Fuse determination method, apparatus, device, and medium for energy storage power station

Abstract

The application provides a fuse determination method, device, equipment and medium for an energy storage power station. The application relates to the technical field of lithium battery safety of an energy storage power station. The fuse determination method comprises the following steps: determining, based on calibration parameters of an energy storage battery, an expected discharge duration of the energy storage battery under the condition that cumulative discharge charge of the energy storage battery reaches a preset state of charge variation; discharging the energy storage battery within the expected discharge duration under the condition that the energy storage battery is in multiple states of charge, so as to collect current and voltage output by the energy storage battery and obtain voltage sequences and current sequences of the energy storage battery in the multiple states of charge; predicting, based on the voltage sequences and the current sequences, current when the energy storage battery is subjected to external short circuit, so as to obtain short circuit current of the energy storage battery in the state of charge; and determining the model of a fuse of the energy storage power station according to the structure of the energy storage power station and the short circuit current of the energy storage battery in the multiple states of charge.

Description

Technical Field

[0001] This application relates to the field of lithium battery safety technology for energy storage power stations, and more specifically, to a method, apparatus, equipment, and medium for determining fuses for energy storage power stations. Background Technology

[0002] Clean energy sources, such as wind power and photovoltaics, are intermittent and fluctuate, requiring energy storage systems to achieve peak shaving and smooth output. Due to the limitations of terrain or cost of traditional energy storage methods, lithium-ion energy storage power stations have become the best choice due to their advantages such as speed, high energy density, and long lifespan.

[0003] However, in actual operation, once a battery encounters an external short circuit or other fault, a huge surge current will be generated in a very short time, which can easily lead to thermal runaway or even fire and explosion. Accurate calculation of the short-circuit current is crucial for the selection of DC-side fuses in energy storage power stations. Summary of the Invention

[0004] In view of this, this application provides a method, apparatus, equipment and medium for determining fuses in energy storage power stations.

[0005] One aspect of this application provides a method for determining a fuse in an energy storage power station. The energy storage power station includes multiple energy storage batteries. The method includes: determining the expected discharge time of the energy storage battery when the cumulative discharge charge of the energy storage battery reaches a preset state of charge change based on the calibration parameters of the energy storage battery; discharging the energy storage battery within the expected discharge time while the energy storage battery is in multiple states of charge, to collect the current and voltage output by the energy storage battery, and obtain the voltage sequence and current sequence of the energy storage battery in the multiple states of charge; predicting the current when the energy storage battery experiences an external short circuit based on the voltage sequence and current sequence, and obtaining the short-circuit current of the energy storage battery in the state of charge; and determining the type of fuse for the energy storage power station according to the structure of the energy storage power station and the short-circuit current of the energy storage battery in the multiple states of charge.

[0006] According to embodiments of this application, the multiple states of charge include a first state of charge and a second state of charge. When the energy storage battery is in multiple states of charge, it is discharged within a predetermined discharge duration to collect the current and voltage output by the energy storage battery, obtaining voltage and current sequences for the energy storage battery in each of the multiple states of charge. This includes: when the energy storage battery is in the first state of charge, sampling the output current and output voltage generated by the discharge of the energy storage battery within a sampling duration to obtain a first voltage sequence and a first current sequence for the energy storage battery in the first state of charge; and when the energy storage battery is in the second state of charge, sampling the output current and output voltage generated by the discharge of the energy storage battery within a sampling duration to obtain a second voltage sequence and a second current sequence for the energy storage battery in the second state of charge.

[0007] According to embodiments of this application, the current of an energy storage battery when an external short circuit occurs is predicted based on a voltage sequence and a current sequence to obtain the short-circuit current of the energy storage battery in a charged state. This includes: fitting parameters of the energy storage battery using a first voltage sequence and a first current sequence to obtain a first ohmic internal resistance of the energy storage battery in a first charged state; fitting parameters of the energy storage battery using a second voltage sequence and a second current sequence to obtain a second ohmic internal resistance of the energy storage battery in a second charged state; and predicting the current of the energy storage battery when an external short circuit occurs based on the resistance values ​​of the first ohmic internal resistance and the second ohmic internal resistance, respectively, to determine the first short-circuit current and the second short-circuit current of the energy storage battery.

[0008] According to an embodiment of this application, an energy storage power station includes multiple battery clusters connected in parallel, each battery cluster includes multiple battery packs connected in series, and each battery pack includes multiple energy storage batteries connected in series. The model of the fuse for the energy storage power station is determined based on the structure of the energy storage power station and the short-circuit currents of the energy storage batteries under multiple states of charge. This includes: determining the short-circuit current range of the energy storage power station based on the number of battery clusters, the first short-circuit current, and the second short-circuit current; predicting the cumulative heat required for fusing based on a preset fusing time window and the short-circuit current range to determine the range of the Joule integral; and selecting a fuse based on the range of the Joule integral to determine the fuse model.

[0009] According to an embodiment of this application, the method for determining the fuse of an energy storage power station further includes: determining the corresponding environmental parameters based on the geographical environment where the energy storage power station is located; wherein, selecting the fuse based on the range of Joule integral to determine the fuse model includes: selecting the fuse based on the range of Joule integral and environmental parameters to determine the fuse model.

[0010] According to an embodiment of this application, the first ohmic internal resistance of the energy storage battery is obtained by fitting parameters to the energy storage battery using a first voltage sequence and a first current sequence under a first charged state, including: establishing a corresponding equivalent circuit model using the first voltage sequence and the first current sequence, wherein the equivalent circuit model includes the first ohmic internal resistance as a parameter to be optimized; and fitting parameters to the first ohmic internal resistance in the equivalent circuit model based on the trust region reflection algorithm to obtain the first ohmic internal resistance of the energy storage battery.

[0011] According to an embodiment of this application, the calibration parameters include nominal capacity and discharge rate. Based on the calibration parameters of the energy storage battery, the expected discharge time of the energy storage battery is determined when the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge. This includes: determining the total cumulative discharge charge of the energy storage battery based on the nominal capacity and the preset change in state of charge; and estimating the discharge time of the energy storage battery based on the discharge rate and the total cumulative discharge charge to determine the expected discharge time of the energy storage battery.

