Method for realizing in-phase online equalization of modularized battery energy storage system based on NLM

Abstract

The invention provides a method for realizing in-phase online equalization of a modular battery energy storage system based on an NLM, and the method comprises the steps: S1, regularly obtaining SOCj, x and (1-SOC) j, x, rechargeable energy SOEj, x and dischargeable energy SODEj, x of a module DC side battery through a battery management system BMS according to an equalization control period Tequ; s2, acquiring an equalization index of each module according to engineering requirements, determining an input priority sequence during charging and discharging, and generating a battery voltage queue of all modules; and S3, obtaining the size of a modulation wave in each power control period, and determining the first k modules which should be input currently and the total number k of the input modules. In-phase equalization is realized by fully utilizing an alternating-current reactive energy exchange process and a reactive state of the system, a blind area of a traditional method is eliminated, an application range of the in-phase equalization is expanded, in-phase module equalization is realized in each power frequency period, an operation boundary of the system is not influenced at all, charging of some modules in one power frequency period is realized, and charging efficiency is improved. Some modules discharge, and the equalization speed is higher.

Description

Technical Field

[0001] The present application relates to the technical field of battery balancing control, and in particular, to a method and system for realizing intra-phase online balancing in a modular battery energy storage system based on NLM. Background Art

[0002] Modular converter technology can achieve efficient high-voltage and large-capacity power conversion and is widely used in motor drive, grid reactive power compensation, DC transmission, medium-voltage direct-mounted energy storage and other fields. Cascaded H-bridge and modular multi-level are two typical modular converter technologies. Modulation technology converts the modulation wave output by the control algorithm into switching instructions for the converter power devices, which directly affects the converter efficiency and response speed and is one of the core technologies of modular converters.

[0003] With the large-scale application of battery energy storage in independent energy storage of power grids and new energy stations, the demand for indicators such as efficiency, single-unit capacity and dynamic response speed is getting higher and higher. Therefore, battery energy storage systems based on modular converter technology have received more and more attention and application. In order to obtain good output voltage and current harmonic characteristics, a large number of modules per phase of the modular battery energy storage system is required, usually no less than 8 for 6kV systems, no less than 12 for 10kV systems, and no less than 40 for 35kV systems.

[0004] The balanced control of batteries is an essential function of battery energy storage system. The modulation technology of modular converter is closely related to the implementation method of balanced control of modular battery energy storage system.

[0005] The modulation technologies for modular converters mainly include carrier stacking PWM modulation (LS-PWM), carrier phase shift PWM modulation (PS-PWM) and nearest level modulation. Carrier stacking PWM modulation will cause unbalanced power distribution between modules, so carrier rotation is required between different modules, which is more complicated. Carrier phase shift PWM modulation does not have this problem.

[0006] The intra-phase balancing based on carrier phase-shift PWM modulation adjusts the modulation wave size of each module, changes the size of power distribution between modules without changing the power direction, thereby achieving the purpose of online balancing.

[0007] Recently, level modulation has the advantages of good output waveform quality and low switching loss in situations where the number of modules per phase ranges from dozens to hundreds. It is widely used in situations where a large number of modules are required to achieve high-voltage flexible DC transmission and in high-voltage dynamic reactive generators. In view of the differences in parameters and losses between different modules, a capacitor voltage sorting algorithm is generally used to maintain the capacitor voltage balance of each module. The basic process is:

[0008] First, the capacitor voltage value of each submodule is monitored and input into the controller for sequencing.

[0009] Secondly, measure the direction of the bridge arm current to determine whether it charges or discharges the capacitors of each submodule. Thirdly, at the next level change moment, if the bridge arm current charges the submodule capacitor, the submodule with a lower capacitor voltage in the bridge tube will be put into operation; if the bridge arm current discharges the submodule capacitor, the submodule with a higher capacitor voltage in the bridge will be put into operation. Whether the capacitor voltage is high or low is determined by the order of the submodule capacitor voltages.

