Electric grid energy storage voltage regulation zone optimization method, device, medium and apparatus

Abstract

A method, device, medium, and equipment for optimizing energy storage voltage regulation partitions for a power grid, in which the method for optimizing energy storage voltage regulation partitions for a power grid includes a step (S110) of performing cluster partitioning for a power grid according to a power grid operation parameter, and a step (S120) of constructing an optimization partition model in which an energy storage device regulates the voltage of each cluster partition, and the energy storage device regulates the voltage of the cluster partition, and obtaining a node range for which each energy storage device regulates the voltage.

Description

[Technical field]

[0001] This application claims priority to a Chinese patent application bearing application number 202211468915.6, filed with the China Patent Office on November 22, 2022, the entire contents of which are incorporated herein by reference.

[0002] The present application relates to the technical field of power systems, such as power grid energy storage voltage regulation partition optimization methods, devices, media and equipment. [Background technology]

[0003] As distributed power sources such as solar power generation devices are accessed on a large scale by grid-connected sources, the randomness of power on the grid continues to increase, increasing the risk of node voltages on the grid exceeding their limits.

[0004] In order to solve the problem of voltage exceeding the limit when a large number of distributed power sources such as photovoltaic power generation devices are accessed to the power grid, the measures to be taken, under the premise of not changing the grid framework, are mainly: when a single photovoltaic power generation device is accessed, reactor compensation at the access point, voltage control of the photovoltaic power generation grid-connected inverter and installation of energy storage equipment can be used; when multiple photovoltaic power generation devices are accessed, reactor compensation method for compensating at the end, reactive power control method of master controller and inverter combination and installation of energy storage equipment can be used. On-load voltage regulation transformer tap adjustment, active power limiting, reactive power regulation device such as capacitor bank and reactor can also solve the problem of voltage exceeding the limit when a large number of photovoltaic power generation devices are accessed. Among them, the distributed energy storage equipment system has the characteristics of being flexible and controllable, and can effectively solve the problem of voltage exceeding the limit caused by random changes in the output of distributed power sources such as photovoltaic power generation devices. In order to improve the speed of voltage control, the voltage adjustment method for energy storage equipment in the related art usually requires voltage partitioning to determine the area in which each energy storage equipment is responsible for voltage control.

[0005] The above-mentioned voltage partitioning method for voltage regulation of energy storage equipment mainly partitions multiple power generating devices according to electrical distance, and the partitioning is not rational, so there is still a risk that the node voltage of the power grid will exceed the limit, which creates a safety risk for the operation of the power grid. Summary of the Invention

[0006] The embodiments of the present application provide a grid energy storage voltage regulation partition optimization method, which solves the problem that the partition in the related art is not reasonable and there still exists a safety risk in the operation of the grid.

[0007] The present application, performing cluster partitioning on the electric grid in response to electric grid operating parameters; The present invention provides a power grid energy storage voltage regulation section optimization method, which includes: regulating the voltage of each cluster section by an energy storage device; constructing an optimization section model in which the energy storage device regulates the voltage of the cluster section; and obtaining a node range for which each energy storage device regulates the voltage.

[0008] Preferably, the power grid operation parameters include at least one of a topology structure, a line parameter, a load parameter, and a distributed generation parameter, and the distributed generation includes a photovoltaic power generation device.

[0009] Preferably, the step of performing cluster partitioning on the power distribution network in response to a parameter of the power distribution network comprises: Obtaining power flow data including a node voltage of each node in a power distribution network by a power flow calculation; calculating voltage sensitivities between nodes according to the node voltages; calculating an electrical distance between nodes in a power distribution network as a function of voltage sensitivities between the nodes; and performing cluster partitioning on a power distribution network according to the obtained electrical distances between the nodes.

[0010] Preferably, the load parameters form a load daily curve and the distributed generation parameters form a photovoltaic power output daily curve, and the power flow calculation selects the load daily curve and the photovoltaic power output daily curve.

