Charge balance control method and device of battery energy storage system, equipment and medium

Abstract

The embodiment of the invention provides a charge balance control method and device for a battery energy storage system, equipment and a medium, and the method comprises the steps: constructing a state of charge (SOC) physical model according to the pre-collected physical parameters of each battery in the battery energy storage system, and setting a target value based on a preset control target, and through a preset control protocol and an SOC physical model, each battery performs iterative calculation based on the current state and the received information of other batteries until the SOC value of each battery reaches an SOC target value and the output power value of each battery reaches an output power target value, and a control target is met. According to the scheme, through constructing an SOC physical model, setting a control target value and implementing an iterative calculation process, state-of-charge balance control and supply-demand balance of the distributed battery energy storage system with switching topology and non-uniform communication delay are realized.

Description

Technical Field

[0001] The present application relates to the field of electric energy storage technology, and in particular to a charge balance control method, device, equipment and medium for a battery energy storage system. Background Art

[0002] In the power system, power generation and load demand change over time, which poses a severe challenge to the balance of power supply and demand. In order to meet user needs and ensure the stable operation of the power system, the Battery Energy Storage System (BESS) has emerged as an effective solution. BESS can not only provide additional power when power generation is insufficient, but also store excess power when the load is low, so as to achieve the rational allocation and utilization of power. Especially in microgrids, the introduction of BESS is of great significance to improving system stability and flexibility. However, the effective operation of BESS depends on reasonable active power distribution and state of charge (SOC) management, which is the key to ensure that BESS can work continuously and efficiently.

[0003] In order to achieve the SOC balance of BESS, the existing technology mainly adopts the supply and demand balance and SOC balance control strategies. The supply and demand balance strategy ensures that the power output of BESS can meet the load demand, and matches the load changes by adjusting the active power in real time. The SOC balance strategy focuses on the balance of the state of charge between energy storage units of different capacities, and keeps the SOC values ​​of each energy storage unit dynamically consistent through the control algorithm. This balancing strategy helps to avoid overcharging and overdischarging of the battery system, extend the battery life, and improve the overall performance of BESS. However, in practical applications, due to the instability of the communication link and the dynamic changes of the topology, such as bandwidth limitations, data packet loss, time delays, and disconnection and reconnection of links between batteries, the SOC balance control of BESS has brought great challenges.

[0004] In summary, how to solve the BESS scheduling problem with communication delay and inter-battery communication switching links is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0005] The embodiments of the present application provide a charge balance control method, device, equipment and medium for a battery energy storage system, which are used to solve the BESS scheduling problem with communication delay and inter-battery communication switching links.

[0006] In a first aspect, an embodiment of the present application provides a charge balance control method for a battery energy storage system, comprising:

[0007] Constructing a state of charge (SOC) physical model based on pre-collected physical parameters of each battery in the battery energy storage system, wherein the SOC physical model is used to calculate the SOC value of each battery;

[0008] Setting a target value based on a preset control target, the target value including an SOC target value and an output power target value;

[0009] Through the preset control protocol and the SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries until the SOC value of each battery reaches the SOC target value and the output power value of each battery reaches the output power target value, satisfying the control objective. The control protocol is based on SOC control gain, speed tracking error gain and speed control gain as well as communication delay, and is designed through multi-agent consistency control theory.

[0010] In a possible implementation, the preset control protocol and the SOC physical model are used to iteratively calculate each battery based on the current state and the received information of other batteries, including:

[0011] Introducing auxiliary variables into the SOC physical model to obtain a kinetic model;

[0012] Determine a control input model based on a preset tracking allocation relationship and gain coefficient and a communication delay;

[0013] The current state of each battery and the received information of other batteries are controlled based on the control input model, and iterative calculation is performed in conjunction with the kinetic model.

[0014] In a possible implementation manner, constructing the SOC physical model according to the pre-collected physical parameters of each battery in the battery energy storage system includes:

[0015] For each battery, construct a first physical model according to an initial SOC value of the battery, a capacity of the battery, a charge and discharge coefficient of the battery, and an output current of the battery;

[0016] The first physical model is discretized and simplified to obtain the SOC physical model.

[0017] In a possible implementation, the method further includes:

[0018] The control target is set according to the SOC value and output power of each battery.

[0019] In a possible implementation manner, setting the control target according to the SOC value and output power of each battery includes:

[0020] The SOC value of each battery is equal to the SOC target value, the output power value of each battery is equal to the output power target value, and the total power of the battery energy storage system is equal to the supply-demand deviation, which are set as initial control targets;

[0021] An auxiliary speed variable is introduced into the initial control target to transform the initial control target into the control target.

[0022] In a possible implementation, the method further includes:

[0023] For each battery, the output current corresponding physical model of the battery is determined according to the power, output voltage of the battery and the conversion efficiency of the rectifier during discharge and charge operations.

[0024] In a possible implementation manner, before discretizing and simplifying the first physical model to obtain the SOC physical model, the method further includes:

[0025] Convert the first physical model based on the physical model corresponding to the output current to obtain a second physical model;

[0026] Accordingly, the first physical model is discretized and simplified to obtain the SOC physical model, including:

[0027] The second physical model is discretized and simplified to obtain the SOC physical model.

