Battery power supply capability evaluation method and system for backup integrated uninterruptible power supply

Abstract

The application provides a battery power supply capacity evaluation method and system for a backup integrated uninterruptible power supply. The method comprises: obtaining and saving battery parameters at a current sampling time; in response to a power supply request of a power grid, obtaining and saving a health state, a state of charge and an energy state of the battery at the current sampling time according to the battery parameters at the current and previous sampling times and the health state, the state of charge and the energy state of the battery at the previous sampling time, and obtaining available energy of the battery at the current sampling time according to the health state, the state of charge and the energy state; starting from the current sampling time, tracing back for a preset time length, extracting the battery parameters and the health state of the battery at each sampling time within the tracing back time length, determining the response capacity of the battery within the tracing back time length based on the battery parameters and the health state, and determining the power supply capacity of the battery to the power grid based on the available energy at the current sampling time and / or the response capacity within the tracing back time length. The application can more accurately evaluate the power supply capacity of the battery.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method and system for evaluating the battery power supply capacity of an integrated backup and storage uninterruptible power supply. Background Technology

[0002] With the rapid development of artificial intelligence technology, the demand for computing power across various industries is experiencing explosive growth. Data centers, as the core infrastructure for computing power, are expanding rapidly. Among these, uninterruptible power supplies (UPS) systems, which integrate backup and storage, are receiving widespread attention as key equipment for ensuring the reliability of power supply to data centers. The batteries in UPS systems need to have fast response capabilities. On the one hand, they can be used to provide backup power for applications such as data centers to ensure the stable operation of the load. On the other hand, they can also be used for daily energy storage and to assist the power grid in peak shaving and valley filling, thus achieving interaction with the power grid. The battery types for such UPS systems include, but are not limited to, lithium-ion batteries, sodium-ion batteries, lithium metal batteries, semi-solid-state batteries, and solid-state batteries.

[0003] In actual operation, the state changes of such batteries are more complex due to the influence of various factors such as current and temperature. Existing battery management systems typically assess a battery's ability to interact with the grid based on its state of charge, lacking monitoring of the battery's dynamic characteristics. This results in insufficient accuracy in assessing the battery's operating state under actual operating conditions, especially when the integrated backup and storage uninterruptible power supply (UPS) system participates in grid interaction. Such inaccurate state assessment directly affects the system's power supply capacity to the grid, and in severe cases, may even jeopardize the safety of the entire integrated backup and storage UPS system. Therefore, there is a need to provide a method and system for assessing the battery power supply capacity of an integrated backup and storage UPS. Summary of the Invention

[0004] This invention provides a method and system for evaluating the battery power supply capability of an integrated backup and storage uninterruptible power supply, which improves the problem of inaccurate evaluation results caused by using only the state of charge of the battery to evaluate the performance of the integrated backup and storage uninterruptible power supply system.

[0005] This invention provides a battery performance evaluation method for an integrated backup and storage uninterruptible power supply. The method includes: acquiring and storing battery parameters at the current sampling time; responding to a power supply request from the power grid, obtaining and storing the battery's health state, state of charge, and state of energy at the current sampling time based on the battery parameters at the current and previous sampling times, as well as the battery's health state, state of charge, and state of energy at the previous sampling time, and thereby obtaining the battery's available energy at the current sampling time; starting from the current sampling time, backtracking for a preset time length, extracting the battery parameters and health state at each sampling time within the backtracking time, and determining the battery's response capability within the backtracking time based on each battery parameter and health state; and determining the battery's ability to supply power to the power grid based on the available energy at the current sampling time and / or the response capability within the backtracking time.

[0006] In one embodiment of the present invention, battery parameters include measured temperature, measured current, and measured terminal voltage. Based on the battery parameters at the current and previous sampling times, and the battery's health state, state of charge, and state of energy at the previous sampling time, the battery's health state, state of charge, and state of energy at the current sampling time are obtained and stored, and the battery's usable energy at the current sampling time is obtained accordingly. This includes: inputting the measured temperature, measured current, and measured terminal voltage at the current sampling time, and the battery's state of charge, health state, and state of energy at the previous sampling time, into a state transition model to obtain predicted values ​​for the battery's state of charge, health state, and state of energy at the current sampling time; based on The battery internal resistance at the current sampling time is determined based on the predicted health state and measured temperature. The predicted terminal voltage at the current sampling time is determined based on the battery internal resistance, measured current, and pre-acquired open-circuit voltage. The Kalman gain is calculated based on the prediction error between the predicted and measured terminal voltages. The predicted state of charge, health state, and state of energy at the current sampling time are corrected based on the Kalman gain to obtain and save the corrected state of charge, health state, and state of energy. The available energy of the battery at the current sampling time is calculated based on the corrected state of health and state of energy.

[0007] In one embodiment of the present invention, the battery internal resistance at the current sampling time is: Among them, R current,t Let T be the battery internal resistance at the current sampling time t, and k be a preset resistance correction coefficient. t R is the measured temperature at the current sampling time t. rated R is the rated internal resistance of the battery. e This is the battery's internal resistance at the termination point. This is the predicted health status value at the current sampling time t.