[0011] Preferably, the voltage sensitivity between the nodes is a relationship between a change in the amount of effective power injected into one of the two nodes and a change in the node voltage of the other node, and the calculation formula therefor is as follows: JPEG0007681119000001.jpg1953 Among them, E i is the voltage at node i, and P j is the power of node j, and ∂E i / ∂P jrepresents the change in voltage at node i due to a change in unit power at node j, and U N is the nominal voltage value of the distribution network, and R i is the equivalent resistance value between node i and node i-1, and min(i,j) is the minimum function. When calculating the voltage sensitivity between the nodes, the lower limit of the accumulation is set to i=1 and the upper limit is the minimum value among i, j.

[0012] Preferably, the electrical distance between nodes in the power distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows: JPEG0007681119000002.jpg1857 JPEG0007681119000003.jpg3146 Among them, d ij is the electrical distance between node i and node j, and S ij is the element in the i-th row and j-th column of the sensitivity matrix, and max j S ij is the maximum value among the elements of the j-th column in the sensitivity matrix, and N is the number of nodes in the power distribution network.

[0013] Preferably, the cluster partitioning of the power distribution network includes describing the electrical coupling degree of each node of the power distribution network according to a modularity definition method based on the electrical distance weight, and performing cluster partitioning of the power distribution network using the overall modularity of the power distribution network as an index.

[0014] Preferably, the above-mentioned calculation formula for performing cluster partitioning on the power distribution network is as follows: JPEG0007681119000004.jpg1671 JPEG0007681119000005.jpg1686 where ρ is the modularity of the system, m is the sum of the edge weights of the network, and k i and k jare the sum of edge weights of the edges connected to node i and node j, respectively, and δ(i,j) is the defined discrimination parameter, where δ(i,j)=1 if node i and node j are located within one voltage partition, and δ(i,j)=0 otherwise.

[0015] Preferably, when constructing the above-mentioned optimization division model, the objective function is to minimize the power usage of all energy storage devices, and the objective function is expressed as follows: JPEG0007681119000006.jpg1834 Of these, N ess is the number of all energy storage facilities, and P j is the output power of the energy storage facility located at node j.

[0016] Preferably, the constraints of the optimization zone model include at least one of a 01 constraint, a node voltage constraint, and an energy storage facility output power constraint.

[0017] Preferably, the 01 constraint determines whether the node belongs to a partition served by an energy storage facility, and the expression is as follows: JPEG0007681119000007.jpg1829 Among them, μ i、j indicates whether node i belongs to the partition in which energy storage facility j is responsible for voltage regulation, and μ i、j The value of is 0 or 1, and μ i、j If is equal to 1, it means that node i belongs to the partition served by energy storage facility j, and μ i、j If is equal to 0, it indicates that node i does not belong to the partition served by,energy storage facility j.

[0018] Preferably, said node voltage constraint satisfies that the voltage of each node should be greater than a minimum allowed voltage value and less than a maximum allowed voltage value due to the adjustment of the energy storage facility.

[0019] Preferably, the expression for the voltage of each node to be greater than the minimum allowable voltage value due to the adjustment of the energy storage facility is as follows: JPEG0007681119000008.jpg2353 Among them, U i is the voltage of node i before the energy storage device participates in voltage regulation, and S i、j represents the voltage sensitivity coefficient for node i of the power regulation of the energy storage facility located at node j, and U min is the minimum voltage allowed.

[0020] Preferably, the expression for the voltage of each node to be less than the maximum allowable voltage value due to the adjustment of the energy storage device is as follows: JPEG0007681119000009.jpg1061 In the formula, U max is the maximum voltage allowed.

[0021] Preferably, the output power constraint of the energy storage device satisfies that the output power of the energy storage device participating in voltage regulation is less than the maximum allowable power value, and the expression is as follows: JPEG0007681119000010.jpg1054 Among them, P j、max is the maximum power of the output power of the energy storage facility located at node j.

[0022] The present application, A calculation unit configured to obtain node voltages of each node in the power distribution network, construct a voltage sensitivity matrix, and obtain a cluster partition of the power distribution network; The present invention provides a power distribution grid energy storage voltage regulation section optimization device, comprising: a model construction unit configured to construct an optimization section model in which the energy storage equipment controls the voltage of the cluster section according to the charging and discharging power constraints of the energy storage equipment, with the goal of minimizing the total charging and discharging power of the energy storage equipment, and adopt a mixed integer linear programming to solve the problem, so as to obtain the node range that each energy storage equipment is responsible for by regulating the voltage.

