Low-voltage area distributed energy storage coordination control method and system and storage medium

Abstract

This application provides a coordinated control method, system, and storage medium for distributed energy storage in low-voltage distribution areas. An objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable of the distributed energy storage and the consistency control quantity. Constraints are established, and a proportional-integral consistency algorithm is used to solve the optimization problem composed of the objective function and constraints, obtaining the optimal consistency control quantity. Based on this, a corrected angular frequency reference value is calculated. If the local state measurement error of the distributed energy storage meets a preset event triggering condition, the distributed energy storage is controlled to broadcast its current state. A frequency reference command is generated based on the corrected angular frequency reference value, enabling the distributed energy storage to adjust the converter output using the frequency reference command. This achieves coordinated control of distributed energy storage, improves the stability of the power grid under extreme events, effectively reduces redundant data traffic in the communication network, thereby reducing the communication burden and improving the resilience of the distribution network.

Description

Technical Field

[0001] This invention relates to the field of distributed energy storage control technology, and in particular to a method, system and storage medium for coordinated control of distributed energy storage in low-voltage distribution areas. Background Technology

[0002] In low-voltage distribution networks, distributed energy storage plays a role in smoothing source-load fluctuations, achieving peak shaving and valley filling, and providing voltage support. However, its massive dispersion and strong randomness have led to communication resource bottlenecks and multi-device coordination conflicts in the grid's dispatch and control.

[0003] In existing technologies, firstly, while traditional consensus algorithms based on continuous communication can achieve global information acquisition, they severely consume communication bandwidth and have extremely high reliability requirements for the communication network, resulting in high system costs and poor robustness. Secondly, existing distributed control strategies typically require the design of additional voltage observers, and the convergence of the controller is highly dependent on the precise setting of initial values. After extreme events (such as communication topology changes or node failures), the system often struggles to achieve self-recovery, leading to control failure. Finally, while there is considerable research on economic dispatch for DC microgrids, it often separates frequency recovery from economic allocation control or requires broadcasting multiple variables, resulting in heavy communication burdens and weak privacy protection capabilities. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, system and storage medium for coordinated control of distributed energy storage in low-voltage distribution areas, which can reduce communication burden and improve the resilience of distribution network operation.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for coordinated control of distributed energy storage in low-voltage distribution areas includes: An objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable and the consistency control quantity of distributed energy storage, and constraints are established. The optimal consistency control quantity is obtained by solving the optimization problem consisting of the objective function and the constraints using the proportional-integral consensus algorithm. The corrected angular frequency reference value of the distributed energy storage is calculated based on the optimal consistency control quantity. Obtain the local state measurement error of the distributed energy storage; Determine whether the local state measurement error meets the preset event triggering conditions. If yes, control the distributed energy storage to broadcast the current state; otherwise, do not broadcast. The frequency reference command for the distributed energy storage is generated based on the corrected angular frequency reference value, so that the distributed energy storage can use the frequency reference command to adjust the converter output.

[0006] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A low-voltage distribution area distributed energy storage coordinated control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the aforementioned low-voltage distribution area distributed energy storage coordinated control method.

[0007] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps of the above-described low-voltage distribution energy storage coordinated control method.

[0008] The beneficial effects of this invention are as follows: An objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable of distributed energy storage and the consistency control quantity. Constraints are established, and the optimization problem consisting of the objective function and constraints is solved using a proportional-integral consistency algorithm to obtain the optimal consistency control quantity. Based on the optimal consistency control quantity, a corrected angular frequency reference value is calculated. It is then determined whether the acquired local state measurement error of the distributed energy storage meets the preset event triggering conditions. If so, the distributed energy storage is controlled to broadcast its current state. A frequency reference command for the distributed energy storage is generated based on the corrected angular frequency reference value, enabling the distributed energy storage to adjust the converter output using the frequency reference command. This achieves coordinated control of distributed energy storage by solving the optimization problem through the proportional-integral consistency algorithm. It eliminates the need for additional voltage observers and controller initialization, allowing for self-recovery and improving the stability of the power grid under extreme events. Furthermore, the introduction of preset event triggering conditions ensures data transmission only when necessary, effectively reducing redundant data traffic in the communication network, thereby reducing the communication burden and improving the resilience of the distribution network. Attached Figure Description

[0009] Figure 1 This is a flowchart of a low-voltage distribution energy storage coordinated control method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the low-voltage distribution area system structure in a distributed energy storage coordination control method for low-voltage distribution areas according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the output of the distributed energy storage regulating converter in a low-voltage distribution area distributed energy storage coordinated control method according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a low-voltage distribution area distributed energy storage coordinated control system according to an embodiment of the present invention. Detailed Implementation

