Dynamic partition determination method and device considering power grid load side resource adjustment capability

Abstract

The invention relates to the technical field of power systems, and provides a dynamic partition determination method and device considering the power grid load side resource adjustment capacity, and the method comprises the steps: obtaining the basic data of a power system, constructing a Jacobian matrix through combining a Newton-Raphson method under polar coordinates and the basic data, and carrying out the calculation of the Jacobian matrix; determining an augmented sensitivity matrix about PQ nodes based on the Jacobian matrix, and constructing a spatial electrical distance matrix according to the augmented sensitivity matrix; determining an initial partitioning result of the power system by combining an agglomerated hierarchical clustering method with the spatial electrical distance matrix; then, judging the reserve of each power partition, and ensuring that the reserve meets a preset threshold value; and if the reserve of all the power partitions does not meet the standard, correcting and re-evaluating the partition result until the reserve of all the power partitions reaches the standard, thereby obtaining a target partition result. According to the embodiment of the invention, through a dynamic partitioning strategy, the stability and flexibility of the power system are effectively improved, the resource configuration is optimized, and the efficient utilization of the regulation resources at the load side of the power grid is ensured.

Description

Technical Field

[0001] The present disclosure relates to the technical field of power systems, and in particular, to a method and device for determining dynamic partitions considering the regulation resource capacity of the grid load side. Background Art

[0002] With the popularization of electric vehicles and the increasing demand for clean energy, the power grid is facing new challenges. Traditional power grid partitioning usually performs fixed partitioning based on the topological structure or power flow situation of the power grid, without fully considering the spatio-temporal variation characteristics of adjustable resources on the load side, especially the charging demand of electric vehicles. The charging behavior of electric vehicles is affected by factors such as user travel habits, electricity prices, and the distribution of charging facilities, resulting in large fluctuations in its load in terms of time and space.

[0003] In related technologies, existing power grid technologies mainly focus on power flow analysis and power grid reliability assessment. Traditional power grid partitioning methods mainly rely on the structure or power flow distribution of the power grid. However, these methods ignore the resources on the load side, especially the spatio-temporal fluctuation characteristics of load-side resources such as electric vehicles. The current dispatching models do not fully consider these factors, resulting in the failure to maximize the utilization of load-side resources. Summary of the Invention

[0004] At least one embodiment of the present disclosure provides a method and device for determining dynamic partitions considering the regulation resource capacity of the grid load side. Through the dynamic partitioning strategy, the stability and flexibility of the power system are effectively improved, the resource allocation is optimized, and the efficient utilization of the grid load-side regulation resources is ensured.

[0005] An embodiment of the present disclosure provides a method for determining dynamic partitions considering the regulation resource capacity of the grid load side, including:

[0006] Obtain the basic data of the power system, and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data; wherein, the basic data includes PQ node information and PV node information;

[0007] Determine an augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix;

[0008] Determine an initial partitioning result for the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve of each power partition in the initial partitioning result meets a preset threshold;

[0009] If it meets the requirement, determine the initial partitioning result as the target partitioning result;

[0010] If not, correct the initial partition result, and re-determine whether the reserve of each power partition in the corrected partition result meets the preset threshold until the reserve of each power partition in the corrected partition result meets the preset threshold, and obtain the target partition result.

[0011] The embodiment of the present disclosure provides a dynamic partition determination device considering the regulation resource capacity on the grid load side, including:

[0012] A matrix construction module, configured to obtain the basic data of the power system, and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data; wherein, the basic data includes PQ node information and PV node information;

[0013] A matrix determination module, configured to determine an augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix;

[0014] A system partition module, configured to determine an initial partition result for the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve of each power partition in the initial partition result meets the preset threshold;

[0015] A partition determination module, configured to, if satisfied, determine the initial partition result as the target partition result;

[0016] A partition correction module, configured to, if not satisfied, correct the initial partition result, and re-determine whether the reserve of each power partition in the corrected partition result meets the preset threshold until the reserve of each power partition in the corrected partition result meets the preset threshold, and obtain the target partition result.

[0017] The embodiment of the present disclosure provides a computer device, including: a processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor. When the computer device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the dynamic partition determination method considering the regulation resource capacity on the grid load side as described in any of the above possible implementation manners is executed.

[0018] The embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the dynamic partition determination method considering the regulation resource capacity on the grid load side as described in any of the above possible implementation manners is implemented.

[0019] The dynamic partition determination method and device for considering the regulation resource capacity on the load side of the power grid provided in the embodiments of the present disclosure obtain the basic data of the power system, construct the Jacobian matrix by combining the Newton-Raphson method in polar coordinates and power information, and then determine the augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, and construct the spatial electrical distance matrix accordingly; the agglomerative hierarchical clustering method is combined with the spatial electrical distance matrix to determine the initial partition result of the power system; subsequently, the reserve of each power partition is judged to ensure that it meets the preset threshold; if not, the partition result is corrected and re-evaluated until the reserves of all power partitions meet the standard, so as to obtain the target partition result.

