Optimal management method for state of charge of energy storage battery, and energy storage device and storage medium

Abstract

The present application relates to the technical field of energy storage control. Disclosed are an optimal management method for the state of charge of an energy storage battery, and an energy storage device and a storage medium. The optimal management method for the state of charge of an energy storage battery comprises: determining a state-of-charge partition management policy of an energy storage system composed of a plurality of low-voltage battery packs; performing unified management on the state of charge of the energy storage system, such that the state of charge of the energy storage system is subjected to charging and discharging control on the basis of the state-of-charge partition management policy; determining the charging power and discharging power of the energy storage system on the basis of the temperature and state of charge of each low-voltage battery pack; and performing automatic equalization management on the states of charge of all the low-voltage battery packs of the energy storage system on the basis of a preset state-of-charge equalization control policy. Thus, the optimal management of the states of charge of parallel-connected and networked low-voltage battery packs can be realized, and even if the states of charge of the low-voltage battery packs are inconsistent, the state of charge of an energy storage system can still accurately reflect a battery charging and discharging capability of the energy storage system.

Description

Energy storage battery power optimization management method, energy storage device and storage medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on September 7, 2023, with application number 202311154153.7 and application name “A method for optimizing the management of energy storage battery power, energy storage equipment and storage medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of energy storage control technology, and in particular to a method for optimizing the power management of an energy storage battery, an energy storage device, and a storage medium. Background Art

[0003] Currently, due to energy resource constraints, energy storage systems are increasingly being used in power plants, industrial and commercial users, and homes. Energy storage systems generally consist of photovoltaic panels, photovoltaic inverters (PCS / Inv, also known as power conversion systems or inverters), and energy storage batteries. Energy storage batteries include high-voltage and low-voltage battery pack solutions. High-voltage battery packs consist of multiple low-voltage batteries connected in series and connected to an inverter, while low-voltage battery packs consist of individual low-voltage batteries that are boosted via a DC / DC converter and then connected to an inverter. Because low-voltage battery packs are independent, have minimal impact on each other, and are safe, most manufacturers are increasingly favoring low-voltage battery packs. When multiple low-voltage battery packs are connected in parallel to form a network to form an energy storage system, the battery state of charge (Soc) of each low-voltage battery pack can vary. This means the energy storage system's battery state of charge (Soc) cannot accurately reflect the system's battery charge and discharge capabilities, making it impossible to guarantee the safety of charging and discharging battery packs with varying charge levels.

[0004] Summary of the Invention

[0005] The embodiments of the present application aim to provide a method for optimizing the management of energy storage battery power, an energy storage device, and a storage medium, which can solve the problem that the battery power of the existing energy storage system cannot accurately reflect the battery charging and discharging capacity of the energy storage system.

[0006] To solve the above technical problems, the first embodiment of the present application provides a method for optimizing the power management of an energy storage battery, the method comprising:

[0007] Determine the power zoning management strategy for an energy storage system consisting of multiple low-voltage battery packs;

[0008] Performing unified management of the power of the energy storage system so that the power of the energy storage system is charged and discharged according to the power zoning management strategy;

[0009] Determining the charging power and discharging power of the energy storage system according to the temperature and power of each low-voltage battery pack;

[0010] According to the preset battery power balancing control strategy, the power of all low-voltage battery packs in the energy storage system is automatically balanced and managed.

[0011] Optionally, determining a power partition management strategy for an energy storage system composed of multiple low-voltage battery packs includes:

[0012] Define the three parameters of maximum charging capacity, grid power outage backup capacity, and maximum discharge capacity. The battery capacity satisfies the following relationship: 0 ≤ maximum discharge capacity ≤ grid power outage backup capacity ≤ maximum charging capacity ≤ 100%;

[0013] The battery power of the energy storage system is divided into four power partitions according to the maximum charging power, grid power outage backup power and maximum discharging power, and the power protection ranges and power partition management strategies of the four power partitions are determined.

[0014] Optionally, the unified management of the power of the energy storage system so that the power of the energy storage system is controlled to be charged and discharged according to the power partition management strategy includes:

[0015] Calculating the original power of the energy storage system using a weighted average;

[0016] The power boundary transformation algorithm is used to perform power inspection and transformation processing at the original power partition boundary.

[0017] Optionally, the using of an electric quantity boundary transformation algorithm to perform electric quantity inspection and transformation processing at the original electric quantity partition boundary includes:

[0018] (1) According to the battery power of each low-voltage battery pack in the energy storage system, the low-voltage battery pack is divided into four sets according to four power partitions;

[0019] (2) If all low-voltage battery packs are in one of the sets, calculate the battery power of the energy storage system according to the first power calculation formula without making any changes; otherwise, go to (3);

[0020] (3) Evaluate the high and low limits of battery power;

[0021] (4) determining the basic battery capacity and battery pack set of the energy storage system;

[0022] (5) Calculate the battery power of the energy storage system according to the second power calculation formula.

[0023] Optionally, the evaluating the upper and lower limits of the battery power includes:

[0024] If charging is possible, the maximum battery capacity is less than the maximum charging capacity; if discharging is possible, the minimum battery capacity is greater than the grid power outage backup capacity; if backup power is possible, the minimum battery capacity is greater than the maximum discharge capacity.

