An energy storage system distributed charging and discharging consistency control method based on an extended state observer

Abstract

The present application relates to a kind of energy storage system dispersion based on extended state observer charge-discharge consistency control method, belong to the coordinated control field of battery energy storage system.The method is first to the energy storage battery state of charge modeling, introduce virtual leader and set charge-discharge threshold;Composite control law containing state feedback and feedforward compensation is constructed, communication burden is reduced by dynamic and static hybrid event trigger mechanism with electric quantity state dependence;Design extended state observer online estimation and compensation the coupling term between energy storage unit, without global communication topology information can complete controller design.The present application effectively solves the problem of distributed control dependent on global information and limited communication bandwidth, while realizing the consistent convergence of each battery state of charge, overcharge and overdischarge are avoided, and the system control performance and engineering applicability are improved.

Description

Technical Field

[0001] This invention belongs to the field of coordinated control of battery energy storage systems, and specifically relates to a distributed charge and discharge consistency control method for energy storage systems based on an extended state observer. Background Technology

[0002] With the continuous growth of energy demand and the increasing awareness of environmental protection, renewable energy power generation has become a global trend in the power generation field. Renewable energy includes wind power, hydropower, solar power, geothermal energy, and biomass energy, and is an important part of the world's energy system, characterized by large development potential, wide resource distribution, sustainable utilization, and low environmental impact. By incorporating renewable energy into microgrids, energy conservation and emission reduction can be achieved. A microgrid is a power network composed of small power generation systems distributed in different locations, consisting of distributed power sources, battery energy storage systems, loads, and monitoring and protection devices. Compared with traditional large power grids, microgrids can achieve self-control, protection, and management. They can operate independently in an islanded manner to meet local electricity demand, or they can operate in grid-connected mode, serving as backups and mutual supports for the large power grid. They have advantages such as flexibility, economy, environmental protection, and high efficiency, greatly improving the reliability and stability of the power grid.

[0003] The role of battery energy storage systems in DC microgrids is reflected in three aspects.

[0004] (1) Provide short-term power supply. When a microgrid switches from grid-connected mode to islanded mode, there may be a power deficit on the load side. The energy storage system can fill the power deficit and play a role in smooth transition, thereby ensuring uninterrupted power supply to important loads;

[0005] (2) Economic dispatch. During peak electricity demand, the energy storage system discharges, and during off-peak electricity demand, the energy storage system stores excess electricity, which plays a role in peak shaving and valley filling, improves energy utilization, and saves the operating costs of the microgrid;

[0006] (3) Improve the power quality of DC microgrids. When the output power of renewable energy fluctuates, the energy storage system can effectively smooth power changes, stabilize the bus voltage, and eliminate the adverse effects of the intermittency of renewable energy on the microgrid. It can be seen that the energy storage system can ensure the dynamic balance of supply and demand through charging or discharging, meet the power demand of the load side, and is an indispensable and important component of DC microgrids.

[0007] A balance between power supply and demand is a prerequisite for the safe and efficient operation of a microgrid. A mismatch between power supply and demand may lead to…

[0008] This can cause fluctuations in bus frequency and voltage, and even lead to power system collapse. Therefore, designing a coordinated control strategy for battery energy storage systems to effectively mitigate power fluctuations is a crucial control objective for microgrid energy management. In fact, the state of charge (SOC) of a battery energy storage system is closely related to its input / output power. If only power balance is considered while ignoring the system's own capacity limitations, individual battery cells may overcharge or over-discharge, reducing the system's lifespan and energy utilization, and making the microgrid more susceptible to shocks. Considering the output characteristics and lifespan of battery cells, in practical applications, battery cells of the same model are generally selected to form the battery energy storage system. However, due to manufacturing processes or operating environments, the SOC of each battery cell will inevitably be inconsistent, and this inconsistency cannot be eliminated. Therefore, developing necessary coordinated control strategies for battery energy storage systems to achieve both supply-demand balance with the DC microgrid and SOC balance within the system itself is crucial.

