A power distribution network energy storage voltage regulation partition optimization method, device, medium and equipment

Abstract

This application relates to a method, apparatus, medium, and equipment for optimizing voltage regulation zones in a power distribution network using energy storage. The method includes the following steps: dividing the power distribution network into clustered zones based on its operating parameters; regulating the voltage of each clustered zone using energy storage devices; constructing an optimized zoning model for voltage regulation by the energy storage devices in the clustered zones; and obtaining the node range for voltage regulation by each energy storage device. This application can determine the charging and discharging power constraints of each energy storage device, reduce the total charging and discharging power of the energy storage devices, and reduce the cost of voltage regulation by the energy storage devices while ensuring a reasonable system voltage level.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method, apparatus, medium and equipment for optimizing voltage regulation zones in distribution networks using energy storage. Background Technology

[0002] With the large-scale integration of distributed power sources such as photovoltaics into the distribution network, the randomness of power in the distribution network is constantly increasing, and the risk of voltage exceeding the limit at distribution network nodes is increasing.

[0003] To address the voltage limit exceedance issue when a large number of distributed power sources, such as photovoltaic (PV) generators, are connected to the distribution network, solutions without altering the existing grid structure include: for single PV installations, point-of-connection reactor compensation, voltage control of the PV grid-connected inverter, and installation of energy storage devices; for multiple PV installations, end-of-line compensation reactors, central control combined with inverter reactive power control, and installation of energy storage devices. Adjusting the tap changer of on-load tap changers, limiting active power, and installing reactive power regulation devices such as capacitor banks and reactors can also resolve voltage limit exceedance issues when numerous PV installations are connected. Distributed energy storage systems, with their flexibility and controllability, can effectively address voltage limit exceedances caused by random variations in the output of distributed power sources such as PV. Existing voltage regulation methods for energy storage devices typically require voltage zoning to determine the area each energy storage device is responsible for controlling, in order to improve the speed of voltage control.

[0004] Existing voltage zoning methods for energy storage device voltage regulation mainly rely on electrical distance for zoning, neglecting the impact of energy storage device capacity and maximum charge / discharge power. To ensure the effectiveness of voltage zoning in energy storage device voltage regulation and the safe operation of the system, it is necessary to consider the constraints of energy storage device capacity and maximum charge / discharge power.

[0005] Therefore, how to provide a method for optimizing voltage regulation zones in distribution networks based on energy storage is an urgent problem to be solved. Summary of the Invention

[0006] This application provides a distribution network energy storage voltage regulation zoning optimization method to address the problem that existing voltage zoning methods for energy storage devices mainly rely on electrical distance, neglecting the impact of energy storage device capacity and maximum charging / discharging power. To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0007] In a first aspect, this application provides a method for optimizing voltage regulation zones in distribution networks using energy storage, comprising the following steps:

[0008] The distribution network is divided into clusters and partitions based on the distribution network operation parameters;

[0009] By adjusting the voltage of each cluster partition using energy storage devices, an optimized partitioning model for adjusting the voltage of cluster partitions using energy storage devices is constructed, thereby obtaining the node range for which each energy storage device is responsible for voltage regulation.

[0010] Optionally, the power distribution network operating parameters include one or more of the following: topology, line parameters, load parameters, and distributed generation parameters, wherein the distributed generation includes photovoltaic power.

[0011] Optionally, the step of clustering and partitioning the distribution network according to its parameters includes:

[0012] Power flow data is obtained through power flow calculation, and the power flow data includes node voltages;

[0013] The inter-node voltage sensitivity is calculated using the node voltage.

[0014] Based on the voltage sensitivity calculation, calculate the electrical distance between each node of the distribution network;

[0015] The optimal partition of the distribution network is determined based on the obtained electrical distance.

[0016] Optionally, the load parameters and distributed power generation parameters are respectively used to form daily load curves and daily photovoltaic output curves, and the power flow calculation selects typical daily load curves and daily photovoltaic output curves.

[0017] Optionally, the inter-node voltage sensitivity is the relationship between the change in active power injection between two nodes and the change in node voltage, and its calculation formula is as follows:

[0018]

[0019] Among them, E i P is the voltage at node i. j It is the power of node j. U represents the voltage change at node i caused by a unit power change at node j. N R is the rated voltage value of the nodes in the distribution network. i Let i be the equivalent resistance between node i and node i-1, and min(i,j) be the minimum value function. When calculating the node voltage sensitivity, the lower limit of accumulation is set to i=1, and the upper limit is the minimum value of the corresponding value between i and j.