[0012] Another aspect of this application provides a fuse determination device for an energy storage power station, comprising: a duration determination module, used to determine the expected discharge duration of the energy storage battery when the cumulative discharge charge of the energy storage battery reaches a preset state-of-charge change amount based on the calibration parameters of the energy storage battery; a data acquisition module, used to discharge the energy storage battery within the expected discharge duration when the energy storage battery is in multiple states of charge, to acquire the current and voltage output by the energy storage battery, and obtain the voltage sequence and current sequence of the energy storage battery in multiple states of charge; a prediction module, used to predict the current of the energy storage battery when an external short circuit occurs based on the voltage sequence and current sequence, and obtain the short-circuit current of the energy storage battery in the state of charge; and a model determination module, used to determine the model of the fuse of the energy storage power station according to the structure of the energy storage power station and the short-circuit current of the energy storage battery in multiple states of charge.

[0013] Another aspect of this application provides an electronic device comprising:

[0014] One or more processors;

[0015] Memory, used to store one or more programs.

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described above.

[0017] Another aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed, are used to implement the method described above.

[0018] According to embodiments of this application, the expected discharge duration can be determined based on calibration parameters and preset state-of-charge (SOC) changes. Since the expected discharge duration is controlled within milliseconds, the open-circuit voltage drift problem caused by significant SOC changes in conventional long-pulse tests can be avoided. Furthermore, the establishment of concentration polarization can be suppressed, enabling the acquired voltage and current data to reflect ohmic and electrochemical polarization characteristics, thus improving the accuracy of subsequent parameter identification. Additionally, based on the short-circuit current obtained from the energy storage battery under various SOC states, the peak value range of the energy storage battery can be obtained, ensuring that the maximum breaking capacity of the fuse matches the potential current fluctuations during selection. Moreover, this application avoids problems such as underestimation or miscalculation of fuse breaking capacity and mismatch of fusing range caused by inaccurate short-circuit current calculations, reducing the risk of protection failure, maloperation, or cascading tripping, and improving the reliability and safety of the DC-side protection system of the energy storage power station. Attached Figure Description

[0019] The above and other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0020] Figure 1 An exemplary system architecture for determining fuses for energy storage power plants, according to embodiments of this application, is illustrated.

[0021] Figure 2 A flowchart illustrating the determination of a fuse for an energy storage power station according to an embodiment of this application is shown schematically.

[0022] Figure 3 This is a schematic diagram illustrating the current and voltage data collected from the energy storage battery.

[0023] Figure 4 This is a schematic diagram of the structure of a first-order RC equivalent circuit model.

[0024] Figure 5 A block diagram of a fuse determination device for an energy storage power station according to an embodiment of this application is shown schematically.

[0025] Figure 6 A block diagram of an electronic device suitable for implementing a fuse determination method for an energy storage power station, according to an embodiment of this application, is shown schematically. Detailed Implementation

[0026] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0028] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0029] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0030] Currently, the most direct method for obtaining the short-circuit current of lithium-ion energy storage batteries is to conduct external short-circuit tests. However, such destructive tests place extremely high demands on the testing equipment and pose significant safety hazards. Identifying lithium-ion energy storage battery parameters based on equivalent circuit models and then calculating the short-circuit current is a safer and more feasible alternative. However, HPPC (Hybrid Pulse Power Characteristic Test), commonly used for parameter identification, has significant drawbacks. On the one hand, the test timescale does not match the actual short-circuit scenario; long pulses inevitably lead to a drop in open-circuit voltage and the occurrence of concentration polarization, affecting the accuracy of parameter identification. On the other hand, the accuracy of parameter identification is highly sensitive to the selection of time window data; different time windows yield different accuracy results.

[0031] Furthermore, conventional methods often focus on steady-state or long-pulse characteristics, making it difficult to accurately capture the short-circuit peak current, which is entirely dominated by ohmic internal resistance, at the instant a short circuit occurs. If fuse selection is based on inaccurate short-circuit peak current, the maximum breaking capacity of the fuse will be underestimated, easily leading to fuse burnout or continuous arcing in the event of a real short circuit. On the other hand, it will also result in an inaccurate match between the fuse's pre-arc characteristics and its fusing range, leading to protection failure, false tripping, or cascading tripping, ultimately causing complete failure of the DC-side protection. Therefore, there is an urgent need for a short-circuit current calculation method that can accurately reflect the transient characteristics of lithium-ion energy storage batteries and provide accurate parameter identification.

[0032] This application provides a method for determining a fuse in an energy storage power station. The energy storage power station includes multiple energy storage batteries. The method includes: determining the expected discharge time of the energy storage battery when the cumulative discharge charge of the energy storage battery reaches a preset state of charge change based on the calibration parameters of the energy storage battery; discharging the energy storage battery within the expected discharge time while the energy storage battery is in multiple states of charge, to collect the current and voltage output by the energy storage battery, and obtain the voltage sequence and current sequence of the energy storage battery in multiple states of charge; predicting the current when the energy storage battery experiences an external short circuit based on the voltage sequence and current sequence, and obtaining the short-circuit current of the energy storage battery in the state of charge; and determining the model of the fuse for the energy storage power station according to the structure of the energy storage power station and the short-circuit current of the multiple energy storage batteries in multiple states of charge.

[0033] Figure 1 An exemplary system architecture 100, according to an embodiment of this application, can be applied to a fuse determination method for an energy storage power station. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this application, in order to help those skilled in the art understand the technical content of this application, but do not mean that the embodiments of this application cannot be used in other devices, systems, environments or scenarios.

[0034] like Figure 1 As shown, the exemplary system architecture 100 according to this embodiment may include an energy storage power station 110, a first energy storage battery 111-1, a second energy storage battery 111-2, a third energy storage battery 111-3, a fourth energy storage battery 111-4, ..., an nth energy storage battery 111-n, and a terminal device 120.