[0008] In one embodiment of the present invention, the available energy at the current sampling time is E. available,t =x 2,t ·x 3,t ·C rated ·η, where x 2,t and x 3,t C represents the health state and energy state of the battery at the current sampling time t, respectively. rated Where η is the rated capacity of the battery, η is the preset charge / discharge efficiency of the inverter, and E is the rated capacity of the battery. available,t This represents the available energy at the current sampling time t.

[0009] In one embodiment of the present invention, the battery parameters include measured temperature, measured current, and measured terminal voltage. Starting from the current sampling time, a preset time length is traced back to extract the battery parameters and health status at each sampling time within the traceback time. Based on each battery parameter and health status, the battery's response capability within the traceback time is determined, including: starting from the current sampling time, a preset time length is traced back to extract the measured terminal voltage and health status at each sampling time within the traceback time, and selecting the maximum and minimum measured terminal voltages within the traceback time; based on the health status at each sampling time within the traceback time, the average health status of the battery within the traceback time is calculated; based on the maximum measured terminal voltage, minimum measured terminal voltage, average health status, and the battery internal resistance at the current sampling time, the battery's response capability within the traceback time is calculated.

[0010] In one embodiment of the present invention, the battery's response capability during the retracing period is: Among them, P grid (t-Δt,t) represents the battery's response capability within a backtracking time Δt, starting from the current sampling time t. oc V is the pre-acquired open-circuit voltage. max V min These represent the maximum and minimum measured terminal voltages within the traceback period, R. current Let SOH be the battery internal resistance at the current sampling time. ave This represents the average health status over the backtracking period.

[0011] In one embodiment of the present invention, determining the battery's ability to supply power to the grid based on the available energy at the current sampling time includes: determining whether the available capacity at the current sampling time is greater than or equal to a preset energy threshold; if so, determining that the battery can supply power to the grid according to the power supply request; otherwise, determining that the battery cannot supply power to the grid according to the power supply request.

[0012] In one embodiment of the present invention, determining the battery's ability to supply power to the grid based on the available energy at the current sampling time and the response capability within the backtracking time further includes: determining whether the available capacity at the current sampling time is greater than or equal to a preset energy threshold; if so, determining whether the response capability within the backtracking time is greater than or equal to a preset capability threshold, and if the response capability within the backtracking time is greater than or equal to the capability threshold, determining that the battery can supply power to the grid according to the power supply request; otherwise, determining that the battery cannot supply power to the grid according to the power supply request.

[0013] In one embodiment of the present invention, the evaluation method further includes: inputting the available energy of the battery at a preset number of historical sampling times into a pre-trained available energy prediction model to obtain the available energy prediction value of the battery at multiple future sampling times; wherein, the available energy prediction model is a time-series prediction model; and determining the battery's ability to supply power to the power grid based on the available energy prediction value.

[0014] This invention also provides a battery power supply capability assessment system for an integrated backup and storage uninterruptible power supply. The system includes: a battery parameter acquisition module for acquiring and storing battery parameters at the current sampling time; an available energy determination module for responding to a power supply request from the power grid, obtaining and storing the battery's health state, state of charge, and energy state at the current sampling time based on the battery parameters at the current and previous sampling times, as well as the battery's health state, state of charge, and state of energy at the previous sampling time, and thereby obtaining the battery's available energy at the current sampling time; a response capability determination module for extracting battery parameters and health states at each sampling time within the backtracking time, starting from the current sampling time, and determining the battery's response capability within the backtracking time based on each battery parameter and health state; and an assessment module for determining the battery's ability to supply power to the power grid based on the available energy at the current sampling time and / or the response capability within the backtracking time.

[0015] The present invention also provides an electronic device, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device enables the battery power supply capability assessment method of the integrated backup and storage uninterruptible power supply as described above.

[0016] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer processor, causes the computer to perform any of the above-mentioned methods for evaluating the battery power supply capability of an integrated backup and storage uninterruptible power supply.

[0017] The beneficial effects of this invention are as follows: This invention proposes a method and system for evaluating the battery power supply capacity of an integrated backup and storage uninterruptible power supply. After acquiring the battery parameters at the current sampling time, it combines the battery's health status, state of charge, and state of energy at the previous sampling time to dynamically estimate the battery's state value at the current sampling time and further calculate the available energy. Furthermore, by reviewing historical sampling data, it analyzes the fluctuations in battery parameters and changes in the battery's health status during the review period, thereby determining the battery's response capability during the review period. The integrated backup and storage uninterruptible power supply system can determine whether a battery has the ability to supply power to the grid based on the battery's available energy at the current sampling time and / or its response capability during the review period. Through this multi-faceted evaluation method, the battery's power supply capacity can be evaluated more accurately. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0019] In the attached diagram:

[0020] Figure 1 This is a flowchart illustrating a method for evaluating the battery power supply capability of an integrated backup and storage uninterruptible power supply according to an embodiment of the present invention.