[0020] Optionally, the electrical distance between each node of the distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows:

[0021]

[0022]

[0023] Where, d ij S is the electrical distance between node i and node j. ij It is the element in the i-th row and j-th column of the sensitivity matrix. It is the maximum value of the element in the j-th column of the sensitivity matrix; N is the number of network nodes in the distribution network.

[0024] Optionally, the optimal partitioning of the distribution network includes: a modularity definition method based on the weight of the electrical distance, which describes the electrical coupling degree of each node of the distribution network and uses the overall modularity of the distribution network as an indicator.

[0025] Optionally, the calculation formula for determining the optimal partition of the distribution network system is:

[0026]

[0027]

[0028] Where ρ is the system modularity, m is the sum of network edge weights, and k i and k j Let δ(i,j) be the sum of the edge weights of the edges connecting nodes i and j, respectively. Let δ(i,j) be the defined discrimination parameter. If nodes i and j are located in the same voltage zone, then δ(i,j) = 1. Otherwise, δ(i,j) = 0.

[0029] Optionally, when constructing the optimized partitioning model, the objective function is to minimize the power utilization of all energy storage devices.

[0030]

[0031] Where, N ess P represents the total number of energy storage devices. j Let be the output power of the energy storage device located at node j.

[0032] Optionally, the constraints of the optimized partitioning model include one or more of the following: 01 constraints, node voltage constraints, and energy storage device output power constraints.

[0033] Optionally, the expression for determining whether a node belongs to the partition under the responsibility of the energy storage device is as follows:

[0034]

[0035] Use μ i,j Indicates whether node i belongs to the zone where energy storage device j is responsible for voltage regulation, μ i,j The value can be 0 or 1; when μ i,j When μ equals 1, it indicates that node i belongs to the partition managed by energy storage device j; when μ equals 1, it indicates that node i belongs to the partition managed by energy storage device j. i,j When the value is 0, it means that node i does not belong to the partition that energy storage device j is responsible for.

[0036] Optionally, the node voltage constraint satisfies that the voltage of each node, regulated by the energy storage device, must be greater than the minimum value, and the voltage of each node, regulated by the energy storage device, must be less than the maximum allowable value.

[0037] Optionally, the expression for ensuring that the voltage of each node is greater than the minimum value through regulation by the energy storage device is as follows:

[0038]

[0039] Among them, U i The voltage at node i before the energy storage device participates in voltage regulation; S n,j U represents the voltage sensitivity coefficient of the energy storage device located at node j to the power regulation at node i; min This is the minimum allowable voltage.

[0040] Optionally, the expression for ensuring that the voltage of each node is less than the maximum allowable value through regulation by the energy storage device is as follows:

[0041] μ i,j U i +P j S n,j ≤U max (9)

[0042] In the formula, U max This represents the maximum permissible voltage.

[0043] Optionally, the output power constraint method of the energy storage device is that the output power of the energy storage device must be less than the maximum allowable value when participating in voltage regulation, and its expression is:

[0044] -P j,max ≤P j ≤P j,max (10)

[0045] Among them, P j,max This represents the maximum output power of the energy storage device located at node j.

[0046] Secondly, this application provides a distribution network energy storage voltage regulation zoning optimization device, including a computing unit and a model building unit, wherein:

[0047] The computing unit is used to obtain node voltages, construct voltage sensitivity matrices, and obtain distribution network cluster partitions;

[0048] The model building unit is used to construct an optimized partitioning model for voltage partitioning control of energy storage devices based on the charging and discharging power constraints of the energy storage devices and with the goal of minimizing the total charging and discharging power of the energy storage devices. The model is solved using mixed integer linear programming to obtain the node range for voltage regulation of each energy storage device.

[0049] Thirdly, this application provides a computer storage medium storing a program thereon, which, when executed by a processor, implements the steps in the distribution network energy storage voltage regulation zoning optimization method.

[0050] Fourthly, this application provides a computer device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the distribution network energy storage voltage regulation zoning optimization method.

