Base station long-time energy storage system and method

Abstract

The embodiment of the invention provides a long-time energy storage system of a base station. The system comprises a main control unit, an interaction unit and a plurality of energy storage modules, the main control unit is configured to obtain the electric quantity information of each energy storage module from each slave control unit when the working load of the long-time energy storage system of the base station meets a preset load condition; determining and executing an electric quantity balancing strategy according to the connection relationship between the energy storage modules and the electric quantity information of the energy storage modules; when the preset load condition is not met, voltage information and temperature information of each energy storage module are acquired from each slave control unit; determining whether the long-time energy storage system of the base station works normally or not based on the voltage information and the temperature information of each energy storage module and the parameters of the currently applied conversion unit; and in response to the fact that the energy storage system of the base station does not work normally for a long time, determining an early warning instruction, and pushing the early warning instruction to the user through the interaction unit.

Description

Technical Field

[0001] This specification relates to the field of long-term energy storage, and in particular to a base station long-term energy storage system and a backup power control method. Background Art

[0002] With the rapid growth of modern energy demand and the widespread application of distributed energy systems, energy storage technology has been widely used in power regulation, new energy grid connection and emergency power supply.

[0003] During long-term operation, the performance of energy storage systems may deteriorate due to aging, uneven power load, uneven heat dissipation, or line damage caused by over-discharge of battery packs. However, the power balance of current energy storage systems is difficult to dynamically adapt to the power differences between different energy storage modules; and it mainly relies on preset fixed parameters, making it difficult to timely identify the potential risks of sudden line interruptions, resulting in the system being unable to respond quickly and effectively when a fault occurs.

[0004] Therefore, it is necessary to provide a base station long-term energy storage system and method to improve the overall performance and operational safety of the base station long-term energy storage system. Summary of the invention

[0005] One or more embodiments of the present specification provide a base station long-term energy storage system, the system comprising a main control unit, an interactive unit and a plurality of energy storage modules based on modular plug-in; the plurality of energy storage modules are connected by cables, each energy storage module is configured with a battery pack, a conversion unit, a power sensor, a voltage sensor, a temperature sensor and a slave control unit, and the slave control unit is communicatively connected with the main control unit; the conversion unit controls the energy flow direction and energy flow specification of the energy storage module based on conversion unit parameters, and the slave control unit obtains the power information, voltage information and temperature information of the energy storage module from the power sensor, the voltage sensor and the temperature sensor respectively; the main control unit is configured to ensure that the workload of the long-term energy storage system of the base station meets the expected When the load condition is set, the following operations are performed: the power information of each energy storage module is obtained from each slave control unit; the power balancing strategy is determined and executed according to the connection relationship between each energy storage module and the power information of each energy storage module; the main control unit is configured to perform the following operations when the workload of the base station long-term energy storage system does not meet the preset load condition: the voltage information and temperature information of each energy storage module are obtained from each slave control unit; based on the voltage information, temperature information of each energy storage module and the currently applied conversion unit parameters, it is determined whether the base station long-term energy storage system is working normally; in response to the base station long-term energy storage system not working properly, an early warning instruction is determined, and the early warning instruction is pushed to the user through the interactive unit.

[0006] One or more embodiments of this specification provide a base station long-term energy storage method. The method includes: when the workload of the base station long-term energy storage system meets the preset load condition: obtain the power information of each of the energy storage modules from each of the slave control units; determine and execute the power balancing strategy according to the connection relationship between each of the energy storage modules and the power information of each of the energy storage modules; when the workload of the base station long-term energy storage system does not meet the preset load condition: obtain the voltage information and temperature information of each of the energy storage modules from each of the slave control units; based on the voltage information, temperature information of each of the energy storage modules and the currently applied conversion unit parameters, determine whether the base station long-term energy storage system is working normally; in response to the base station long-term energy storage system not working properly, determine an early warning instruction, and push the early warning instruction to the user through the interactive unit.

[0007] One or more embodiments of the present specification provide a base station long-term energy storage device, including a processor, wherein the processor is used to execute a base station long-term energy storage method.

[0008] One or more embodiments of the present specification provide a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a base station long-term energy storage method. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0010] Figure 1 is a schematic diagram of a base station long-term energy storage system according to some embodiments of this specification;

[0011] Figure 2 is an exemplary flow chart of a base station long-term energy storage method according to some embodiments of this specification;

[0012] Figure 3 is an exemplary schematic diagram of determining the power balancing strategy according to some embodiments of this specification;

[0013] Figure 4 is an exemplary flow chart of determining distributed inhalation parameters according to some embodiments of the present specification. DETAILED DESCRIPTION

[0014] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0017] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0018] Figure 1 Schematic diagram of a base station long-term energy storage system according to some embodiments of this specification. In some embodiments, the base station long-term energy storage system 100 includes a main control unit 110, an interaction unit 120 and a plurality of energy storage modules, such as energy storage module 130-1, energy storage module 130-2, ..., energy storage module 130-n.

[0019] The main control unit 110 refers to a global control unit in the base station long-term energy storage system.

[0020] In some embodiments, the main control unit 110 may include a server and a terminal. The server may process information and / or data related to the base station long-term energy storage system 100 to perform one or more of the following functions described in this application. In some embodiments, the server may include a processor. The terminal may be one or more terminal devices or software used by one or more technicians, including mobile phones, tablets, and computers.

[0021] In some embodiments, the master control unit is configured to perform the following operations when the workload of the base station long-term energy storage system meets the preset load conditions: obtain the power information of each energy storage module from each slave control unit; determine and execute the power balancing strategy based on the connection relationship between each energy storage module and the power information of each energy storage module.