[0023] The present application provides a computer storage medium having stored thereon a program that, when executed by a processor, implements steps in a power grid energy storage voltage regulation partition optimization method.

[0024] The present application provides a computing device comprising a memory, a processor, and a program stored in the memory and operable on the processor, the program, when executed by the processor, implementing steps in a method for optimizing an energy storage voltage regulation partition of an electrical grid. [Brief description of the drawings]

[0025] [Figure 1A] FIG. 2 is a flow diagram of a grid energy storage voltage regulation partition optimization method according to an exemplary embodiment. [Figure 1B] FIG. 1 is a topology diagram of a power distribution network according to one embodiment. [Diagram 2] FIG. 2 is a schematic diagram of a specific flow of a power grid energy storage voltage regulation partition optimization method according to an exemplary embodiment; [Diagram 3] FIG. 2 is a structural schematic diagram of a power grid energy storage voltage regulation block optimization device according to an exemplary embodiment; [Figure 4] FIG. 2 is a structural schematic diagram of a computer device according to an exemplary embodiment; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] The following description and drawings show specific implementations of the present document for those skilled in the art to practice them. In the present document, the terms "first", "second", etc. are merely used to distinguish one element from another element, and do not require or imply the existence of any actual relationship or order between these elements. In practice, the first element may be called the second element, and vice versa. Furthermore, the terms "comprise", "include", or any other variations thereof are intended to cover a non-exclusive inclusion, whereby a structure, device, or apparatus that includes a set of elements includes not only those elements, but also other elements not expressly listed or elements inherent in such structure, device, or apparatus. Unless further limited, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the structure, device, or apparatus that includes the element. The embodiments in the present document are described in a progressive manner, and the emphasis in each embodiment is on the differences from other embodiments, and the same and similar parts between the embodiments may be referred to each other.

[0027] The orientations or positional relationships indicated by the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document are based on the orientations or positional relationships shown in the drawings, and are merely intended to facilitate and simplify the description of this document, and do not indicate or imply that such devices or elements must have a specific orientation, be configured and operated in a specific orientation, and therefore cannot be understood as limiting this application. In the description of this document, unless otherwise specified and limited, the terms "attach", "connect", and "connect" should be understood in a broad sense, for example, mechanical connection or electrical connection, or internal communication between two elements, may be directly connected, or may be indirectly connected through an intermediate medium, and a person skilled in the art can understand the specific meaning of the above terms according to the specific situation.

[0028] In this document, unless otherwise stated, the term "plurality" means two or more than two.

[0029] In this document, the symbol " / " indicates that the objects before and after are in an "or" relationship. For example, A / B means A or B.

[0030] In this document, the term "and / or" is a relationship that describes the relationship of objects and indicates that a three-way relationship can exist. For example, A and / or B means A or B, or A and B.

[0031] Where not inconsistent, embodiments and features of the embodiments in the present application may be combined with each other.

[0032] The present application considers the impact of the capacity and maximum charge / discharge power of the energy storage equipment, and realizes the effectiveness of voltage division in voltage regulation of the energy storage equipment and the safe operation of the system.

[0033] Referring to FIG. 1A, the present embodiment provides a power grid energy storage voltage regulation partition optimization method, which includes the following steps.

[0034] At S110, cluster partitioning is performed on the power grid according to the power grid operating parameters.

[0035] In S120, an optimized partition model is constructed in which the energy storage device adjusts the voltage of each cluster partition, and the energy storage device adjusts the voltage of the cluster partition, and a node range for which each energy storage device adjusts the voltage is obtained.

[0036] Referring to FIG. 1B, FIG. 1B shows a topology diagram of a power distribution network, which is divided into three cluster sections and includes an Energy Storage System (ESS), as well as electrical equipment such as electricity usage equipment and solar power plants that access the power distribution network, represented by black filled circles.