[0051] The technical solutions provided in this application embodiment may include the following beneficial effects:

[0052] Based on typical scenarios of power distribution network operation, this application considers the charging and discharging power constraints of each energy storage device and aims to minimize the total charging and discharging power of the energy storage devices. It constructs an optimized partitioning model for voltage partitioning control of energy storage devices and uses mixed integer linear programming to solve the problem. This yields the node range for voltage regulation of each energy storage device, reduces the total charging and discharging power of the energy storage devices, and lowers the cost of voltage regulation of energy storage devices while ensuring a reasonable system voltage level.

[0053] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0054] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0055] Figure 1 This is a flowchart illustrating a distribution network energy storage voltage regulation zoning optimization method according to an exemplary embodiment;

[0056] Figure 2 This is a schematic diagram illustrating the specific process of a distribution network energy storage voltage regulation zoning optimization method according to an exemplary embodiment;

[0057] Figure 3 This is a schematic diagram of the structure of a distribution network energy storage voltage regulation zoning optimization device according to an exemplary embodiment;

[0058] Figure 4This is a schematic diagram of the structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0059] The following description and accompanying drawings fully illustrate specific embodiments described herein to enable those skilled in the art to practice them. Some embodiments may include or substitute parts and features of other embodiments. The scope of the embodiments herein encompasses the entire scope of the claims and all available equivalents thereof. Throughout this document, the terms “first,” “second,” etc., are used only to distinguish one element from another without requiring or implying any actual relationship or order between the elements. Indeed, a first element can also be referred to as a second element, and vice versa. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a structure, apparatus, or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the structure, apparatus, or device that includes said element. The various embodiments described herein are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments; similar or identical parts between embodiments can be referred to interchangeably.

[0060] The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" used in this document to indicate orientation or positional relationships are based on the orientation or positional relationships shown in the accompanying drawings and are used only for the convenience of describing this document and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting this application. In the description herein, unless otherwise specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two elements, or direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0061] In this document, unless otherwise stated, the term "multiple" means two or more.

[0062] In this article, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0063] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0064] Where there is no conflict, the embodiments and features described in this application may be combined with each other.

[0065] Please refer to Figure 1 This embodiment provides a method for optimizing voltage regulation zones in distribution networks using energy storage, including the following steps:

[0066] The distribution network is divided into clusters and partitions based on the distribution network operation parameters;

[0067] By adjusting the voltage of each cluster partition using energy storage devices, an optimized partitioning model for adjusting the voltage of cluster partitions using energy storage devices is constructed, thereby obtaining the node range for which each energy storage device is responsible for voltage regulation.

[0068] Combination Figure 2 In one embodiment, the power distribution network operating parameters include one or more of the following: topology, line parameters, load parameters, and distributed generation parameters, wherein distributed generation includes photovoltaic power.

[0069] In one embodiment, clustering the distribution network according to its parameters includes:

[0070] Power flow data is obtained through power flow calculations, and the power flow data includes node voltages.

[0071] Calculate the inter-node voltage sensitivity using node voltage;

[0072] Based on the voltage sensitivity calculation, calculate the electrical distance between each node in the distribution network;

[0073] The optimal partition of the distribution network is determined based on the obtained electrical distance.

[0074] In one embodiment, load parameters and distributed power generation parameters form daily load curves and daily photovoltaic output curves, respectively, and power flow calculations select typical daily load curves and daily photovoltaic output curves.

[0075] In one embodiment, the inter-node voltage sensitivity is the relationship between the change in active power injection between two nodes and the change in node voltage, and its calculation formula is as follows:

[0076]

[0077] Among them, E i P is the voltage at node i. j It is the power of node j. U represents the voltage change at node i caused by a unit power change at node j.N R is the rated voltage value of the nodes in the distribution network. i Let be the equivalent resistance value between node i and node i-1.

[0078] In one embodiment, the electrical distance between nodes in the distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows:

[0079]

[0080]

[0081] Where, d ij S is the electrical distance between node i and node j. ij It is the element in the i-th row and j-th column of the sensitivity matrix. It is the maximum value of the element in the j-th column of the sensitivity matrix; N is the number of network nodes in the distribution network, or the above equations (2) and (3) can be transformed into:

[0082]

[0083] In the formula, S ik It is the element in the i-th row and k-th column of the sensitivity matrix, S jk It is the element in the j-th row and k-th column of the sensitivity matrix, X in equations (2) and (3) above. ik X jk X ij These symbols are for simplifying formulas and have no special physical meaning.