[0022] In some embodiments, the main control unit is also configured to perform the following operations when the workload of the base station long-term energy storage system meets the non-preset load conditions: obtain the power information, voltage information, and temperature information of each energy storage module from each slave control unit; based on the voltage information, temperature information, and currently applied conversion unit parameters of each energy storage module, determine whether the base station long-term energy storage system is working normally; in response to the base station long-term energy storage system not working properly, determine an early warning instruction, and push the early warning instruction to the user through the interactive unit.

[0023] In some embodiments, the main control unit is further configured to: determine the power balancing threshold corresponding to each energy storage module based on the usage time and power information of the battery group of each energy storage module; determine the power balancing strategy based on the power balancing threshold corresponding to each energy storage module, the connection relationship between each energy storage module, and the power information of each energy storage module.

[0024] In some embodiments, the main control unit is further configured to: in response to the base station long-term energy storage system not working properly, obtain multiple voltage information collected by the voltage sensor at multiple time points; based on the multiple voltage information and the currently applied conversion unit parameters, determine the battery flow characteristics corresponding to the multiple time points; based on the battery flow characteristics corresponding to the multiple time points, evaluate the line interruption risk; according to the line interruption risk, adjust the working parameters of one or more target lines; the target lines include charging lines and / or discharging lines.

[0025] In some embodiments, the main control unit is further configured to: determine the heat dissipation demand distribution for a period of time in the future based on the power information, voltage information, and temperature information of each energy storage module, the heat dissipation demand distribution including the required heat dissipation of at least one energy storage module; and determine the distributed air intake parameters according to the heat dissipation demand distribution for a period of time in the future.

[0026] The interaction unit 120 is a unit in the base station long-term energy storage system that interacts with the user and transmits information data. For example, the interaction unit can be equipped with a display screen or an access terminal device, and technicians and / or users can interact with the base station long-term energy storage system 100 through a visual interface.

[0027] In some embodiments, the main control unit can push the warning instruction to the user through the interactive unit. For more information, please refer to Figure 2 and its description.

[0028] Energy storage modules refer to modules that store, release and manage energy in the base station long-term energy storage system. For example, energy includes but is not limited to electrical energy, thermal energy, etc.

[0029] In some embodiments, multiple energy storage modules may be connected via multiple cables. For example, each energy storage module may be connected to at least one adjacent energy storage module via at least one line.

[0030] In some embodiments, each energy storage module is configured with a battery pack (such as battery pack 131-1, battery pack 131-2, ..., battery pack 131-n), a conversion unit (such as conversion unit 132-1, conversion unit 132-2, ..., conversion unit 132-n), a sensor (such as sensor 133-1, sensor 133-2, ..., sensor 133-n) and a slave control unit (such as slave control unit 134-1, slave control unit 134-2, ..., slave control unit 134-n).

[0031] In some embodiments, the energy storage module may adopt a modular plug-in design. For example, the energy storage module may be connected to the main control unit 110 and / or other energy storage modules via a plug-in connector. The plug-in connector includes but is not limited to a power interface and a communication interface to achieve energy transmission and data interaction.

[0032] The battery pack can store and release the electric energy required by the base station long-term energy storage system, and is composed of multiple battery cells. For example, each battery cell can be a lithium-ion battery, a nickel-hydrogen battery, etc.

[0033] In some embodiments, the base station long-term energy storage system can operate in two modes: charging mode and discharging mode. In the charging mode, the base station long-term energy storage system can be connected to an external power supply device (not shown in the figure) and store electrical energy through the battery pack in the energy storage module to continuously provide the required electrical energy to the base station long-term energy storage system. In the discharging mode, the battery pack in the energy storage module can release the stored electrical energy to meet the power demand of the base station long-term energy storage system or the power supply demand of other loads.

[0034] The conversion unit is configured to control the energy flow direction and flow specifications in the energy storage module to achieve energy conversion and transmission in the base station long-term energy storage system. In some embodiments, the conversion unit can control the energy flow direction and energy flow specifications of the energy storage module based on the conversion unit parameters.

[0035] In some embodiments, the transformation unit parameters may include one or more of energy flow direction parameters and energy flow specification parameters.

[0036] Among them, the energy flow direction parameter can indicate the energy transmission flow direction of the energy storage module. For example, in the charging mode of the base station long-term energy storage system, electric energy can be input into the energy storage module from the external power supply device; in the discharge mode, electric energy can be output from the energy storage module. Energy flow specification parameters may include but are not limited to the transmission form of electric energy (such as AC or DC), current limit value and voltage limit value.

[0037] In some embodiments, the base station long-term energy storage system further includes a switch of the control circuit (not shown in the figure), and the switching direction of energy flow is switched by the switch element in the control circuit. For example, it may include at least one switch element and at least one diode.

[0038] The power sensor is configured to collect power information in the energy storage module, for example, the remaining power of the energy storage module, the change of charge and discharge power, etc.

[0039] The voltage sensor is configured to collect voltage information of the energy storage module when it is running. For example, the voltage of the energy storage module when the base station long-term energy storage system is running, the voltage data of the base station long-term energy storage system under the charging model and the voltage data under the discharging mode can be collected.

[0040] The temperature sensor is configured to collect temperature information when the energy storage module is in operation. For example, the temperature data of the energy storage module in operation or the temperature data of the base station long-term energy storage system in the charging and discharging mode can be collected.

[0041] The slave control unit refers to a local control unit in the energy storage module. In some embodiments, the slave control unit may include a server and a terminal. The server may process information and / or data related to the energy storage module. For more information about the server and the terminal, please refer to the above-mentioned master control unit and its description, which will not be repeated here.