[0025] Optionally, determining the basic battery capacity and battery pack set of the energy storage system includes:

[0026] If the battery capacity of a low-voltage battery pack is greater than the grid power outage backup capacity, the basic battery capacity is equal to the grid power outage backup capacity, and the condition for the low-voltage battery pack to be selected into the battery pack set is that the grid power outage backup capacity is less than the battery capacity;

[0027] If there is no low-voltage battery pack whose battery capacity is greater than the grid power outage backup capacity, and if there is a low-voltage battery pack whose battery capacity is greater than the maximum discharge capacity, then the basic battery capacity is equal to the maximum discharge capacity, and the condition for the low-voltage battery pack to be selected into the battery pack set is that the maximum discharge capacity is less than the battery capacity.

[0028] Optionally, the preset battery capacity balancing control strategy includes:

[0029] During charging, low-voltage battery packs with low battery power are given priority in allocating charging power; if there are multiple low-voltage battery packs with the same battery power, they will participate in charging power distribution at the same time;

[0030] During discharge, low-voltage battery packs with higher battery levels are given priority in allocating discharge power; if there are multiple low-voltage battery packs with the same battery levels, they all participate in the discharge power distribution at the same time.

[0031] Optionally, the energy storage battery power optimization management method further includes: adjusting the maximum charging power, the grid power outage backup power and the maximum discharging power according to the energy storage parameter adjustment principle.

[0032] Accordingly, the second aspect embodiment of the present application provides an energy storage device, comprising: a memory, a processor, and a computer program stored on the memory and running on the processor. When the computer program is executed by the processor, it implements the energy storage battery power optimization management method described in the first aspect embodiment of the present application.

[0033] Accordingly, the third aspect embodiment of the present application provides a computer storage medium, on which a program of the energy storage battery power optimization management method is stored. When the program of the energy storage battery power optimization management method is executed by a processor, the energy storage battery power optimization management method described in the first aspect embodiment of the present application is implemented.

[0034] Compared with the prior art, the present application provides a method for optimizing the power management of energy storage batteries, an energy storage device, and a storage medium. The method for optimizing the power management of energy storage batteries includes: determining a power zoning management strategy for an energy storage system composed of multiple low-voltage battery packs; uniformly managing the power of the energy storage system so that the power of the energy storage system is charged and discharged according to the power zoning management strategy; determining the charging power and discharging power of the energy storage system based on the temperature and power of each low-voltage battery pack; and automatically balancing the power of all low-voltage battery packs in the energy storage system according to a preset battery power balancing control strategy. This allows for optimized power management of low-voltage battery packs in parallel networking. Even if the battery power Soc of each low-voltage battery pack is inconsistent, the battery power Soc of the energy storage system can accurately reflect the battery charge and discharge capabilities of the energy storage system. Furthermore, a power partitioning management strategy is adopted, with different charge and discharge management strategies adopted for different power partitions, thereby improving the safety of charging and discharging of battery packs with different power levels. Using a preset battery power balancing control strategy, all low-voltage battery packs in the energy storage system are automatically managed for power balancing during the charging and discharging process, allowing each low-voltage battery pack to charge or discharge at maximum power. The battery charge and discharge power parameters are dynamically adjusted based on the temperature and power of each low-voltage battery pack to ensure the safety of charging and discharging the low-voltage battery pack and to improve the battery life of the low-voltage battery pack. This solves the problem that the battery power of existing energy storage systems cannot accurately reflect the battery charge and discharge capabilities of the energy storage system and cannot guarantee the safety of charging and discharging battery packs with different power levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings. These exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements. Unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0036] FIG1 is a schematic diagram of the structure of an energy storage system provided by the present application, which is formed by networking multiple low-voltage battery packs in parallel;

[0037] FIG2 is a flow chart of a method for optimizing the management of energy storage battery power provided by the present application;

[0038] FIG3 is another flow chart of a method for optimizing energy storage battery power management provided by the present application;

[0039] FIG4 is a schematic structural diagram of an energy storage device provided in this application. DETAILED DESCRIPTION

[0040] In order to facilitate the understanding of the present application, the present application is described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as being "fixed to" another element, it can be directly on the other element, or there can be one or more centered elements therebetween. When an element is described as being "connected to" another element, it can be directly connected to the other element, or there can be one or more centered elements therebetween. The terms "upper", "lower", "inner", "outer", "bottom" and the like used in this specification indicate an orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", "third" and the like are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0041] Unless otherwise defined, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs. The terms used in this specification and in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the relevant listed items.

[0042] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0043] Currently, due to energy resource constraints, energy storage systems are increasingly being used in power plants, industrial and commercial users, and homes. Energy storage systems generally consist of photovoltaic panels, photovoltaic inverters (PCS / Inv), and energy storage batteries. Energy storage batteries include high-voltage and low-voltage battery pack solutions. High-voltage battery packs consist of multiple low-voltage batteries connected in series and connected to an inverter, while low-voltage battery packs consist of individual low-voltage batteries that are boosted via a DC / DC converter and then connected to an inverter. Because low-voltage battery packs are independent, have minimal impact on each other, and are safe, most manufacturers are increasingly preferring low-voltage battery packs.

[0044] As shown in Figure 1, multiple low-voltage battery packs are connected in parallel to form an energy storage system. In Figure 1, four low-voltage batteries (BAT1, BAT2, BAT3, and BAT4) are each boosted by a DC / DC converter and connected in parallel to the inverter PCS. The DC / DC converter and BMS (Battery Management System) enable energy storage, power measurement, charge and discharge power control, and battery status management.