[0009] However, while research on the collaborative control of battery energy storage systems employs a distributed approach, the control protocols are still designed using a centralized method, utilizing Laplace matrices of the global communication graph. Typically, battery energy storage systems are widely distributed, making it difficult to obtain global information. Reports on decentralized control are scarce, and in decentralized charge / charge consistency control problems, the control protocol design is not based on Laplace matrices of the global communication graph. If decentralized control could be adopted for the collaborative control of battery energy storage systems, the need for global information in the control protocol design could be overcome. Summary of the Invention

[0010] The purpose of this invention is to design a distributed controller for a battery energy storage system to prevent overcharging or over-discharging, thereby improving the lifespan of the battery energy storage system and the energy utilization rate of the battery. Therefore, this invention provides a distributed charge and discharge consistency control method for an energy storage system based on an extended state observer.

[0011] To achieve the above objectives, the technical solution of the present invention is: a distributed charge-discharge consistency control method for energy storage systems based on an extended state observer, comprising:

[0012] The state of charge of each energy storage battery is obtained, and the tracking error is determined based on the preset reference state of charge.

[0013] Based on the state deviation between each energy storage battery and its neighboring nodes and the tracking error, a composite control law containing control input components and feedforward compensation terms is constructed.

[0014] Based on the preset dynamic and static mixed event triggering conditions that are dependent on the power state, determine the timing of information broadcasting for each energy storage battery;

[0015] An extended state observer is used to estimate the coupling terms corresponding to each energy storage battery online, and the estimated values ​​are substituted into the composite control law as the feedforward compensation terms to regulate the power of each energy storage battery and achieve charging consistency control.

[0016] Furthermore, before the step of acquiring the state of charge of each energy storage battery and determining the tracking error based on a preset reference state of charge, the method further includes:

[0017] Establish a first-order dynamic model of the energy storage battery, and define the state of charge of energy storage battery i as follows: The output power is And establish the following relationship:

[0018] i=1,2,⋯,N

[0019] in, The nominal capacity of energy storage battery i is... The output voltage of energy storage battery i;

[0020] Set reference state of charge and define energy storage batteries Tracking error .

[0021] Furthermore, the reference state of charge Set to 1 during charging and to 0.2 during discharging.

[0022] Furthermore, the composite control law is expressed as:

[0023]

[0024] in, It is a distributed control input component used to achieve system state consistency. This is a feedforward compensation term used to suppress interference.

[0025] The The calculation formula is:

[0026]

[0027] Where K is the feedback gain matrix that needs to be designed. Let i be the set of neighbors of energy storage battery i. Let k be the trigger time of energy storage battery i. These are the elements of the adjacency matrix corresponding to the system. Let be the connection weight between energy storage battery i and the virtual leader. When the virtual leader and energy storage battery i are connected by an edge... ,otherwise .

[0028] Furthermore, the distributed controller is designed to minimize performance metrics:

[0029]

[0030] in, It is a positive semi-definite constant matrix. It is a positive definite constant matrix. , All are given index parameter matrices;

[0031] The feedback gain matrix K is obtained by solving the following Riccati equation:

[0032]

[0033] in To find the matrix, For the system matrix, in this system, , And through the formula The feedback gain matrix K is calculated.

[0034] Furthermore, the triggering condition for the mixed dynamic and static events that are dependent on the power state is expressed as follows:

[0035]

[0036] in, , The sampling period is and These are the dynamic and static threshold parameters for the triggering mechanism, respectively, both of which are positive real numbers; This is the latest trigger moment for energy storage battery j.

[0037] Furthermore, the coupling item Defined as:

[0038]

[0039] in, Let be the tracking error of neighbor node j.

[0040] Furthermore, the extended state observer estimates the coupling terms using the following state equation:

[0041]

[0042] in, To address tracking errors The estimated value, For coupling terms The estimated value, The observer gain matrix is... The value to be designed.

[0043] The feedforward compensation term The value is the estimated value. .

[0044] Furthermore, the observer gain matrix By configuring the following energy storage battery The poles of the observation error system are determined by:

[0045]

[0046] in, , .

[0047] The present invention also provides an electronic device, characterized in that it comprises:

[0048] A processor for executing the distributed charging consistency control method for energy storage systems based on an extended state observer as described above;

[0049] Memory for storing the executable instructions of the processor;

[0050] The communication module is used to interact with neighboring nodes based on the event triggering conditions under the control of the processor.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] (1) The method of this invention can overcome the problem of difficulty in obtaining global information. Since the battery energy storage system is composed of several interconnected subsystems, the system dimension is high or the subsystems are located in different geographical locations. Information transmission between the subsystems is subject to certain constraints. Even if information transmission is not affected, the computational load may be too large to adopt a distributed control strategy. After adopting a distributed control structure, each subsystem only decides its own control based on its own information, which facilitates a rapid response to coupling terms that appear in the subsystem, which is beneficial to improving the quality of control.