[0042] In some embodiments, the slave control unit is configured to be communicatively connected with the master control unit.

[0043] In some embodiments, the slave control unit is configured to obtain power information, voltage information, and temperature information of the energy storage module from a power sensor, a voltage sensor, and a temperature sensor, respectively.

[0044] In some embodiments, the slave control unit is further configured to receive instructions issued by the master control unit and control the conversion unit in the energy storage module to adjust the conversion unit parameters. Figure 2 and its description.

[0045] It should be noted that the above description of the base station long-term energy storage system 100 and its module units is only for the convenience of description and cannot limit this specification to the scope of the embodiments. It is understandable that for those skilled in the art, after understanding the principle of the system, it is possible to arbitrarily combine the various module units, or form a subsystem to connect with other module units without deviating from this principle. In some embodiments, Figure 1 The main control unit 110, the interactive unit 120 and the multiple energy storage modules based on modular plug-in disclosed in the specification can be different module units in a system, or one module unit can realize the functions of two or more module units mentioned above. For example, each module unit can share a storage module, or each module unit can have its own storage module. Such variations are all within the protection scope of this specification.

[0046] Figure 2 is an exemplary flow chart of a base station long-term energy storage method according to some embodiments of this specification. Figure 2 As shown, the process 200 includes the following steps. In some embodiments, the process 200 can be executed by a processor in the main control unit.

[0047] In some embodiments, the main control unit is configured to perform the following operation steps 210-220 when the workload of the base station long-term energy storage system meets the preset load condition. The preset load condition can determine whether the base station long-term energy storage system is in an idle state. Meeting the preset load condition includes but is not limited to the current of the energy storage module being less than or equal to the preset current threshold, the power being less than or equal to the preset power threshold, etc. The preset current threshold and the power threshold can be pre-constructed based on prior knowledge.

[0048] Step 210, obtaining power information of each energy storage module from each slave control unit.

[0049] In some embodiments, each energy storage module is configured with a power sensor to collect power information in each energy storage module; the slave control unit in each energy storage module can transmit the power information to the master control unit through the network to obtain the power information of each energy storage module.

[0050] Step 220, determining and executing a power balancing strategy based on the connection relationship between the energy storage modules and the power information of the energy storage modules.

[0051] The power balancing strategy refers to a strategy for adjusting the power of the battery groups in multiple energy storage modules so that the power of each energy storage module tends to be balanced. For example, the processor can execute the power balancing strategy so that the power of the battery groups in multiple energy storage modules reaches an average value, which is power balancing.

[0052] In some embodiments, the processor may determine and execute a power balancing strategy by looping through the power of each energy storage module based on the average power of all energy storage modules and the connection relationship between each energy storage module.

[0053] Exemplarily, the processor can calculate the average power of all energy storage modules as the power balancing value; loop through the power of each energy storage module and select any energy storage module; if the power of the current energy storage module is equal to the balancing value, continue to traverse and mark the state of the current energy storage module; if the power of the current energy storage module is greater than the balancing value, transfer the power to the next energy storage module until the power of the current energy storage module is equal to the balancing value, or the power of the next energy storage module reaches or exceeds the balancing value, continue to traverse and mark the state of the current energy storage module; if the power of the current energy storage module is less than the balancing value, and the next energy storage module If the power of an energy storage module is greater than or equal to the difference required for the current energy storage module to reach the equilibrium value, power is obtained from the next energy storage module until the power of the current energy storage module is equal to the equilibrium value, and the traversal continues and the status of the current energy storage module is marked; if the power of the current energy storage module is less than the equilibrium value, and the power of the next energy storage module is less than the difference required for the current energy storage module to reach the equilibrium value, the entire power of the next energy storage module is obtained, and the traversal continues and the status of the current energy storage module is marked; until the status of all energy storage modules is marked as "processed", the cycle ends, and the power of each energy storage module tends to be balanced.

[0054] Among them, if the current energy storage module does not meet any of the following conditions, the status of the energy storage module will be marked as "unprocessed"; if the current energy storage module meets the following conditions at the same time, the status of the energy storage module will be marked as "processed": Condition 1, the power of the current energy storage module is equal to the target balancing value; Condition 2, the previous energy storage module connected to the current energy storage module has been marked as "processed", or the current energy storage module is not connected to the previous energy storage module.

[0055] In some embodiments, the main control unit is further configured to: determine the power balancing threshold corresponding to each energy storage module based on the usage time and power information of the battery pack of each energy storage module; determine the power balancing strategy based on the power balancing threshold corresponding to each energy storage module, the connection relationship between each energy storage module, and the power information of each energy storage module. For more information, please refer to Figure 3 and its description.

[0056] In some embodiments, the main control unit is configured to perform the following operation steps 230-250 when the workload of the base station long-term energy storage system does not meet the preset load condition. Wherein, not meeting the preset load condition includes that the current of the energy storage module exceeds the preset current threshold, or the power exceeds the preset power threshold, etc.

[0057] Step 230, obtaining voltage information and temperature information of each energy storage module from each slave control unit.

[0058] In some embodiments, each energy storage module is also configured with a voltage sensor and a temperature sensor to collect voltage information and temperature information in each energy storage module; the main control unit can obtain voltage information and temperature information of each energy storage module from each slave control unit through the network.

[0059] Step 240, based on the voltage information, temperature information and currently applied conversion unit parameters of each energy storage module, determine whether the base station long-term energy storage system is working normally.

[0060] The currently applied conversion unit parameters refer to the conversion unit parameters applied by the conversion unit in the base station long-term energy storage system at the current moment. For more information about conversion unit parameters, see Figure 1 and its description.