[0010] Definitions:

[0011] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0012] In existing technologies, traditional consensus algorithms based on continuous communication consume significant communication bandwidth when acquiring global information, placing high demands on network reliability and resulting in high system costs and poor robustness. Furthermore, existing distributed control strategies often require additional voltage observers, and their convergence is sensitive to initial values, making self-recovery difficult after communication topology changes or node failures. While there is considerable research on economic dispatch for DC microgrids, most studies separate frequency recovery from economic allocation control or require broadcasting multiple variables, increasing communication burden and weakening privacy protection capabilities.

[0013] To at least address the aforementioned issues, an objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable of distributed energy storage and the consistency control quantity. Constraints are established, and the proportional-integral (PI) consensus algorithm is used to solve the optimization problem, yielding the optimal consistency control quantity. Based on this optimal consistency control quantity, a corrected angular frequency reference value is calculated. If the acquired local state measurement error of the distributed energy storage meets a preset event triggering condition, the distributed energy storage broadcasts its current state. A frequency reference command is generated based on the corrected angular frequency reference value, enabling the distributed energy storage to adjust the converter output using this command. In this way, the optimization problem can be solved using the PI consensus algorithm, achieving coordinated control of distributed energy storage. This eliminates the need for additional voltage observers and allows for self-recovery without controller initialization, improving the stability of the power grid under extreme events. Furthermore, the introduction of preset event triggering conditions ensures data transmission only when necessary, effectively reducing redundant data traffic in the communication network, thereby lowering the communication burden and improving the resilience of the distribution network.

[0014] The following details a method for coordinated control of distributed energy storage in low-voltage distribution areas according to the present invention. Please refer to [link / reference]. Figure 1 The method 100 includes steps 101 to 106: Step 101: Construct an objective function with the goal of minimizing the difference between the initial frequency deviation variable and the consistency control quantity of distributed energy storage, and establish constraints.

[0015] Step 102: Use the proportional-integral consensus algorithm to solve the optimization problem consisting of the objective function and the constraints to obtain the optimal consensus control quantity.

[0016] Step 103: Calculate the corrected angular frequency reference value of the distributed energy storage based on the optimal consistency control quantity.

[0017] Step 104: Obtain the local state measurement error of the distributed energy storage.

[0018] Step 105: Determine whether the local state measurement error meets the preset event triggering conditions. If yes, control the distributed energy storage to broadcast the current state; otherwise, do not broadcast.

[0019] Step 106: Generate a frequency reference command for the distributed energy storage based on the corrected angular frequency reference value, so that the distributed energy storage can use the frequency reference command to adjust the converter output.

[0020] This includes low-voltage distribution systems such as multiple distributed energy storage and load systems. Figure 2 As shown.

[0021] In one embodiment of the present invention, in step 101, an objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable and the consistency control quantity of distributed energy storage, specifically as follows: ; In the formula, This represents the difference between the initial frequency deviation variable and the consistency control variable. This indicates the number of distributed energy storage systems participating in the control of the low-voltage distribution area. Indicates the first Consistency control quantity for distributed energy storage. Indicates the first The initial frequency deviation variable of a distributed energy storage system; Establish the constraints as follows: ; In the formula, Indicates the first The initial frequency deviation variable of a distributed energy storage system.

[0022] in, , Indicates the first Real-time output active power of distributed energy storage.

[0023] As described above, under the condition of satisfying system constraints, we need to find the optimal consistency control quantity so that the system can both restore the average frequency and achieve active power distribution by the droop control coefficient.

[0024] In one embodiment of the present invention, step 102 includes steps 1021 to 1023: Step 1021: Substitute the constraints into the objective function to obtain an unconstrained convex optimization problem.

[0025] Step 1022: Generate the control differential equations for the distributed energy storage based on the unconstrained convex optimization problem.

[0026] Step 1023: Solve the control differential equation to obtain the optimal consistency control quantity for the distributed energy storage.

[0027] As described above, using the proportional-integral (PI) consensus algorithm to solve the above optimization problem reduces the complexity of designing a voltage observer separately in traditional methods, eliminates the need for special initialization of the controller, and allows the system to self-recover from any initial state, thus enhancing system resilience.

[0028] In one embodiment of the present invention, step 1021 specifically includes: ; In the formula, Indicates all The steady-state value after convergence.

[0029] The optimal solution to the unconstrained convex optimization problem satisfies: ; In the formula, This indicates the consistency control quantity for distributed energy storage. The gradient of the objective function.