[0021] Figure 2 This is a structural block diagram of a battery power supply capability evaluation system for an integrated backup and storage uninterruptible power supply provided in one embodiment of the present invention.

[0022] Figure 3 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. Detailed Implementation

[0023] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0024] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0025] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0026] The inventors discovered that with the rapid development of artificial intelligence technology, the demand for computing power across various industries is experiencing explosive growth, and data centers, as the core infrastructure for computing power, are expanding rapidly. Uninterruptible power supply (UPS) systems, as key equipment for ensuring the reliability of power supply to data centers, have received widespread attention. Early data center UPS systems mostly used relatively low-cost lead-acid or nickel-cadmium batteries as energy storage units. However, with the continuous expansion of data center scale and the increasing demands for power supply stability, how to tap the energy storage potential of data center UPS systems and achieve coordinated operation with the power grid has become a focus of academic and industrial attention. Against this backdrop, data centers have begun to gradually adopt integrated backup and storage UPS systems. The batteries in this system need to have fast response capabilities, serving both as backup power for their application scenarios (such as data centers) to ensure stable load operation, and as daily energy storage, assisting the power grid in peak shaving and valley filling to achieve interaction with the grid. These batteries include, but are not limited to, lithium-ion batteries, sodium-ion batteries, lithium metal batteries, semi-solid-state batteries, and solid-state batteries. Among them, lithium-ion batteries include, but are not limited to, lithium iron phosphate batteries, ternary lithium batteries, and lithium titanate batteries.

[0027] Due to the different performance characteristics of the various battery types mentioned above, lithium-ion batteries will be used as an example for explanation purposes. Lithium-ion batteries are widely used in integrated backup and storage uninterruptible power supply (UPS) systems due to their high energy density, long cycle life, fast charge and discharge speeds, and deep discharge capability, thereby improving the overall energy storage capacity and power supply performance of the system. However, research on battery management for such integrated backup and storage UPS systems is limited. Establishing an effective battery management system to ensure the reliability and safety of the integrated backup and storage UPS system is an urgent problem to be solved.

[0028] To address the above issues, this invention provides a method for evaluating the battery power supply capacity of an integrated backup and storage uninterruptible power supply (UPS). After acquiring the battery parameters at the current sampling time, the method combines the State of Health (SOH), State of Charge (SOC), and State of Energy (SOE) from the previous sampling time to dynamically estimate the battery's state value at the current sampling time and further calculate the battery's available energy at the current sampling time. Furthermore, by reviewing historical sampling data, the method analyzes the fluctuations in battery parameters and changes in the battery's health state over the review period, thereby determining the battery's response capability within the review period. The integrated backup and storage UPS system can determine whether a battery has the ability to supply power to the grid based on the battery's available energy at the current sampling time and / or its response capability over the review period. This multi-faceted evaluation method allows for a more accurate assessment of the battery's power supply capacity.

[0029] It should be noted that the application scenarios of the battery power supply capability assessment method of the present invention include, but are not limited to, data centers, medical institutions or financial systems. The present invention can be applied to any scenario with high requirements for power supply reliability, and is not limited here.

[0030] like Figure 1 As shown, the method for evaluating the battery power supply capability of an integrated backup and storage uninterruptible power supply includes the following steps:

[0031] S11. Obtain and save the battery parameters at the current sampling time.

[0032] In an integrated uninterruptible power supply (UPS) system, the battery, as the primary power supply unit, is responsible for providing power to the grid. Therefore, the battery's operating status has a significant impact on the overall reliability of the UPS system. To quickly and accurately assess the battery's power supply capacity to the grid, its operating status needs continuous monitoring and real-time analysis. At each sampling moment, battery parameters are collected by sensors. These parameters characterize the battery's operating status at the current sampling moment and include, but are not limited to, battery temperature, battery terminal voltage, and battery current. It should be noted that the battery type described in this application is not limited to lithium-ion batteries; it can also include sodium-ion batteries, semi-solid-state batteries, and all-solid-state batteries, as well as other energy storage components with high energy density and good dynamic response capabilities. Any battery unit capable of providing a stable power output to the grid is acceptable and is not limited here.

[0033] S12. In response to the power supply request from the power grid, based on the battery parameters at the current and previous sampling times, as well as the battery's health state, state of charge, and state of energy at the previous sampling time, obtain and save the battery's health state, state of charge, and state of energy at the current sampling time, and thereby obtain the battery's available energy at the current sampling time.

[0034] Upon receiving a power supply request from the power grid, the integrated backup and storage uninterruptible power supply (UPS) system uses battery parameters acquired at the current sampling time, along with the stored battery health, state of charge (SOC), and state of energy (SGE) from the previous sampling time. This data is input into a state estimation model, where state transition equations are used to predict the state. The predicted state value is then corrected using the battery parameters at the current sampling time, resulting in the battery's health, SOC, and SGE at the current sampling time. Based on the health and SGE, the available energy of the battery at the current sampling time is determined. Available energy characterizes the maximum energy that can be released while ensuring safe battery operation.