[0061] In some embodiments, the processor may compare the voltage information of each energy storage module with the voltage threshold, or compare the temperature information with the temperature threshold, to determine whether the base station long-term energy storage system is working properly. For example, when the base station long-term energy storage system is running, the voltage of any energy storage module is greater than the voltage threshold, or the temperature of any energy storage module is greater than the temperature threshold, and it is determined that the base station long-term energy storage system is not working properly.

[0062] The processor may determine the voltage threshold and the temperature threshold based on the currently applied conversion unit parameters. For example, the processor may determine the voltage threshold and the temperature threshold by querying a first preset table based on the currently applied conversion unit parameters. The first preset table may include a correspondence between an energy flow direction parameter, an energy flow specification parameter, and a voltage threshold and a temperature threshold, and is pre-constructed based on historical data or prior knowledge.

[0063] In some embodiments, the main control unit is further configured to: in response to the base station long-term energy storage system not working properly, obtain multiple voltage information collected by the voltage sensor at multiple time points; determine the battery flow characteristics based on the multiple voltage information and the currently applied conversion unit parameters; based on the battery flow characteristics, evaluate the line interruption risk; according to the line interruption risk, adjust the working parameters of one or more target lines; the target lines include charging lines and / or discharging lines.

[0064] In some embodiments, in response to the base station long-term energy storage system not working properly, the technician can obtain multiple voltage information collected by the voltage sensor at multiple time points according to the needs. For example, the multiple time points may include the current time point, multiple historical time points before the current time point, etc.

[0065] Battery flow characteristics refer to characteristics related to the flow of battery energy.

[0066] In some embodiments, the battery flow characteristics include energy flow direction and voltage fluctuation, etc. Among them, voltage fluctuation refers to the range and amplitude of voltage changes in the base station long-term energy storage system during the charging and discharging process.

[0067] In some embodiments, the processor may determine the battery flow characteristics based on multiple voltage information and currently applied conversion unit parameters. For example, the ratio of the voltage mean to the voltage variance at multiple historical time points is used as the voltage fluctuation of the battery flow characteristics; the energy flow direction in the currently applied conversion unit parameters is used as the energy flow direction of the battery flow characteristics.

[0068] Line interruption risk refers to the risk of interruption of the connecting lines between multiple energy storage modules.

[0069] In some embodiments, the processor may determine the line interruption risk in a variety of ways.

[0070] For example, if the voltage fluctuation in the battery flow characteristic is less than or equal to the voltage fluctuation threshold, the line interruption risk is 0; if the voltage fluctuation in the battery flow characteristic is greater than the voltage fluctuation threshold, the line interruption risk is determined by calculating the following formula (1). R line =k×(ΔV-V th ) (1)

[0071] Among them, R line is the line interruption risk, k is a preset constant, ΔV is the voltage fluctuation, V th Voltage fluctuation threshold. The voltage fluctuation threshold may include a discharge fluctuation threshold and a charge fluctuation threshold. The processor may select a corresponding threshold according to the current charge and discharge mode of the base station long-term energy storage system. For example, in the charge mode, the voltage fluctuation threshold selects the charge fluctuation threshold.

[0072] In some embodiments, the processor may determine the voltage fluctuation threshold in a variety of ways. For example, a technician may perform multiple charging and discharging experiments of a base station long-term energy storage system as required to determine the voltage fluctuation threshold.

[0073] In some embodiments, the power fluctuation threshold is also related to the average number of connections of each energy storage module and the total usage time of multiple battery packs in the energy storage module. The total usage time of multiple battery packs can be determined based on a timer. For more information, see Figure 3 and its description.

[0074] For example, when the base station long-term energy storage system operates in charging mode, the voltage fluctuation threshold is positively correlated to the total usage time of multiple battery packs when charging. The longer the total time, the larger the charging fluctuation threshold. In discharge mode, the voltage fluctuation threshold is positively correlated to the average number of connections of each energy storage module. The larger the average number of connections, the larger the discharge fluctuation threshold.

[0075] The processor may calculate the average number of connections based on the sum of the number of connections between multiple energy storage modules and the total number of energy storage modules. The number of connections refers to the number of connections between an energy storage module and other energy storage modules. For example, the energy storage system includes energy storage modules A, B, C, and D. If A is connected to B and C, the number of connections of A is 2.

[0076] In some embodiments, the processor may also construct a vector to be matched based on the power information, voltage information, temperature information, and current conversion unit parameters of multiple energy storage modules; based on the vector to be matched, a plurality of reference vectors constructed based on the power information, voltage information, temperature information, and historical conversion unit parameters of multiple energy storage modules in the historical data are matched for similarity, and the fault record corresponding to the reference vector with the highest similarity is used as the line interruption risk. The similarity may be represented by cosine similarity, vector distance, etc.; the line interruption risk corresponding to the reference vector may be determined by statistical analysis of known fault records in the historical data. For example, if the power information, voltage information, temperature information, and current conversion unit parameters of the energy storage module corresponding to the reference vector have caused a line interruption, the line interruption risk is high, such as the line interruption risk may take a value of 1, etc. Otherwise, the line interruption risk may take a value of 0.

[0077] The target line refers to at least one line in the line whose working parameters need to be determined. For example, the target line includes charging lines and / or discharging lines of multiple battery packs, etc.; the working parameters of the target line include charging and discharging cut-off voltages of multiple battery packs, etc. Among them, the charging and discharging cut-off voltage means that when the voltage of the battery pack reaches the upper limit or lower limit set in the working parameters, the technicians can actively stop the charging or discharging of the base station long-term energy storage system to prevent the battery pack from overcharging or over-discharging.