[0045] Since the battery state of charge (Soc) of each low-voltage battery pack can be inconsistent, for example, in Figure 1, the battery state of charge of battery BAT1 is 50%, the battery state of charge of battery BAT2 is 20%, the battery state of charge of battery BAT3 is 20%, and the battery state of charge of battery BAT4 is 10%. This will cause the following problems:

[0046] 1. Users and energy management algorithms do not care about the power level of a specific battery pack, but only the total power level of the energy storage system. The power level can accurately describe the battery charge and discharge capability characteristics of the energy storage system. That is, the battery power Soc of the energy storage system cannot accurately reflect the battery charge and discharge capability of the energy storage system.

[0047] 2. How to improve the safety of charging and discharging battery packs with different capacities.

[0048] 3. How to make the entire energy storage system have maximum discharge power output.

[0049] 4. The life of low-voltage batteries is generally required to be more than 10 years. How to optimize the battery life cycle?

[0050] In view of this, the present application provides a method for optimizing the management of the power of energy storage batteries, which determines a power zoning management strategy for an energy storage system composed of multiple low-voltage battery packs; uniformly manages the power of the energy storage system so that the power of the energy storage system is controlled for charging and discharging according to the power zoning management strategy; determines the charging power and discharging power of the energy storage system according to the temperature and power of each low-voltage battery pack; and automatically balances the power of all low-voltage battery packs of the energy storage system according to a preset battery power balancing control strategy. This can achieve optimized management of the power of a parallel network of low-voltage battery packs, and even if the battery power of each low-voltage battery pack is inconsistent, the battery power of the energy storage system can accurately reflect the battery charging and discharging capacity of the energy storage system, thereby solving the problem that the battery power of the existing energy storage system cannot accurately reflect the battery charging and discharging capacity of the energy storage system and cannot ensure the safety of charging and discharging of battery packs with different power levels.

[0051] In order to facilitate understanding of the above inventive concepts of the present application, the above inventive concepts of the present application are described in more detail below with reference to the accompanying drawings and specific embodiments.

[0052] In one embodiment, as shown in FIG2 , the present application provides a method for optimizing the management of the power of an energy storage battery. The method for optimizing the management of the power of an energy storage battery includes:

[0053] S1. Determine a power partitioning management strategy for an energy storage system consisting of multiple low-voltage battery packs;

[0054] S2. Centrally manage the power of the energy storage system so that the charge and discharge of the energy storage system is controlled according to the power zoning management strategy;

[0055] S3. Determine the charging power and discharging power of the energy storage system based on the temperature and power of each low-voltage battery pack;

[0056] S4. According to the preset battery power balancing control strategy, the power of all low-voltage battery packs of the energy storage system is automatically balanced and managed.

[0057] In this embodiment, a method for optimizing the power management of energy storage batteries is provided, including: determining a power zoning management strategy for an energy storage system composed of multiple low-voltage battery packs; uniformly managing the power of the energy storage system so that the power of the energy storage system is charged and discharged according to the power zoning management strategy; determining the charging power and discharging power of the energy storage system based on the temperature and power of each low-voltage battery pack; and automatically balancing the power of all low-voltage battery packs in the energy storage system according to a preset battery power balancing control strategy. This allows for optimized power management of low-voltage battery packs in parallel networking. Even if the battery power Soc of each low-voltage battery pack is inconsistent, the battery power Soc of the energy storage system can accurately reflect the battery charge and discharge capabilities of the energy storage system. Furthermore, a power partitioning management strategy is adopted, with different charge and discharge management strategies adopted for different power partitions, thereby improving the safety of charging and discharging of battery packs with different power levels. Using a preset battery power balancing control strategy, all low-voltage battery packs in the energy storage system are automatically managed for power balancing during the charging and discharging process, allowing each low-voltage battery pack to charge or discharge at maximum power. The battery charge and discharge power parameters are dynamically adjusted based on the temperature and power of each low-voltage battery pack to ensure the safety of charging and discharging the low-voltage battery pack and improve the battery life of the low-voltage battery pack. This solves the problem that the battery power Soc of existing energy storage systems cannot accurately reflect the battery charge and discharge capabilities of the energy storage system and cannot guarantee the safety of charging and discharging battery packs with different power levels.

[0058] In one embodiment, in step S1, the power partition management strategy of the energy storage system composed of multiple low-voltage battery packs is determined. Specifically, it includes:

[0059] S11. Define three parameters: maximum charging capacity chg_max, grid power outage backup capacity soc_res, and maximum discharge capacity dod_max. The battery capacity soc satisfies the following relationship: 0≤dod_max≤soc_res≤chg_max≤100%.

[0060] Generally, lithium batteries should be charged and discharged within the range of 30% to 80% of the power level, which will cause less damage to the battery and have a higher charging and discharging efficiency. Try to avoid charging and discharging in very low or very high power areas.

[0061] In this application, the energy storage system defines the following three parameters: maximum charge capacity chg_max, maximum discharge capacity dod_max, and grid outage backup capacity soc_res. The maximum discharge capacity dod_max represents the emergency charge capacity at the maximum discharge depth. dod stands for depth of discharge in English and depth of discharge in Chinese.

[0062] The energy storage system supports power backup during grid outages. When the grid is normal, sufficient power needs to be reserved to provide backup power to the load in the event of a grid outage. This backup power is called the grid outage backup power soc_res.

[0063] The battery capacity soc of the energy storage system satisfies the following relationship: 0≤dod_max≤soc_res≤chg_max≤100%.