[0010] The above method is simple and effective, but it will lead to a higher switching frequency. In order to reduce the switching frequency and reduce the switching loss, there is a capacitor voltage optimization balance control method. Its basic principle is to set a set of upper and lower limits of voltage near the rated capacitor voltage, and focus the balance control on the sub-modules where the capacitor voltage exceeds the limit. For the sub-modules where the capacitor voltage does not exceed the limit, the capacitor voltage value is processed in combination with the charging and discharging conditions of the bridge arm current, and then sorted. The purpose of this treatment is to increase the probability that the sub-module where the capacitor voltage does not exceed the limit will maintain the original switching state when the next action of the trigger control is triggered to a certain extent, so as to reduce the switching frequency.

[0011] In the recent level-modulated modular battery energy storage system, the battery cluster voltage is used as the basis for sorting, imitating the capacitor voltage sorting method. Due to the inconsistency of the battery cells in the cluster, some batteries may be over-voltage or under-voltage, causing safety problems.

[0012] However, if the above capacitor voltage sorting method is directly applied to a modular cascade battery energy storage system using nearest level modulation, the inconsistency of battery cells within the cluster will cause some batteries to be over-voltage or under-voltage, thereby causing safety problems.

[0013] The online balancing control method based on carrier phase shift modulation to change the size of the modulation wave must use the deviation of active power to achieve balancing when the modular battery energy storage system inputs and outputs active power. If the system is not in an active charging and discharging state, the balancing function cannot be achieved.

[0014] In view of this, the present invention is proposed. Summary of the invention

[0015] In view of the defects in the prior art, the purpose of this application is to provide a method for realizing online intra-phase balancing in a modular battery energy storage system based on NLM, utilizing the reactive state of the system to realize online intra-phase balancing, eliminating the blind spots of traditional methods and expanding the scope of application of intra-phase balancing.

[0016] In one aspect of the present application, a method for realizing online balancing within a phase in a modular battery energy storage system based on NLM is provided, the method comprising:

[0017] S1. Obtain the SOC of the battery on the DC side of the module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x ;

[0018] S2. According to the project requirements, obtain the balancing index of each module, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules;

[0019] S3. Obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

[0020] Furthermore, in S2, it includes:

[0021] S21, set the charge and discharge balance indicators to EQU_CHG j,x ,EQU_DCHG j,x ;

[0022] S22, select SOC j,x and (1-SOC) j,x , as a balance indicator, or rechargeable energy SOE j,x and dischargeable energy SODE j,x as an indicator of equilibrium.

[0023] Furthermore, in S22, it includes:

[0024] When selecting SOC j,x and (1-SOC) j,x When used as a balance indicator, EQU_CHG j,x ,=(1-SOC) j,x ;EQU_DCHG j,x =SOC j,x ;

[0025] Rechargeable Energy SOE j,x and dischargeable energy SODE j,x When used as a balance indicator, EQU_CHG j,x ,=SODE j,x ;EQU_DCHG j,x =SOE j,x .

[0026] Furthermore, after S22, the method further includes:

[0027] S23, obtain the charge and discharge balance index EQU_CHG j,x ,EQU_DCHGj,x ;

[0028] S24, according to EQU_CHG j,x , and EQU_DCHG j,x The modules are sorted according to the set sorting method as the priority order for input during charging and discharging.

[0029] Further, in S24, the set sorting method is: sorting the modules of the phase in descending order.

[0030] Furthermore, after S24, the method further includes:

[0031] S25. List the battery voltage queues of all modules in this phase according to the priority order of charging: [U chg (1),U chg (2),U chg (3),…,U chg (n)];

[0032] S26. List the battery voltage queues of all modules in this phase according to the priority order of discharge: [U dchg (1),U dchg (2),U dchg (3),…,U dchg (n)].

[0033] Furthermore, S3 includes:

[0034] S31, at the beginning of each power control period Tp, the equalization algorithm needs to read the current modulation wave size Ux from the power control algorithm;

[0035] S32, monitoring the module current direction, and determining whether the current is charging or discharging the module battery at this moment;

[0036] S33. According to the current modulation wave size Ux and the battery voltage queue, determine the first k modules that should be put into use for current charging or discharging, and the total number k of modules put into use.