[0035] Optionally, in one embodiment of the present invention, the battery parameters include measured temperature, measured current, and measured terminal voltage, and step S12 includes the following process:

[0036] S121. Input the measured temperature, measured current, and measured terminal voltage at the previous sampling time, as well as the battery's state of charge, state of health, and state of energy at the previous sampling time, into the state transition model to obtain the predicted values ​​of the battery's state of charge, state of health, and state of energy at the current sampling time.

[0037] In response to the power grid's power supply request, to accurately assess the battery's operating state at the current sampling time, a state transition model is used to predict the battery's state of charge, state of health, and state of energy. Specifically, the measured temperature, measured terminal voltage, and measured terminal voltage at the previous sampling time t are input into the state transition model along with the state variables from the previous sampling time. Formulas (1) to (3) are used to obtain the predicted values ​​of the state of charge, state of health, and state of energy at the current sampling time:

[0038]

[0039] in, x is the predicted state of charge at the current sampling time t. 1,t-1 For the state of charge at the previous sampling time t-1, I t-1 C is the measured current at the previous sampling time. rated Δt is the rated capacity of the battery, e1 is the sampling interval, and e1 is the process noise, which is used to represent random disturbances that are not accurately described by the model during the state transition process.

[0040]

[0041] in, x is the predicted health status value at the current sampling time t. 2,t-1 E represents the health status at the previous sampling time t-1. a The activation energy is preset, R = 8.314 J / (mol·T), and the gas constant is preset, T t-1 e1 represents the measured temperature at the previous sampling time t-1, T0 represents the preset reference temperature (usually T0 = 25℃ to represent room temperature), and e2 represents the process noise, which is used to represent random disturbances that the model does not accurately describe during the state transition process.

[0042]

[0043] in, x is the predicted energy state value at the current sampling time t. 3,t-1 V represents the energy state at the previous sampling time t-1. ave e3 is the open-circuit voltage of the battery, ensuring the battery's potential under no current load. e3 is the process noise, used to represent random disturbances that the model does not accurately describe during state transitions.

[0044] S122. Based on the predicted health status and measured temperature at the current sampling time, determine the battery internal resistance at the current sampling time.

[0045] Since the battery internal resistance is a key factor in measuring the battery's ability to respond to current, and it is affected by the battery's health status and temperature, the battery internal resistance at the current sampling time can be calculated based on the predicted health status and the measured temperature at the current sampling time, as shown in formula (4):

[0046]

[0047] Among them, R current,t Let T be the battery internal resistance at the current sampling time t, and k be a preset resistance correction coefficient. t R is the measured temperature at the current sampling time t. rated R is the rated internal resistance of the battery. e The internal resistance of the battery is the termination resistance, typically R. rated twice as much, This is the predicted health status value at the current sampling time t.

[0048] S123. Based on the battery internal resistance, measured current and pre-acquired open-circuit voltage at the current sampling time, determine the predicted terminal voltage at the current sampling time.

[0049] After calculating the battery internal resistance based on the predicted health status and the measured temperature at the current sampling time, the predicted terminal voltage at the current sampling time can be deduced from the observation equation of the terminal voltage based on the battery's equivalent circuit model, as shown in formula (5):

[0050]

[0051] in, I is the predicted terminal voltage at the current sampling time t. t This represents the measured current at the current sampling time t.

[0052] S124. Calculate the Kalman gain based on the prediction error between the predicted terminal voltage and the measured terminal voltage at the current sampling time.

[0053] Kalman filtering is used to correct the predicted states obtained at the current sampling time t, thereby improving the accuracy of the predicted states. Specifically, the predicted terminal voltage at the current sampling time t is calculated. and measured terminal voltage z t The prediction error is calculated, and the Kalman gain at the current sampling time is obtained by using the predicted state covariance and the observation noise covariance. The predicted state covariance is derived from the covariance of the previous sampling time through the state transition equation and the process noise covariance, while the observation noise covariance is preset based on the prediction error of the terminal voltage. The specific Kalman filtering method is existing technology and will not be detailed here.

[0054] S125. Based on the Kalman gain, the predicted values ​​of the state of charge, health, and energy at the current sampling time are corrected to obtain the corrected state of charge, health, and energy at the current sampling time and are saved.

[0055] After calculating the Kalman gain at the current sampling moment, it is weighted and fused with the prediction error of the terminal voltage. Based on this, the previously obtained predicted values ​​of state of charge, state of health, and state of energy are corrected to obtain the corrected state at the current sampling moment. Specifically, as shown in formula (6):

[0056]

[0057] Where i∈{1,2,3}, they correspond to the battery's state of charge, state of health, and state of energy, respectively, and x i,t The corrected state values ​​at the current sampling time t (including state of charge, health state, and energy state). The predicted value for the current sampling time t is obtained through formulas (1) to (3) above, K t Let z be the Kalman gain at the current sampling time t. tThis represents the measured terminal voltage at the current sampling time t. The corrected state of charge, state of health, and state of energy are used for subsequent calculations of available energy and response capability to assess the battery's power supply capacity.