[0035] Energy storage power station 110 can be a power device that realizes the storage, release and energy management of electrical energy. It can be configured on the generation side of wind farms, photovoltaic power stations or thermal power plants to smooth the fluctuation of new energy output, track power generation plans or participate in frequency regulation auxiliary services; it can be connected to the transmission and distribution network as an independent entity for peak shaving and frequency regulation and delaying grid equipment investment; it can also be set up in industrial and commercial parks, data centers or microgrids to improve power quality.

[0036] The energy storage power station 110 may include multiple energy storage batteries, such as the first energy storage battery 111-1, the second energy storage battery 111-2, the third energy storage battery 111-3, the fourth energy storage battery 111-4, ..., the nth energy storage battery 111-n as shown in the figure.

[0037] Terminal device 120 can be used to collect the voltage and current sequences of any energy storage battery in the energy storage power station, process the collected current and voltage sequences, and display the processing results (such as the short-circuit current of the energy storage battery and the model of the fuse of the energy storage power station, etc.). Then, the processing results are applied to the selection of fuses in the energy storage power station 110.

[0038] It should be understood that Figure 1 The number of terminal devices and energy storage batteries shown is merely illustrative. Depending on the implementation requirements, any number of terminal devices and energy storage batteries can be included.

[0039] Figure 2 A flowchart illustrating the determination of a fuse for an energy storage power station according to an embodiment of this application is shown schematically.

[0040] like Figure 2 As shown, the method includes operations S201 to S204.

[0041] In operation S201, based on the calibration parameters of the energy storage battery, the expected discharge time of the energy storage battery is determined when the cumulative discharge charge of the energy storage battery reaches the preset change in state of charge.

[0042] According to embodiments of this application, the aforementioned energy storage battery can be a lithium-ion battery, which is a secondary battery system that achieves electrochemical energy storage and conversion based on the reversible insertion / extraction reaction of lithium ions between the positive and negative electrodes. Its basic structure mainly consists of a positive electrode such as lithium iron phosphate, a negative electrode such as graphite or silicon-based material, an electrolyte, and a separator. During charging and discharging, lithium ions pass through the electrolyte and are inserted or extracted into the active materials of the positive and negative electrodes, while electrons flow through the external circuit to form a current. Based on different polarization mechanisms, the dynamic response characteristics of lithium-ion batteries can be divided into three categories: ohmic polarization, electrochemical polarization, and concentration polarization. Ohmic polarization originates from the resistance of the electrolyte, electrode materials, and contact interfaces, with a response time in the microsecond range; electrochemical polarization is related to the charge transfer process, with a time constant in the millisecond range; concentration polarization is caused by the limitation of the diffusion rate of lithium ions in the solid electrode and liquid electrolyte, and its establishment typically requires several seconds to tens of seconds.

[0043] According to embodiments of this application, the calibration parameters of the aforementioned energy storage battery may include nominal capacity and preset discharge rate. Then, using the ampere-hour integration principle, the boundary value of the theoretical discharge duration under the constraint of the maximum permissible change in state of charge can be calculated, determining the upper limit of the duration of the millisecond-level discharge pulse. This upper limit yields the expected discharge duration. Within the expected discharge duration, if the energy storage battery discharges, the open-circuit voltage in the energy storage battery can remain constant. The aforementioned open-circuit voltage represents the voltage value when the positive and negative electrodes of the energy storage battery reach electrochemical equilibrium under conditions of sufficient rest and no external load. This open-circuit voltage corresponds to the battery's state of charge and can be calculated using parameters.

[0044] In operation S202, with the energy storage battery in multiple states of charge, the energy storage battery is discharged within the expected discharge time to collect the current and voltage output by the energy storage battery, thereby obtaining the voltage sequence and current sequence of the energy storage battery in multiple states of charge.

[0045] According to embodiments of this application, the aforementioned multiple states of charge may include a fully charged state, a 1% state of charge, a 90% state of charge, a 30% state of charge, etc. For different states of charge, a constant current pulse excitation with a predicted discharge duration can be applied to the energy storage battery, and the terminal voltage response and loop current of the energy storage battery can be recorded synchronously at a predetermined sampling frequency, thereby obtaining discrete time series data sets corresponding to multiple states of charge, i.e., voltage sequences and current sequences under multiple states of charge. The predetermined sampling frequency can be... .

[0046] According to an embodiment of this application, further, during discharge, voltage and current can be collected based on a sampling duration less than or equal to the expected discharge duration. The expected discharge duration is only used as the upper limit of the discharge collection time, and the time length corresponding to the sampling duration is not limited.

[0047] In operation S203, based on the voltage sequence and current sequence, the current when the energy storage battery is subjected to an external short circuit is predicted, and the short circuit current when the energy storage battery is in a charged state is obtained.

[0048] According to embodiments of this application, the above steps first utilize voltage and current sequence data collected within the expected discharge duration to construct a discrete-time difference equation based on a first-order RC equivalent circuit model (first-order RC equivalent model). Then, this difference equation is used for parameter identification, thereby obtaining key model parameters of the energy storage battery, such as ohmic internal resistance, polarization internal resistance, and polarization capacitance, under specific states of charge. Furthermore, parameter identification can be performed on voltage and current sequences corresponding to different states of charge, thereby obtaining the ohmic internal resistance, polarization internal resistance, and polarization capacitance under different states of charge.

[0049] According to the embodiments of this application, the parameters identified under different states of charge can then be substituted into a short-circuit model that includes an external resistor. The short-circuit model can simulate the current value, which can be used as a predicted value of the external short-circuit fault current of the energy storage battery under that state of charge.

[0050] In operation S204, the model of the fuse for the energy storage power station is determined based on the structure of the energy storage power station and the short-circuit current of the energy storage battery under multiple states of charge.

[0051] According to the embodiments of this application, the short-circuit peak current calculation results of each energy storage battery under multiple states of charge can be comprehensively evaluated based on the arrangement structure of the energy storage batteries in the energy storage power station. Based on the peak current, the key electrical parameters and model specifications of each level of fuse in the energy storage power station can be determined.