[0028] In a second aspect, an embodiment of the present application provides a charge balance control device for a battery energy storage system, comprising:

[0029] A construction module, used to construct a state of charge (SOC) physical model based on pre-collected physical parameters of each battery pack in the battery energy storage system, wherein the SOC physical model is used to calculate the SOC value of each battery pack;

[0030] A setting module, used for setting a target value based on a preset control target, wherein the target value includes an SOC target value and an output power target value;

[0031] The iterative module is used to perform iterative calculations on each battery pack based on the current state and the information received from other battery packs through a preset control protocol and the SOC physical model until the SOC value of each battery pack reaches the SOC target value and the output power value of each battery pack reaches the output power target value, thereby satisfying the control objective. The control protocol is designed based on the SOC control gain, speed tracking error gain, speed control gain and communication delay through multi-agent consistency control theory.

[0032] In a possible implementation, the iteration module is specifically used to:

[0033] Introducing auxiliary variables into the SOC physical model to obtain a kinetic model;

[0034] Determine a control input model based on a preset tracking allocation relationship and gain coefficient and a communication delay;

[0035] The current state of each battery and the received information of other batteries are controlled based on the control input model, and iterative calculation is performed in conjunction with the kinetic model.

[0036] In a possible implementation manner, the building block is specifically used to:

[0037] For each battery, construct a first physical model according to an initial SOC value of the battery, a capacity of the battery, a charge and discharge coefficient of the battery, and an output current of the battery;

[0038] The first physical model is discretized and simplified to obtain the SOC physical model.

[0039] In a possible implementation manner, the setting module is further used to:

[0040] The control target is set according to the SOC value and output power of each battery.

[0041] In a possible implementation manner, the setting module is specifically configured to:

[0042] The SOC value of each battery is equal to the SOC target value, the output power value of each battery is equal to the output power target value, and the total power of the battery energy storage system is equal to the supply-demand deviation, which are set as initial control targets;

[0043] An auxiliary speed variable is introduced into the initial control target to transform the initial control target into the control target.

[0044] In a possible implementation, the device further includes:

[0045] The determination module is used to determine, for each battery, a physical model corresponding to the output current of the battery according to the power, output voltage of the battery and conversion efficiency of the rectifier during discharge and charge operations.

[0046] In a possible implementation, the device further includes:

[0047] A conversion module, configured to convert the first physical model based on the physical model corresponding to the output current to obtain a second physical model;

[0048] Accordingly, the construction module discretizes and simplifies the first physical model to obtain the SOC physical model, which specifically includes:

[0049] The second physical model is discretized and simplified to obtain the SOC physical model.

[0050] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0051] The memory stores computer-executable instructions;

[0052] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0053] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0054] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0055] The charge balance control method, device, equipment and medium of the battery energy storage system provided in the embodiment of the present application build a state of charge SOC physical model based on the pre-collected physical parameters of each battery in the battery energy storage system, set the target value based on the pre-set control target, and through the preset control protocol and SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries until the SOC value of each battery reaches the SOC target value and the output power value of each battery reaches the output power target value, and the control target is met. Through accurate SOC monitoring and prediction, as well as optimized control strategies, the charging and discharging efficiency of the battery energy storage system is improved, and efficient energy utilization is achieved. By avoiding overcharging or over-discharging of batteries and balancing the SOC between batteries, the service life of the battery is extended and the cost of replacing batteries is reduced. The distributed control strategy and iterative calculation process ensure the stability and reliability of the system, and the normal operation of the system can be maintained even when some batteries fail or communication delays occur, thereby realizing the charge state balance control and supply and demand balance of the distributed battery energy storage system with switching topology and non-uniform communication delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0057] Figure 1 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 1 ;

[0058] Figure 2 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 2 ;

[0059] Figure 3 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 3 ;

[0060] Figure 4 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 4 ;

[0061] Figure 5 are four directed graphs of BESS;

[0062] Figure 6 is a schematic diagram of a finite switching mechanism with four states;

[0063] Figure 7 P with switching topology and non-uniform delay communication topology for different battery capacities i and SOC iterative simulation schematic;

[0064] Figure 8 P with the same battery capacity with switching topology and non-uniform delay communication topology i and SOC iterative simulation schematic;

[0065] Fig. 9 A schematic diagram of the structure of a charge balance control device for a battery energy storage system provided in this application;

[0066] Fig.10 A schematic diagram of the structure of the electronic device provided in this application.

[0067] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0068] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0069] The following is an explanation of professional terms:

[0070] Battery Energy Storage System (BESS): A system that uses lithium batteries or lead batteries as energy storage carriers to store and supply electrical energy for a certain period of time. The electrical energy provided by this system has functions such as smooth transition, peak shaving and valley filling, frequency and voltage regulation, etc. It is an important part of the modern energy field, and its efficient operation is inseparable from the synergy of multiple core systems, including battery packs, battery management systems, energy management systems, energy storage converters, etc.