[0064] The maximum charging capacity (chg_max), grid outage backup capacity (soc_res), and maximum discharge capacity (dod_max) can be dynamically adjusted based on external conditions. The maximum discharge capacity (dod_max) and maximum charging capacity (chg_max) are dynamically adjusted based on factors such as photovoltaic power generation characteristics, weather forecasts, grid alarms, and operating dates, taking into account requirements such as energy storage backup capacity, energy storage management economics, and battery cycle life. In practical applications, the maximum discharge capacity (dod_max), the maximum charging capacity (chg_max), and the grid outage backup capacity (soc_res) are generally set at 10%, 95%, and 30%.

[0065] S12: Divide the battery power of the energy storage system into four power zones according to the maximum charging power chg_max, the grid power outage backup power soc_res, and the maximum discharging power dod_max, and determine the power protection ranges and power zone management strategies of the four power zones.

[0066] Specifically, based on the maximum charging capacity chg_max, the grid outage backup capacity soc_res, and the maximum discharge capacity dod_max, the battery capacity of the energy storage system is divided into four power zones: emergency power zone, backup power zone, normal power zone, and full battery zone. The power protection ranges and power zone management strategies for these four power zones are determined as follows:

[0067] The power protection range of the emergency power replenishment zone is: 0≤soc≤dod_max, and the power partition management strategy is: no discharge, timely power replenishment, so that soc is not lower than dod_max.

[0068] The power protection range of the backup power working area is: dod_max < soc ≤ soc_res, and the power partition management strategy is: rechargeable, not discharging when connected to the grid, and capable of providing backup power when off-grid.

[0069] The power protection range of the normal working area is: Soc_res < soc < chg_max, and the power partition management strategy is: rechargeable and dischargeable.

[0070] The power protection range of the battery full charge area is: Soc ≥ Chg_max, and the power partition management strategy is: not allowing charging and dischargeable.

[0071] The power management strategies for each power partition are shown in Table 1 below.

[0072] Table 1: Power Management Strategies for Power Partitions

[0073] In this embodiment, by adopting the power partition management strategy for the energy storage system composed of multiple low-voltage battery packs, different charge and discharge management strategies are adopted for different power partitions. For a single low-voltage battery pack, the power partition management strategy is strictly implemented. The power partition that does not allow charging will never be charged, the power partition that does not allow discharging will never be discharged, and the power partition that needs emergency power replenishment will be replenished in a timely manner; for the entire energy storage system, it is determined whether to allow charging or discharging according to the battery power characteristics of all low-voltage battery packs, improving the safety of charging and discharging of battery packs with different powers, enhancing the safety of charging and discharging of low-voltage battery packs, and extending the battery life of low-voltage battery packs.

[0074] In one embodiment, in step S2, the power of the energy storage system is uniformly managed so that the power of the energy storage system is controlled for charging and discharging according to the power partition management strategy. Specifically, it includes:

[0075] S21. Calculate the original power of the energy storage system using weighted average.

[0076] The battery power of the energy storage system composed of multiple low-voltage battery packs can be calculated by weighted average using the first power calculation formula (1.1), where Cap i is the capacity of the i-th low-voltage battery pack, and soc i is the power of the i-th low-voltage battery pack.

[0077] As shown in Figure 1, assuming that the charge and discharge power of each low-voltage battery is 2.5 kw, the maximum discharge power dod_max is taken as 10%, the maximum charge power chg_max is taken as 95%, and the grid power outage backup power soc_res is taken as 30%. Then the battery power calculated by the energy storage system in each scenario is shown in Table 2.

[0078] Table 2 Calculated battery capacity of the energy storage system in various scenarios

[0079] In Table 2, the battery capacity of battery BAT1 is Soc1, the battery capacity of battery BAT2 is Soc2, the battery capacity of battery BAT3 is Soc3, and the battery capacity of battery BAT4 is Soc4. The battery capacity of the energy storage system is the average value Soc.

[0080] For scenarios where the power of low-voltage battery packs is relatively balanced (such as CASE1, CASE7, and CASE8 in Table 2), according to the power partitioning management strategy in Table 1, the battery power soc of the energy storage system truly reflects the battery charging and discharging capabilities.

[0081] For scenarios where the low-voltage battery pack power varies significantly (e.g., Case 3, Case 4, and Case 5 in Table 2), the battery power SOC of the energy storage system cannot accurately reflect the battery's charge and discharge capabilities. The reasons are:

[0082] For case 3, the average soc is 7.5%. According to the power partition management strategy in Table 1, it cannot provide backup power. In fact, battery BAT4 can still provide 2.5 kW of backup power.

[0083] Case 4, the average soc is 95%, and it cannot be charged according to the power partition management strategy in Table 1. In fact, battery BAT1 and battery BAT2 are not fully charged and need to be charged by 5kw.

[0084] Case 5, the average soc is 27.5%. According to the power partition management strategy in Table 1, it cannot be discharged. In fact, battery BAT1 can discharge 2.5 kW.

[0085] S22. Use the power boundary transformation algorithm to perform power inspection and transformation processing at the original power partition boundary.

[0086] In scenarios where the low-voltage battery packs have large variations in charge (e.g., Case 3, Case 4, and Case 5 in Table 2), the energy storage system's battery charge SOC cannot accurately reflect the battery's charge and discharge capabilities. In this case, a charge boundary transformation algorithm can be used to perform charge checks and transformations at the original charge partition boundaries.

[0087] Using the power boundary conversion algorithm, the goals of the soc are:

[0088] (1) The battery capacity soc of the energy storage system truly reflects the battery's charge and discharge capabilities (see Table 1). If it can be charged, the battery capacity soc is not higher than the maximum charge capacity chg_max; if it can be discharged, the battery capacity soc is not lower than the grid power outage backup capacity soc_res; if it can be backed up, the battery capacity soc is not lower than the maximum discharge capacity dod_max;

[0089] (2) The battery capacity SOC after transformation changes smoothly without jumping. A high value indicates a large amount of actual capacity, while a low value indicates a small amount of actual capacity.