[0058] S126. Based on the corrected health state and energy state at the current sampling time, calculate the available energy of the battery at the current sampling time.

[0059] Based on the battery's corrected health state and energy state at the current sampling time t, the available energy E of the battery at the current sampling time t can be calculated using formula (7). available,t :

[0060] E available,t =x 2,t ·x 3,t ·C rated ·η (7)

[0061] Where, x 2,t and x 3,t The health state and energy state of the battery at the current sampling time t are respectively obtained by formula (6) above, where η is the preset charge / discharge efficiency of the inverter, and E available,t This represents the available energy at the current sampling time t.

[0062] S13. Starting from the current sampling time, backtrack for a preset time length, extract the battery parameters and health status of the battery at each sampling time within the backtracking time, and determine the battery's response capability within the backtracking time based on each battery parameter and health status.

[0063] Starting from the current sampling time t, a preset time length is traced back, and the battery parameters and corresponding health status at each pre-stored sampling time within this traceback period are extracted. These battery parameters include, but are not limited to, the measured temperature, measured current, and measured terminal voltage of the battery. By analyzing these historical battery parameters, the range of battery parameter variations can be determined. By analyzing the changes in historical health status, the overall health level of the battery during this period can be determined. Response capability characterizes the maximum instantaneous power the battery can provide in the current state. It is used to determine the battery's response speed and strength to dynamic events such as grid frequency fluctuations and voltage drops. Generally, a higher response capability indicates that the battery can provide support faster.

[0064] In an optional embodiment of the present invention, the battery parameters include measured temperature, measured current, and measured terminal voltage, and step S13 includes the following process:

[0065] Starting from the current sampling time, the system traces back a preset time length to extract the measured terminal voltage and health status of the battery at each sampling time within the traceback period. The system then selects the maximum and minimum measured terminal voltages within the traceback period. Based on the health status at each sampling time within the traceback period, the system calculates the average health status of the battery within the traceback period. Finally, based on the maximum measured terminal voltage, minimum measured terminal voltage, average health status, and the battery's internal resistance at the current sampling time, the system calculates the battery's response capability within the traceback period.

[0066] Specifically, starting from the current sampling time t, a preset time length (e.g., 10 minutes) is traced back, and the measured terminal voltage and health status at each sampling time within this traceback period are extracted. By comparing all the extracted measured terminal voltages, the maximum and minimum measured terminal voltages are selected to accurately characterize the voltage fluctuation range. The average of all health statuses within this traceback period is then taken, and the resulting average health status reflects the overall performance status of the battery within the traceback period. After obtaining the maximum measured terminal voltage, the minimum measured terminal voltage, and the average health status, the battery internal resistance at the current sampling time t is obtained using the above formula (6). Using the battery equivalent circuit model, the battery's response capability within the traceback period can be calculated using formula (8):

[0067]

[0068] Among them, P grid (t-Δt,t) represents the battery's response capability within a backtracking time Δt, starting from the current sampling time t. oc V is the pre-acquired open-circuit voltage. max V min These represent the maximum and minimum measured terminal voltages within the traceback period, R. current,t Let SOH be the battery internal resistance at the current sampling time. ave To measure the average health status over the backtracking period, for and The smaller value.

[0069] S14. Determine the battery's ability to supply power to the grid based on the available energy at the current sampling time and / or the response capability during the backtracking period.

[0070] In an optional embodiment of the present invention, step S14 includes the following process:

[0071] Determine whether the available capacity at the current sampling time is greater than or equal to the preset energy threshold: if yes, determine that the battery can supply power to the grid according to the power supply request; otherwise, determine that the battery cannot supply power to the grid according to the power supply request.

[0072] Specifically, the integrated backup and storage uninterruptible power supply system calculates the available energy E of the battery at the current sampling time t. available,t Then, it is compared with a preset energy threshold to determine whether the battery has the ability to provide reverse power to the grid. The energy threshold E is... threshold The calculation method is shown in formula (9):

[0073] E threshold =E demand (t)+SOE min ·C rated ·V rated (9)

[0074] Among them, E demand (t) represents the energy required by the power grid at the current sampling time t, SOE min The minimum energy threshold preset for the battery, V rated This refers to the battery's rated voltage. When the available energy E... available,t Greater than or equal to the energy threshold E threshold A reading of 'full' indicates that the battery has sufficient energy and the ability to provide reverse power to the grid according to its power supply requests. Conversely, a reading of 'low' indicates that the battery's current energy is too low to meet power supply demands and is unsuitable for power supply tasks.

[0075] In an optional embodiment of the present invention, step S14 further includes the following process:

[0076] Determine whether the available capacity at the current sampling time is greater than or equal to the preset energy threshold. If so, determine whether the response capability within the backtracking time is greater than or equal to the preset capability threshold. If the response capability within the backtracking time is greater than or equal to the capability threshold, determine that the battery can supply power to the grid according to the power supply request. Otherwise, determine that the battery cannot supply power to the grid according to the power supply request.