[0071] State of Charge (SOC): The available state of charge remaining in the battery, that is, the current charge level of the battery, indicating the proportion of the electrical energy stored in the battery to its total capacity. Value range: The value range of SOC is 0-1. When SOC=0, it means that the battery is fully discharged, and when SOC=1, it means that the battery is fully charged.

[0072] In the power system, power generation and load demand change over time, which poses a severe challenge to the balance of power supply and demand. In order to meet user needs and ensure the stable operation of the power system, BESS has emerged as an effective solution. BESS can not only provide additional power when power generation is insufficient, but also store excess power when the load is low, so as to achieve the reasonable allocation and utilization of power. Especially in microgrids, the introduction of BESS is of great significance to improving system stability and flexibility. However, the effective operation of BESS depends on reasonable active power distribution and SOC management, which is the key to ensure that BESS can work continuously and efficiently. In order to achieve the SOC balance of BESS, the existing technology mainly adopts supply and demand balance and SOC balance control strategies. The supply and demand balance strategy ensures that the power output of BESS can meet the load demand by adjusting the active power in real time to match the load changes. The SOC balance strategy focuses on the balance of the state of charge between energy storage units of different capacities, and keeps the SOC values ​​of each energy storage unit dynamically consistent through the control algorithm. This balance strategy helps to avoid overcharging and overdischarging of the battery system, prolong the battery life, and improve the overall performance of BESS. However, in practical applications, the instability of communication links and the dynamic changes of topology structures, such as bandwidth limitation, data packet loss, time delay, and disconnection and reconnection of battery links, pose great challenges to the SOC balance control of BESS.

[0073] In view of the above problems, the present application provides a charge balance control method, device, equipment and medium for a battery energy storage system to solve the BESS scheduling problem with communication delay and inter-battery communication switching link. Specifically, the prior art mainly adopts supply and demand balance and SOC balance control strategies. The supply and demand balance strategy ensures that the power output of the BESS can meet the load demand and matches the load change by adjusting the active power in real time. The SOC balance strategy focuses on the balance of the state of charge between energy storage units of different capacities, and keeps the SOC values ​​of each energy storage unit dynamically consistent through the control algorithm. This balance strategy helps to avoid overcharging and overdischarging of the battery system, extend the battery life, and improve the overall performance of the BESS. However, in practical applications, due to the instability of the communication link and the dynamic changes of the topology, such as bandwidth limitation, data packet loss, time delay, and disconnection and reconnection of the inter-battery link, the SOC balance control of the BESS is greatly challenged. In view of these problems, the inventor studied whether it is possible to design an auxiliary variable tracking strategy to achieve charge state balance control of a distributed BESS with switching topology and non-uniform communication delay. The total active power of BESS globally asymptotically tracks the supply-demand mismatch, while the SOC value converges asymptotically to a common value, non-uniform communication delays can be safely tolerated, and even the communication connection between batteries may not have a directed spanning tree. The design of the control strategy ensures that the final SOC values ​​of all BESSs are equal and the required output power is shared, which achieves the balance between SOC state of charge and supply and demand. Based on this, the solution of this application is proposed.

[0074] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0075] Figure 1 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0076] S101: Construct a SOC physical model based on pre-collected physical parameters of each battery in the battery energy storage system.

[0077] In this step, in order to ensure the SOC balance of the battery energy storage system (BESS), it is first necessary to accurately calculate the SOC value of each battery in the battery energy storage system. Therefore, it is necessary to collect the physical parameters of each battery in the BESS in advance, and then construct the SOC physical model based on the physical parameters. The SOC physical model can be used to calculate the SOC value of each battery.

[0078] Specifically, for each battery, a first physical model is constructed according to the initial SOC value of the battery, the capacity of the battery, the charge and discharge coefficient of the battery, and the output current of the battery; a physical model corresponding to the output current of the battery is determined according to the power, output voltage of the battery, and the conversion efficiency of the rectifier during discharge and charging operations; the first physical model is transformed based on the physical model corresponding to the output current to obtain a second physical model; the second physical model is discretized and simplified to obtain an SOC physical model.

[0079] It should be noted that the pre-collected physical parameters may include battery capacity, internal resistance, charge and discharge efficiency, etc. The constructed SOC physical model describes how the SOC value of the battery changes over time and how it is affected by the charge and discharge operations.

[0080] The SOC physical model can be expressed by the following formula:

[0081]

[0082] Among them, t+δ represents the time t+δ, δ represents the sampling interval, , For the The charge and discharge coefficient of each battery satisfies the , in charging mode , and the Coulomb efficiency , For the The output voltage of each battery, Indicates The capacity of the battery, Indicates The output power of each battery, Indicates The conversion efficiency of a rectifier during discharge and charge operation.

[0083] It should be noted that the use of discrete time equations to describe the SOC physical model is convenient for processing and analysis in digital systems. The introduction of the sampling interval δ allows the SOC to be updated at discrete time points. And the battery's SOC value can be easily updated in each sampling cycle.

[0084] S102: Setting a target value based on a pre-set control target.

[0085] In this step, in order to achieve battery state of charge balance and supply-demand balance for BESS, the specific state or performance index that the BESS is expected to achieve during operation can be set as a target value, wherein the set target value generally includes an SOC target value and an output power target value.