[0037] With reference to FIG. 2, in one embodiment, the power grid operation parameters include one or more of a topology structure, line parameters, load parameters, and distributed generation parameters, and the distributed generation includes a solar power generation device.

[0038] In this embodiment, the topology structure is the topology structure of a power distribution network, the line parameters are parameters of the conductors in the power distribution network, such as material, cross-sectional area, length, and resistance at standard temperature, etc., the load parameters are parameters of the electrical equipment accessed by the power distribution network, including active power and reactive power, and the distributed power parameters include a wide voltage input range (voltage range, frequency range), output voltage, and output power.

[0039] In one embodiment, performing cluster partitioning on the power distribution network according to parameters of the power distribution network includes obtaining power flow data including node voltages of each node in the power distribution network by power flow calculation, calculating voltage sensitivities between the nodes according to the node voltages, calculating electrical distances between the nodes in the power distribution network according to the voltage sensitivities between the nodes, and performing cluster partitioning on the power distribution network according to the obtained electrical distances between the nodes.

[0040] In this embodiment, the nodes are electrical equipment such as electricity-consuming equipment and solar power plants that are connected to the power grid.

[0041] In one embodiment, the load parameters form a load daily curve and the distributed generation parameters form a solar power output daily curve, and the power flow calculation selects the load daily curve and the solar power output daily curve.

[0042] In one embodiment, the voltage sensitivity between nodes is the relationship between the change in the amount of active power injected between two nodes and the change in the node voltage, and the calculation formula is as follows: JPEG0007681119000011.jpg1946(1) Among them, E iis the voltage at node i, and P j is the power of node j, and ∂E i / ∂P j represents the change in voltage at node i due to a change in unit power at node j, and U N is the nominal voltage value of the distribution network, and R i is the equivalent resistance value between node i and node i-1, and min(i,j) is the minimum function. When calculating the voltage sensitivity between the nodes, the lower limit of the accumulation is set to i=1 and the upper limit is the minimum value among i, j.

[0043] The relationship between the change in active power injection between two nodes and the change in node voltage can be understood as the relationship between the change in active power injection at one of the two nodes and the change in node voltage at the other node.

[0044] In one embodiment, the electrical distance between nodes in the power distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows: JPEG0007681119000012.jpg1754(2) JPEG0007681119000013.jpg2347(3) Among them, d ij is the electrical distance between node i and node j, and S ij is the element in the i-th row and j-th column of the sensitivity matrix, and max j S ij is the maximum value among the elements of the j-th column in the sensitivity matrix, and N is the number of nodes in the power distribution network. Alternatively, the above formulas (2) and (3) can be transformed as follows: JPEG0007681119000014.jpg2382(23) In the formula, S ik is the element in the i-th row and k-th column of the sensitivity matrix, and S jkis the element in the jth row and kth column of the sensitivity matrix, and is X in the above formulas (2) and (3). ik , X jk , X ij is a symbol used to simplify mathematical expressions and does not have any special physical meaning.

[0045] In one embodiment, performing cluster partitioning on the power distribution network includes describing the electrical connectivity of each node of the power distribution network according to a modularity definition method based on electrical distance weights, and performing cluster partitioning on the power distribution network using the overall modularity of the power distribution network as an index.

[0046] In one embodiment, the calculation formula for performing cluster partitioning on the power grid is as follows: JPEG0007681119000015.jpg1670(4) JPEG0007681119000016.jpg1476(5) where ρ is the modularity of the system, m is the sum of the edge weights of the network, and k i and k j are the sum of edge weights of the edges connected to node i and node j, respectively, and δ(i,j) is the defined discrimination parameter, where δ(i,j)=1 if node i and node j are located within one voltage partition, and δ(i,j)=0 otherwise.

[0047] In one embodiment, when constructing the optimization partition model, the objective function is to minimize the power usage of all energy storage devices, and the objective function is expressed as follows: JPEG0007681119000017.jpg1835(6) Of these, N ess is the number of all energy storage facilities, and P j is the output power of the energy storage facility located at node j.