[0084] In one embodiment, the optimal partitioning of the distribution network includes: a modularity definition method based on the weight of electrical distance to describe the degree of electrical coupling of each node in the distribution network, and using the overall modularity of the distribution network as an indicator.

[0085] In one embodiment, the formula for determining the optimal partition of the distribution network system is:

[0086]

[0087]

[0088] Where ρ is the system modularity, m is the sum of network edge weights, and k i and k j Let δ(i,j) be the sum of the edge weights of the edges connecting nodes i and j, respectively. Let δ(i,j) be the defined discrimination parameter. If nodes i and j are located in the same voltage zone, then δ(i,j) = 1. Otherwise, δ(i,j) = 0.

[0089] In one embodiment, when constructing the optimized partitioning model, the objective function is to minimize the power utilization of all energy storage devices.

[0090]

[0091] Where, N ess P represents the total number of energy storage devices. j Let be the output power of the energy storage device located at node j.

[0092] In one embodiment, the constraints for optimizing the partitioning model include one or more of the following: 01 constraints, node voltage constraints, and energy storage device output power constraints.

[0093] In one embodiment, the expression for determining whether a node belongs to the partition under the responsibility of the energy storage device using the 01 constraint is:

[0094]

[0095] Use μ i,j Indicates whether node i belongs to the zone where energy storage device j is responsible for voltage regulation, μ i,j The value can be 0 or 1; when μ i,j When μ equals 1, it indicates that node i belongs to the partition managed by energy storage device j; when μ equals 1, it indicates that node i belongs to the partition managed by energy storage device j. i,j When the value is 0, it means that node i does not belong to the partition that energy storage device j is responsible for.

[0096] In one embodiment, the node voltage constraint satisfies that the voltage of each node, regulated by the energy storage device, must be greater than the minimum value, and the voltage of each node, regulated by the energy storage device, must be less than the maximum allowable value.

[0097] In one embodiment, the expression for ensuring that the voltage of each node is greater than the minimum value through regulation by the energy storage device is as follows:

[0098]

[0099] Among them, U i The voltage at node i before the energy storage device participates in voltage regulation; S n,j U represents the voltage sensitivity coefficient of the energy storage device located at node j to the power regulation at node i; min This is the minimum allowable voltage.

[0100] In one embodiment, the expression for ensuring that the voltage of each node is less than the maximum allowable value through regulation by the energy storage device is as follows:

[0101] μ i,j U i +P j S n,j ≤U max (9)

[0102] In the formula, U max This represents the maximum permissible voltage.

[0103] In one embodiment, the output power constraint method for the energy storage device is that the output power of the energy storage device must be less than the maximum allowable value when participating in voltage regulation, and its expression is as follows:

[0104] -P j,max ≤P j ≤P j,max (10)

[0105] Among them, P j,max This represents the maximum output power of the energy storage device located at node j.

[0106] This application reads the distribution network topology, line parameters, historical load parameters, and distributed generation parameters; selects typical daily load curves and typical daily photovoltaic output curves to perform power flow calculations, obtains power flow data such as node voltages, constructs a voltage sensitivity matrix, and divides the distribution network into clusters; based on the electrical distance of node voltage sensitivity, the clusters are divided, and the voltage of each cluster is regulated by energy storage devices; when the distribution network energy storage devices regulate the voltage of each cluster, the charging and discharging power constraints of each energy storage device are considered, and an optimized partitioning model for voltage partitioning control of energy storage devices is constructed with the goal of minimizing the total charging and discharging power of energy storage devices. Mixed integer linear programming (MILP) is used to solve the model, obtaining the node range responsible for voltage regulation by each energy storage device; the aim is to overcome the shortcomings of existing voltage regulation methods for energy storage devices, which mainly partition based on electrical distance, neglecting the influence of energy storage device capacity and maximum charging and discharging power. This application proposes a method for voltage zoning in energy storage equipment regulation, considering both the capacity and maximum charging / discharging power of the energy storage devices. It employs mixed-integer linear programming to improve the effectiveness of voltage zoning and ensure safe system operation. The proposed voltage zoning optimization method considers the charging / discharging power constraints of each energy storage device, reducing the total charging / discharging power and lowering the cost of voltage regulation while maintaining a reasonable system voltage level.