[0052] Specifically, the fuse's maximum breaking capacity must be greater than the maximum short-circuit current that may occur in the protected circuit, and its rated voltage must also be higher than the maximum DC open-circuit voltage. The rated current needs to be adjusted for battery charge / discharge rate and environmental factors. When encountering a maximum short-circuit current surge, the fuse should remain inactive for a preset short period to avoid maloperation due to normal operating fluctuations. Conversely, when encountering a minimum short-circuit current, it should reliably fuse and clear the fault within a specified longer period. Furthermore, the fuse's pre-arc Joule integral... The upper limit must be less than the thermal withstand limit of the protected equipment to ensure that the protection action is completed before irreversible damage to the equipment occurs; by comparing the matching relationship between the fuse parameters of different models and the calculated short-circuit current range, it is possible to screen out the appropriate models that meet the selective matching requirements.

[0053] According to embodiments of this application, the expected discharge duration can be determined based on calibration parameters and preset state-of-charge (SOC) changes. Since the expected discharge duration is controlled within milliseconds, the open-circuit voltage drift problem caused by significant SOC changes in conventional long-pulse tests can be avoided. Furthermore, the establishment of concentration polarization can be suppressed, enabling the acquired voltage and current data to reflect ohmic and electrochemical polarization characteristics, thus improving the accuracy of subsequent parameter identification. Additionally, based on the short-circuit current obtained from the energy storage battery under various SOC states, the peak value range of the energy storage battery can be obtained, ensuring that the maximum breaking capacity of the fuse matches the potential current fluctuations during selection. Moreover, this application avoids problems such as underestimation or miscalculation of fuse breaking capacity and mismatch of fusing range caused by inaccurate short-circuit current calculations, reducing the risk of protection failure, maloperation, or cascading tripping, and improving the reliability and safety of the DC-side protection system of the energy storage power station.

[0054] According to an embodiment of this application, the calibration parameters include nominal capacity and discharge rate. Based on the calibration parameters of the energy storage battery, the expected discharge time of the energy storage battery is determined when the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge. This includes: determining the total cumulative discharge charge of the energy storage battery based on the nominal capacity and the preset change in state of charge; and estimating the discharge time of the energy storage battery based on the discharge rate and the total cumulative discharge charge to determine the expected discharge time of the energy storage battery.

[0055] According to embodiments of this application, the total cumulative discharge charge allowed to be released by the energy storage battery during testing can be determined based on the charge conversion relationship and a preset state-of-charge change. This preset state-of-charge change can be set to an extremely small value, such as one ten-thousandth, to ensure that the internal chemical composition of the battery remains almost unchanged during pulse discharge, thereby maintaining a constant open-circuit voltage and avoiding measurement errors introduced by state-of-charge drift. Based on the discharge current intensity corresponding to the discharge rate, combined with the aforementioned total cumulative discharge charge, the expected discharge duration can be determined.

[0056] According to embodiments of this application, the nominal capacity mentioned above can refer to the rated charge that a lithium-ion energy storage battery can release under specified standard charge and discharge conditions, such as an ambient temperature of 25°C, and its unit of measurement is ampere-hour (Ah) or milliampere-hour (mAh). The nominal capacity can reflect the theoretical energy storage capacity of the battery.

[0057] According to the embodiments of this application, the above-mentioned discharge rate is a dimensionless parameter characterizing the relative intensity of the discharge current, which can be defined as the ratio of the discharge current value to the nominal capacity of the battery. Here, 1C means that when the battery is discharged with a current intensity that is numerically equal to the nominal capacity, it can be discharged from a fully charged state to the cutoff voltage within 1 hour.

[0058] According to an embodiment of this application, the following example illustrates the calculation of the expected discharge duration.

[0059] The relationship between the preset change in state of charge and the expected discharge duration can be expressed as shown in formula (1).

[0060] (1)

[0061] in, It can represent the nominal capacity of a lithium-ion energy storage battery. It can represent the instantaneous discharge current value. It can represent the discharge rate, in calculation hour Can be taken , It can represent the preset change in state of charge.

[0062] Furthermore, the expected discharge duration can be calculated using formula (2). .

[0063] (2)

[0064] Only when Only when the voltage is sufficiently low can the open-circuit voltage of the energy storage battery be considered constant. Therefore, it can be set... This means the allowable change in state of charge (SOC) should not exceed one ten-thousandth. Taking a discharge rate of 1C and a nominal capacity of 280 Ah as an example, substituting into the above formula yields an expected discharge duration of 0.36s. Therefore, if the pulse discharge time is less than 0.36s, it can be assumed that the SOC of the energy storage battery remains unchanged during the pulse discharge process, and the open-circuit voltage of the battery remains constant.

[0065] According to embodiments of this application, by using a preset change in state of charge as a quantitative constraint, a conversion relationship between the total cumulative discharged charge and the nominal battery capacity can be established, thus limiting the amount of charge allowed to be released during pulse discharge to an extremely small range. This limitation ensures that the stoichiometry of the active materials inside the battery remains almost constant during testing, thereby physically guaranteeing a constant open-circuit voltage. This avoids measurement errors caused by state of charge drift and provides a stable and reliable current and voltage reference for subsequent parameter identification.

[0066] According to embodiments of this application, the multiple states of charge include a first state of charge and a second state of charge. When the energy storage battery is in multiple states of charge, it is discharged within a predetermined discharge duration to collect the current and voltage output by the energy storage battery, obtaining voltage and current sequences for the energy storage battery in each of the multiple states of charge. This includes: when the energy storage battery is in the first state of charge, sampling the output current and output voltage generated by the discharge of the energy storage battery within a sampling duration to obtain a first voltage sequence and a first current sequence for the energy storage battery in the first state of charge; and when the energy storage battery is in the second state of charge, sampling the output current and output voltage generated by the discharge of the energy storage battery within a sampling duration to obtain a second voltage sequence and a second current sequence for the energy storage battery in the second state of charge.