[0037] Furthermore, in S33, it specifically includes:

[0038] Determine when charging:

[0039] Then the first charging priority module is put into use;

[0040] Then the first and second charging priority modules are put into use;

[0041] Then the 1st, 2nd and 3rd charging priority modules are put into use;

[0042] And so on. Then the 1st, 2nd, ..., kth charging priority modules are put into use;

[0043] Until Stop the comparison and determine the total number k of modules put into charging;

[0044] Determine when to discharge:

[0045] Then the first discharge priority module is put into use;

[0046] Then the first and second discharge priority modules are put into use;

[0047] Then the 1st, 2nd and 3rd discharge priority modules are put into use;

[0048] And so on. Then the 1st, 2nd, ..., kth discharge priority modules are put into use;

[0049] Until Stop the comparison and determine the total number of modules put into discharge.

[0050] Further, in S1, wherein,

[0051] j=abc, indicating the phase where the module is located; x=1, 2, ..., N, indicating the serial number of the module in the phase or bridge arm.

[0052] A second aspect of the present invention provides a system for realizing intra-phase online balancing of a modular battery energy storage system based on NLM, comprising:

[0053] The acquisition module is used to obtain the SOC of the DC side battery of each module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x ;

[0054] The selection module is used to obtain the balancing index of each module according to the project needs, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules;

[0055] The determination module is used to obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

[0056] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0057] This application makes full use of the characteristic that the instantaneous power direction will change once in each power frequency cycle during the energy exchange process of AC reactive power. When the module power is discharging outward, the module with high discharge priority is put into operation first, and when the module power is charging inward, the module with high charging priority is put into operation first. Thus, the module balance within the phase is integrated into each power frequency cycle, and the balance control does not have any impact on the operating boundary of the system; the reactive state of the system is used to achieve the balance within the phase, eliminating the blind spots of the traditional method, expanding the adaptability of the balance within the phase, and realizing that some modules are charged and some modules are discharged in one power frequency cycle, and the balance speed is faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0059] Figure 1 This is a flow chart of a method for achieving online balancing within a phase in a modular battery energy storage system based on NLM according to an embodiment of the present application.

[0060] Figure 2 This is a flow chart of step S2 in one embodiment of the present application.

[0061] Figure 3 This is a flow chart of step S3 in one embodiment of the present application. DETAILED DESCRIPTION

[0062] The present application is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements can also be made without departing from the concept of the present application. These all belong to the protection scope of the present application.

[0063] The present application provides a method for realizing online intra-phase balancing in a modular battery energy storage system based on NLM, fully utilizing the energy exchange process of AC reactive power, integrating the module balancing within the phase into each power frequency cycle, and achieving balancing control without any impact on the operating boundary of the system; utilizing the reactive state of the system to realize intra-phase balancing, eliminating the blind spots of traditional methods, expanding the adaptability of intra-phase balancing, and realizing that some modules are charged and some modules are discharged within one power frequency cycle, and the balancing speed is faster.

[0064] Reference Figure 1 As shown, a method for realizing online balancing within a phase in a modular battery energy storage system based on NLM in an embodiment of the present application is shown, and the method includes:

[0065] S1. Obtain the SOC of the battery on the DC side of the module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x .

[0066] S2. According to the project requirements, obtain the balancing index of each module, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules.

[0067] S3. Obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

[0068] The present application ensures the balance between battery modules in the battery pack by real-time monitoring and dynamic adjustment of the SOC (state of charge) and chargeable / dischargeable energy of each module, thereby improving the cycle life and performance of the entire battery pack, and performing balancing control in combination with the reactive state of the system, breaking the limitation of traditional methods that only rely on a single parameter of voltage or SOC, and being able to achieve effective balancing under more complex working conditions, expanding the adaptability of the balancing strategy, and achieving faster balancing speed while some modules are charging and some modules are discharging within one power frequency cycle.

[0069] Specifically, assuming that the number of modules per phase of the modular cascade H-bridge battery energy storage system or the number of modules per bridge arm of the modular multi-level battery energy storage system is N, the battery management system (BMS) is used to collect the status information of the DC side battery of each module according to the preset balancing control period Tequ, including the state of charge SOC j,x 、(1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x .

[0070] Wherein, j=abc, indicating the phase where the module is located; x=1,2,…,N, indicating the serial number of the module in the phase or bridge arm.