[0090] Specifically, in step S22, the power boundary transformation algorithm is used to perform power inspection and transformation processing at the original power partition boundary. The specific process includes:

[0091] (1) According to the battery capacity soc of each low-voltage battery pack in the energy storage system, the low-voltage battery pack is divided into the following four sets according to four capacity partitions: the first set Set1 (battery capacity soc ≤ maximum discharge capacity dod_max), the second set Set2 (maximum discharge capacity dod_max < battery capacity soc ≤ grid power outage backup capacity soc_res), the third set Set3 (grid power outage backup capacity soc_res < battery capacity soc < maximum charge capacity chg_max), and the fourth set Set4 (battery capacity soc ≥ maximum charge capacity chg_max).

[0092] (2) If all low-voltage battery packs are in one of the sets, calculate the battery capacity of the energy storage system according to the first capacity calculation formula (1.1) without making any changes. Otherwise, go to (3).

[0093] (3) Evaluate the upper and lower limits of the battery power. If charging is possible, the maximum battery power soc_max < the maximum charging power chg_max; if discharging is possible, the minimum battery power soc_min > the grid power backup power soc_res; if backup power is possible, the minimum battery power soc_min > the maximum discharge power dod_max.

[0094] (4) Determine the basic battery capacity soc_base and battery pack set Set of the energy storage system k :

[0095] (A) If the battery capacity soc of a low-voltage battery pack is greater than the grid power outage backup capacity soc_res, then the battery base capacity soc_base = grid power outage backup capacity soc_res, and the low-voltage battery pack is selected into the battery pack set Set k The condition is that the grid power outage backup power soc_res < battery power soc.

[0096] (B) If there is no low-voltage battery pack whose battery capacity soc is greater than the grid power outage backup capacity soc_res, and if there is a low-voltage battery pack whose battery capacity soc is greater than the maximum discharge capacity dod_max, then the battery base capacity soc_base = the maximum discharge capacity dod_max, and the low-voltage battery pack is selected into the battery pack set Set kThe condition is that the maximum discharge capacity dod_max < battery capacity soc.

[0097] (5) The battery power soc of the energy storage system is calculated according to the second power calculation formula (1.2), and the battery power soc of the energy storage system is used for user display and energy management.

[0098] In the second power calculation formula (1.2), the denominator represents the sum of all low-voltage battery capacities, and the numerator represents the battery pack set Set k The current amount of power used for calculation, battery power soc k The calculation is shown in formula (1.3). The battery capacity soc calculated by the method of this embodiment will not be greater than the maximum charging capacity chg_max.

[0099] After transformation using the power boundary transformation algorithm, the battery power of various scenarios shown in Table 2 is shown in the last column (soc after transformation), and can be fully controlled by the power partition management strategy shown in Table 1 for charging and discharging, namely: Case 3, Case 4 and Case 5 solve the problem of incorrect battery power characterization. In Case 3, the transformed battery power is 10.5% higher than the maximum discharge power dod_max (10%), which can be used for backup power and output a certain amount of electrical energy; in Case 4, the transformed power is 93.5% lower than the maximum charge power chg_max (95%), which can be charged; in Case 5, the transformed power is 32.5% higher than the grid power outage backup power soc_res (30%), which can be discharged.

[0100] In this embodiment, by uniformly managing the energy storage system's power, the energy storage system's power is controlled for charge and discharge according to the power partitioning management strategy. This ensures that when charging is possible, the battery power SOC is less than the maximum charge power; when discharging is possible, the battery power SOC is greater than the grid power outage backup power (grid-connected scenario) or emergency charging power (off-grid scenario). This provides energy management and users with a logical power level, and the power level does not fluctuate. This allows for optimized power management of low-voltage battery packs in parallel networking. Even if the battery power SOCs of the various low-voltage battery packs are inconsistent, the energy storage system's battery power SOC accurately reflects the battery charge and discharge capabilities of the energy storage system.

[0101] In one embodiment, in step S3, the charging power and discharging power of the energy storage system are determined according to the temperature and power level of each low-voltage battery pack.

[0102] Assuming that Pchg is the battery charge and discharge power parameter related to temperature, and Pdchg is the battery charge and discharge power parameter related to power, then for a low-voltage battery pack i, at the current temperature temp i and battery charge soc i The charging power is shown in formula (2.1), and the discharging power is shown in formula (2.2).

[0103] In this application, the energy storage system is composed of multiple low-voltage battery packs, which can be represented by the emergency power replenishment power Pemgt, charging power Pchg and discharge power Pdchg. The calculation methods of the emergency power replenishment power Pemgt, charging power Pchg and discharge power Pdchg are shown in (2.3), (2.4) and (2.5). Among them, for the charging power Pchg and discharge power Pdchg, all low-voltage battery packs are involved in the calculation; the emergency power replenishment battery pack set Set j The condition is that the battery power soc < the maximum discharge power dod_max. The low-voltage battery pack that meets this condition participates in the calculation of the emergency power Pemgt.

[0104] When managing energy storage, the battery capacity soc is first used to determine whether the energy storage system is chargeable or dischargeable. Then, the three parameters of the emergency power replenishment power Pemgt, charging power Pchg and discharging power Pdchg are used to determine the size of the emergency power replenishment, chargeable and dischargeable power, and perform energy distribution and management.