[0067] According to the embodiments of this application, the first state of charge can represent a fully charged state, and the second state of charge can represent a 1% state of charge. The short-circuit current obtained under the above two states of charge can be used as the basis for screening fuses.

[0068] Figure 3 This is a schematic diagram illustrating the current and voltage data collected from the energy storage battery.

[0069] According to the embodiments of this application, the following example uses a fully charged state, with reference to... Figure 3 Further explanation is needed. When a lithium-ion energy storage battery is fully charged, at an ambient temperature of 25°C, it can be used... The sampling frequency is used to perform millisecond-level pulse discharge tests on the battery. Specifically: first, the lithium-ion energy storage battery under test is fully charged to the cutoff voltage using a constant current and constant voltage charging method; then the battery is allowed to rest for a while. Finally, apply a discharge rate of 100% to the battery. A constant current discharge pulse with a duration equal to the sampling time can be used to obtain, for example... Figure 3 The current and voltage sequences are shown. The sampling duration described above can be less than or equal to the expected discharge duration.

[0070] Similarly, the above method can be used to collect current and voltage data of energy storage batteries under other states of charge, thereby obtaining multiple sets of voltage sequences and multiple sets of current sequences.

[0071] According to embodiments of this application, by sampling under the first and second states of charge, a first voltage sequence, a first current sequence, a second voltage sequence, and a second current sequence covering different charge ranges can be obtained, thereby establishing a mapping relationship between model parameters and state of charge. The above steps can minimize the limitations of single-point testing, enabling a complete characterization of the dynamic characteristics of the energy storage battery across the entire state of charge range. This allows subsequent parameter identification results to accurately reflect changes in internal resistance and polarization characteristics caused by differences in state of charge during actual operation, improving the adaptability and universality of the short-circuit current calculation model across all operating conditions.

[0072] According to embodiments of this application, the current of an energy storage battery when an external short circuit occurs is predicted based on a voltage sequence and a current sequence to obtain the short-circuit current of the energy storage battery in a charged state. This includes: fitting parameters of the energy storage battery using a first voltage sequence and a first current sequence to obtain a first ohmic internal resistance of the energy storage battery in a first charged state; fitting parameters of the energy storage battery using a second voltage sequence and a second current sequence to obtain a second ohmic internal resistance of the energy storage battery in a second charged state; and predicting the current of the energy storage battery when an external short circuit occurs based on the resistance values ​​of the first ohmic internal resistance and the second ohmic internal resistance, respectively, to determine the first short-circuit current and the second short-circuit current of the energy storage battery.

[0073] According to embodiments of this application, a discrete-time difference equation for a first-order RC equivalent circuit model is constructed based on a first voltage sequence and a first current sequence. The objective function is to minimize the sum of squared residuals between the calculated and measured voltages. Parameter identification is performed using a nonlinear least squares method. In this optimization process, the ohmic internal resistance can be considered as one of the key parameters to be identified. Its value characterizes the instantaneous resistance of the electrolyte, electrode materials, and contact interfaces inside the battery to the current. The first ohmic internal resistance obtained thus reflects the ohmic polarization characteristics of the energy storage battery under its first state of charge.

[0074] Similarly, based on the second voltage sequence and the second current sequence, the second ohmic internal resistance of the energy storage battery under the second state of charge is obtained using the same parameter identification algorithm. Since the ohmic internal resistance of a lithium-ion energy storage battery exhibits a non-linear characteristic with respect to the state of charge, the second ohmic internal resistance usually differs from the first ohmic internal resistance. By performing parameter fitting under different states of charge, a discrete mapping relationship between the ohmic internal resistance and the state of charge is established.

[0075] According to an embodiment of this application, the first ohmic internal resistance of the energy storage battery is obtained by fitting parameters to the energy storage battery using a first voltage sequence and a first current sequence under a first charged state, including: establishing a corresponding equivalent circuit model using the first voltage sequence and the first current sequence, wherein the equivalent circuit model includes the first ohmic internal resistance as a parameter to be optimized; and fitting parameters to the first ohmic internal resistance in the equivalent circuit model based on the trust region reflection algorithm to obtain the first ohmic internal resistance of the energy storage battery.

[0076] Figure 4 This is a schematic diagram of the structure of a first-order RC equivalent circuit model.

[0077] According to the embodiments of this application, the following is combined with Figure 4 The process of parameter identification is further described.

[0078] According to embodiments of this application, when a lithium-ion energy storage battery encounters an external short-circuit fault, a huge surge current is generated within a very short time. When a lithium-ion energy storage battery encounters a short-circuit current surge, its internal ohmic polarization and electrochemical polarization respond rapidly. However, due to the limited diffusion rate of lithium ions in the solid and liquid phases, slow concentration polarization has not yet been established. The ohmic internal resistance and the first-order RC loop (first-order RC loop) in the first-order RC equivalent circuit model fully encompass the polarization characteristics of this transient stage. Therefore, a method such as... Figure 4 The first-order RC equivalent circuit model shown is used to model the lithium-ion energy storage battery.

[0079] According to an embodiment of this application, the first-order RC equivalent circuit model of a lithium-ion energy storage battery can be shown in formula (3).

[0080] (3)

[0081] in, It can represent the open-circuit voltage of an energy storage battery; The internal resistance is ohmic; This is the internal resistance to polarization; Polarizing capacitor; This is the terminal voltage of the RC circuit; This is the discharge current value; the discharge current is defined as positive. This represents the rate of change of the terminal voltage of the RC circuit.

[0082] Based on a first-order RC equivalent circuit model, the model parameters are globally optimized and identified using discrete-time difference equations and nonlinear least squares method. When using the voltage and current sequences obtained above for identification, the resulting parameters are relatively accurate.

[0083] The discrete-time difference equation of the first-order RC equivalent circuit model is shown in Equation (4).

[0084] (4)

[0085] in, Indicates the first Predicted terminal voltage at each sampling time, It can represent the first The instantaneous current value flowing through the energy storage battery at each sampling time. It can represent the sampling interval duration, and e represents the natural constant. It can represent a time constant. This indicates the element number in the sampled voltage and current sequences.