[0071] Then, according to the engineering requirements and the real-time status of the battery module, the balancing index of each module is calculated, the priority order of charging and discharging is determined according to the balancing index, and the battery voltage queue of all modules is generated, where the voltage queue is: a list of modules sorted based on the balancing index. In each power control cycle, according to the current operating requirements of the system (such as reactive power status, load demand, etc.) and the size of the modulation wave, the first k modules that should be put into balancing operation are determined, and finally the total number of modules k to be put into operation is determined.

[0072] Among them, NLM (Nearest Level Modulation, NLM) is the SOC balancing strategy based on the nearest level modulation; S0C (State of Charge, SOC) is the charge state of the sub-module within the phase.

[0073] For example, there is an energy storage system with 4 battery modules, numbered A, B, C, and D. During a certain balancing control cycle, the BMS collects the following data:

[0074] SOC: A=80%, B=70%, C=90%, D=80%;

[0075] SOE: A=75kWh, B=65kWh, C=88kWh, D=80kWh;

[0076] SODE: A=20kWh, B=25kWh, C=8kWh, D=20kWh;

[0077] Based on these data and the preset balancing algorithm, the system calculates the balancing index of each module and sorts and determines the priority of charging and discharging. Assuming that the system currently needs to supplement a certain amount of reactive power, and considering the battery's SOC and chargeable and dischargeable energy, it is decided to select module C with a higher SOC and module D with the most dischargeable energy for discharge, while module B with a lower SOC and module A with the most chargeable energy for charging, thereby achieving intra-phase balancing. In a specific power control cycle, the number and order of modules actually put into balancing are determined based on the size and demand of the modulation wave.

[0078] Reference Figure 2 As shown, in some possible embodiments, in S2, it includes:

[0079] S21, set the charge and discharge balance indicators to EQU_CHG j,x ,EQU_DCHG j,x .

[0080] S22, select SOC j,x and (1-SOC) j,x , as a balance indicator, or rechargeable energy SOE j,x and dischargeable energy SODE j,x as an indicator of equilibrium.

[0081] In this application, the balancing indicators (SOC or maximum charge and discharge current) are obtained from the battery management system (BMS) and are continuously updated during operation, and the update cycle is generally within 1 second.

[0082] In the above embodiment, in S22, one specific implementation method includes:

[0083] When selecting SOC j,x and (1-SOC) j,x When used as a balance indicator, EQU_CHG j,x ,=(1-SOC) j,x ;EQU_DCHG j,x =SOC j,x .

[0084] In the above embodiment, another specific implementation is: rechargeable energy SOE j,x and dischargeable energy SODE j,x When used as a balance indicator, EQU_CHG j,x ,=SODE j,x ;EQU_DCHG j,x =SOE j,x .

[0085] According to the engineering requirements, select appropriate equalization indicators, which can be based on SOC (EQU_CHG j,x =(1-SOC) j,x ,EQU_DCHG j,x =SOC j,x ) or based on chargeable / dischargeable energy (EQU_CHG j,x =SODE j,x ,EQU_DCHG j,x =SOE j,x ) The system can flexibly choose to use SOC or chargeable and dischargeable energy as the balancing indicator according to different operating conditions and requirements, which helps to cope with complex operating conditions and ensure the effectiveness of the balancing strategy. At the same time, the balancing indicator based on SOC can directly reflect the remaining capacity of the battery, while the balancing indicator based on chargeable and dischargeable energy takes into account the current state of the battery and the future charge and discharge capabilities, and more accurately evaluates the balancing needs of the battery module, thereby achieving more refined balancing control.

[0086] In the above embodiment, after S22, the method further includes:

[0087] S23, obtain the charge and discharge balance indicator EQU_CHG j,x ,EQU_DCHG j,x .

[0088] S24, according to EQU_CHG j,x , and EQU_DCHG j,x The modules are sorted according to the set sorting method as the priority order for input during charging and discharging.

[0089] In the above embodiment, in S24, the sorting method is set as: sorting the modules of the phase in descending order.

[0090] Specifically, assuming that the charge equalization indicator is EQU_CHG j,x ,EQU_DCHG j,x . Select SOC according to project needs. j,x and (1-SOC) j,x , as a balance indicator, or rechargeable energy SOE j,x and dischargeable energy SODE j,x As a balance indicator. That is, EQU_CHG j,x ,=(1-SOC) j,x ;EQU_DCHG j,x =SOC j,x ; or EQU_CHG j,x ,=SODE j,x ;EQU_DCHG j,x =SOE j,x . And respectively for EQU_CHG j,x , and EQU_DCHG j,x The modules of the phase are sorted in descending order as the priority order for input during charging and discharging.