[0078] In some embodiments, the processor can adjust the operating parameters of one or more target lines according to the line interruption risk. For example, when the base station long-term energy storage system is operating in charging mode, the higher the line interruption risk, the lower the charging cut-off voltage is; in discharging mode, the higher the line interruption risk is, the higher the discharge cut-off voltage is.

[0079] In some embodiments, the target line also includes access lines and / or exit lines of multiple battery packs; adjusting the operating parameters of one or more target lines according to the line interruption risk also includes: the processor can determine multiple candidate operating parameters; for each candidate operating parameter, based on the candidate operating parameter, the current line interruption risk, the current power, voltage, temperature of each energy storage module, and the currently applied conversion unit parameters, the line interruption risk in the future period is determined through a line interruption risk prediction model; based on the line interruption risk in the future period, the operating parameters are determined.

[0080] In some embodiments, the target lines also include incoming lines and / or outgoing lines of multiple battery packs.

[0081] For example, in charging mode, the external power supply device can be connected to the energy storage module that needs to be charged through an access line, and turned on by the switch in the control circuit to input electrical energy into the energy storage module, or disconnected by the exit line control switch to exit the energy storage module from the charging circuit.

[0082] In some embodiments, technicians can randomly adjust the operating parameters within the allowable range according to needs, thereby determining one or more candidate operating parameters. For example, the processor can randomly adjust the upper and lower limits of the charge and discharge cut-off voltage within the allowable range.

[0083] In some embodiments, the processor can determine the line interruption risk in the future through the line interruption risk prediction model based on the candidate working parameters, the current line interruption risk, the current power, voltage, temperature of each energy storage module, and the current applied conversion unit parameters. For example, the line interruption risk in the next week or the next month after the current moment.

[0084] In some embodiments, the line interruption risk prediction model may be a machine learning model, such as a neural network (NN).

[0085] In some embodiments, the input of the line interruption risk prediction model may include candidate operating parameters, current line interruption risk, current power, voltage, temperature of each energy storage module, and currently applied conversion unit parameters; the output of the line interruption risk prediction model may be the line interruption risk in the future corresponding to the candidate operating parameters. The current line interruption risk may be determined based on the battery flow characteristics and voltage fluctuation threshold, or based on historical data. For more information, please refer to Figure 2 The above description will not be repeated here.

[0086] In some embodiments, the input of the line interruption risk prediction model also includes the distribution of heat dissipation demand in the future period of time.

[0087] The heat dissipation demand distribution in the future period refers to a sequence of heat dissipation required by multiple energy storage modules, which can be composed of the heat dissipation required sampled in the future period, arranged in chronological order. The heat dissipation required refers to the heat that needs to be discharged when the base station long-term energy storage system is running. The processor can determine the heat dissipation required in the future period based on historical data or based on the second prediction model. For more information, please refer to Figure 4 and its description.

[0088] In some embodiments of this specification, the heat dissipation demand distribution reflects the heat generated by the base station long-term energy storage system during operation. If the heat cannot be discharged in time, the continuous high temperature will accelerate the aging of the line material, further causing thermal runaway of the battery pack and increasing the risk of failure. By introducing the heat dissipation demand distribution for a period of time in the future into the input of the line interruption risk prediction model, the heat dissipation required in the future period can be predicted and evaluated, thereby more comprehensively evaluating the line risk.

[0089] In some embodiments, the training samples of the line interruption risk prediction model may include sample operating parameters of the base station long-term energy storage system in the first time period, sample line interruption risks in the first time period, sample power in the first time period, sample voltage in the first time period, sample temperature in the first time period, and sample conversion unit parameters in the first time period.

[0090] The training label corresponding to the training sample may be the line interruption risk of the base station long-term energy storage system in the second time period. The first time period is earlier than the second time period, for example, the first time period may be the current time period, and the second time period may be a future time period after the current time period.

[0091] The training samples can be determined based on historical data. For example, the risk of sample line interruption in the first time period can be determined by statistical analysis of known fault records in the historical data. For example, if the energy storage module power information, voltage information, temperature information, and current conversion unit parameters corresponding to the historical data have caused line interruption, then the risk of sample line interruption in the first time period is relatively high, such as the sample line interruption risk can be taken as 1, etc.

[0092] The training labels corresponding to the training samples can be manually acquired and annotated based on historical data. For example, the training labels corresponding to the training samples can be acquired in the same manner as the sample line interruption risk in the first time period based on historical data.

[0093] In some embodiments, the line interruption risk prediction model can be obtained by training multiple training samples with training labels. The processor can perform the following training process to obtain the line interruption risk prediction model. The training process includes: obtaining multiple training samples with labels to form a training sample set, and performing multiple rounds of iterations based on the training sample set.

[0094] Among them, at least one round of iteration includes: selecting one or more training samples from the training data set, inputting one or more training samples into the initial prediction model, and obtaining the model prediction output corresponding to the one or more training samples; substituting the model prediction output corresponding to the one or more training samples and the labels corresponding to the one or more training samples into the formula of the predefined loss function, and calculating the value of the loss function; according to the value of the loss function, iteratively updating the model parameters in the initial prediction model until the iteration end condition is met, and the iteration is terminated to obtain the trained line interruption risk prediction model. Among them, the iterative update of the model parameters of the initial prediction model can be performed by a variety of methods, for example, it can be updated based on the gradient descent method.

[0095] In some embodiments, the processor may select a candidate operating parameter with the lowest risk of line interruption as a target operating parameter to adjust the operating parameters of one or more target lines.