[0086] The core of nonlinear least squares lies in finding the optimal combination of parameters. ,Right now This aims to minimize the error between the calculated predicted terminal voltage and the voltage values ​​in the acquired voltage sequence. The objective function constructed in this application... To minimize the sum of squared residuals, as shown in formula (5).

[0087] (5)

[0088] in, Indicates the first Predicted terminal voltage at each sampling time, Indicates the first The actual terminal voltage obtained at each sampling time. This represents the total number of elements in the voltage and current sequences.

[0089] To solve the aforementioned nonlinear optimization problem, the Trust Region Reflective (TRR) algorithm can be used for global optimization. The TRR algorithm has outstanding applicability and advantages in parameter identification. On the one hand, parameters such as the polarization resistance and time constant of lithium-ion energy storage batteries have strict non-negativity, allowing for direct upper and lower bound constraints on the parameter vector. When the iteration process reaches the parameter boundaries, it can adaptively adjust the optimization direction through a reflection mechanism, effectively avoiding infeasible solutions that violate physical meaning, such as negative internal resistance and negative time constants, during the fitting process. On the other hand, since the discrete difference equation contains complex exponential decay terms... This leads to the objective function exhibiting highly nonlinear and multi-local minima. The trust region reflection algorithm approximates the true objective function by using a quadratic model within the dynamically updated trust region radius, which not only ensures the global convergence speed when far from the extreme point, but also greatly improves the local fitting accuracy when approaching the extreme point.

[0090] According to an embodiment of this application, after fitting the parameter combination, the short-circuit current can be further calculated.

[0091] In the time domain, reference Figure 4 The differential equation of the RC circuit is shown in formula (6).

[0092] (6)

[0093] in, This represents a specific moment in the sampling process. Indicates an instantaneous moment The instantaneous value of the current flowing through the RC circuit.

[0094] By performing a Laplace transform on the above equation and rearranging it, we can obtain formula (7).

[0095] (7)

[0096] in, Represents a complex frequency variable. This represents the terminal voltage of the RC circuit in the complex frequency domain. This represents the short-circuit current of a lithium-ion energy storage battery in the complex frequency domain. This represents the initial polarization voltage of the RC circuit, i.e. .

[0097] In the complex frequency domain, the open-circuit voltage can be considered as having an amplitude of Step stimulus Then the Kirchhoff voltage equation for the entire battery short-circuit loop is shown in formula (8).

[0098] (8)

[0099] in, , The preset external short-circuit resistance is represented by formula (7). Substituting formula (7) into formula (8) yields formula (9).

[0100] = (9)

[0101] Extract the characteristic equation of the first-order closed-loop system as shown in formula (9), and find its characteristic roots. As shown in formulas (10) and (11).

[0102] (10)

[0103] (11)

[0104] Furthermore, the short-circuit current of a lithium-ion energy storage battery in the complex frequency domain... As shown in formula (12).

[0105] (12)

[0106] right By performing the inverse Laplace transform, the analytical solution of the short-circuit current in the time domain can be obtained, as shown in formula (13).

[0107] (13)

[0108] Then, it can be assumed that the energy storage battery is in a fully rested state. At the moment the external short circuit occurs, the short circuit current reaches its maximum value. Therefore, it can be deduced that the short circuit circuit is determined only by the internal resistance of the ohm and the external short circuit resistance. The formula for calculating the short circuit current is shown in formula (14).

[0109] (14)

[0110] According to embodiments of this application, by fitting parameters using corresponding voltage and current sequences under the first and second states of charge, respectively, the first and second ohmic internal resistances that vary with the state of charge can be obtained. Then, based on the first and second ohmic internal resistances, the predicted first and second short-circuit currents can be identified, enabling the identification of the maximum short-circuit current peak of the energy storage battery under extreme conditions such as full charge, while also considering the fault current characteristics under medium and low charge states. Based on this, fuse selection can be performed, ensuring that the fuse has sufficient breaking capacity when the battery is in any state of charge, effectively avoiding protection blind spots or malfunction risks caused by differences in state of charge. This enables reliable selective protection coordination throughout the entire process from full charge to deep discharge, improving the safety and stability of the DC-side protection system of the energy storage power station.

[0111] According to an embodiment of this application, an energy storage power station includes multiple battery clusters connected in parallel, each battery cluster includes multiple battery packs connected in series, and each battery pack includes multiple energy storage batteries connected in series. The model of the fuse for the energy storage power station is determined based on the structure of the energy storage power station and the short-circuit currents of the multiple energy storage batteries under multiple states of charge. This includes: determining the short-circuit current range of the energy storage power station based on the number of battery clusters, a first short-circuit current, and a second short-circuit current; predicting the cumulative heat required for fusing based on a preset fusing time window and the short-circuit current range to determine the range of the Joule integral; and selecting a fuse based on the range of the Joule integral to determine the fuse model.

[0112] According to embodiments of this application, the energy storage batteries in the energy storage power station adopt a hierarchical series-parallel topology to achieve flexible configuration of voltage levels and capacity. In terms of physical structure, Individual energy storage batteries are first connected in series to form a battery pack; at the system level... The battery packs are connected in series to form a high-voltage battery cluster to meet the DC-side voltage requirements; ultimately Each battery cluster is connected in parallel to the DC bus via a combiner cabinet, forming a complete energy storage power station. Under the above topology, each level of electrical node is equipped with a fuse as a DC-side short-circuit protection device: battery pack level protection is provided in the individual cell series circuit, battery cluster level protection is provided in the battery pack series circuit, and energy storage power station level protection is provided in the cluster parallel bus.

[0113] Based on the number of parallel battery clusters in the energy storage power station and the first and second short-circuit currents corresponding to the energy storage batteries under various states of charge, the maximum and minimum short-circuit current values ​​that may occur in the circuit during an external short-circuit fault are determined, thus defining the amplitude range of the DC-side short-circuit current of the energy storage power station. This range covers everything from the maximum inrush current under the worst operating conditions to the minimum fault current of a single battery cluster or under low charge conditions, providing complete current boundary conditions for the subsequent design of the thermal withstand and breaking capacity of the fuse.