[0107] In one embodiment, a distribution network energy storage voltage regulation zoning optimization device is provided, comprising a computing unit and a model building unit, wherein:

[0108] The computing unit is used to obtain node voltages, construct voltage sensitivity matrices, and obtain distribution network cluster partitions.

[0109] The model building unit is used to construct an optimized partitioning model for voltage partitioning control of energy storage devices based on the charging and discharging power constraints of the energy storage devices and with the goal of minimizing the total charging and discharging power of the energy storage devices. The model is solved using mixed integer linear programming to obtain the node range for voltage regulation of each energy storage device.

[0110] Combination Figure 3 In one embodiment, a distribution network energy storage voltage regulation zoning optimization device is provided, which realizes distribution network energy storage equipment voltage regulation zoning optimization control through the steps in the distribution network energy storage voltage regulation zoning optimization method disclosed in any of the above embodiments.

[0111] In one embodiment, a computer storage medium is provided having a program stored thereon, characterized in that, when executed by a processor, the program implements the steps as described in any of the above embodiments of the distribution network energy storage voltage regulation zoning optimization method.

[0112] In one embodiment, a computer device is provided, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the distribution network energy storage voltage regulation zoning optimization method.

[0113] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores static and dynamic information data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0114] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the device to which the present application is applied. Specific devices may include more or fewer components than those shown in the figure, or may combine certain components, or may have different component arrangements.

[0115] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0116] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the method embodiments described above.

[0117] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Wherein: any reference to memory, storage, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0118] It should be noted that the above description is merely some embodiments of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

[0119] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0120] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for optimizing voltage regulation zones in a power distribution network using energy storage, characterized in that, Includes the following steps: The distribution network is divided into clusters and partitions based on the distribution network operation parameters; By adjusting the voltage of each cluster partition using energy storage devices, an optimized partitioning model for adjusting the voltage of cluster partitions using energy storage devices is constructed, thereby obtaining the node range for which each energy storage device is responsible for voltage regulation. When constructing the optimized zoning model, the objective function is to minimize the power utilization of all energy storage devices, which is expressed as follows: (6) in, The total number of all energy storage devices. For the node The output power of the energy storage device; The constraints for optimizing the partitioned model include one or more of the following: 0-1 constraints, node voltage constraints, and energy storage device output power constraints. The expression for ensuring that the voltage at each node is greater than the minimum value through regulation by the energy storage device is as follows: (8) in, Before the energy storage device participates in voltage regulation, the node voltage; Indicates that it is located at node Energy storage device power regulation on nodes Voltage sensitivity coefficient; This is the minimum allowable voltage value; The expression for ensuring that the voltage at each node is less than its maximum value through regulation by the energy storage device is as follows: (9) In the formula, This represents the maximum permissible voltage.

2. The distribution network energy storage voltage regulation zoning optimization method according to claim 1, characterized in that, The power distribution network operating parameters include one or more of the following: topology, line parameters, load parameters, and distributed generation parameters, wherein the distributed generation includes photovoltaic power.

3. The distribution network energy storage voltage regulation zoning optimization method according to claim 2, characterized in that, The process of dividing the distribution network into clusters based on its parameters includes: Power flow data is obtained through power flow calculation, and the power flow data includes node voltages; The inter-node voltage sensitivity is calculated using the node voltage. Based on the voltage sensitivity calculation, calculate the electrical distance between each node of the distribution network; The optimal partition of the distribution network is determined based on the obtained electrical distance.

4. The distribution network energy storage voltage regulation zoning optimization method according to claim 3, characterized in that, The load parameters and distributed power generation parameters form the daily load curve and the daily photovoltaic output curve, respectively. The power flow calculation selects typical daily load curves and daily photovoltaic output curves.

5. The distribution network energy storage voltage regulation zoning optimization method according to claim 4, characterized in that, The inter-node voltage sensitivity is the relationship between the change in active power injection between two nodes and the change in node voltage, and its calculation formula is as follows: (1) in, It is a node voltage, It is a node power, Represents a node The node caused by the unit power change The amount of voltage change. The rated voltage value of the nodes in the distribution network. For nodes With nodes The equivalent resistance between them As a minimum function, the lower limit of accumulation is set to [value] when calculating node voltage sensitivity. =1, upper limit is The minimum value between.