[0086] Specifically, the SOC target value is the SOC level that all battery packs are expected to eventually reach, which is used to achieve a balance in battery state of charge, extend battery life, and optimize the overall performance of the BESS. The output power target value is the output power that the BESS needs to provide to meet the supply and demand balance of the power system and support the stable operation of the power grid.

[0087] It should be noted that the set target value is a specific manifestation of the control target. By setting specific SOC target values ​​and output power target values, the control target is converted into a quantifiable and traceable indicator.

[0088] The designed control objectives provide guidance for setting target values. For example, in order to achieve battery state of charge balance, a reasonable SOC target value needs to be set; in order to achieve supply and demand balance, the output power target value needs to be set according to the real-time needs of the power system.

[0089] In the control strategy of BESS, the set target value and control target are interrelated and mutually reinforcing. By implementing the control strategy, the SOC and output power of BESS gradually approach the set target value, thereby achieving the control target of battery state of charge balance and supply and demand balance.

[0090] When the SOC and output power of the BESS successfully approach the set target values, it can be considered that the control target has been achieved. At this time, the BESS not only achieves the balance of the battery state of charge, but also meets the supply and demand balance requirements of the power system.

[0091] S103: Through the preset control protocol and SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries until the SOC value of each battery reaches the SOC target value and the output power value of each battery reaches the output power target value, thereby meeting the control target.

[0092] In this step, in order for BESS to achieve SOC balance and supply and demand balance, data sharing is required between batteries, including SOC, output power and other information. Based on the pre-set control protocol, each battery will be iteratively updated according to its current state and the information received from other batteries. This control protocol will ensure that each battery can still work in a coordinated and consistent manner in a complex communication environment and gradually approach the set control target. According to the control protocol, each battery will continuously update its output power and SOC set values. Through continuous iterative updates, the SOC and output power of each battery will gradually approach the set target values, achieving battery state of charge balance and supply and demand balance. Among them, the control protocol is designed based on SOC control gain, speed tracking error gain, speed control gain and communication delay through multi-agent consistency control theory.

[0093] Specifically, auxiliary variables are introduced into the SOC physical model to obtain a dynamic model. Based on the preset tracking allocation relationship, gain coefficient and communication delay, a control input model is determined. Based on the control input model, the current state of each battery and the information received from other batteries are controlled, and iterative calculations are performed in conjunction with the dynamic model.

[0094] The charge balance control method of the battery energy storage system provided in the embodiment of the present application builds a state of charge SOC physical model based on the pre-collected physical parameters of each battery in the battery energy storage system, sets a target value based on a pre-set control target, and through a preset control protocol and SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries until the SOC value of each battery reaches the SOC target value and the output power value of each battery reaches the output power target value, thereby meeting the control target. Through accurate SOC monitoring and prediction, as well as optimized control strategies, the charging and discharging efficiency of the battery energy storage system is improved, and efficient energy utilization is achieved. By avoiding overcharging or over-discharging of batteries and balancing the SOC between batteries, the service life of the battery is extended and the cost of replacing batteries is reduced. The distributed control strategy and iterative calculation process ensure the stability and reliability of the system, and the normal operation of the system can be maintained even when some batteries fail or communication delays occur, thereby achieving charge state balance control and supply and demand balance of a distributed battery energy storage system with switching topology and non-uniform communication delay.

[0095] Figure 2 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 2 ,like Figure 2 As shown, based on the above embodiment, step S103 specifically includes:

[0096] S201: Introduce auxiliary variables into the SOC physical model to obtain a dynamic model.

[0097] In this step, a BESS with N nodes is considered, and auxiliary variables are introduced to make the original system equivalent to a second-order discrete system, thereby obtaining a dynamic model. This model describes the discrete time update process of the battery cell SOC and velocity vector. Through iterative calculation, the system can track the SOC and velocity vector.

[0098] It should be noted that the transformation of the original system into a second-order discrete system is to facilitate the subsequent control strategy design. In a second-order discrete system, the state change of the system can be described by introducing velocity variables and acceleration variables. By properly designing the control protocol, the state of the system can gradually approach the target value.

[0099] Specifically, the dynamic model can be expressed as:

[0100]

[0101] in: is the control input vector of battery i = 1, ..., N, used to adjust the output power and SOC value of the battery, Represents the auxiliary speed variable. The dynamic mode is obtained by introducing the auxiliary speed variable based on formula (1). And the introduction of the auxiliary variable makes the control system more flexible and controllable.

[0102] S202: Determine a control input model based on a preset tracking allocation relationship, gain coefficient, and communication delay.

[0103] In this step, in order to achieve the state of charge balance control and supply and demand balance of the distributed battery energy storage system with switching topology and non-uniform communication delay, control input is required in the battery iterative calculation process. Therefore, the control input needs to consider the deviation between the current state of the battery and the tracking target, the deviation between the state of the adjacent battery and the tracking target, and the influence of communication delay. By adjusting the gain coefficient, the convergence speed and stability of the system can be controlled.

[0104] Specifically, the control input model is expressed as:

[0105]

[0106] in: They are speed tracking error gain, SOC control gain and speed control gain respectively, and the communication delay from multi-agent j to i is It means that in discrete-time systems, it is reasonable to set ,in , is greater than or equal to The smallest integer of is the upper limit of communication delay.