[0048] In one embodiment, the constraints of the optimization zone model include one or more of an 01 constraint, a node voltage constraint, and an energy storage facility output power constraint.

[0049] In one embodiment, the 01 constraint determines whether the node belongs to a partition served by an energy storage facility, and the expression is as follows: JPEG0007681119000018.jpg1826(7) Among them, μ i、j indicates whether node i belongs to the partition in which energy storage facility j is responsible for voltage regulation, and μ i、j The value of is 0 or 1, and μ i、j If is equal to 1, it means that node i belongs to the partition served by energy storage facility j, and μ i、j If is equal to 0, it indicates that node i does not belong to the partition served by,energy storage facility j.

[0050] In one embodiment, the node voltage constraint satisfies that the voltage of each node should be greater than the minimum allowed voltage and less than the maximum allowed voltage due to the adjustment of the energy storage facility.

[0051] In one embodiment, the expression for the voltage of each node to be greater than the minimum allowable voltage value due to the adjustment of the energy storage facility is as follows: JPEG0007681119000019.jpg2148(8) Among them, U i is the voltage of node i before the energy storage device participates in voltage regulation, and S i、j represents the voltage sensitivity coefficient for node i of the power regulation of the energy storage facility located at node j, and U min is the minimum voltage allowed.

[0052] In one embodiment, the expression for the voltage at each node to be less than the maximum allowable voltage value due to the adjustment of the energy storage facility is as follows: JPEG0007681119000020.jpg849(9) In the formula, U max is the maximum voltage allowed.

[0053] In one embodiment, the output power constraint of the energy storage device is such that the output power of the energy storage device participating in voltage regulation is less than the maximum allowable power value, and the expression is as follows: JPEG0007681119000021.jpg1052(10) Among them, P j、max is the maximum power of the output power of the energy storage facility located at node j.

[0054] The method of the present application includes: reading a topology structure, line parameters, historical load parameters, and distributed power parameters of a power distribution network, selecting a daily load curve and a daily photovoltaic power output curve, performing a power flow calculation, obtaining power flow data such as node voltages, constructing a voltage sensitivity matrix, performing cluster partitioning for the power distribution network, calculating the electrical distance between the nodes based on the voltage sensitivity between the nodes, performing cluster partitioning according to the electrical distance between the nodes, adjusting the voltage of each partition using energy storage devices, taking into account the charge and discharge power constraints of each energy storage device when the energy storage devices of the power distribution network adjust the voltage of each partition, aiming to minimize the total charge and discharge power of the energy storage devices, constructing an optimized partition model for voltage partition control of the energy storage devices, and adopting mixed integer linear programming (MILP) to solve the problem, and obtaining a node range for which each energy storage device adjusts the voltage. This application proposes that when the energy storage equipment regulates the voltage in a section, the capacity and maximum charge and discharge power of the energy storage equipment are considered, the total charge and discharge power of the energy storage equipment is minimized, an optimization section model of the voltage section control of the energy storage equipment is constructed, and a mixed integer linear programming is adopted to solve the problem, and each energy storage equipment obtains the node range that it is responsible for regulating the voltage, so as to improve the effectiveness of the voltage section in the voltage regulation of the energy storage equipment and ensure the safe operation of the system. The proposed energy storage equipment voltage section optimization method considers the charge and discharge power constraints of each energy storage equipment, reduces the total charge and discharge power of the energy storage equipment, ensures that the voltage level of the system is reasonable, and at the same time reduces the cost of voltage regulation of the energy storage equipment.

[0055] In one embodiment, a power distribution grid energy storage voltage regulation zone optimization device is provided, which includes a calculation unit 1 and a model construction unit 2, in which the calculation unit 1 is configured to obtain node voltages of each node in the power distribution grid, construct a voltage sensitivity matrix, and obtain cluster zones of the power distribution grid; the model construction unit 2 is configured to, according to the charge and discharge power constraints of the energy storage equipment, aim to minimize the total charge and discharge power of the energy storage equipment, construct an optimization zone model in which the energy storage equipment controls the voltage of the cluster zone, and adopt a mixed integer linear programming to solve the problem and obtain the node range for which each energy storage equipment is responsible for voltage regulation.