[0030] In one embodiment of the present invention, step 1022 specifically includes: ; In the formula, Indicates the first The first derivative of the consistency control quantity of a distributed energy storage system with respect to time. Indicates the first The first derivative of the integral auxiliary variable of a distributed energy storage system with respect to time. This represents the first preset weighting coefficient (a positive real number), used to adjust the convergence speed. Indicates the relationship with the first A distributed energy storage system is a set of neighboring nodes that are directly connected in the communication topology. express Time of the first The initial frequency deviation variable of a distributed energy storage system. Indicates the first The first distributed energy storage The sampling time of the next triggered event express Time of the first The initial frequency deviation variable of each neighboring node, Indicates the first The first distributed energy storage The sampling time of the next triggered event This represents the second preset weighting coefficient (a positive real number), used to adjust the convergence speed. express Time of the first An integral auxiliary variable for distributed energy storage. express Time of the first The integral auxiliary variable of each neighboring node, Indicates the gradient compensation coefficient. This represents the gradient term of the objective function. express Time of the first The initial frequency deviation variable of a distributed energy storage system. , Indicates the first The first distributed energy storage The sampling time of the next triggered event.

[0031] As described above, it achieves synchronous optimization of frequency recovery and power distribution without relying on continuous communication and controller initialization. It has self-recovery capability after communication interruption or network reconstruction, helping low-voltage distribution areas cope with random fluctuations on both the source and load sides, and improving the collaborative efficiency of distributed energy storage and the operational resilience of the distribution network.

[0032] In one embodiment of the present invention, step 103 specifically includes: ; In the formula, express Time of the first A reference value for the corrected angular frequency of distributed energy storage. Indicates the system's rated frequency. Indicates the first The droop control coefficient for distributed energy storage. express Time of the first Real-time output active power of distributed energy storage.

[0033] The optimal consistency control quantity is used to improve the single droop control, thereby satisfying two control objectives: (1) frequency control at the rated frequency; (2) active power between energy storage units. According to the droop control coefficient Distribute the allocation.

[0034] Specifically, under the optimal solution, Right now Therefore The same applies. The transformation yields Both sides simultaneously Summing yields In steady state, the frequency of the entire system is the same, therefore The above analysis shows that, under this control strategy, if the optimization problem can obtain the optimal solution, the output frequency of all energy storage converters can recover to the rated frequency in steady state. At the same time, active power can also be allocated according to the droop control coefficient.

[0035] In one embodiment of the present invention, step 104 includes steps 1041 to 1042: Step 1041: Calculate the first measurement error of the initial frequency deviation variable based on the current continuous initial frequency deviation variable of the distributed energy storage and the initial frequency deviation variable at the sampling time of the previous triggering event, specifically as follows: ; In the formula, The first measurement error represents the initial frequency deviation variable.

[0036] Step 1042: Calculate the second measurement error of the integral auxiliary variable based on the current continuous integral auxiliary variable of the distributed energy storage and the integral auxiliary variable at the sampling time of the previous triggering event, specifically as follows: ; In the formula, The second measurement error represents the auxiliary variable used for integration. express Time of the first An integral auxiliary variable for distributed energy storage.

[0037] As described above, the local state measurement error, which includes the first measurement error of the initial frequency deviation variable and the second measurement error of the integral auxiliary variable, is defined to determine whether the current state needs to be broadcast. This can ensure necessary data synchronization while reducing communication frequency.

[0038] In one embodiment of the present invention, step 105 includes: If the first measurement error and the second measurement error are substituted into the preset event triggering condition, it is determined whether the condition is met. If yes, the distributed energy storage is controlled to broadcast the current state; otherwise, the broadcast is not performed. The preset event triggering condition is: ; In the formula, This represents the first preset event trigger gain threshold (positive scalar). Indicates the periodic sampling time point The first measurement error, This represents the second preset event trigger gain threshold (positive scalar). Indicates the periodic sampling time point The second measurement error, k =0,1,2...

[0039] Specifically, the left side of the inequality represents the current cumulative error energy, and the right side represents the consistency deviation between neighboring nodes.

[0040] As described above, by pre-setting event triggering conditions to communicate only when necessary, the communication burden is greatly reduced, and the controller achieves independence from the initial state, thus possessing a natural self-recovery capability after communication interruption or network reconstruction.

[0041] In one embodiment of the present invention, step 105, controlling the current state of the distributed energy storage broadcast, includes: The initial frequency deviation variable and integral auxiliary variable of the distributed energy storage broadcast are controlled.