[0107] It is important to note that in a discrete-time system, there is a delay of at least one sampling period when the states are exchanged between cells.

[0108] represents the speed tracking error term, which is used to adjust the speed variable of the battery to track the predefined target speed.

[0109] It represents the SOC control item, which takes into account the SOC information of neighboring batteries and adjusts its own output to balance the SOC of the entire system. Communication delay is introduced to allow the system to tolerate non-uniform communication delay.

[0110] Represents the speed control term, which is similar to the SOC control term, but adjusts the speed variable to ensure that the speed variable of all batteries eventually converges to the same value.

[0111] This formula can ensure that the battery energy storage system can maintain SOC balance and supply-demand matching in the presence of switching topology and non-uniform communication delay. Through reasonable parameter settings, the stability, speed and accuracy of the control system can be improved.

[0112] The tracking allocation relationship is expressed as:

[0113]

[0114] This formula describes a predefined process of tracking a target and tracking speed. and Respectively represent the tracking targets of SOC and velocity vector, Represents the predetermined value of the velocity vector. This formula is used to guide the changes in battery SOC and auxiliary variables. By setting appropriate tracking allocation variables, accurate control of the battery state can be achieved.

[0115] An explicit mathematical description is proposed for predefined tracking allocation, which provides a clear criterion for designing feasible tracking allocation protocols under global supply and demand mismatch conditions. And the formula provides a clear tracking target, so that the control system can work according to the predetermined target. Through reasonable tracking allocation, it can be ensured that the battery energy storage system meets the requirements of supply and demand balance and SOC balance.

[0116] S203: Control the current state of each battery and the received information of other batteries based on the control input model, and perform iterative calculation in conjunction with the dynamic model.

[0117] In this step, the input of each battery is calculated in real time through the above-mentioned control input model, and then the obtained input is substituted into the dynamic model for iterative calculation until the control target is met, thereby achieving charge state balance control and supply and demand balance of the distributed battery energy storage system.

[0118] The charge balance control method of the battery energy storage system provided in the embodiment of the present application introduces auxiliary variables into the SOC physical model to obtain a dynamic model, determines the control input model based on the preset tracking allocation relationship and gain coefficient and communication delay, controls the current state of each battery and the information received from other batteries based on the control input model, and performs iterative calculations in conjunction with the dynamic model. The above method effectively solves the charge state balance control and supply and demand balance problems of distributed battery energy storage systems with switching topology and non-uniform communication delay by introducing auxiliary variables and distributed control protocols.

[0119] Figure 3 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 3 ,like Figure 3 As shown, based on the above embodiment, step S101 specifically includes:

[0120] S301: For each battery, a first physical model is constructed according to the initial SOC value of the battery, the capacity of the battery, the charge and discharge coefficient of the battery, and the output current of the battery.

[0121] S302: Discretize and simplify the first physical model to obtain an SOC physical model.

[0122] Optionally, the method further includes: for each battery, determining a physical model corresponding to the output current of the battery according to the power, output voltage of the battery and conversion efficiency of the rectifier during discharge and charge operations.

[0123] Therefore, before step S302, the first physical model needs to be transformed based on the physical model corresponding to the output current to obtain the second physical model.

[0124] Correspondingly, step S302 specifically includes: discretizing and simplifying the second physical model to obtain the SOC physical model.

[0125] By defining SOC as the ratio of the remaining charge capacity to the battery capacity, the battery's state of charge can be intuitively reflected. At the same time, the change in SOC is calculated by integrating the output current, taking into account the battery's charging and discharging process. The relationship between power and current is established in order to convert the control target (power tracking) into current control. By introducing the conversion efficiency factor, the energy loss of the battery during the charging and discharging process is taken into account. In order to facilitate the design and implementation of the control strategy, the SOC model is simplified. Through approximate processing, the change in SOC is directly linked to the power output, which provides a basis for the subsequent control protocol design.

[0126] Specifically, the first physical model is expressed as:

[0127]

[0128] in: Indicates The capacity of the battery, For the The remaining charge capacity of each battery, For the The initial remaining charge of each battery, For the The output current of a battery. For the The charge and discharge coefficient of each battery satisfies the , in charging mode , and the Coulomb efficiency .

[0129] This formula describes the physical model of the state of charge (SOC) of a single battery in a battery energy storage system (BESS). Factors such as the remaining charge capacity, initial remaining charge, output current, and charge and discharge coefficient of the battery are taken into account to calculate the battery SOC. It provides an accurate calculation method for the battery SOC, which is the basis for the battery management system (BMS) to perform status monitoring and control. By integrating the output current, the battery SOC can be tracked in real time, thereby achieving real-time monitoring of the battery status.