[0114] Furthermore, based on the short-circuit current range and the preset fusing time window, by integrating the square of the current over time, the range of accumulated heat energy required for reliable breaking of the fuse can be predicted, thus determining the allowable upper and lower limits of the Joule integral. Specifically, the lower limit of the Joule integral corresponds to the threshold for short-term non-fusing under the maximum short-circuit current, while the upper limit corresponds to the threshold for reliable fusing over a long period under the minimum short-circuit current. By comparing the Joule integral range with the fusing Joule integral characteristics of candidate fuse models, suitable models whose thermal characteristic parameters fall within the range are selected, ensuring that the fuse can achieve correct selective protection action when encountering short-circuit faults of varying severity.

[0115] According to embodiments of this application, the method for determining the fuse for an energy storage power station further includes:

[0116] The corresponding environmental parameters are determined based on the geographical environment of the energy storage power station; among them, the fuse is selected based on the range of Joule integral to determine the fuse model, including: selecting fuses based on the range of Joule integral and environmental parameters to determine the fuse model.

[0117] According to embodiments of this application, firstly, the maximum breaking capacity of the fuse must be greater than the maximum short-circuit peak current that may flow in the circuit. That is, for battery pack-level or battery cluster-level protection, the maximum breaking capacity of the fuse is required to be greater than the short-circuit current. For parallel busbar protection, the maximum breaking capacity of the busbar fuse must be greater than [a certain value]. .

[0118] Secondly, the rated voltage of the selected fuse should be greater than the open-circuit voltage. Its rated current needs to be adjusted based on the battery charge / discharge rate, combined with environmental parameters such as altitude and ambient temperature, to ensure that the fuse will not malfunction during normal operation.

[0119] Finally, the pre-arc Joule integral is determined based on the physical withstand limit of the protected equipment and the coordination between the upper and lower fuse stages. Joule in front of the arc The breaking time must be less than the physical withstand limit of the protected equipment to ensure that the fuse melts before irreversible damage to the protected equipment. This is based on a preset breaking time range. and the battery state of charge and Short-circuit current range This allows us to calculate the upper and lower limits of the Joule integral for fuse failure. This is to ensure that the fuse withstands the maximum short-circuit current. During the impact, it can If no malfunction occurs within the specified time, the lower limit of its fuse Joule integral must be set to [value missing]. Meanwhile, in order to ensure that the minimum short-circuit current is encountered... At that time, it was possible The fault must be quickly cleared within the specified time, and the upper limit of its fuse Joule integral must be set to [value missing]. By comparing the fuse parameters, we can filter out fuses whose actual Joule integral values ​​fall within a certain range. The fuse inside is used to determine the fuse model.

[0120] According to embodiments of this application, by introducing a parameter for the number of parallel battery clusters into the energy storage power station's hierarchical topology, and combining the first and second short-circuit currents under different states of charge, a complete short-circuit current range covering the worst extreme conditions to lower states of charge is constructed. This allows for a more comprehensive quantification of the superposition effect of battery cluster currents and the impact of state-of-charge differences on fault current, ensuring that the current boundary used for fuse selection includes both the maximum expected inrush current and the minimum fault current, thereby effectively eliminating protection blind spots caused by incomplete fault current estimation. Furthermore, environmental parameters can be incorporated into the calculation of the fuse's rated current to obtain a corrected rated current, which can then be used as a reference for fuse selection. These steps consider the impact of thin air and extreme temperatures at high altitudes on the fuse's current-carrying capacity, avoiding maloperation caused by a decrease in the fuse's current-carrying capacity due to temperature changes, and improving the fuse's adaptability and robustness to environmental changes.

[0121] Figure 5 A block diagram of a fuse determination device for an energy storage power station according to an embodiment of this application is shown schematically.

[0122] like Figure 5 As shown, the fuse determination device 500 for energy storage power stations includes a duration determination module 510, a data acquisition module 520, a prediction module 530, and a model determination module 540.

[0123] The duration determination module 510 is used to determine the expected discharge duration of the energy storage battery when the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge, based on the calibration parameters of the energy storage battery.

[0124] The acquisition module 520 is used to discharge the energy storage battery within the expected discharge time when the energy storage battery is in multiple states of charge, so as to acquire the current and voltage output by the energy storage battery and obtain the voltage sequence and current sequence of the energy storage battery in multiple states of charge.

[0125] The prediction module 530 is used to predict the current of the energy storage battery when an external short circuit occurs, based on voltage and current sequences, to obtain the short-circuit current of the energy storage battery when it is in a state of charge.

[0126] The model determination module 540 is used to determine the model of the fuse of the energy storage power station based on the structure of the energy storage power station and the short-circuit current of multiple energy storage batteries in multiple states of charge.

[0127] Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or implemented by hardware or firmware in any other reasonable manner by integrating or packaging circuits, or implemented in any one of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0128] For example, any multiple of the duration determination module 510, acquisition module 520, prediction module 530, and model determination module 540 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this application, at least one of the duration determination module 510, acquisition module 520, prediction module 530, and model determination module 540 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the duration determination module 510, acquisition module 520, prediction module 530 and model determination module 540 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0129] It should be noted that the data processing system part in the embodiments of this application corresponds to the data processing method part in the embodiments of this application. The specific description of the data processing system part is referred to in the data processing method part, and will not be repeated here.

[0130] Figure 6 A block diagram of an electronic device suitable for implementing the methods described above, according to an embodiment of this application, is illustrated schematically. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0131] like Figure 6 As shown, an electronic device 600 according to an embodiment of this application includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a ROM 602 (Read-Only Memory) or a program loaded from a storage portion 608 into a RAM 603 (Random Access Memory). The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0132] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 602 and / or RAM 603. It should be noted that programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in one or more memories.

[0133] According to embodiments of this application, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to a bus 604. The electronic device 600 may also include one or more of the following components connected to the input / output (I / O) interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0134] According to embodiments of this application, the method flow according to embodiments of this application can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by processor 601, it performs the functions defined in the system of embodiments of this application. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0135] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0136] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0137] For example, according to embodiments of this application, a computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 as described above.