[0105] In this embodiment, the battery charge and discharge power parameters can be dynamically adjusted according to the temperature and power level of each low-voltage battery pack to ensure the safety of charging and discharging of the low-voltage battery pack and improve the battery life of the low-voltage battery pack.

[0106] In one embodiment, in step S4, the power of all low-voltage battery packs of the energy storage system is automatically balanced and managed according to a preset battery power balancing control strategy.

[0107] According to Table 2, if the battery charge of the low-voltage battery packs varies greatly, the battery charge SOC obtained by using the charge boundary transformation algorithm can be discharged, but the charge and discharge power is quite different from the capacity of the energy storage system. Only when the battery charge of all low-voltage battery packs is relatively balanced can the charge and discharge power be relatively large. Therefore, during the charge and discharge process, the battery charge of all low-voltage battery packs can be balanced through reasonable power distribution.

[0108] The energy storage management of the energy storage system of this application generally prioritizes the load through photovoltaic power generation, and the surplus power is used to charge the energy storage battery composed of a low-voltage battery pack, or to quickly charge the low-voltage battery during a specified time period. If photovoltaic power generation is not enough to power the load, the energy storage battery needs to discharge to meet the load's power demand. The discharged energy storage battery is generally rarely directly fed into the power grid. Therefore, there are certain requirements for the power of charging and discharging the energy storage battery, which is allocated by the energy storage management algorithm.

[0109] Under given power charging and discharging conditions, the preset battery charge balancing control strategies include:

[0110] (1) During charging, low-voltage battery packs with low battery SOC are given priority in allocating charging power; if there are multiple low-voltage battery packs with the same battery SOC, they can participate in charging power allocation at the same time;

[0111] (2) During discharge, the low-voltage battery pack with a high battery SOC is given priority in allocating discharge power; if there are multiple low-voltage battery packs with the same battery SOC, they can participate in the discharge power distribution at the same time.

[0112] The charging power allocation algorithm used by the energy storage system of this application performs charging power allocation. The specific process is as follows:

[0113] (1) Energy management algorithm inputs rechargeable power chgPower;

[0114] (2) Initialize variables now_soc = -1, lookfor_soc = 101;

[0115] (3) Find the minimum power lookfor_soc greater than the variable now_soc among the battery power soc of all low-voltage battery packs;

[0116] (4) If the minimum charge lookfor_soc>variable now_soc and the minimum charge lookfor_soc<maximum charge chg_max, then all low-voltage batteries with a charge soc equal to the minimum charge lookfor_soc are input into the list ListM and go to (5); otherwise, the allocation ends (no rechargeable battery).

[0117] (5) Calculate the allocable power Pavg of each low-voltage battery, Pavg = chgPower / ListM.size() (number of batteries), and the actual allocated power Palloc of the low-voltage battery, Palloc = min{Pchgi, Pavg}, where min represents the minimum value;

[0118] (6) Update the parameters: chgPower = chgPower - ∑Palloc, now_soc = lookfor_soc, lookfor_soc = 101; ∑Palloc represents the power allocated for the battery level lookfor_soc.

[0119] (7) If the rechargeable power chgPower has been fully allocated or the low-voltage battery packs have been fully allocated, end the process; otherwise, go to step (3).

[0120] The discharge power allocation algorithm used in the energy storage system of this application performs the charging power allocation as follows:

[0121] (1) The energy management algorithm inputs the discharge power demand dchgPower.

[0122] (2) Initialize the variables: now_soc = 101, lookfor_soc = -1.

[0123] (3) Search for the maximum battery level lookfor_soc that is smaller than now_soc among the battery levels soc of all low-voltage battery packs.

[0124] (4) If the maximum battery level lookfor_soc < now_soc and lookfor_soc > the basic battery level soc_base, then input all low-voltage batteries with the battery level soc equal to lookfor_soc into the list ListM and go to step (5); otherwise, end the allocation (no dischargeable batteries).

[0125] (5) Calculate the allocable power Pavg for each low-voltage battery, Pavg = chgPower / ListM.size() (number of batteries), and the actual allocated power Palloc for the low-voltage battery, Palloc = min{Pdchgi, Pavg}, where min represents taking the minimum value.

[0126] (6) Update the parameters: dchgPower = dchgPower - ∑Palloc, now_soc = lookfor_soc, lookfor_soc = -1; ∑Palloc represents the power allocated for the battery level lookfor_soc.

[0127] (7) If the discharge power demand dchgPower has been fully allocated or the low-voltage battery packs have been fully allocated, end the process; otherwise, go to step (3).

[0128] In this embodiment, the power of all low-voltage battery packs in the energy storage system is automatically balanced according to a preset battery power balancing control strategy; and a charging power distribution algorithm and a discharging power distribution algorithm are adopted to give priority to the low-voltage battery with the lowest charging power and the low-voltage battery with the highest discharging power. After several rounds of charging and discharging, the power of all low-voltage battery packs is automatically balanced, and each low-voltage battery pack can be charged or discharged to achieve maximum power charging or discharging.

[0129] In one embodiment, as shown in FIG3 , the energy storage battery power optimization management method further includes: S5 , according to the energy storage parameter adjustment principle, optimizing the three parameters of the maximum charging power chg_max, the grid power outage backup power soc_res and the maximum discharge power dod_max.

[0130] Specifically, as previously mentioned, the energy boundary transformation algorithm and energy partition management strategy for unified energy storage system management rely on three parameters: maximum charge capacity chg_max, grid outage backup capacity soc_res, and maximum discharge capacity dod_max. These three parameters significantly impact the energy storage system's capacity, backup capability, and low-voltage battery life.

