear, easy to implement, and do not require complex calculations or analysis. In addition, by introducing the preset current amplitude as a reference standard, the size of the preset current amplitude can be adjusted according to different application scenarios and needs to adapt to different system configurations and operating requirements.

[0094] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0095] Based on the same inventive concept, embodiments of the present application also provide an energy storage system fault detection device for implementing the aforementioned energy storage system fault detection method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more energy storage system fault detection device embodiments provided below can be found in the above-described limitations of the energy storage system fault detection method and will not be further elaborated here.

[0096] In an exemplary embodiment, as shown in FIG8 , a fault detection device for an energy storage system is provided, comprising: a sampling module 802 , a processing module 804 , a fault detection module 806 , and an arcing determination module 808 , wherein:

[0097] The sampling module 802 is used to sample the DC current of the energy storage system;

[0098] The processing module 804 is configured to perform a fast Fourier transform on the DC current to obtain a frequency spectrum corresponding to the DC current;

[0099] The fault detection module 806 is configured to determine a fault condition of the energy storage system based on the rate of change of the current within the target frequency band when the spectrum corresponding to the DC current differs from a reference standard spectrum within the target frequency band; the reference standard spectrum is the spectrum corresponding to the DC current under normal operation of the energy storage system.

[0100] In an exemplary embodiment, the fault detection module 806 includes:

[0101] A judgment unit, used to judge whether the current change rate of the target frequency band is within a preset range; the preset range is used to represent the current change rate range when arcing occurs in the energy storage system;

[0102] The fault detection unit is used to determine that arcing has occurred in the energy storage system when the current change rate in the target frequency band is within a preset range.

[0103] In an exemplary embodiment, the fault detection module 806 includes:

[0104] A first parameter acquisition unit is used to acquire the maximum short-circuit current of the energy storage system and the maximum short-circuit time corresponding to the maximum short-circuit current;

[0105] The upper threshold value determining unit is used to determine the ratio of the maximum short-circuit current to the maximum short-circuit time as the upper threshold value of a preset range.

[0106] In an exemplary embodiment, the fault detection module 806 further includes:

[0107] The second parameter acquisition unit is used to obtain the maximum operating current of the energy storage system under normal operation and the duration of the maximum operating current; the maximum operating current is the maximum current that occurs when the energy storage system performs rapid power scheduling;

[0108] The upper threshold value determining unit is used to determine the ratio of the maximum operating current to the duration as the lower threshold value of the preset range.

[0109] In an exemplary embodiment, the fault detection device for the energy storage system further includes:

[0110] The first cycle module is configured to keep sampling the DC current of the energy storage system when the current change rate in the target frequency band is not within a preset range.

[0111] In an exemplary embodiment, the processing module 804 includes:

[0112] an extraction unit for extracting an AC component of a DC current;

[0113] A processing unit, configured to perform a fast Fourier transform on the AC component to obtain a frequency spectrum corresponding to the AC component;

[0114] The spectrum determining unit is configured to determine the spectrum corresponding to the AC component as the spectrum corresponding to the DC current.

[0115] In an exemplary embodiment, the fault detection device for the energy storage system further includes:

[0116] The second loop module is used to keep sampling the DC current of the energy storage system when there is no difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band.

[0117] In an exemplary embodiment, the fault detection module 806 further includes:

[0118] a spectrum matching determination unit, configured to determine, when the target current amplitude is greater than a preset current amplitude, whether a spectrum corresponding to the DC current and a reference standard spectrum are different within a target frequency band;

[0119] The target current amplitude is the current amplitude of the spectrum corresponding to the DC current within the target frequency band, and the preset current amplitude is the current amplitude of the reference standard spectrum within the target frequency band.

[0120] Each module in the aforementioned energy storage system fault detection device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0121] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in Figure 9. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WiFi, a mobile cellular network, NFC (near field communication), or other technologies. When the computer program is executed by the processor, it implements a fault detection method for an energy storage system. The display unit of the computer device is used to form a visually visible image, and may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0122] Those skilled in the art will understand that the structure shown in Figure 9 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0123] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0124] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0125] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0126] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0127] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, 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.

[0128] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A fault detection method for an energy storage system, characterized in that: The method comprises: Sampling the DC current of the energy storage system; Performing a fast Fourier transform on the direct current to obtain a frequency spectrum corresponding to the direct current; When a spectrum corresponding to the DC current differs from a reference standard spectrum in a target frequency band, a fault condition of the energy storage system is determined based on a current change rate within the target frequency band; the reference standard spectrum is a spectrum corresponding to the DC current under normal operation of the energy storage system.

2. The method according to claim 1, characterized in that Determining a fault condition of the energy storage system based on the current change rate within the target frequency band includes: Determine whether the current change rate of the target frequency band is within a preset range; the preset range is used to represent the current change rate range when arcing occurs in the energy storage system; When the current change rate in the target frequency band is within a preset range, it is determined that arcing occurs in the energy storage system.