[0056] In relation to FIG. 3 , in one embodiment, a power grid energy storage voltage regulation partition optimization device is provided, which realizes optimized control of a voltage regulation partition of an energy storage facility in a power grid by steps in the power grid energy storage voltage regulation partition optimization method disclosed in any of the above embodiments.

[0057] In one embodiment, a computer storage medium is provided having stored thereon a program which, when executed by a processor, implements the steps of any one of the embodiments of the grid energy storage voltage regulation partition optimization method described above.

[0058] In one embodiment, a computing device is provided that includes a memory, a processor, and a program stored in the memory and executable by the processor, the program, when executed by the processor, implementing steps in a method for optimizing an energy storage voltage regulation partition of an electrical grid.

[0059] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in FIG. 4. The computer device includes a processor, a memory, and a network interface, which are connected by a system bus. The processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data of static information and dynamic information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes the steps in the above method embodiment.

[0060] In one embodiment, there is further provided a computing device comprising a memory having a computer program stored therein and a processor, the computing device implementing the steps of the above method embodiments when the processor executes the computer program.

[0061] In one embodiment, a computer readable storage medium is provided having stored thereon a computer program which, when executed by a processor, implements the steps of the above method embodiments.

[0062] Those skilled in the art can understand that the implementation of all or part of the flow of the method of the above embodiment can be completed by hardware associated with computer program instructions, and the computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the flow of the embodiment including the above method can be realized. Any reference to memory, storage, database, or other medium used in the embodiments of the present application may 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, optical memory, etc. Volatile memory may include Random Access Memory (RAM) or external cache memory. By way of explanation and not by way of restriction, RAM may be of various types, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0063] Also, although operations have been described employing a particular order, this should not be understood as requiring that these operations be performed in the particular order or sequence shown. In certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although the above discussion includes specific implementation details, these should not be construed as limiting the scope of the present application. Some features that are described in the context of a single embodiment may be implemented in a single embodiment in combination. Multiple features that are described in the context of a single embodiment may be implemented in multiple embodiments alone or in any suitable subcombination.

Claims

1. performing cluster partitioning on the electric grid in response to electric grid operating parameters; Adjusting the voltage of each cluster section by the energy storage device, constructing an optimized section model in which the energy storage device adjusts the voltage of the cluster section, and obtaining a node range that each energy storage device is responsible for by adjusting the voltage; When constructing the above-mentioned optimization division model, the objective function is to minimize the power usage of all energy storage devices, and the objective function is as follows: Wherein, N ess is the number of all energy storage devices, and P j is the output power of the energy storage device located at node j; A power grid energy storage voltage regulation partition optimization method.

2. The power grid operation parameters include at least one of a topology structure, a line parameter, a load parameter, and a distributed power source parameter, and the distributed power source includes a solar power generation device; The method of claim 1.

3. performing cluster partitioning on the electric power grid in response to the electric power grid operating parameters, Obtaining power flow data including a node voltage of each node in a power distribution network by a power flow calculation; calculating voltage sensitivities between nodes according to the node voltages; calculating an electrical distance between nodes in a power distribution network as a function of voltage sensitivities between the nodes; and performing cluster partitioning on a power distribution network according to the obtained electrical distances between the nodes. The method of claim 2.

4. The load parameters form a load daily curve, and the distributed generation parameters form a photovoltaic power output daily curve, and the power flow calculation selects a load daily curve and a photovoltaic power output daily curve. The method according to claim 3.

5. The voltage sensitivity between the nodes is the relationship between the change in the amount of active power injected into one of the two nodes and the change in the node voltage of the other node, and the calculation formula is as follows: Among them, E. ｉ is the voltage at node i, and P ｊ is the power of node j, and ∂E ｉ / ∂P ｊ represents the change in voltage at node i due to a change in unit power at node j, and U Ｎ is the nominal voltage value of the distribution network, and R ｉ is the equivalent resistance between node i and node i-1, and min(i,j) is the minimum function. When calculating the voltage sensitivity between the nodes, the lower limit of the accumulation is set to i=1, and the upper limit is the minimum of i, j. The method according to claim 4.