[0020] In this way, through the dynamic partition strategy, this embodiment effectively improves the stability and flexibility of the power system, optimizes the resource allocation, and ensures the efficient utilization of the regulation resources on the load side of the power grid.

[0021] To make the above objects, features, and advantages of the present disclosure more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings required to be cited in the embodiments will be briefly introduced below. The accompanying drawings are incorporated into the specification and constitute a part of the specification. These drawings show embodiments that conform to the present disclosure and, together with the specification, are used to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only show some embodiments of the present disclosure and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0023] Figure 1 Shows a flowchart of a dynamic partition determination method for considering the regulation resource capacity on the load side of the power grid provided in the embodiments of the present disclosure;

[0024] Figure 2 Shows a flowchart of a method for constructing a Jacobian matrix provided in the embodiments of the present disclosure;

[0025] Figure 3 Shows a flowchart of a method for determining an augmented sensitivity matrix provided in the embodiments of the present disclosure;

[0026] Figure 4 Shows a flowchart of a method for determining an initial partition result provided in the embodiments of the present disclosure;

[0027] Figure 5 Shows a flowchart of a method for judging the reserve of a power partition provided in the embodiments of the present disclosure;

[0028] Figure 6 shows a flowchart of a method for dynamically adjusting a target partition result provided by an embodiment of the present disclosure;

[0029] Figure 7 shows a schematic structural diagram of a dynamic partition determination device considering the regulation resource capacity of the power grid load side provided by an embodiment of the present disclosure;

[0030] Figure 8 shows a schematic structural diagram of a computer device provided by an embodiment of the present disclosure. Detailed implementation manners

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are only some, rather than all, of the embodiments of the present disclosure. The components of the embodiments of the present disclosure described and illustrated herein generally may be arranged and designed in a variety of different configurations. Therefore, the detailed description of the embodiments of the present disclosure provided herein is not intended to limit the scope of the present disclosure claimed, but merely represents selected embodiments of the present disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of the present disclosure without creative efforts fall within the scope of the present disclosure.

[0032] It should be noted that like reference numerals and letters denote like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

[0033] The term "and / or" in this article merely describes an association relationship and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, both A and B exist simultaneously, and B exists alone. In addition, the term "at least one" in this article means any one of a plurality or any combination of at least two of a plurality. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set composed of A, B, and C.

[0034] To facilitate the understanding of this embodiment, the execution subject of the dynamic partition determination method considering the regulation resource capacity on the grid load side provided by the embodiments of the present disclosure will be introduced in detail first. The execution subject of the dynamic partition determination method considering the regulation resource capacity on the grid load side provided by the embodiments of the present disclosure is a computer device. This computer device can be a server. Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, big data, and artificial intelligence platforms.

[0035] The following will explain in detail the dynamic partition determination method considering the regulation resource capacity on the grid load side provided by the embodiments of the present application with reference to the accompanying drawings. Refer to Figure 1 As shown, it is a flowchart of a dynamic partition determination method considering the regulation resource capacity on the grid load side provided by the embodiments of the present disclosure. The method includes the following S101 to S105:

[0036] S101, obtain the basic data of the power system, and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data.

[0037] Among them, the basic data includes PQ node information, PV node information, and slack node information. Here, PQ nodes represent nodes with known active and reactive power loads, usually load centers or consumption ends. In the power system, these PQ nodes consume electric energy, and both their active power and reactive power are known. The PQ node information specifically includes the voltage amplitude corresponding to each PQ node (although in actual power flow calculations, the voltage amplitude is usually to be solved, but an estimated value or default value may be given in the initial data), active power information, and reactive power information. PV nodes are nodes that represent known active power and voltage amplitude, usually generator nodes. Generator nodes provide electric energy in the power system, and both their active power and voltage amplitude are known, while the reactive power may be adjusted according to the needs of the system. The PV node information includes the voltage amplitude and active power information corresponding to each PV node. Slack nodes represent special nodes in the power system used to maintain power balance and voltage stability. In power flow calculations, slack nodes are usually used as reference nodes, and both their voltage amplitude and phase angle are known, and are usually set as the voltage and phase reference points of the system.

[0038] In some other embodiments, the basic data may also include line parameter information, transformer parameter information, etc., which can describe the electrical characteristics and connection methods of various components in the power system, and will not be specifically limited here.