3. The method according to claim 2, characterized in that Before determining whether the current change rate of the target frequency band is within a preset range, the method further includes: Obtaining a maximum short-circuit current of the energy storage system and a maximum short-circuit time corresponding to the maximum short-circuit current; A ratio of the maximum short-circuit current to the maximum short-circuit time is determined as an upper threshold of the preset range.

4. The method according to claim 2, characterized in that Before determining whether the current change rate of the target frequency band is within a preset range, the method further includes: Obtaining a maximum operating current of the energy storage system under normal operation and a duration of the maximum operating current; the maximum operating current is the maximum current occurring when the energy storage system performs rapid power scheduling; A ratio of the maximum operating current to the duration is determined as a lower threshold of the preset range.

5. The method according to claim 2, characterized in that After determining whether the current change rate of the target frequency band is within a preset range, the method further includes: When the current change rate in the target frequency band is not within the preset range, the DC current of the energy storage system is kept sampled.

6. The method according to claim 1, characterized in that The performing a fast Fourier transform on the direct current to obtain a frequency spectrum corresponding to the direct current includes: extracting an AC component of the DC current; Performing a fast Fourier transform on the AC component to obtain a frequency spectrum corresponding to the AC component; The frequency spectrum corresponding to the AC component is determined as the frequency spectrum corresponding to the DC current.

7. The method according to claim 1, characterized in that After obtaining the spectrum corresponding to the direct current, the method further includes: When there is no difference between the frequency spectrum corresponding to the direct current and the reference standard frequency spectrum in the target frequency band, the direct current of the energy storage system is kept sampled.

8. The method according to claim 1, characterized in that Determining whether a spectrum corresponding to the DC current differs from a reference standard spectrum in a target frequency band includes: When the target current amplitude is greater than the preset current amplitude, determining that a frequency spectrum corresponding to the direct current and the reference standard frequency spectrum are different within the target frequency band; The target current amplitude is the current amplitude of the spectrum corresponding to the direct current within the target frequency band, and the preset current amplitude is the current amplitude of the reference standard spectrum within the target frequency band.

9. A fault detection device for an energy storage system, characterized in that: The device comprises: A sampling module, used to sample the DC current of the energy storage system; a processing module, configured to perform a fast Fourier transform on the DC current to obtain a frequency spectrum corresponding to the DC current; a fault detection module configured to determine a fault condition of the energy storage system based on a rate of change of current within a target frequency band when a frequency spectrum corresponding to the DC current differs from a reference standard frequency spectrum within a target frequency band; the reference standard frequency spectrum being a frequency spectrum corresponding to the DC current under normal operation of the energy storage system.

10. The device according to claim 9, characterized in that The fault detection module includes: A judgment unit, used to judge whether the current change rate of the target frequency band is within a preset range; the preset range is used to represent the current change rate range when arcing occurs in the energy storage system; The fault detection unit is used to determine that arcing has occurred in the energy storage system when the current change rate in the target frequency band is within a preset range.

11. The device according to claim 10, characterized in that The fault detection module also includes: A first parameter acquisition unit is used to acquire the maximum short-circuit current of the energy storage system and the maximum short-circuit time corresponding to the maximum short-circuit current; The upper threshold value determining unit is used to determine the ratio of the maximum short-circuit current to the maximum short-circuit time as the upper threshold value of a preset range.

12. The device according to claim 10, characterized in that The fault detection module also includes: The second parameter acquisition unit is used to obtain the maximum operating current of the energy storage system under normal operation and the duration of the maximum operating current; the maximum operating current is the maximum current that occurs when the energy storage system performs rapid power scheduling; The upper threshold value determining unit is used to determine the ratio of the maximum operating current to the duration as the lower threshold value of the preset range.

13. The device according to claim 10, characterized in that The fault detection device of the energy storage system further includes: The first cycle module is configured to keep sampling the DC current of the energy storage system when the current change rate in the target frequency band is not within a preset range.

14. The device according to claim 9, characterized in that The processing module includes: an extraction unit for extracting an AC component of a DC current; A processing unit, configured to perform a fast Fourier transform on the AC component to obtain a frequency spectrum corresponding to the AC component; The spectrum determining unit is configured to determine the spectrum corresponding to the AC component as the spectrum corresponding to the DC current.

15. The device according to claim 9, characterized in that The fault detection device of the energy storage system further includes: The second loop module is used to keep sampling the DC current of the energy storage system when there is no difference between the spectrum corresponding to the DC current and the reference standard spectrum in the target frequency band.

16. The device according to claim 9, characterized in that The fault detection module also includes: a spectrum matching determination unit, configured to determine, when the target current amplitude is greater than a preset current amplitude, whether a spectrum corresponding to the DC current and a reference standard spectrum are different within a target frequency band; The target current amplitude is the current amplitude of the spectrum corresponding to the DC current within the target frequency band, and the preset current amplitude is the current amplitude of the reference standard spectrum within the target frequency band.

17. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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