[0096] In some embodiments of this specification, a trained line interruption risk prediction model can be used to predict the line interruption risk in future time periods, and the charging and discharging working parameters can be actively adjusted to avoid sudden line interruptions that cause failures in the base station long-term energy storage system.

[0097] In some embodiments of this specification, the operating parameters of one or more target lines are adjusted by the line interruption risk, which can effectively protect the line interruption risk between multiple energy storage modules, improve the operating stability of the base station long-term energy storage system, and avoid battery damage caused by overcharging or over-discharging. For example, in charging mode, lowering the charging cut-off voltage can reduce the load of the line and avoid instability of the connection line due to excessive current or voltage; in discharging mode, increasing the discharge cut-off voltage can reduce the discharge current and avoid damage caused by line overload or over-discharging of the battery pack.

[0098] Step 250, in response to the base station long-term energy storage system not working properly, determine a warning instruction, and push the warning instruction to the user through the interaction unit.

[0099] In some embodiments, the main control unit can push the warning instruction to the user through the interactive unit. For example, the main control unit can display the warning information on the screen through a visual interface.

[0100] In some embodiments of this specification, when the workload of the base station long-term energy storage system meets the preset load condition, by determining and executing the power balancing strategy, the power of multiple energy storage modules is more evenly distributed, avoiding the interruption of work due to exhaustion of a certain energy storage module, so that the entire base station long-term energy storage system operates in a more efficient state. At the same time, when the power of multiple energy storage modules is close to balance, it can avoid the accelerated aging of a certain energy storage module due to long-term low power, which helps to maintain the health of the battery pack and prevent the performance degradation caused by aging of the battery pack. When the workload of the base station long-term energy storage system does not meet the preset load condition, the voltage information and temperature monitoring of the base station long-term energy storage system can be used to quickly detect potential abnormalities or faults, and dynamically adjust to reduce instability caused by excessive temperature or abnormal voltage, and through early warning instructions, users can timely detect abnormalities and reduce losses caused by faults.

[0101] It should be noted that the above description of the process 200 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the process under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0102] Figure 3 This is an exemplary schematic diagram of determining the power balancing strategy according to some embodiments of this specification.

[0103] In some embodiments, Figure 3 As shown, the main control unit is further configured to: determine the power balancing threshold 330 corresponding to each energy storage module based on the power information 310 and the usage time 320 of the battery group of each energy storage module; determine the power balancing strategy 350 based on the power balancing threshold 330 corresponding to each energy storage module, the connection relationship 340 between each energy storage module, and the power information 310 of each energy storage module.

[0104] In some embodiments, the slave control unit further includes a timer, and the slave control unit can determine the usage time of the battery pack in each energy storage module through the timer, and transmit the usage time to the master control unit through the network.

[0105] In some embodiments, the processor may determine the power balancing threshold corresponding to each energy storage module in a variety of ways based on the usage time and power information of the battery groups of each energy storage module. For example, the processor may calculate and determine the power balancing threshold of the current energy storage module based on the average power of all energy storage modules at the current moment, the average usage time of all battery groups, and the usage time of the battery groups of the energy storage modules at the current moment by the following formula (2).

[0106] Among them, Q thi It is represented as the power balancing threshold of energy storage module i, is the average power of all energy storage modules at the current moment, is the average usage time of all battery packs, t i is the usage time of the battery pack of energy storage module i.

[0107] In some embodiments, the power balancing threshold corresponding to each energy storage module is related to the line interruption risk of the energy storage module in the future.

[0108] In some embodiments, the processor may also determine the power balancing threshold corresponding to each energy storage module based on the risk of line interruption of the energy storage module in the future. Greater than the used time t i , the current energy storage module power balancing threshold is calculated and determined by the following formula (3):

[0109] For example, if the average time used is Less than the used time t i , the current energy storage module power balancing threshold is calculated and determined by the following formula (4):

[0110] Among them, R f Represents the risk of line interruption over a period of time in the future.

[0111] In some embodiments of this specification, if the average usage time of all battery packs is greater than the usage time of the current energy storage module, it means that the battery pack of the current energy storage module is relatively new; if the average usage time is less than the usage time, it means that the battery pack of the current energy storage module is relatively old and its performance is aged. By correlating the power balancing threshold with the risk of line interruption of the energy storage module in the future, the burden of new battery packs and aging battery packs can be balanced according to the usage time of different energy storage modules. For example, when determining the power balancing process later, a higher power balancing threshold can be determined by formula (3) to give full play to the performance of the new battery pack, while the performance of the aging battery is poor, and the lower power balancing threshold can be determined by formula (4) to reduce its burden.

[0112] In some embodiments, the power balancing threshold corresponding to each energy storage module is also related to the balancing loss.

[0113] Balancing loss refers to the energy loss of the energy storage module during the power balancing process. In some embodiments, the processor can determine the balancing loss of all energy storage modules based on the power balancing threshold of all energy storage modules and the power of all energy storage modules at the current moment.

[0114] For example, the processor may determine the balancing loss of all energy storage modules based on the power balancing threshold of the current energy storage module and the power of the current energy storage module at the current moment, for example, by calculating and determining the balancing loss using the following formula (5).

[0115] Where L is the balanced loss corresponding to n energy storage modules in the base station long-term energy storage system, Q thi is the power balancing threshold of energy storage module i obtained in formula (2), Q i is the power of energy storage module i at the current moment, and k2 is a preset constant.

[0116] In some embodiments, the processor may also determine the power balancing threshold corresponding to each energy storage module based on the balancing loss. For example, the processor calculates and determines the power balancing threshold based on the balancing loss by using the following formula (6).