[0077] In practical operation, although batteries have sufficient energy to supply power to the grid, they may not be able to meet the grid's high-power demand in a short period when faced with grid frequency fluctuations or voltage disturbances. This results in an inability to provide the required energy to the grid on demand, affecting the stability of the power supply. To improve this situation, this embodiment also combines the battery's available capacity at the current sampling time with its response capability during the backtracking period to jointly determine the battery's power supply capability. Specifically, when the battery's available energy at the current sampling time is greater than or equal to an energy threshold, it further determines whether the response capability during the backtracking period is greater than or equal to the capability threshold. If this condition is met, it indicates that the battery at the current sampling time not only has sufficient energy reserves but can also quickly respond to the grid's power supply request, meeting the grid's high-power demand in a short period. Therefore, the current battery has the capability to provide reverse power to the grid. Conversely, if the battery's response capability during the backtracking period is less than the capability threshold, or if the available energy at the current sampling time is less than the energy threshold, it indicates that the battery cannot provide reverse power to the grid. This joint determination mechanism of available energy and response capability further improves the accuracy of the battery's power supply capability assessment.

[0078] In an optional embodiment of the present invention, the evaluation method further includes the following process: inputting the available energy of the battery at a preset number of historical sampling times into a pre-trained available energy prediction model to obtain the available energy prediction value of the battery at multiple future sampling times; wherein, the available energy prediction model is a time-series prediction model; and determining the battery's ability to supply power to the grid based on the available energy prediction value.

[0079] To assess the future power supply capacity of batteries and improve the response efficiency of integrated backup and storage uninterruptible power supply systems (UPS) in interaction with the power grid, this invention can input the available energy from multiple historical sampling moments (e.g., the past 20 minutes) into a pre-trained available energy prediction model. By extracting the changing characteristics of these historical available energy values, predicted available energy values ​​for multiple future sampling moments are obtained. This allows for proactive response judgments when receiving power supply requests from the power grid in the future, significantly improving response speed and accuracy. The available energy prediction model is a time-series prediction model, which includes, but is not limited to, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), or Transformer-based models. Any model with time-series data processing capabilities and capable of multi-step prediction is acceptable and is not limited here.

[0080] It should be noted that the present invention can also obtain the battery's available energy and corresponding response capability at a preset number of historical sampling times by inputting them into a pre-trained prediction model, thereby obtaining the battery's predicted available energy and corresponding response capability at multiple future sampling times, and determining the battery's ability to supply power to the grid accordingly. The prediction model is a time-series prediction model, which includes, but is not limited to, long short-term memory networks, gated recurrent units, or models based on the Transformer architecture; any model with time-series data processing capabilities and capable of multi-step prediction is acceptable and is not limited here.

[0081] Furthermore, in an integrated backup and storage uninterruptible power supply (UPS) system, when the battery is used as backup power for applications such as data centers, it does not participate in the grid's power supply tasks, thus making it impossible to monitor changes in its health status in a timely manner. To address this issue, this invention also obtains the battery temperature and measured internal resistance of the integrated backup and storage UPS at the current sampling time; based on the battery temperature at the current sampling time and a preset reference temperature, the measured internal resistance is temperature-corrected to obtain the corrected internal resistance of the battery at the current sampling time; based on the corrected internal resistance, the battery's rated internal resistance, and a preset termination internal resistance, the battery's health status at the current sampling time is obtained.

[0082] Specifically, an AC signal of a fixed frequency (e.g., 1kHz) is applied to the battery every preset time interval (e.g., 12 hours) and sampled. The measured internal resistance of the battery is calculated by collecting the voltage response at the current sampling time, and the internal resistance is corrected by the measured temperature at the current sampling time to obtain the corrected internal resistance, as shown in formula (10):

[0083] R current =R measure ·exp[k(T t -T0)](10)

[0084] Among them, R current To correct the internal resistance, R measure To measure the internal resistance, T t Let T0 be the measured temperature at the current sampling time t, T0 be the preset reference temperature (e.g., 25℃), and k be the temperature coefficient (generally 0.0039). Based on the corrected internal resistance, the health status at the current sampling time is calculated according to formula (11) using the battery's rated internal resistance and termination internal resistance:

[0085]

[0086] Where SOH represents the battery's health status at the current sampling moment, and R init R is the rated internal resistance of the battery. endTo terminate the internal resistance, it is typically twice the rated internal resistance. This method allows for regular monitoring of the battery's health; when the state of harmonic equilibrium (SOH) is low, a timely warning and reminder to replace the battery will be provided.

[0087] like Figure 2 As shown, the battery power supply capability assessment system 200 of the integrated backup and storage uninterruptible power supply includes: a battery parameter acquisition module 210, an available energy determination module 220, a response capability determination module 230, and an assessment module 240. The battery parameter acquisition module 210 acquires and stores the battery parameters at the current sampling time. The available energy determination module 220, in response to a power supply request from the grid, obtains and stores the battery's health state, state of charge, and energy state at the current sampling time based on the battery parameters at the current and previous sampling times, as well as the battery's health state, state of charge, and state of energy at the previous sampling time, and thereby determines the battery's available energy at the current sampling time. The response capability determination module 230, starting from the current sampling time, traces back a preset time length, extracts the battery parameters and health state at each sampling time within the traceback time, and determines the battery's response capability within the traceback time based on each battery parameter and health state. The assessment module 240 determines the battery's ability to supply power to the grid based on the available energy at the current sampling time and / or the response capability within the traceback time.