[0130] set up and Respectively The conversion efficiency of a rectifier during discharge and charge operation is defined as:

[0131]

[0132]

[0133] in: For the The output power of each battery, For the The output voltage of the battery is , then transform the above formula (5) to obtain the second physical model:

[0134]

[0135] Each battery has an identification variable indicating physical quantities, such as state of charge (SOC), output active power, power deviation gap, etc. It is assumed that communication between BESS units can be performed at discrete time points. Update time point Will take the form Indicates that represents the sampling interval, is the initial moment. Therefore, The charging and discharging process of a battery can be described by a discrete time equation, that is, formula (1) is obtained by discretely simplifying formula (6).

[0136] Specifically, we first discretize formula (6):

[0137]

[0138] To simplify the problem, assume Due to the battery parameters ,as well as ,for ,have ,in is a constant. Therefore, we can simplify to get formula (1).

[0139] The charge balance control method of the battery energy storage system provided in the embodiment of the present application is to construct a first physical model for each battery according to the initial SOC value of the battery, the capacity of the battery, the charge and discharge coefficient of the battery, and the output current of the battery, and to discretize and simplify the first physical model to obtain the SOC physical model. Through the above method, the calculation process of the battery SOC is simplified to make it suitable for digital control systems. Through the discrete time equation, the SOC value of the battery can be updated more conveniently and accurately in each sampling period.

[0140] Figure 4 Schematic diagram of the charge balance control method of the battery energy storage system provided in this application Figure 4 ,like Figure 4 As shown, the method can also set a control target according to the SOC value and output power of each battery, and setting the control target specifically includes:

[0141] S401: The SOC value of each battery is equal to the SOC target value, the output power value of each battery is equal to the output power target value, and the total power of the battery energy storage system is equal to the supply-demand deviation, which are set as initial control targets.

[0142] S402: Introducing an auxiliary speed variable into the initial control target to convert the initial control target into a control target.

[0143] The multi-agent consensus control theory is applied to solve the energy allocation problem and battery state of charge (SOC) balance problem of battery energy storage system (BESS). The state of the agent includes the output active power and the battery state of charge value. A control protocol is designed so that the final SOC value of all BESSs regarded as agents is equal, and the output power can track the designed value, that is, the battery state of charge balance and supply and demand balance are achieved. The initial control objective can be written as:

[0144]

[0145]

[0146]

[0147] in, It is a multi-agent It is a multi-agent Neighbors, , is the same as The power component related to the battery capacity of each battery.

[0148] Formula (7) requires that the output power of each battery eventually tracks the design value , specifically, is the total supply-demand gap Power allocated by battery capacity. The principle of setting this control target is to ensure that each battery shares the corresponding power according to its capacity, avoiding overcharging or over-discharging of some batteries, thereby extending the service life and overall performance of the battery pack.

[0149] Formula (8) requires that the SOC of all batteries eventually converge to the same value, which is an important control objective in BESS because Formula (8) ensures energy balance among the battery pack. If the SOC of some batteries is much higher or lower than that of other batteries, then these batteries may be overstressed during the charge and discharge process, resulting in performance degradation or damage. Therefore, by making the SOC of all batteries tend to be equal through control strategies, the battery pack can be protected and its overall efficiency can be improved.

[0150] Formula (9) ensures that the total output power of all batteries tracks the deviation between supply and demand The principle of setting this control target is to ensure that the battery energy storage system can accurately respond to changes in supply and demand in the power system. If it is positive, it means that the power system needs additional power to make up for the shortfall between supply and demand. At this time, the battery energy storage system should be in discharge mode. If it is negative, it means that the power system has excess power, and the battery energy storage system should be in charging mode. By controlling the sum of the power of all batteries to be equal to , which can ensure that the battery energy storage system can effectively balance the supply and demand changes of the power system.

[0151] It should be noted that , It represents the gap between supply and demand. Indicates the discharge mode, Indicates charging mode. is the total active power demand, is the total active power supplied.

[0152] Auxiliary speed variables can be used as a new dimension of system control, making the system more controllable. By designing appropriate control strategies, the auxiliary speed variables can converge to the desired steady-state value, thereby ensuring the stability of the system. In battery energy storage systems, controlling the auxiliary speed variables can ensure that the power distribution and state of charge of the battery reach the desired balance state.

[0153] Therefore, by introducing the auxiliary speed variable .

[0154] The control objective can be written as:

[0155]

[0156]

[0157]

[0158] Formula (10) This goal means that, after a long time, the auxiliary speed variable of each battery Will converge to a gap with the deviation between supply and demand Steady-state values ​​related to battery capacity distribution .because and is inversely proportional, so this also means that the power will converge to a steady-state value proportional to the battery capacity .

[0159] Notice , that is, the auxiliary speed variables of all batteries are equal in steady state, which ensures fair distribution of power.

[0160] This goal of formula (11) ensures that over time, the state of charge of all cells will converge to the same value. This helps maintain balance between the battery pack and prevents some cells from being overcharged or discharged.

[0161] Formula (12) This goal indicates that after a long time, the auxiliary speed variable of all batteries The weighted sum of ) will converge to the supply-demand deviation gap .

[0162] because , this goal essentially says that the sum of the power of all batteries will equal the charging or discharging demand of the system , which ensures that the system can meet the overall power requirements.