[0117] The meanings of the symbols in the formulas can be found in the above formulas (2) and (5), and will not be repeated here.

[0118] In some embodiments of this specification, the power balancing process involves balancing loss, for example, transferring energy from a high-power module to a low-power module. Due to resistance, conduction efficiency, etc., this process inevitably causes energy loss. By introducing balancing loss, the power balancing threshold can be adjusted dynamically to avoid ignoring excessive adjustments caused by insufficient balancing due to energy loss during subsequent power balancing, thereby extending the life of the energy storage module and reducing maintenance and replacement costs.

[0119] In some embodiments, the processor can also determine the power balancing strategy by looping through the power of each energy storage module according to the power balancing threshold of all energy storage modules and the connection relationship between each energy storage module. For example, the processor replaces the power balancing value in the above-mentioned method of determining the power balancing strategy in this specification with the power balancing threshold corresponding to each energy storage module, and loops through the power of each energy storage module. At this time, the power balancing no longer needs to reach the balancing value. The power balancing strategy can be determined when the power of each energy storage module reaches the corresponding power balancing threshold. For more information on how to loop through and determine the power balancing strategy, please refer to Figure 2 and its description.

[0120] In some embodiments of the present specification, the power balancing threshold is dynamically adjusted by the usage time of the battery pack of the energy storage module. When the power balancing strategy is subsequently executed, a higher proportion of power can be allocated to the battery pack in better health (such as a new battery pack). The new battery pack can bear more loads and give full play to its high capacity, low internal resistance and high-efficiency charging and discharging capabilities, thereby avoiding the waste of power resources, and can also reduce the load of aging battery packs and extend their lifespan.

[0121] Figure 4 FIG. 1 is an exemplary flow chart of determining distributed inhalation parameters according to some embodiments of the present specification. Figure 4 As shown, the process 400 includes the following steps. In some embodiments, the process 400 can be executed by a processor in the main control unit.

[0122] In some embodiments, the base station long-term energy storage system is based on natural aspiration cooling; the base station long-term energy storage system also includes multiple air intake units, and the multiple air intake units are distributedly deployed at at least one energy storage module in the base station long-term energy storage system; the processor can determine the heat dissipation demand distribution in the future period based on the power information, voltage information, and temperature information of each energy storage module, and the heat dissipation demand distribution includes the required heat dissipation of at least one energy storage module; according to the heat dissipation demand distribution in the future period, the distributed air intake parameters are determined.

[0123] Step 410, based on the power information, voltage information, and temperature information of each energy storage module, determine the heat dissipation demand distribution for a period of time in the future, for example, the heat dissipation demand distribution for the next week or the next month after the current moment.

[0124] In some embodiments, determining the heat dissipation demand distribution for a period of time in the future based on the power, voltage, and temperature of each energy storage module also includes: the processor can determine the heat dissipation demand distribution for a period of time in the future through a second prediction model based on the power, voltage, temperature, and line interruption risk of each energy storage module. The second prediction model refers to a model for predicting the heat dissipation demand distribution for a period of time in the future.

[0125] In some embodiments, the second prediction model may be a machine learning model, such as a neural network (NN).

[0126] In some embodiments, the input of the second prediction model may include the power, voltage, temperature and line interruption risk of each energy storage module in the future; the output may include the heat dissipation demand distribution in the future. For more information about the power, voltage, temperature and line interruption risk of energy storage modules in the future, please refer to Figure 1 and related instructions.

[0127] In some embodiments, the input of the second prediction model also includes a power balancing strategy. For more information about the power balancing strategy, see Figure 2 and its description.

[0128] In some embodiments of the present specification, by using a trained second prediction model, the heat dissipation demand in the future can be quickly and accurately predicted, which is helpful for allocating appropriate air intake volume and air intake power to different energy storage modules in advance to avoid unnecessary power consumption.

[0129] Step 420, determining distributed air intake parameters according to the heat dissipation demand distribution in the future period of time.

[0130] In some embodiments, the distributed air intake parameters may include the air intake power and air intake volume of each air intake unit in the base station long-term energy storage system.

[0131] In some embodiments, the processor may determine the distributed air intake parameters based on the heat dissipation demand distribution in the future. For example, the processor may determine the distributed air intake parameters by querying a second preset table based on the heat dissipation demand distribution in the future. The second preset table may include a correspondence between the heat dissipation demand distribution and the air intake power and air intake volume of each air intake unit. The second preset table may be pre-constructed based on historical data or prior knowledge.

[0132] In some embodiments of the present specification, an air intake unit is introduced to directly dissipate heat from the energy storage module, and excess heat is taken away by air flow, and the distributed air intake parameters are adjusted separately according to the heat dissipation requirements of the energy storage module; if the distributed air intake parameters are directly corrected, the experiment needs to be repeated, which is not only cumbersome, but may also consume a lot of resources due to the lack of directionality in the parameter adjustment itself. By directly correcting the heat dissipation, the cumbersome experimental process can be avoided; by predicting the distribution of heat dissipation requirements in the future to determine the distributed air intake parameters, the heat dissipation requirements of each module in the future can be identified in advance, making the distributed air intake parameter settings of the air intake unit more accurate, avoiding overheating of the energy storage module due to insufficient heat dissipation, and improving the stability of the base station long-term energy storage system.