[0091] The module with the highest priority when charging is called the first charging priority module, the module with the second charging priority is called the second charging priority module, and so on, until the Nth charging priority module.

[0092] The module with the highest priority during discharge is called the first discharge priority module, the module with the second discharge priority is called the second discharge priority module, and so on, until the Nth discharge priority module.

[0093] In the above embodiment, after S24, the method further includes:

[0094] S25. List the battery voltage queues of all modules in this phase according to the priority order of charging: [U chg (1),U chg (2),U chg (3),…,U chg (n)].

[0095] S26. List the battery voltage queues of all modules in this phase according to the priority order of discharge: [U dchg (1),U dchg (2),U dchg (3),…,U dchg (n)].

[0096] This application calculates the charging and discharging balancing indexes and sorts the modules according to the set sorting method (such as descending order). The system can clearly determine the priority order of each module in the balancing process, and the battery voltage queue generated according to the sorting results provides the system with flexible dynamic adjustment space. It helps the system to perform balancing control more efficiently, reduce balancing time, and improve overall efficiency. When the system is running, the modules in the queue can be dynamically selected for balancing operations according to actual needs, achieving more precise balancing control.

[0097] Specifically, according to the actual state and needs of the system, select appropriate balancing indicators (such as SOC, chargeable and dischargeable energy, etc.) for calculation. For example, when charging, use (1-SOC) or dischargeable energy as the charging balancing indicator; when discharging, use SOC or chargeable energy as the discharge balancing indicator. Then, obtain the calculated charging and discharging balancing indicator values ​​from the system, sort the module's balancing indicators according to the set sorting method (such as descending order), and the sorting results will be used as the priority order of the modules during charging and discharging; generate a battery voltage queue, for the charging process, list the battery voltage queues of all modules according to the priority order of charging; for the discharging process, list the queues according to the priority order of discharging.

[0098] U chg and Udchg They all represent the module battery voltage.

[0099] Sort the modules according to the charge balancing index, and take the module voltages one by one in order to get [U chg (1),U chg (2),U chg (3),…,U chg (n)].

[0100] Sort the modules according to the discharge balance index, and take the module voltages one by one in order to get [U dchg (1),U dchg (2),U dchg (3),…,U dchg (n)].

[0101] For example, there are three battery modules A, B, and C, whose charging balance indicators (taking (1-SOC) as an example) are 0.3, 0.2, and 0.1, respectively, and their discharging balance indicators (taking SOC as an example) are 0.7, 0.8, and 0.9, respectively. Sort the balance indicators of the modules in descending order to get the charging and discharging priorities. For the charging process, the priority results obtained by sorting are A, B, and C (because 0.3>0.2>0.1); for the discharging process, the priority results obtained by sorting are C, B, and A (because 0.9>0.8>0.7).

[0102] Reference Figure 3 As shown, in some possible embodiments, in S3, it includes:

[0103] S31. At the beginning of each power control period Tp, read the current modulation wave size Ux.

[0104] Specifically, the equalization algorithm of the present application reads the current modulation wave size Ux from the power control algorithm, wherein the power control algorithm generates the instantaneous value size Ux of the modulation wave, which is passed as a result variable to the equalization algorithm of the present application as input. The power control algorithm is an independent algorithm, and there are many different implementation methods, which are not described in this application as prior art.

[0105] In the prior art, even if the modular battery energy storage system is in an operating state where only active power is interacted with the grid, the phase of the modulation wave is different from the phase of the grid-connected current due to the voltage phase deviation caused by the grid-connected inductance. Therefore, in most operating states, the modulation wave and current waveform of the modular battery energy storage system will be in phase or in reverse within one power frequency cycle.

[0106] During the period when the two are in phase, the instantaneous power state of the energy storage system is to emit power outward, and at this time, the module with high SOC is discharged first; during the period when the two are in phase, the instantaneous power state of the energy storage system is to absorb power from the outside, and at this time, the module with low SOC is charged first. In this way, different modules can be charged and discharged as needed within one power frequency cycle, thereby achieving balance of modules within the phase. Different from the traditional online balancing control method based on carrier phase shift modulation, which only adjusts the charging power or discharging power of the module without changing the balancing idea of ​​power direction, this application realizes that some modules are charged and some modules are discharged within one power frequency cycle, and the balancing speed is faster.