[0042] In one optional implementation, while controlling the distributed energy storage to broadcast its current state, the method further includes: The local state measurement error is reset to 0.

[0043] As described above, controlling the initial frequency deviation variable and integral auxiliary variable of distributed energy storage broadcasting achieves information synchronization, which is conducive to realizing more effective distributed energy storage control.

[0044] The method of the present invention described above is applied to a specific example as follows: Construct a system containing 5 distributed energy storage units ( i A low-voltage distribution area microgrid model (e.g., 1, 2, 3, 4, 5) is provided, with an undirected connected graph as the communication topology. Configuration. =314 rad / s, droop control factor m 1 = 0.02, m 2 = 0.04 m 3 = 0.03 m 4 = 0.05 m 5=0.01, initial configuration state: The system is initially in a steady state, and the output power of each energy storage unit is balanced. Configure control parameters: a =1.5, b =0.8, =0.5, sampling period h =0.1s, and All are 0.01.

[0045] exist tAt time 5 seconds, the load in the distribution area suddenly increased by 1.5 pu, causing the system frequency to drop (frequency deviation). At this point, the system initiates the above-described method of the present invention for coordinated control, as follows: The system constructs an objective function based on the current active power deficit. The aim is to simultaneously restore the frequency to its rated value and increase the active power to its rated value. m i The theoretical solution for the optimal consistency control quantity is calculated by allocating the parameters.

[0046] Initialize integral variables for each energy storage unit (No precise initialization is required; in this example, it is set to 0), and the control differential equations are started: ; The system no longer communicates continuously, but instead detects local state measurement errors at 0.1-second intervals. t At 5.1s, node 1 detected a cumulative error energy of 0.008, which is less than the threshold, so it did not trigger communication and remained in sleep mode. t At 5.3s, the cumulative error energy of node 1 reaches 0.015, the preset event trigger condition is met, and it is determined to be "event triggered". Node 1 broadcasts its current state ( Give the error to the neighboring node and reset the error to 0.

[0047] Each energy storage unit will calculate Correcting the droop control reference value Generate a new frequency reference command to adjust the converter output, such as... Figure 3 As shown.

[0048] Please refer to Figure 4 The present invention also provides a low-voltage distribution area distributed energy storage coordinated control system 200, including a memory 201, a processor 202, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the low-voltage distribution area distributed energy storage coordinated control method described above.

[0049] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps of the low-voltage distribution area distributed energy storage coordinated control method described above.

[0050] In summary, the low-voltage distributed energy storage coordinated control method, system, and storage medium of this invention construct an objective function with the goal of minimizing the difference between the initial frequency deviation variable of the distributed energy storage and the consistency control quantity, and establish constraints. The proportional-integral consistency algorithm is used to solve the optimization problem composed of the objective function and constraints to obtain the optimal consistency control quantity. Based on the optimal consistency control quantity, a corrected angular frequency reference value is calculated. It is then determined whether the acquired local state measurement error of the distributed energy storage meets the preset event triggering conditions. If so, the distributed energy storage is controlled to broadcast its current state. A frequency reference command for the distributed energy storage is generated based on the corrected angular frequency reference value, enabling the distributed energy storage to adjust the converter output using the frequency reference command. Thus, by solving the optimization problem through the proportional-integral consistency algorithm, coordinated control of distributed energy storage is achieved. The system requires the design of additional voltage observers and can self-recover without controller initialization, improving the stability of the power grid under extreme events. Furthermore, it introduces preset event triggering conditions, allowing data transmission only when necessary, effectively reducing redundant data traffic in the communication network, thus lowering the communication burden and improving the resilience of the distribution network. It also achieves synchronous optimization of frequency recovery and power distribution without relying on continuous communication and controller initialization, possessing self-recovery capabilities after communication interruptions or network reconfiguration. This helps low-voltage distribution areas cope with random fluctuations on both the source and load sides, improving the collaborative efficiency of distributed energy storage and the operational resilience of the distribution network. Additionally, it defines a local state measurement error, including a first measurement error of the initial frequency deviation variable and a second measurement error of the integral auxiliary variable, to determine whether the current state needs to be broadcast, ensuring necessary data synchronization while reducing communication frequency.