[0163] The charge balance control method of the battery energy storage system provided in the embodiment of the present application sets the SOC value of each battery equal to the SOC target value, the output power value of each battery equal to the output power target value, and the total power of the battery energy storage system equal to the supply and demand deviation as the initial control target, introduces an auxiliary speed variable into the initial control target, and converts the initial control target into a control target. The above method realizes the charge state balance control and supply and demand balance of the distributed battery energy storage system with switching topology and non-uniform communication delay by reasonably designing the control target.

[0164] For example, in order to verify the effectiveness of the design of the above model, a BESS network with a switched directed topology and non-uniform communication delay can be selected for numerical simulation for verification. Figure 5 are four directed graphs of BESS, Figure 6 is a finite switching mechanism with four states. Figure 5 In this graph, there are no spanning trees with edge weight 1 in any of the graphs. The sampling time of the network is In addition, the time delays of edges (1,2) and (1,3) are seconds, and the time delays of edges and are seconds, and the time delay between edges (2,3) and (2,4) is Seconds. The protocol parameters are .exist Figure 6 In the example, a four-state The finite state mechanism represents the network state with switching topology and time delay. Start, every seconds to switch to the next state. Note that The communication diagram The union of has a spanning tree.

[0165] Numerical simulation is applied to simulate two cases: A. Battery cells with different capacities and switching topologies and non-uniform communication delay; B. Battery cells with the same capacity and switching topologies and non-uniform communication delay. The model parameters of BESS are given in Table 1, and . Set the initial battery status , and the initial active power of the battery .

[0166] Table 1

[0167]

[0168] In case A, the parameters of the five batteries are given in Table 1. Assume that Seconds, ,exist hour, ,exist Seconds, . Figure 7 P with switching topology and non-uniform delay communication topology for different battery capacities i and iterative simulation of SOC, Figure 8 P with the same battery capacity with switching topology and non-uniform delay communication topology i and iterative simulation of SOC, Figure 7 The SOC and active power changes of the battery cells in Case A are shown. It can be seen that even in the case of switching topology and non-uniform communication delay, the scheme can achieve supply and demand balance and SOC balance of BESS with battery cells of different capacities. In addition, each battery has a different charge and discharge share according to the battery capacity. The battery capacity ratio of these five batteries is 1:2:3:3:3. The power allocated to each battery is proportional to its capacity, so the power allocation of each battery is This shows that although the BESSs with different capacity battery cells have different initial state SOCs and different charge and discharge efficiencies, the energy scheduling target can still be achieved.

[0169] In case B, the parameters of the five batteries are the same as those of battery 1 in Table 1. Assume that Seconds, ,exist hour, ,exist hour, . Figure 8The state of charge (SOC) and power variation of the battery cells in Case B are shown. It can be seen that the scheme can achieve supply-demand balance and SOC balance for BESS (Battery Energy Storage System) using battery cells of the same capacity. The capacity of each battery is the same, so the power is evenly distributed to each battery. It can be seen that even in the case of switching topologies and non-uniform communication delays, the SOC variable can be balanced to a common dynamic value and the power variable satisfies the supply-demand mismatch.

[0170] Fig. 9 A schematic diagram of the structure of the charge balance control device of the battery energy storage system provided in this application, such as Fig. 9 As shown, the charge balance control device 900 of the battery energy storage system provided in this embodiment includes:

[0171] The construction module 901 is used to construct a state of charge (SOC) physical model according to the pre-collected physical parameters of each battery pack in the battery energy storage system. The SOC physical model is used to calculate the SOC value of each battery pack.

[0172] The setting module 902 is used to set target values ​​based on a preset control target, where the target values ​​include an SOC target value and an output power target value.

[0173] Iteration module 903 is used to perform iterative calculations on each battery pack based on the current state and the information received from other battery packs through a preset control protocol and SOC physical model until the SOC value of each battery pack reaches the SOC target value and the output power value of each battery pack reaches the output power target value, thereby satisfying the control objective. The control protocol is based on SOC control gain, speed tracking error gain, speed control gain and communication delay, and is designed through multi-agent consistency control theory.

[0174] Optionally, the iteration module 903 is specifically used for:

[0175] Auxiliary variables are introduced into the SOC physical model to obtain a kinetic model;

[0176] Determine a control input model based on a preset tracking allocation relationship and gain coefficient and a communication delay;

[0177] The control input model controls the current state of each battery and the information received from other batteries, and performs iterative calculations in conjunction with the kinetic model.

[0178] In a possible implementation, the construction module 901 is specifically used to:

[0179] For each battery, a first physical model is constructed according to the initial SOC value of the battery, the capacity of the battery, the charge and discharge coefficient of the battery, and the output current of the battery;

[0180] The first physical model is discretized and simplified to obtain the SOC physical model.

[0181] In a possible implementation, the setting module 902 is further configured to:

[0182] The control target is set according to the SOC value and output power of each battery.

[0183] Optionally, the setting module 902 is specifically used to:

[0184] The SOC value of each battery is equal to the SOC target value, the output power value of each battery is equal to the output power target value, and the total power of the battery energy storage system is equal to the supply-demand deviation, which are set as initial control targets;

[0185] An auxiliary speed variable is introduced into the initial control target to transform the initial control target into a control target.