[0107] S32, monitoring the module current direction, and determining whether the current is charging or discharging the module battery at this moment.

[0108] S33. According to the current modulation wave size Ux and the battery voltage queue, determine the first k modules that should be put into use for current charging or discharging, and the total number k of modules put into use.

[0109] Specifically, at the beginning of each power control cycle Tp, the balancing algorithm first interacts with the power control algorithm to read the current modulation wave size Ux; the balancing algorithm needs to monitor the current direction of the battery module in the current system, which is achieved by measuring the voltage and current at both ends of the battery module, and combined with the system's operating status (such as charging mode or discharging mode) to determine whether the current is charging or discharging the module battery; based on the read modulation wave size Ux and the previously generated battery voltage queue, the balancing algorithm will determine the first k modules that should be charged or discharged in the current power control cycle. Among them, k is a dynamic value that depends on the total demand of the system, the modulation wave size, and the capacity and status of each module.

[0110] If the current process is charging, the balancing algorithm will select the first k modules for charging according to the priority order of charging (i.e., the modules with the highest order in the battery voltage queue); similarly, if the current process is discharging, the modules will be selected according to the priority order of discharging.

[0111] This application can more accurately control the balancing process, reduce unnecessary energy losses, and improve balancing efficiency by dynamically determining the module to be charged or discharged according to the size of the modulation wave and the state of the battery module. In principle, the battery energy storage system can operate in a combined active and reactive operating state; however, the traditional online balancing control method based on carrier phase shift modulation must use the deviation of active power to achieve balancing when the modular battery energy storage system inputs and outputs active power; if the system is not in an active charging and discharging state, the balancing function cannot be achieved. This application uses the reactive state of the system to achieve intra-phase balancing, eliminating the blind spots of traditional methods and expanding the scope of application of intra-phase balancing.

[0112] The previous online balancing control method must use the deviation of active power to achieve balancing when the modular battery energy storage system inputs and outputs active power. If the system is not in an active charging and discharging state, the balancing function cannot be achieved. The present invention uses the reactive state of the system to achieve intra-phase balancing, eliminating the blind spots of traditional methods and expanding the scope of application of intra-phase balancing.

[0113] For example: suppose there are three battery modules A, B, and C, and their charging priority order is A>B>C (sorted based on a certain balance indicator). The current system is in charging mode, and the modulation wave size Ux indicates that the system requires a certain charging current.

[0114] Read the modulation wave size: The equalization algorithm reads the current modulation wave size Ux from the power control algorithm.

[0115] Monitor current direction: Confirm that the current direction is charging through monitoring.

[0116] Determine the modules to be charged: Based on the modulation wave size Ux and the charging priority order (A>B>C), the balancing algorithm determines the first k modules to be charged in the current power control cycle. If k is equal to 1, only module A is charged; if k is equal to 2, modules A and B are charged; and so on. If k is greater than the total number of modules, all modules are charged. The balancing algorithm dynamically adjusts the number and order of modules to be charged to ensure that the system can efficiently complete the charging task, and uses the reactive state of the system to achieve intra-phase balancing, eliminating the blind spots of traditional methods and expanding the scope of adaptability of intra-phase balancing.

[0117] In the above embodiment, S33 specifically includes:

[0118] Determine when charging:

[0119] Then the first charging priority module is put into use;

[0120] Then the first and second charging priority modules are put into use.

[0121] Then the 1st, 2nd and 3rd charging priority modules are put into use.

[0122] And so on. Then the 1st, 2nd, ..., kth charging priority modules are put into use.

[0123] Until Stop the comparison and determine the total number k of modules put into charging.

[0124] Determine when to discharge:

[0125] Then the first discharge priority module is put into operation.

[0126] Then the first and second discharge priority modules are activated.

[0127] Then the 1st, 2nd and 3rd discharge priority modules are put into operation.

[0128] And so on. Then the 1st, 2nd, ..., kth discharge priority modules are put into operation.