[0133] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0134] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0135] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0136] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0137] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0138] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0139] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A base station long-term energy storage system, characterized in that: It includes a main control unit, an interactive unit and multiple energy storage modules based on modular plug-in; The multiple energy storage modules are connected by cables, each of which is equipped with a battery pack, a conversion unit, a power sensor, a voltage sensor, a temperature sensor and a slave control unit, and the slave control unit is communicatively connected with the main control unit; the conversion unit controls the energy flow direction and energy flow specification of the energy storage module based on the conversion unit parameters, and the slave control unit obtains the power information, voltage information and temperature information of the energy storage module from the power sensor, the voltage sensor and the temperature sensor respectively; The main control unit is configured to perform the following operations when the workload of the base station long-term energy storage system meets a preset load condition: Obtaining power information of each of the energy storage modules from each of the slave control units; Determine and execute a power balancing strategy based on the connection relationship between the energy storage modules and the power information of the energy storage modules; The main control unit is configured to perform the following operations when the workload of the base station long-term energy storage system does not meet the preset load condition: Acquire voltage information and temperature information of each of the energy storage modules from each of the slave control units; Based on the voltage information, temperature information and the currently applied conversion unit parameters of each of the energy storage modules, determining whether the base station long-term energy storage system is working normally; In response to the base station long-term energy storage system not working properly, a warning instruction is determined, and the warning instruction is pushed to the user through the interaction unit.

2. The system according to claim 1, characterized in that The main control unit is further configured as: Determine the power balancing threshold corresponding to each of the energy storage modules based on the usage time and power information of the battery packs of each of the energy storage modules; The power balancing strategy is determined based on the power balancing threshold corresponding to each of the energy storage modules, the connection relationship between the energy storage modules, and the power information of each energy storage module.

3. The system according to claim 1, characterized in that The main control unit is further configured as: In response to the base station long-term energy storage system not working properly, acquiring a plurality of voltage information collected by a voltage sensor at a plurality of time points; Determining battery flow characteristics based on the plurality of voltage information and the currently applied conversion unit parameters; assessing a line interruption risk based on the battery flow characteristics; According to the line interruption risk, operating parameters of one or more target lines are adjusted; the target lines include charging lines and / or discharging lines.

4. The system according to claim 1, characterized in that The base station long-term energy storage system is based on natural aspiration cooling; The base station long-term energy storage system further comprises a plurality of air suction units, and the plurality of air suction units are distributedly deployed at at least one energy storage module in the base station long-term energy storage system; The main control unit is also configured as: Based on the power information, voltage information, and temperature information of each of the energy storage modules, determining a heat dissipation demand distribution for a period of time in the future, wherein the heat dissipation demand distribution includes the required heat dissipation of at least one energy storage module; Distributed air intake parameters are determined according to the heat dissipation demand distribution in the future period of time.

5. A long-term energy storage method for a base station, the method is implemented based on a long-term energy storage system for a base station, the long-term energy storage system for a base station comprises a main control unit, an interactive unit and a plurality of energy storage modules based on modular plug-in; the plurality of energy storage modules are connected by cables, each energy storage module is equipped with a battery pack, a conversion unit, a power sensor, a voltage sensor, a temperature sensor and a slave control unit, and the slave control unit is communicatively connected with the main control unit; the conversion unit controls the energy flow direction and energy flow specification of the energy storage module based on conversion unit parameters, and the slave control unit obtains the power information, voltage information and temperature information of the energy storage module from the power sensor, the voltage sensor and the temperature sensor respectively; The method is performed by the main control unit, and includes: When the workload of the base station long-term energy storage system meets the preset load condition: obtaining the power information of each of the energy storage modules from each of the slave control units; Determine and execute a power balancing strategy based on the connection relationship between the energy storage modules and the power information of the energy storage modules; When the workload of the base station long-term energy storage system does not meet the preset load condition: Acquire voltage information and temperature information of each of the energy storage modules from each of the slave control units; Based on the voltage information, temperature information and the currently applied conversion unit parameters of each of the energy storage modules, determining whether the base station long-term energy storage system is working normally; In response to the base station long-term energy storage system not working properly, a warning instruction is determined, and the warning instruction is pushed to the user through the interaction unit.

6. The method according to claim 5, characterized in that Determining the power balancing strategy according to the connection relationship between the energy storage modules and the power information of the energy storage modules includes: Determine the power balancing threshold corresponding to each of the energy storage modules based on the usage time and power information of the battery packs of each of the energy storage modules; The power balancing strategy is determined based on the power balancing threshold corresponding to each of the energy storage modules, the connection relationship between the energy storage modules, and the power information of each energy storage module.

7. The method according to claim 5, characterized in that The method further comprises: In response to the base station long-term energy storage system not working properly, acquiring a plurality of voltage information collected by the voltage sensor at a plurality of time points; Determining battery flow characteristics based on the plurality of voltage information and the currently applied conversion unit parameters; assessing a line interruption risk based on the battery flow characteristics; According to the line interruption risk, operating parameters of one or more target lines are adjusted; the target lines include charging lines and / or discharging lines.

8. The method according to claim 5, characterized in that The base station long-term energy storage system is based on natural aspiration cooling; The base station long-term energy storage system further comprises a plurality of air suction units, and the plurality of air suction units are distributedly deployed at at least one energy storage module in the base station long-term energy storage system; The method further comprises: Based on the power information, voltage information, and temperature information of each of the energy storage modules, determining a heat dissipation demand distribution for a period of time in the future, wherein the heat dissipation demand distribution includes the required heat dissipation of at least one energy storage module; Distributed air intake parameters are determined according to the heat dissipation demand distribution in the future period of time.

9. A base station long-term energy storage device, characterized in that: The apparatus comprises at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is configured to execute at least part of the computer instructions to implement the method according to any one of claims 5 to 8.

10. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the method according to any one of claims 5 to 8.

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