[0131] The maximum discharge capacity (dod_max) affects the lifespan of the low-voltage battery, the capacity of the energy storage system, and the backup capacity. Increasing the maximum discharge capacity (dod_max) will increase the lifespan of the low-voltage battery but reduce the backup capacity.

[0132] The grid outage backup power soc_res affects the discharge capacity and the efficiency of energy storage management. Increasing the grid outage backup power soc_res will enhance the backup capacity but reduce the efficiency of energy storage management.

[0133] The maximum charge capacity chg_max affects battery life and energy storage management efficiency. Increasing the maximum charge capacity chg_max will reduce the low-voltage battery life but improve management efficiency.

[0134] The lifespan of a low-voltage battery generally depends on its maximum charge and discharge cycles, which are affected by the maximum charge and minimum discharge capacities. Charging and discharging in the high and low charge ranges significantly damages lithium ions, shortening battery life. To improve low-voltage battery life, charge and discharge capacities should be kept within the medium charge range. However, insufficient utilization of the high and low charge ranges will affect energy storage capacity. Therefore, high energy storage charge and discharge capacity is essential for scenarios requiring backup power or improving the economic benefits of energy storage.

[0135] Taking into account the low-voltage battery life and energy storage requirements, Table 3 summarizes the principles of parameter adjustment under relevant conditions.

[0136] Table 3 Energy storage parameter adjustment principles

[0137] In Table 3, the energy storage system first sets default values ​​for the three parameters of maximum charging capacity chg_max, grid outage backup capacity soc_res, and maximum discharge capacity dod_max (for example, maximum discharge capacity dod_max is 10%, maximum charging capacity chg_max is 95%, and grid outage backup capacity soc_res is 30%), and then adjusts these parameters up, down, or back to the default values ​​according to different scenarios.

[0138] Case 1 involves increasing backup capacity. If adverse weather conditions such as hurricanes or snow are forecast, or if the grid issues a power outage, or if increased load demand is detected in the near future, these factors necessitate increased energy storage capacity to ensure sufficient energy output during backup. For applications requiring backup power, the maximum charge capacity (chg_max) can be increased to 100%, and the grid outage backup capacity (soc_res) can be increased to over 80%, prioritizing backup power.

[0139] Case 2 is used under normal conditions, with no extreme weather and no power outage notice from the grid. The backup power demand is reduced, which can reduce the backup power soc_res and improve the economic benefits of energy management. It also reduces the maximum charging power chg_max and increases battery life.

[0140] In Cases 3 and 4, the maximum discharge capacity (dod_max) is generally affected by photovoltaic power generation. If the system has photovoltaic power generation, it will prioritize emergency battery charging. If photovoltaic power generation capacity is strong in the near term, the maximum discharge capacity (dod_max) can be lowered to increase the system's backup capacity. If photovoltaic power generation capacity is weak for a sustained period of time, the maximum discharge capacity (dod_max) must be restored to improve battery safety. If the grid is allowed to charge the battery, the maximum discharge capacity (dod_max) is less affected by photovoltaic power generation, and the grid can provide emergency battery charging, reducing the maximum discharge capacity (dod_max).

[0141] In this embodiment, by using the energy storage parameter adjustment principle to dynamically adjust the three parameters of the maximum charging power chg_max, the grid power outage backup power soc_res and the maximum discharge power dod_max according to factors such as photovoltaic power generation characteristics, weather status forecasts, grid alarms, operation dates, etc., it is possible to take into account the requirements of energy storage backup capacity, energy storage management economic benefits, battery cycle life, etc., ensure the safety of charging and discharging of low-voltage battery packs, and improve the battery life of low-voltage battery packs.

[0142] Based on the same concept, in one embodiment, the present application further provides an energy storage device. As shown in FIG4 , the energy storage device 900 includes: a memory 902, a processor 901, and one or more computer programs stored in the memory 902 and executable on the processor 901. The memory 902 and the processor 901 are coupled together via a bus system 903. When the one or more computer programs are executed by the processor 901, the following steps of a method for optimizing the power management of an energy storage battery provided in an embodiment of the present application are implemented:

[0143] S1. Determine a power partitioning management strategy for an energy storage system consisting of multiple low-voltage battery packs;

[0144] S2. Centrally manage the power of the energy storage system so that the charge and discharge of the energy storage system is controlled according to the power zoning management strategy;

[0145] S3. Determine the charging power and discharging power of the energy storage system based on the temperature and power of each low-voltage battery pack;

[0146] S4. According to the preset battery power balancing control strategy, the power of all low-voltage battery packs of the energy storage system is automatically balanced and managed.

[0147] The methods disclosed in the above embodiments of the present application can be applied to or implemented by the processor 901. The processor 901 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in the processor 901. The processor 901 may be a general-purpose processor, a DSP, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc. The processor 901 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium located in the memory 902. The processor 901 reads the information in the memory 902 and, in conjunction with its hardware, completes the steps of the above method.

[0148] It can be understood that the memory 902 in the embodiment of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device; the volatile memory can be random access memory (RAM), by way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), etc. Memory), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0149] It should be noted that the above energy storage device embodiment and method embodiment belong to the same concept, and their specific implementation process is detailed in the method embodiment, and the technical features in the method embodiment are correspondingly applicable in the energy storage device embodiment, which will not be repeated here.