[0129] Until Stop the comparison and determine the total number of modules put into discharge.

[0130] In the above charging and discharging process, from the beginning of determining the input module, the last one of each cumulative comparison is divided by 2 to achieve the rounding effect.

[0131] Specifically, according to the priority order of charging, the battery voltage queues of all modules in this phase are listed [U chg (1),U chg (2),U chg (3),...,U chg (n)]; Similarly, according to the priority order of input during discharge, the battery voltage queue of all modules in this phase is listed [U dchg (1),U dchg (2),U dchg (3),...,U dchg (n)]; At the beginning of each power control cycle Tp, the balancing algorithm obtains the current modulation wave size Ux from the power control algorithm, and at the same time, monitors the direction of the module current to determine whether it is currently in a charging state or a discharging state.

[0132] Charging status processing:

[0133] If the module current charges the battery, compare and judge according to the following steps:

[0134] a) If Then the first charging priority module is put into use;

[0135] b) If Then the first and second charging priority modules are put into use.

[0136] c) If Then the 1st, 2nd and 3rd charging priority modules are put into use.

[0137] d) And so on, such as Then the 1st, 2nd, ..., kth charging priority modules are put into use.

[0138] e) Until Stop comparison. The k+1, k+2, ..., nth charging priority modules are not put into operation.

[0139] According to the above comparison results, the first k modules that should be put into use are determined, and the total number k of modules put into use is recorded.

[0140] For example: Assume that a phase has 3 modules, and their battery voltages are U chg (1)=400V,U chg (2)=380V,U chg (3) = 390V, and the current modulation wave size Ux = 500V.

[0141] In the charging state, first calculate It is smaller than Ux, so the first module is invested.

[0142] Then calculate It is greater than Ux, so the second module is not invested.

[0143] Since the maximum number of modules that meet the conditions (i.e., 1) has been found, the comparison is stopped.

[0144] Finally, only the first module is put into charging, achieving the purpose of dynamically adjusting the module input status according to the battery voltage and the modulation wave size.

[0145] The same goes for battery discharge.

[0146] A second aspect of the present invention provides a system for realizing online balancing within a phase of a modular battery energy storage system based on NLM, comprising:

[0147] The acquisition module is used to obtain the SOC of the DC side battery of each module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x .

[0148] The module selection is used to obtain the balancing index of each module according to the project needs, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules.

[0149] The determination module is used to obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

[0150] Specifically, the SOC (state of charge) of the DC side battery of each module is obtained through the battery management system (BMS) in each balancing control cycle Tequ by acquiring module timing data collection. j,x 、(1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x Where j = abc, indicating the phase where the module is located; x = 1, 2, ..., N, indicating the serial number of the module in the phase or bridge arm. Select the module according to the project requirements and select the appropriate balancing index. For example, you can select SOC j,x and (1-SOC) j,x As a balance indicator for charging and discharging, or choose SOE j,x and SODE j,x . And the charging balance index (such as (1-SOC) j,x or SODE j,x ) in descending order to determine the priority order of input during charging. j,x or SOE j,x) are also sorted in descending order to determine the priority order of input during discharge, and finally generate a battery voltage queue. Determine the module in each power control cycle Tp, obtain the current modulation wave size Ux from the power control algorithm, and at the same time, monitor the direction of the module current to determine whether it is currently in a charging state or a discharging state. If it is in a charging state, according to the charging priority order and the modulation wave size Ux, follow the steps described previously (such as accumulating voltage and comparing) to determine the first k modules to be put into use. If it is in a discharging state, similarly determine the modules to be put into use according to the discharge priority order and Ux. Record the total number of modules currently put into use, k.

[0151] By periodically acquiring battery status information and sorting based on balancing indicators, the system can dynamically adjust the module input status, thereby effectively balancing the SOC or energy status of each battery in the battery pack, reducing the inconsistency between batteries, and making full use of the energy exchange process of AC reactive power. The module balance within the phase is integrated into each power frequency cycle, and the balancing control does not have any impact on the operating boundary of the system; in one power frequency cycle, some modules are charged and some modules are discharged, and the balancing speed is faster. The reactive state of the system is used to achieve intra-phase balancing, eliminating the blind spots of traditional methods and expanding the adaptability of intra-phase balancing.