[0051] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A low-voltage transformer area distributed energy storage coordination control method, characterized in that, include: An objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable and the consistency control quantity of distributed energy storage, and constraints are established. The optimal consistency control quantity is obtained by solving the optimization problem consisting of the objective function and the constraints using the proportional-integral consensus algorithm. The corrected angular frequency reference value of the distributed energy storage is calculated based on the optimal consistency control quantity. Obtain the local state measurement error of the distributed energy storage; Determine whether the local state measurement error meets the preset event triggering conditions. If yes, control the distributed energy storage to broadcast the current state; otherwise, do not broadcast. The frequency reference command for the distributed energy storage is generated based on the corrected angular frequency reference value, so that the distributed energy storage can use the frequency reference command to adjust the converter output.

2. The method of claim 1, wherein, The objective function is constructed with the goal of minimizing the difference between the initial frequency deviation variable and the consistency control variable of distributed energy storage, as follows: ； In the formula, This represents the difference between the initial frequency deviation variable and the consistency control variable. This indicates the number of distributed energy storage systems participating in the control of the low-voltage distribution area. Indicates the first Consistency control quantity for distributed energy storage. Indicates the first The initial frequency deviation variable of a distributed energy storage system; Establish the constraints as follows: ； In the formula, Indicates the first The initial frequency deviation variable of a distributed energy storage system.

3. The method according to claim 1, characterized in that, The optimization problem consisting of the objective function and the constraints is solved using the proportional-integral consensus algorithm, yielding the optimal consensus control variables, including: Substituting the constraints into the objective function yields an unconstrained convex optimization problem. The control differential equations for the distributed energy storage are generated based on the unconstrained convex optimization problem. Solving the control differential equation yields the optimal consistency control quantity for the distributed energy storage.

4. The method according to claim 3, characterized in that, The control differential equations for the distributed energy storage are generated based on the unconstrained convex optimization problem, specifically as follows: ； In the formula, Indicates the first The first derivative of the consistency control quantity of a distributed energy storage system with respect to time. Indicates the first The first derivative of the integral auxiliary variable of a distributed energy storage system with respect to time. This represents the first preset weighting coefficient. Indicates the relationship with the first A distributed energy storage system is a set of neighboring nodes that are directly connected in the communication topology. express Time of the first The initial frequency deviation variable of a distributed energy storage system. Indicates the first The first distributed energy storage The sampling time of the next triggered event express Time of the first The initial frequency deviation variable of each neighboring node, Indicates the first The first distributed energy storage The sampling time of the next triggered event This represents the second preset weighting coefficient. express Time of the first An integral auxiliary variable for distributed energy storage. express Time of the first The integral auxiliary variable of each neighboring node, Indicates the gradient compensation coefficient. This represents the gradient term of the objective function. express Time of the first The initial frequency deviation variable of a distributed energy storage system. , Indicates the first The first distributed energy storage The sampling time of the next triggered event.

5. The method according to claim 4, characterized in that, Obtaining the local state measurement error of the distributed energy storage includes: The first measurement error of the initial frequency deviation variable is calculated based on the current continuous initial frequency deviation variable of the distributed energy storage and the initial frequency deviation variable at the sampling time of the previous triggering event. The second measurement error of the integral auxiliary variable is calculated based on the current continuous integral auxiliary variable of the distributed energy storage and the integral auxiliary variable at the sampling time of the previous triggering event.

6. The method according to claim 5, characterized in that, Determining whether the local state measurement error meets the preset event triggering conditions; if yes, controlling the distributed energy storage to broadcast the current state; otherwise, not broadcasting, including: If the first measurement error and the second measurement error are substituted into the preset event triggering condition, it is determined whether the condition is met. If yes, the distributed energy storage is controlled to broadcast the current state; otherwise, the broadcast is not performed. The preset event triggering condition is: ； In the formula, This indicates the first preset event trigger gain threshold. Indicates the periodic sampling time point The first measurement error, This indicates the second preset event trigger gain threshold. Indicates the periodic sampling time point The second measurement error.

7. The method according to claim 1, characterized in that, Controlling the current state of the distributed energy storage broadcast includes: The initial frequency deviation variable and integral auxiliary variable of the distributed energy storage broadcast are controlled.

8. The method according to claim 3, characterized in that, Substituting the constraints into the objective function yields an unconstrained convex optimization problem, specifically: ； In the formula, Indicates all The steady-state value after convergence Indicates the first The initial frequency deviation variable of a distributed energy storage system. This indicates the number of distributed energy storage systems participating in the control of the low-voltage distribution area. Indicates the first Consistency control quantity for distributed energy storage.

9. A low-voltage distribution area distributed energy storage coordinated control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements each step of the low-voltage distribution area distributed energy storage coordinated control method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the low-voltage distribution area distributed energy storage coordinated control method as described in any one of claims 1 to 8.

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