[0088] Specific limitations regarding the battery power supply capability assessment system for integrated backup and storage uninterruptible power supplies (UPS) can be found in the limitations on the battery power supply capability assessment method for integrated backup and storage UPS mentioned above, and will not be repeated here. Each module in the aforementioned battery power supply capability assessment system for integrated backup and storage UPS can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware format or independent of the processor, or stored in the memory of a computer device in software format, so that the processor can call the corresponding operations of each module.

[0089] It should be noted that, in order to highlight the innovative aspects of this invention, this embodiment does not include modules that are not closely related to solving the technical problems proposed by this invention, but this does not mean that there are no other modules in this embodiment.

[0090] like Figure 3 As shown, the electronic device 3 may include a memory 31, a processor 32 and a bus, and may also include a computer program stored in the memory 31 and that can run on the processor 32, such as a battery power supply capability assessment program for an integrated backup and storage uninterruptible power supply.

[0091] The memory 31 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 31 can be an internal storage unit of the electronic device 3, such as a portable hard drive. In other embodiments, the memory 31 can be an external storage device of the electronic device 3, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 3. Furthermore, the memory 31 can include both internal and external storage units of the electronic device 3. The memory 31 can be used not only to store application software and various types of data installed on the electronic device 3, such as code for evaluating the battery power supply capability of an integrated uninterruptible power supply, but also to temporarily store data that has been output or will be output.

[0092] In some embodiments, the processor 32 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 32 is the control unit of the electronic device 3, connecting various components of the entire electronic device 3 via various interfaces and lines. It executes programs or modules stored in the memory 31 (e.g., a battery power supply capability assessment program for an integrated uninterruptible power supply), and calls data stored in the memory 31 to perform various functions and process data in the electronic device 3.

[0093] The processor 32 executes the operating system of the electronic device 3 and various installed applications. The processor 32 executes the applications to implement the steps in the above-described method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply.

[0094] For example, a computer program may be divided into one or more modules, one or more of which are stored in memory 31 and executed by processor 32 to complete this application. One or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in electronic device 3. For example, the computer program may be divided into a battery parameter acquisition module 210, an available energy determination module 220, a response capability determination module 230, and an evaluation module 240.

[0095] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium, which can be non-volatile or volatile. The software functional module stored in the storage medium includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute some functions of the battery power supply capability evaluation method of the integrated backup and storage uninterruptible power supply according to various embodiments of this application.

[0096] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for evaluating the battery power supply capability of an integrated backup and storage uninterruptible power supply, characterized in that, The method includes: Get and save the battery parameters at the current sampling time; In response to the power supply request from the power grid, based on the battery parameters at the current and previous sampling times, as well as the battery's health state, state of charge, and state of energy at the previous sampling time, the battery's health state, state of charge, and state of energy at the current sampling time are obtained and saved, and the battery's available energy at the current sampling time is obtained accordingly. Starting from the current sampling time, backtrack for a preset time length to extract the battery parameters and health status of the battery at each sampling time within the backtracking time. Based on each battery parameter and health status, determine the battery's response capability within the backtracking time. The battery's ability to supply power to the grid is determined based on the available energy at the current sampling time and / or the response capability within the backtracking time. The battery parameters include measured temperature, measured current, and measured terminal voltage. Starting from the current sampling time, the process involves backtracking for a preset time length to extract the battery parameters and health status at each sampling time within the backtracking period. Based on these parameters and health status, the battery's response capability within the backtracking period is determined, including: Starting from the current sampling time, backtrack for a preset time length, extract the measured terminal voltage and health status of the battery at each sampling time within the backtracking time, and filter out the maximum and minimum measured terminal voltage within the backtracking time. Based on the health status at each sampling moment within the backtracking period, calculate the average health status of the battery within the backtracking period; Based on the maximum measured terminal voltage, the minimum measured terminal voltage, the average health state value, and the battery internal resistance at the current sampling time, the response capability of the battery within the backtracking time is calculated. Wherein, the response capability of the battery during the backtracking time is Among them, P grid (t-Δt,t) represents the battery's response capability within a backtracking time Δt, starting from the current sampling time t. oc V is the pre-acquired open-circuit voltage. max V min R represents the maximum and minimum measured terminal voltages within the backtracking time, respectively. current Let SOH be the battery internal resistance at the current sampling time. ave The average health status over the specified backtracking period.

2. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 1, characterized in that, The battery parameters include measured temperature, measured current, and measured terminal voltage. The process of obtaining and saving the battery's health state, state of charge, and state of energy at the current sampling time based on the battery parameters at the current and previous sampling times, and accordingly obtaining the battery's available energy at the current sampling time, includes: The measured temperature, measured current, and measured terminal voltage at the current sampling time, as well as the state of charge, state of health, and state of energy of the battery at the previous sampling time, are input into the state transition model to obtain the predicted values ​​of the state of charge, state of health, and state of energy of the battery at the current sampling time. Based on the predicted health status and measured temperature at the current sampling time, determine the battery internal resistance at the current sampling time; Based on the battery internal resistance, measured current, and pre-acquired open-circuit voltage at the current sampling time, determine the predicted terminal voltage at the current sampling time; The Kalman gain is calculated based on the prediction error between the predicted terminal voltage and the measured terminal voltage at the current sampling time. The predicted values ​​of state of charge, state of health, and state of energy at the current sampling time are corrected based on Kalman gain, and the corrected state of charge, state of health, and state of energy at the current sampling time are obtained and saved. Based on the corrected health status and energy status at the current sampling time, the available energy of the battery at the current sampling time is calculated.

3. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 2, characterized in that, The battery internal resistance at the current sampling time is Among them, R current,t Let T be the battery internal resistance at the current sampling time t, and k be a preset resistance correction coefficient. t R is the measured temperature at the current sampling time t. rated R is the rated internal resistance of the battery. e The termination internal resistance of the battery is [value missing]. T0 is the predicted health status value at the current sampling time t, and T0 is the preset reference temperature.

4. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 2, characterized in that, The available energy at the current sampling time is E available,t =x 2,t ·x 3,t ·C rated ·η, where x 2,t and x 3,t C represents the health state and energy state of the battery at the current sampling time t, respectively. rated The rated capacity of the battery is η, the preset charge / discharge efficiency of the inverter is E. available,t This represents the available energy at the current sampling time t.

5. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 1, characterized in that, Determining the battery's ability to supply power to the grid based on the available energy at the current sampling time includes: Determine whether the available capacity at the current sampling moment is greater than or equal to a preset energy threshold: If so, it is determined that the battery is capable of supplying power to the power grid according to the power supply request; Otherwise, it is determined that the battery is unable to supply power to the power grid according to the power supply request.

6. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 1, characterized in that, Determining the battery's ability to supply power to the grid based on the available energy at the current sampling time and the response capability within the backtracking time also includes: Determine whether the available capacity at the current sampling moment is greater than or equal to the preset energy threshold: If so, determine whether the response capability within the backtracking time is greater than or equal to a preset capability threshold, and if the response capability within the backtracking time is greater than or equal to the capability threshold, determine that the battery can supply power to the power grid according to the power supply request; Otherwise, it is determined that the battery is unable to supply power to the power grid according to the power supply request.

7. The method for evaluating the battery power supply capability of the integrated backup and storage uninterruptible power supply according to claim 1, characterized in that, The evaluation method also includes: The available energy of the battery at a preset number of historical sampling times is input into a pre-trained available energy prediction model to obtain the predicted available energy value of the battery at multiple future sampling times; wherein, the available energy prediction model is a time series prediction model; The battery's ability to supply power to the power grid is determined based on the predicted available energy.

8. A battery power supply capability assessment system for an integrated backup and storage uninterruptible power supply, characterized in that, The system includes: The battery parameter acquisition module is used to acquire and save the battery parameters at the current sampling time. The available energy determination module is used to respond to the power supply request of the power grid, obtain and save the battery's health state, state of charge and energy state at the current sampling time based on the battery parameters at the current and previous sampling time, as well as the battery's health state, state of charge and energy state at the previous sampling time, and thereby obtain the battery's available energy at the current sampling time. The response capability determination module is used to extract the battery parameters and health status of the battery at each sampling time within the backtracking time, starting from the current sampling time and tracing back a preset time length. Based on each battery parameter and health status, the response capability of the battery within the backtracking time is determined. An evaluation module is used to determine the battery's ability to supply power to the power grid based on the available energy at the current sampling time and / or the response capability during the backtracking period; The battery parameters include measured temperature, measured current, and measured terminal voltage. Starting from the current sampling time, the process involves backtracking for a preset time length to extract the battery parameters and health status at each sampling time within the backtracking period. Based on these parameters and health status, the battery's response capability within the backtracking period is determined, including: Starting from the current sampling time, backtrack for a preset time length, extract the measured terminal voltage and health status of the battery at each sampling time within the backtracking time, and filter out the maximum and minimum measured terminal voltage within the backtracking time. Based on the health status at each sampling moment within the backtracking period, calculate the average health status of the battery within the backtracking period; Based on the maximum measured terminal voltage, the minimum measured terminal voltage, the average health state value, and the battery internal resistance at the current sampling time, the response capability of the battery within the backtracking time is calculated. Wherein, the response capability of the battery during the backtracking time is Among them, P grid (t-Δt,t) represents the battery's response capability within a backtracking time Δt, starting from the current sampling time t. oc V is the pre-acquired open-circuit voltage. max V min R represents the maximum and minimum measured terminal voltages within the backtracking time, respectively. current Let SOH be the battery internal resistance at the current sampling time. ave The average health status over the specified backtracking period.

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