[0152] The above describes the specific embodiments of the present application. It should be understood that the present application is not limited to the above specific embodiments, and those skilled in the art can make various modifications or variations within the scope of the claims, which does not affect the substantive content of the present application. The above preferred features can be used in any combination without conflicting with each other.

Claims

1. A method for realizing intra-phase online balancing in a modular battery energy storage system based on NLM, characterized in that: The method comprises: S1. Obtain the SOC of the battery on the DC side of the module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x ; S2. According to the project requirements, obtain the balancing index of each module, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules; S3. Obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

2. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 1, characterized in that: In S2, it includes: S21, set the charge and discharge balance indicators to EQU_CHG j,x ,EQU_DCHG j,x ; S22, select SOC j,x and (1-SOC) j,x , as a balance indicator, or rechargeable energy SOE j,x and dischargeable energy SODE j,x as an indicator of equilibrium.

3. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 2, characterized in that: In S22, it includes: When selecting SOC j,x and (1-SOC) j,x When used as a balance indicator, EQU_CHG j,x , = (1-SOC) j,x ;EQU_DCHG j,x =SOC j,x ; Rechargeable Energy SOE j,x and dischargeable energy SODE j,x When used as a balance indicator, EQU_CHG j,x ,=SODE j,x ;EQU_DCHG j,x =SOE j,x .

4. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 2, characterized in that: After S22, it also includes: S23, obtain the charge and discharge balance indicator EQU_CHG j,x ,EQU_DCHG j,x ; S24, according to EQU_CHG j,x , and EQU_DCHG j,x The modules are sorted according to the set sorting method as the priority order for input during charging and discharging.

5. The method for realizing intra-phase online balancing in a modular battery energy storage system based on NLM according to claim 4, characterized in that: In S24, the set sorting method is: sorting the modules of the phase in descending order.

6. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 5, characterized in that: After S24, it also includes: S25. List the battery voltage queues of all modules in this phase according to the priority order of charging: [U chg (1),U chg (2),U chg (3),…,U chg (n)]; S26. List the battery voltage queues of all modules in this phase according to the priority order of discharge: [U dchg (1),U dchg (2),U dchg (3),…,U dchg (n)].

7. The method for realizing intra-phase online balancing in a modular battery energy storage system based on NLM according to claim 1, characterized in that: In S3, this includes: S31, at the beginning of each power control period Tp, the equalization algorithm needs to read the current modulation wave size Ux from the power control algorithm; S32, monitoring the module current direction, and determining whether the current is charging or discharging the module battery at this moment; S33. According to the current modulation wave size Ux and the battery voltage queue, determine the first k modules that should be put into use for current charging or discharging, and the total number k of modules put into use.

8. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 7, characterized in that: In S33, specifically including: Determine when charging: Then the first charging priority module is put into use; Then the first and second charging priority modules are put into use; Then the 1st, 2nd and 3rd charging priority modules are put into use; And so on. Then the 1st, 2nd, ..., kth charging priority modules are put into use; Until Stop the comparison and determine the total number k of modules put into charging; Determine when to discharge: Then the first discharge priority module is put into use; Then the first and second discharge priority modules are put into use; Then the 1st, 2nd and 3rd discharge priority modules are put into use; And so on. Then the 1st, 2nd, ..., kth discharge priority modules are put into use; Until Stop the comparison and determine the total number of modules put into discharge.

9. The method for realizing online balancing within a phase in a modular battery energy storage system based on NLM according to claim 1, characterized in that: In S1, j=abc, indicating the phase where the module is located; x=1, 2, ..., N, indicating the serial number of the module in the phase or bridge arm.

10. A system for realizing intra-phase online balancing of a modular battery energy storage system based on NLM, characterized in that: include: The acquisition module is used to obtain the SOC of the DC side battery of each module through the battery management system BMS according to the balancing control cycle Tequ j,x and (1-SOC) j,x , Rechargeable Energy SOE j,x and dischargeable energy SODE j,x ; The selection module is used to obtain the balancing index of each module according to the project needs, determine the input priority order during charging and discharging, and generate the battery voltage queue of all modules; The determination module is used to obtain the size of the modulation wave in each power control cycle, determine the first k modules that should be put into use, and the total number k of modules put into use.

Images