[0053] (2) The method of the present invention achieves SoC balance of charging / discharging of battery energy storage system according to a predetermined threshold, thereby avoiding overcharging and over-discharging problems.

[0054] (3) The method of the present invention designs a dynamic-static hybrid event triggering condition that is dependent on the power state, when the parameter When the parameter is set to 0, the triggering condition for mixed dynamic and static events that are dependent on the power state degenerates into a static threshold triggering mechanism. When the threshold is 0, the dynamic-static mixed event triggering condition, which is dependent on the electrical state, degenerates into a dynamic threshold triggering mechanism. In short, when the system's electrical state changes drastically, the dynamic component of the dynamic-static mixed event triggering mechanism, which is dependent on the electrical state, can avoid the Zeno phenomenon; when the system's electrical state is close to the equilibrium point, i.e., the electrical state error is very small, the static component of the dynamic-static mixed event triggering condition, which is dependent on the electrical state, can overcome the occurrence of the Zeno phenomenon.

[0055] (4) The method of the present invention can be used to solve the distributed control problem of complex interconnected large systems with coupling relationships between various subsystems. The coupling quantity of the battery energy storage system is estimated by using an extended state observer, and the estimated value is used to perform feedforward compensation in the control quantity of the battery energy storage system to improve the system performance index. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the distributed control based on the extended state observer described in this invention.

[0057] Figure 2 This is a graph showing the change in the state of charge of each energy storage battery under the charging conditions of this invention.

[0058] Figure 3 This is a graph showing the input power variation of each energy storage battery under the charging conditions of this invention.

[0059] Figure 4 This is a graph showing the change in the state of charge of each energy storage battery under the discharge conditions of this invention.

[0060] Figure 5 This is a graph showing the output power variation of each energy storage battery under the discharge conditions of this invention. Detailed Implementation

[0061] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.

[0062] This invention provides a distributed charge-discharge consistency control method for energy storage systems based on an extended state observer, comprising:

[0063] The state of charge of each energy storage battery is obtained, and the tracking error is determined based on the preset reference state of charge.

[0064] Based on the state deviation between each energy storage battery and its neighboring nodes and the tracking error, a composite control law containing control input components and feedforward compensation terms is constructed.

[0065] Based on the preset dynamic and static mixed event triggering conditions that are dependent on the power state, determine the timing of information broadcasting for each energy storage battery;

[0066] An extended state observer is used to estimate the coupling terms corresponding to each energy storage battery online, and the estimated values ​​are substituted into the composite control law as the feedforward compensation terms to regulate the power of each energy storage battery and achieve charging consistency control.

[0067] The following is a detailed implementation process of the present invention.

[0068] First, a mathematical model of the battery energy storage system is performed, including the energy storage battery. The dynamic state of charge is

[0069] (1)

[0070] in, For energy storage batteries In time The state of charge, For energy storage batteries Initial state of charge, For energy storage batteries The nominal capacity, Energy storage battery The output current. If the output current Indicates discharge. This indicates that the device is charging.

[0071] Assuming negligible power losses in the converter and identical output voltages for the energy storage batteries, the output power of each battery can be described by the following formula.

[0072] (2)

[0073] The output voltage of energy storage battery i;

[0074] Considering the SoC dynamic equation (1) and output power equation (2) for each energy storage battery, the variables of the SoC With battery unit output power The relationship can further evolve into

[0075] (3)

[0076] As can be seen from equation (3), based on the state of the SoC, capacity and voltage of the energy storage battery, the SoC balance of the energy storage system can be achieved during the charging / discharging process through the power input / output of the energy storage system.

[0077] For ease of further description, the state variables need to be defined as follows:

[0078] ,

[0079] Thus, the following first-order system can be obtained.

[0080] (4)

[0081] Additionally, the leader (referencing the state of charge) is defined as... .

[0082] Overcharging or over-discharging energy storage batteries can reduce their lifespan. Furthermore, considering the impact of the safety and stability of energy storage batteries on the stable operation of microgrids, this invention sets upper charging thresholds for each energy storage battery SoC. 1 and the lower discharge threshold It is 0.2.