[0138] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this application. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the fuse determination method for energy storage power stations provided in the embodiments of this application.

[0139] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0140] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0141] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations are not explicitly described in this application. In particular, without departing from the spirit and teachings of this application, the features described in the various embodiments of this application can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of this application.

[0143] The embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. This application does not depart from its scope, and those skilled in the art can make various substitutions and modifications, all of which should fall within the scope of this application.

Claims

1. A method for determining the fuse in an energy storage power station, the energy storage power station comprising multiple energy storage batteries, characterized in that, Methods for determining fuse failure include: Based on the calibration parameters of the energy storage battery, the expected discharge time of the energy storage battery is determined when the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge. With the energy storage battery in multiple states of charge, the energy storage battery is discharged within a predicted discharge time to collect the current and voltage output by the energy storage battery, thereby obtaining the voltage sequence and current sequence of the energy storage battery in multiple states of charge. Based on the voltage and current sequences, the current of the energy storage battery when an external short circuit occurs is predicted, and the short-circuit current of the energy storage battery in the state of charge is obtained. Based on the structure of the energy storage power station and the short-circuit current of the energy storage battery under multiple states of charge, the model of the fuse of the energy storage power station is determined.

2. The method for determining fuses for energy storage power stations according to claim 1, characterized in that, The multiple states of charge include: a first state of charge and a second state of charge. When the energy storage battery is in each of the multiple states of charge, the energy storage battery is discharged within a predetermined discharge duration to collect the current and voltage output by the energy storage battery, obtaining the voltage sequence and current sequence of the energy storage battery in each of the multiple states of charge, including: When the energy storage battery is in the first state of charge, the output current and output voltage generated by the discharge of the energy storage battery during the sampling time are sampled to obtain the first voltage sequence and the first current sequence of the energy storage battery in the first state of charge. When the energy storage battery is in the second state of charge, the output current and output voltage generated by the discharge of the energy storage battery during the sampling time are sampled to obtain the second voltage sequence and the second current sequence of the energy storage battery in the second state of charge.

3. The method for determining fuses for energy storage power stations according to claim 2, characterized in that, The step of predicting the current of the energy storage battery when an external short circuit occurs based on the voltage and current sequences, and obtaining the short-circuit current of the energy storage battery in the state of charge, includes: The first voltage sequence and the first current sequence are used to fit the parameters of the energy storage battery to obtain the first ohmic internal resistance of the energy storage battery in the first state of charge. The second voltage sequence and the second current sequence are used to fit the parameters of the energy storage battery to obtain the second ohmic internal resistance of the energy storage battery in the second state of charge. Based on the resistance values ​​of the first ohmic internal resistance and the second ohmic internal resistance, the current in the case of an external short circuit in the energy storage battery is predicted, and the first short circuit current and the second short circuit current of the energy storage battery are determined.

4. The method for determining fuses for energy storage power stations according to claim 3, characterized in that, The energy storage power station includes multiple battery clusters connected in parallel, each battery cluster includes multiple battery packs connected in series, and each battery pack includes multiple energy storage batteries connected in series. The determination of the fuse type for the energy storage power station based on its structure and the short-circuit currents of the energy storage batteries under various states of charge includes: The short-circuit current range of the energy storage power station is determined based on the number of battery clusters in the energy storage power station, the first short-circuit current, and the second short-circuit current. Based on the preset fusing time window and the short-circuit current range, the cumulative heat required for fusing is predicted, and the range of the Joule integral is determined. The fuse is selected based on the range of the Joule integral to determine the fuse model.

5. The method for determining fuses for energy storage power stations according to claim 4, characterized in that, Also includes: Determine the corresponding environmental parameters based on the geographical environment of the energy storage power station; The step of selecting a fuse based on the range of the Joule integral to determine the fuse model includes: The fuse is selected based on the range of the Joule integral and the environmental parameters to determine the fuse model.

6. The method for determining fuses for energy storage power stations according to claim 3, characterized in that, The step of fitting parameters of the energy storage battery using the first voltage sequence and the first current sequence to obtain the first ohmic internal resistance of the energy storage battery under the first state of charge includes: A corresponding equivalent circuit model is established using a first voltage sequence and a first current sequence, wherein the equivalent circuit model includes a first ohmic internal resistance as a parameter to be optimized. The first ohmic internal resistance of the energy storage battery is obtained by fitting the parameters of the first ohmic internal resistance in the equivalent circuit model based on the trust region reflection algorithm.

7. The method for determining fuses for energy storage power stations according to claim 1, characterized in that, The calibration parameters include nominal capacity and discharge rate. The determination of the expected discharge duration of the energy storage battery based on these calibration parameters, assuming the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge, includes: The total cumulative discharge charge of the energy storage battery is determined based on its nominal capacity and the preset change in state of charge. The discharge duration of the energy storage battery is estimated based on the discharge rate and the total cumulative discharge charge, and the expected discharge duration of the energy storage battery is determined.

8. A fuse determination device for an energy storage power station, characterized in that, include: The duration determination module is used to determine the expected discharge duration of the energy storage battery when the cumulative discharge charge of the energy storage battery reaches a preset change in state of charge, based on the calibration parameters of the energy storage battery. The acquisition module is used to discharge the energy storage battery within a predicted discharge time when the energy storage battery is in multiple states of charge, so as to acquire the current and voltage output by the energy storage battery and obtain the voltage sequence and current sequence of the energy storage battery in multiple states of charge. The prediction module is used to predict the current of the energy storage battery when an external short circuit occurs based on the voltage sequence and current sequence, so as to obtain the short circuit current of the energy storage battery when it is in the state of charge. The model determination module is used to determine the model of the fuse of the energy storage power station based on the structure of the energy storage power station and the short-circuit current of the energy storage battery under multiple states of charge.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, characterized in that, When the executable instructions are executed by the processor, the processor performs the method according to any one of claims 1 to 7.

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