6. The electrical distance between nodes in the power distribution network is calculated using the Euclidean distance method, and the calculation formula is as follows: Of these, d ｉｊ is the electrical distance between node i and node j, and S ｉｊ is the element in the i-th row and j-th column of the sensitivity matrix, and max ｊ S ｉｊ is the maximum value among the elements in the j-th column of the sensitivity matrix, and N is the number of nodes in the power distribution network. The method according to claim 5.

7. The cluster partitioning of the power distribution network includes describing the electrical coupling degree of each node of the power distribution network according to the modularity definition method based on the electrical distance weight, and performing cluster partitioning of the power distribution network using the overall modularity of the power distribution network as an index. The method according to claim 6.

8. The above-mentioned calculation formula for cluster partitioning of the power distribution network is as follows: where ρ is the modularity of the system, m is the sum of the edge weights of the network, and k ｉ and k ｊ are the sum of edge weights of the edges connected to node i and node j, respectively; δ(i,j) is a defined discrimination parameter, where δ(i,j)=1 if node i and node j are located within one voltage partition, and δ(i,j)=0 otherwise. The method according to claim 7.

9. The constraints of the optimization block model include at least one of a 01 constraint, a node voltage constraint, and an energy storage facility output power constraint; The method of claim 1.

10. The 01 constraint is for determining whether the node belongs to a partition that is served by an energy storage facility, and is expressed as follows: Among them, μ ｉ、ｊ represents whether node i belongs to the partition in which energy storage facility j is responsible for voltage regulation, and μ ｉ、ｊ The value of is 0 or 1, and μ ｉ、ｊ If μ is equal to 1, it indicates that node i belongs to the partition served by energy storage facility j, and μ ｉ、ｊ If is equal to 0, it indicates that node i does not belong to the partition served by,energy storage facility j.

10. The method of claim 9.

11. The expression for satisfying the node voltage constraint that the voltage of each node should be greater than the minimum allowable voltage value due to the adjustment of the energy storage facility is as follows: Among them, U ｉ is the voltage of node i before the energy storage device participates in voltage regulation, and S ｉ、ｊ represents the voltage sensitivity coefficient for node i of the power regulation of the energy storage facility located at node j, and U ｍｉｎ is the minimum voltage allowed, The expression for satisfying the node voltage constraint that the voltage of each node should be less than the maximum allowable voltage value due to the adjustment of the energy storage equipment is as follows: In the formula, U ｍａｘ is the maximum voltage allowed, 10. The method of claim 9.

12. The output power constraint of the energy storage device is such that the output power of the energy storage device participating in voltage regulation is less than the maximum allowable power value, and the expression is as follows: Among them, P ｊ、ｍａｘ is the maximum power value of the output power of the energy storage facility located at node j; 10. The method of claim 9.

13. A calculation unit configured to obtain node voltages of each node in the power distribution network, construct a voltage sensitivity matrix, and obtain a cluster partition of the power distribution network; A model construction unit is configured to construct an optimization partition model in which the energy storage device controls the voltage of the cluster partition according to the charging and discharging power constraint of the energy storage device, with the goal of minimizing the total charging and discharging power of the energy storage device, and adopt a mixed integer linear programming to solve the problem, so that each energy storage device adjusts the voltage to obtain a node range that it is responsible for; When constructing the above-mentioned optimization division model, the objective function is to minimize the power usage of all energy storage devices, and the objective function is as follows: Wherein, N ess is the number of all energy storage devices, and P j is the output power of the energy storage device located at node j; Power grid energy storage voltage regulation partition optimizer.

14. A program is stored which, when executed by a processor, implements the steps of the grid energy storage voltage regulation partition optimization method according to any one of claims 1 to 12. Computer storage media.

15. A method for optimizing an energy storage voltage regulation partition of a power grid comprising: a memory; a processor; and a program stored in the memory and operable on the processor, the method implementing the steps of the method for optimizing an energy storage voltage regulation partition of a power grid according to any one of claims 1 to 12, when the program is executed by the processor. Computer equipment.

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