[0083] The control objective is to design a state feedback controller for each energy storage battery using a virtual leader control method, such that for any initial state... The energy storage battery system reaches asymptotic consistency in capacity, which can be specifically described as follows:

[0084] 1) During charging, each energy storage battery coordinates and controls its input power according to its own SoC, and the input power... The following conditions must be met.

[0085]

[0086] Overcharging must not occur during the charging process, i.e. , .

[0087] 2) During discharge, each energy storage battery coordinates and controls its output power according to its own System-on-Chips (SoC), and the output power... The following conditions must be met.

[0088]

[0089] Over-discharge must not occur during the discharge process, i.e. , .

[0090] As battery energy storage systems become increasingly large, competition for communication resources among energy storage batteries intensifies. Reducing the waste of communication resources in control systems and overcoming the problem of limited communication bandwidth has become a pressing issue in the promotion of network control technology, particularly in battery energy storage collaborative control systems based on wireless networks. One effective way to solve the problem of limited communication bandwidth is event-triggered control.

[0091] Assumption , , ... represents the sampling time interval, where... It is a fixed positive number, called the sampling period. At each sampling time, the event triggering conditions of each energy storage battery are checked. If the energy storage battery meets the conditions at a certain sampling time... The event triggering condition, then the energy storage battery It will sample its state and broadcast the sampled information to its neighbors. Define the energy storage battery. The time-triggered sequence is ,in These trigger sequences belong to a set .

[0092] To reduce the average sampling frequency, the following event-triggered control protocol is designed.

[0093]

[0094] It is the first The latest trigger time of each follower (i.e., energy storage battery j). This is the feedback gain matrix to be designed. It is known that this control protocol contains coupling terms, requiring global information during design. To achieve distributed control of a large system with coupling terms, the control protocol needs to be decomposed into two parts: one serving as the control input, and the other observing the coupling terms as feedforward compensation.

[0095] To address the issue of consistent charging / discharging tracking in distributed energy storage batteries, this invention considers a linear composite controller, also known as a composite control law (or control protocol).

[0096] (5)

[0097] in, It is a distributed control input component used to achieve system state consistency. For feedforward compensation term, it is for The estimated value is used to suppress interference. The feedback gain matrix that needs to be designed.

[0098] Define the tracking error of the energy storage battery i ,right Differentiate and express Substituting, it can be written as:

[0099] (6)

[0100] Energy storage battery The coupling term is , The estimated value is defined as .

[0101] Based on the tracking error system model (6), the correlation terms of the system are not considered. At that time, tracking error system The model can be described by the following nominal system.

[0102] (7)

[0103] As can be seen from (7), since there are no correlation terms, each system can be stabilized, and the gain matrix can be designed using the following Riccati equation.

[0104]

[0105] in, It is a positive semi-definite constant matrix. It is a positive definite constant matrix. and All are given index parameter matrices. To find the positive definite matrix, Since the system matrix is ​​given, the optimal feedback gain matrix in equation (5) is... It can be determined in the following ways.

[0106]

[0107] Furthermore, define local error. For the first For a single energy storage battery, a hybrid dynamic and static event triggering condition with state-of-charge dependence is designed, and the triggering time sequence is as follows:

[0108] (8)

[0109] in, and These are the dynamic and static threshold parameters for the triggering mechanism, respectively, both of which are positive real numbers.

[0110] This invention introduces an extended state observer to monitor energy storage batteries. Coupling terms Make estimates and use the obtained estimates for energy storage batteries. The system architecture of the distributed optimization control method based on extended state observer with feedforward compensation is as follows: Figure 1 As shown, the energy storage battery The model is shown in equation (1).

[0111] Assuming the tracking error system model (6) Bounded disturbance From equation (6), we can obtain the energy storage battery. The expansion state equation is

[0112] (9)

[0113] To obtain the estimated value of the coupling term, a second-order linear extended state observer is designed for the extended state equation (9) as follows.

[0114] (10)

[0115] in, To address tracking errors The estimated value, For coupling terms The estimated value, The observer gain matrix is... The value to be designed.

[0116] Define measurement error as , Further, energy storage batteries can be obtained. Observation error system

[0117] (11)

[0118] Obviously, and Then the energy storage battery This can achieve consistent charging / discharging tracking of energy storage batteries, that is, the consistency problem is transformed into the stability problem of error systems (7) and (11). The optimal feedback gain matrix... Substituting into (11), and stabilizing the system (11), the parameters of the observer can be obtained. .