[0150] In addition, in an exemplary embodiment, the embodiment of the present application further provides a computer storage medium, specifically a computer-readable storage medium, for example, including a memory 902 storing a computer program, wherein the computer storage medium stores one or more programs of a method for optimizing the power management of an energy storage battery. When the one or more programs of the method for optimizing the power management of an energy storage battery are executed by the processor 901, the following steps of the method for optimizing the power management of an energy storage battery provided in the embodiment of the present application are implemented:

[0151] S1. Determine a power partitioning management strategy for an energy storage system consisting of multiple low-voltage battery packs;

[0152] S2. Centrally manage the power of the energy storage system so that the charge and discharge of the energy storage system is controlled according to the power zoning management strategy;

[0153] S3. Determine the charging power and discharging power of the energy storage system based on the temperature and power of each low-voltage battery pack;

[0154] S4. According to the preset battery power balancing control strategy, the power of all low-voltage battery packs of the energy storage system is automatically balanced and managed.

[0155] It should be noted that the program embodiment of the energy storage battery power optimization management method on the above-mentioned computer-readable storage medium and the method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment, and the technical features in the method embodiment are correspondingly applicable in the embodiment of the above-mentioned computer-readable storage medium, which will not be repeated here.

[0156] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0157] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Based on the idea of ​​the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present application as described above. For the sake of simplicity, they are not provided in detail. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions recorded in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing the power management of energy storage batteries, characterized in that: The energy storage battery power optimization management method comprises: Determine the power partition management strategy for energy storage systems composed of multiple low-voltage battery packs; The power of the energy storage system is managed uniformly so that the power of the energy storage system is charged and discharged according to the power partition management strategy; Determining the charging power and discharging power of the energy storage system according to the temperature and power of each low-voltage battery pack; According to the preset battery power balancing control strategy, the power of all low-voltage battery packs of the energy storage system is automatically balanced and managed.

2. The energy storage battery power optimization management method according to claim 1 is characterized in that: The power partition management strategy for determining an energy storage system composed of multiple low-voltage battery packs includes: Define three parameters: maximum charging capacity, grid power outage backup capacity, and maximum discharging capacity. The battery capacity satisfies the following relationship: 0≤maximum discharging capacity≤grid power outage backup capacity≤maximum charging capacity≤100%; According to the maximum charging power, grid power outage backup power and maximum discharging power, the battery power of the energy storage system is divided into four power partitions, and the power protection ranges and power partition management strategies of the four power partitions are determined.

3. The energy storage battery power optimization management method according to claim 2 is characterized in that: The unified management of the power of the energy storage system so that the power of the energy storage system is charged and discharged according to the power partition management strategy includes: Calculating the original power of the energy storage system using a weighted average; The power boundary transformation algorithm is used to perform power inspection and transformation processing at the original power partition boundary.

4. The energy storage battery power optimization management method according to claim 3 is characterized in that: The method of using the power boundary transformation algorithm to perform power inspection and transformation processing at the original power partition boundary includes: According to the battery power of each low-voltage battery pack in the energy storage system, the low-voltage battery pack is divided into four sets according to four power partitions; If all low-voltage battery packs are in one of the sets, the battery power of the energy storage system is calculated according to the first power calculation formula without any change; otherwise, the high and low boundaries of the battery power are evaluated; Determine the basic battery capacity and battery pack set of the energy storage system; The battery power of the energy storage system is calculated according to the second power calculation formula.

5. The energy storage battery power optimization management method according to claim 4 is characterized in that: The evaluation of the upper and lower boundaries of the battery power includes: If charging is possible, the maximum battery capacity is less than the maximum charging capacity; if discharging is possible, the minimum battery capacity is greater than the grid power outage backup capacity; if backup power is possible, the minimum battery capacity is greater than the maximum discharge capacity.

6. The energy storage battery power optimization management method according to claim 4 is characterized in that: Determining the basic battery power and battery pack set of the energy storage system includes: If the battery capacity of a low-voltage battery pack is greater than the grid power outage backup capacity, the basic battery capacity is equal to the grid power outage backup capacity, and the condition for the low-voltage battery pack to be selected into the battery pack set is that the grid power outage backup capacity is less than the battery capacity; If there is no low-voltage battery pack whose battery power is greater than the grid power outage backup power, if there is a low-voltage battery pack whose battery power is greater than the maximum discharge power, then the basic battery power is equal to the maximum discharge power, and the condition for the low-voltage battery pack to be selected into the battery pack set is that the maximum discharge power is less than the battery power.

7. The energy storage battery power optimization management method according to claim 1, characterized in that: The preset battery charge balancing control strategy includes: When charging, low-voltage battery packs with low battery power are given priority in allocating charging power; if there are multiple low-voltage battery packs with the same battery power, they will participate in the charging power allocation at the same time; During discharge, low-voltage battery packs with higher battery power are given priority in allocating discharge power; if there are multiple low-voltage battery packs with the same battery power, they will participate in the discharge power allocation at the same time.

8. The energy storage battery power optimization management method according to claim 2 is characterized in that: The energy storage battery power optimization management method also includes: according to the energy storage parameter adjustment principle, adjusting the maximum charging power, the power grid power failure backup power and the maximum discharge power.

9. An energy storage device, characterized in that: The method is characterized in that it comprises: a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the computer program is executed by the processor, the method for optimizing the power management of an energy storage battery as described in any one of claims 1 to 8 is implemented.

10. A computer storage medium, characterized in that: The computer storage medium stores a program of an energy storage battery power optimization management method, and when the program of the energy storage battery power optimization management method is executed by a processor, the energy storage battery power optimization management method as described in any one of claims 1 to 8 is implemented.

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