6. The distribution network energy storage voltage regulation zoning optimization method according to claim 5, characterized in that, The electrical distance between the nodes of the distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows: (2) (3) in, It is a node With nodes Electrical distance between them It is the first in the sensitivity matrix Line number Column elements, It is the first in the sensitivity matrix The maximum value among the column elements; This represents the number of network nodes in the distribution network.

7. The distribution network energy storage voltage regulation zoning optimization method according to claim 6, characterized in that, The optimal partitioning of the distribution network includes: a modularity definition method based on the weight of the electrical distance, which describes the electrical coupling degree of each node of the distribution network, and uses the overall modularity of the distribution network as an indicator.

8. The distribution network energy storage voltage regulation zoning optimization method according to claim 7, characterized in that, The calculation formula for determining the optimal partition of the distribution network system is as follows: (4) (5) in, For system modularity, The sum of network edge weights. and They are nodes and nodes The sum of the weights of connected edges. For the defined discrimination parameters, if the node With nodes If it is located within a voltage zone, then =1, in other cases =0.

9. The distribution network energy storage voltage regulation zoning optimization method according to claim 1, characterized in that, The expression for determining whether a node belongs to the zone managed by the energy storage device under the 01 constraint is as follows: (7) use Represents a node Does it belong to energy storage equipment? The zone responsible for voltage regulation The value can be 0 or 1; when When equal to 1, it represents a node. It belongs to energy storage equipment The assigned partition; when When equal to 0, it represents a node. Not a type of energy storage device The divisions under my responsibility.

10. The distribution network energy storage voltage regulation zoning optimization method according to claim 1, characterized in that, The energy storage device's output power constraint method requires that the output power of the energy storage device be less than the maximum allowable value when participating in voltage regulation. The expression for this is: (10) in, For the node The maximum output power of the energy storage device.

11. A distribution network energy storage voltage regulation zone optimization device, characterized in that, It includes computational units and model building units, wherein: The computing unit is used to obtain node voltages, construct voltage sensitivity matrices, and obtain distribution network cluster partitions; The model building unit is used to construct an optimized partitioning model for voltage partitioning control of energy storage devices based on the charging and discharging power constraints of the energy storage devices and with the goal of minimizing the total charging and discharging power of the energy storage devices. The model is solved using mixed integer linear programming to obtain the node range for voltage regulation of each energy storage device. When constructing the optimized zoning model, the objective function is to minimize the power utilization of all energy storage devices, which is expressed as follows: (6) in, The total number of all energy storage devices. For the node The output power of the energy storage device; The constraints for optimizing the partitioned model include one or more of the following: 0-1 constraints, node voltage constraints, and energy storage device output power constraints. The expression for ensuring that the voltage at each node is greater than the minimum value through regulation by the energy storage device is as follows: (8) in, Before the energy storage device participates in voltage regulation, the node voltage; Indicates that it is located at node Energy storage device power regulation on nodes Voltage sensitivity coefficient; This is the minimum allowable voltage value; The expression for ensuring that the voltage at each node is less than its maximum value through regulation by the energy storage device is as follows: (9) In the formula, This represents the maximum permissible voltage.

12. The distribution network energy storage voltage regulation zoning optimization device according to claim 11, characterized in that, The power distribution network operating parameters include one or more of the following: topology, line parameters, load parameters, and distributed generation parameters, wherein the distributed generation includes photovoltaic power.

13. The distribution network energy storage voltage regulation zoning optimization device according to claim 12, characterized in that, The distribution network is divided into clusters and partitions based on its parameters, including: Power flow data is obtained through power flow calculation, and the power flow data includes node voltages; The inter-node voltage sensitivity is calculated using the node voltage. Based on the voltage sensitivity calculation, calculate the electrical distance between each node of the distribution network; The optimal partition of the distribution network is determined based on the obtained electrical distance.

14. The distribution network energy storage voltage regulation zoning optimization device according to claim 13, characterized in that, The load parameters and distributed power generation parameters form the daily load curve and the daily photovoltaic output curve, respectively. The power flow calculation selects typical daily load curves and daily photovoltaic output curves.

15. A computer storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the distribution network energy storage voltage regulation zoning optimization method as described in any one of claims 1-10.

16. A computer device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the distribution network energy storage voltage regulation zoning optimization method as described in any one of claims 1-10.

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