[0186] In a possible implementation, the charge balance control device 900 of the battery energy storage system further includes:

[0187] The determination module 904 is used to determine, for each battery, a physical model corresponding to the output current of the battery according to the power and output voltage of the battery and the conversion efficiency of the rectifier during the discharge and charge operations.

[0188] In a possible implementation, the charge balance control device 900 of the battery energy storage system further includes:

[0189] A conversion module 905, configured to convert the first physical model based on the physical model corresponding to the output current to obtain a second physical model;

[0190] Accordingly, the construction module 901 discretizes and simplifies the first physical model to obtain the SOC physical model, which specifically includes:

[0191] The second physical model is discretized and simplified to obtain the SOC physical model.

[0192] The charge balance control device for the battery energy storage system provided in this embodiment can execute the charge balance control method for the battery energy storage system provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail in this embodiment.

[0193] Fig.10 This is a schematic diagram of the structure of the electronic device provided in this application. Fig.10As shown, the electronic device 1000 provided in this embodiment includes: at least one processor 1001 and a memory 1002. Optionally, the device 1000 also includes a communication component 1003. The processor 1001, the memory 1002 and the communication component 1003 are connected via a bus 1004.

[0194] In the specific implementation process, at least one processor 1001 executes the computer execution instructions stored in the memory 1002, so that the at least one processor 1001 executes the methods of the above-mentioned embodiments.

[0195] The specific implementation process of the processor 1001 can be found in the above-mentioned various method embodiments. The implementation principles and technical effects are similar and will not be repeated in this embodiment.

[0196] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0197] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0198] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0199] The present application also provides a computer program product, including a computer program, which implements the methods of the above embodiments when executed by a processor.

[0200] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the methods of the above-mentioned embodiments are implemented.

[0201] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0202] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0203] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0204] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0205] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0206] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0207] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0208] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A charge balance control method for a battery energy storage system, characterized in that: include: Constructing a state of charge (SOC) physical model based on the pre-collected physical parameters of each battery in the battery energy storage system, wherein the SOC physical model is used to calculate the SOC value of each battery; Setting a target value based on a preset control target, the target value including an SOC target value and an output power target value; Through the preset control protocol and the SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries until the SOC value of each battery reaches the SOC target value and the output power value of each battery reaches the output power target value, satisfying the control objective. The control protocol is based on SOC control gain, speed tracking error gain and speed control gain as well as communication delay, and is designed through multi-agent consistency control theory.

2. The method according to claim 1, characterized in that: Through the preset control protocol and the SOC physical model, each battery performs iterative calculation based on the current state and the information received from other batteries, including: Introducing auxiliary variables into the SOC physical model to obtain a kinetic model; Determine a control input model based on a preset tracking allocation relationship and gain coefficient and a communication delay; The current state of each battery and the received information of other batteries are controlled based on the control input model, and iterative calculation is performed in conjunction with the kinetic model.

3. The method according to claim 1, characterized in that The SOC physical model is constructed according to the pre-collected physical parameters of each battery in the battery energy storage system, including: For each battery, construct a first physical model according to an initial SOC value of the battery, a capacity of the battery, a charge and discharge coefficient of the battery, and an output current of the battery; The first physical model is discretized and simplified to obtain the SOC physical model.

4. The method according to claim 1, characterized in that: The method further comprises: The control target is set according to the SOC value and output power of each battery.

5. The method according to claim 2, characterized in that: The control target is set according to the SOC value and output power of each battery, including: The SOC value of each battery is equal to the SOC target value, the output power value of each battery is equal to the output power target value, and the total power of the battery energy storage system is equal to the supply-demand deviation, which are set as initial control targets; An auxiliary speed variable is introduced into the initial control target to transform the initial control target into the control target.

6. The method according to claim 3, characterized in that The method further comprises: For each battery, the output current corresponding physical model of the battery is determined according to the power, output voltage of the battery and the conversion efficiency of the rectifier during discharge and charge operations.

7. The method according to claim 6, characterized in that Before discretizing and simplifying the first physical model to obtain the SOC physical model, the method further includes: Based on the physical model corresponding to the output current, the first physical model is transformed to obtain a second physical model; Accordingly, the first physical model is discretized and simplified to obtain the SOC physical model, including: The second physical model is discretized and simplified to obtain the SOC physical model.

8. A charge balance control device for a battery energy storage system, characterized in that: include: A construction module, used to construct a state of charge (SOC) physical model based on pre-collected physical parameters of each battery pack in the battery energy storage system, wherein the SOC physical model is used to calculate the SOC value of each battery pack; A setting module, used for setting a target value based on a preset control target, wherein the target value includes an SOC target value and an output power target value; The iterative module is used to perform iterative calculations on each battery pack based on the current state and the information received from other battery packs through a preset control protocol and the SOC physical model until the SOC value of each battery pack reaches the SOC target value and the output power value of each battery pack reaches the output power target value, thereby satisfying the control objective. The control protocol is designed based on the SOC control gain, speed tracking error gain, speed control gain and communication delay through multi-agent consistency control theory.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the charge balancing control method for the battery energy storage system according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the charge balancing control method for a battery energy storage system according to any one of claims 1 to 7.

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