[0119] Charging results are as follows Figure 2 As shown, under charging conditions, the energy storage batteries ultimately reach a fully charged state (100%), achieving consistency (the dashed line represents the reference state trajectory of the virtual leader, and the solid line represents the state trajectory of each energy storage battery). The input power of each energy storage battery is as follows: Figure 3 As shown, through information exchange among the various energy storage batteries, the corresponding power is input. When the final power state gradually becomes consistent, the output power converges to 0, thereby preventing overcharging.

[0120] Discharge results are as follows Figure 4 As shown, under discharge conditions, the remaining state of charge (20%) reached by each energy storage battery is consistent (the dashed line represents the reference state trajectory of the virtual leader, and the solid line represents the state trajectory of each energy storage battery). The output power of each energy storage battery is as follows: Figure 5 As shown, through information exchange among the energy storage batteries, the corresponding power is output. When the remaining power status gradually becomes consistent, the output power converges to 0, thereby preventing over-discharge.

[0121] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A distributed charge-discharge consistency control method for an energy storage system based on an extended state observer, characterized in that, include: The state of charge of each energy storage battery is obtained, and the tracking error is determined based on the preset reference state of charge. Based on the state deviation between each energy storage battery and its neighboring nodes and the tracking error, a composite control law containing control input components and feedforward compensation terms is constructed. Based on the preset dynamic and static mixed event triggering conditions that are dependent on the power state, determine the timing of information broadcasting for each energy storage battery; An extended state observer is used to estimate the coupling terms corresponding to each energy storage battery online, and the estimated values ​​are substituted into the composite control law as the feedforward compensation terms to regulate the power of each energy storage battery and achieve charging consistency control.

2. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 1, characterized in that, Before the step of acquiring the state of charge of each energy storage battery and determining the tracking error based on a preset reference state of charge, the method further includes: Establish a first-order dynamic model of the energy storage battery, and define the state of charge of energy storage battery i as follows: The output power is And establish the following relationship: ， in, The nominal capacity of energy storage battery i is... The output voltage of energy storage battery i; Set reference state of charge and define energy storage batteries Tracking error .

3. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 2, characterized in that, The reference state of charge Set to 1 during charging and to 0.2 during discharging.

4. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 2, characterized in that, The composite control law is expressed as follows: in, It is a distributed control input component used to achieve system state consistency. This is a feedforward compensation term used to suppress interference. The The calculation formula is: Where K is the feedback gain matrix that needs to be designed. Let i be the set of neighbors of energy storage battery i. Let k be the trigger time of energy storage battery i. These are the elements of the adjacency matrix corresponding to the system. Let be the connection weight between energy storage battery i and the virtual leader. When the virtual leader and energy storage battery i are connected by an edge... ,otherwise .

5. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 4, characterized in that, Design a distributed controller to minimize performance metrics: in, It is a positive semi-definite constant matrix. It is a positive definite constant matrix. , All are given index parameter matrices; The feedback gain matrix K is obtained by solving the following Riccati equation: in To find the matrix, For the system matrix, , And through the formula The feedback gain matrix K is calculated.

6. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 4, characterized in that, The triggering condition for the mixed dynamic and static events that are dependent on the power state is expressed as follows: in, , The sampling period is and These are the dynamic and static threshold parameters for the triggering mechanism, respectively, both of which are positive real numbers; This is the latest trigger moment for energy storage battery j.

7. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 4, characterized in that, The coupling term Defined as: in, Let be the tracking error of neighbor node j.

8. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 7, characterized in that, The extended state observer estimates the coupling terms using the following state equation: in, To address tracking errors The estimated value, For coupling terms The estimated value, The observer gain matrix is... The value to be designed; The feedforward compensation term The value is the estimated value. .

9. The distributed charge-discharge consistency control method for an energy storage system based on an extended state observer according to claim 8, characterized in that, The observer gain matrix By configuring the following energy storage battery The poles of the observation error system are determined by: in, , .

10. An electronic device, characterized in that, include: A processor for executing the distributed charging consistency control method for an energy storage system based on an extended state observer as described in any one of claims 1 to 9; Memory for storing the executable instructions of the processor; The communication module is used to interact with neighboring nodes based on the event triggering conditions under the control of the processor.

Images