[0039] Specifically, after obtaining these basic data, the Jacobian matrix can be constructed based on the Newton-Raphson method in polar coordinates. Here, the Newton-Raphson method is a numerical method for solving non-linear equations and is widely used in power flow calculations in power systems. In polar coordinates, the power flow equations of a power system can be expressed as a set of non-linear equations. By linearizing these equations and constructing the Jacobian matrix, iterative methods can be used to solve the power flow problem. The Jacobian matrix reflects the relationship between small changes in node voltages and powers in a power system. By constructing the Jacobian matrix, a basis can be provided for subsequent power system analysis and optimization. For example, during the power flow calculation process, the node voltages and powers can be continuously iteratively updated until certain convergence conditions are met. The Jacobian matrix is used to calculate the changes in voltage and power in each iteration, thus guiding the direction and step size of the iterative process.

[0040] Exemplarily, referring to Figure 2 as shown, a method for constructing a Jacobian matrix proposed by the present disclosure may include the following steps S201 to S203:

[0041] S201, for PQ nodes, establish a PQ active power error equation based on the voltage amplitude and active power information corresponding to the PQ node, and establish a PQ reactive power error equation based on the voltage amplitude and reactive power information corresponding to the PQ node.

[0042] Here, in order to describe the relationship between the power state and voltage of a PQ node, a PQ active power error equation can be established based on the voltage amplitude and active power information corresponding to the PQ node. This equation reflects the difference between the actual active power and the desired active power of the PQ node and can be expressed as the following formula:

[0043]

[0044] where, ΔP i pq represents the active power error of PQ node i; P ic pq represents the given active power of PQ node i; U i represents the voltage amplitude of node i; G ij represents the real part in the node admittance matrix, that is, conductance; δ ij represents the voltage phase angle difference between node i and node j; B ij represents the imaginary part in the node admittance matrix, that is, susceptance; n represents the total number of system nodes.

[0045] Similarly, based on the voltage magnitude and reactive power information corresponding to the PQ nodes, a PQ reactive power error equation can be established to describe the relationship between the reactive power state of the PQ nodes and the voltage, which can be expressed as:

[0046]

[0047] where ΔQ i pq represents the reactive power error of PQ node i; Q ic pq represents the specified reactive power of PQ node i.

[0048] S202. For the PV nodes, based on the voltage magnitude and active power information corresponding to the PV nodes, establish a PV active power error equation.

[0049] Similarly, in order to accurately describe the power state of the PV nodes, a PV active power error equation can be established based on the voltage magnitude and active power information corresponding to the PV nodes to reflect the difference between the actual active power and the desired active power of the PV nodes, as shown in the following equation:

[0050]

[0051] where ΔP i pv represents the active power error of PV node i; P ic pv represents the specified active power of PV node i.

[0052] Here, since the reactive power of the PV nodes is unknown, the corresponding reactive power error equation is not constructed when building the error equation, and only the above PV active power error equation needs to be retained.

[0053] S203. Determine the system error equation based on the PQ active power error equation, the PQ reactive power error equation, and the PV active power error equation; expand the system error equation according to the Taylor series to obtain a correction equation; and determine the Jacobian matrix based on the correction equation.

[0054] Specifically, after obtaining the PQ active power error equation, the PQ reactive power error equation, and the PV active power error equation established above, they are integrated together to form a system error equation, which comprehensively describes the relationship between the power state of all nodes in the power system and the voltage.

[0055] To solve this equation, it can be expanded according to the Taylor series to obtain a correction equation. The correction equation is a linearized equation that approximately describes the properties of the system error equation near the current operating point. Here, the correction equation can be expressed as:

[0056]

[0057] Among them, the meanings and calculation methods of each sub-element are as follows:

[0058] When i≠j:

[0059]

[0060] When i = j:

[0061]

[0062]

[0063] The aforementioned correction equation is abbreviated into a block matrix form according to the derivatives of active power with respect to voltage phase angle and voltage amplitude as follows:

[0064]

[0065] Among them, H (n-1)×(n-1) is the partial derivative matrix of active power with respect to power angle (dimension: n - 1×n - 1); N (n-1)×m is the partial derivative matrix of active power with respect to voltage amplitude (dimension: n - 1×m, m is the number of PQ nodes); J m×(n-1) is the partial derivative matrix of reactive power with respect to power angle (dimension: m×n - 1); L m×m is the partial derivative matrix of reactive power with respect to voltage amplitude (dimension: m×m, m is the number of PQ nodes).

[0066] By solving the correction equation, the small changes in voltage and power can be obtained, thereby updating the state of the system. In this process, the Jacobian matrix is the coefficient matrix in the correction equation, reflecting the small change relationship between node voltages and powers in the power system.

[0067] S102. Determine an augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix.

[0068] It can be understood that in a power system, the sensitivity matrix is an important analysis tool used to describe the mutual influence between various nodes in the system. Traditionally, the sensitivity matrix is mainly constructed based on the reactive power / voltage submatrix of the Jacobian matrix obtained from power flow calculations. Such a matrix can only reflect the reactive power / voltage sensitivity between each PQ node (i.e., the load node, whose active power and reactive power are both given), mainly reflecting the control ability of the reactive power in the power system on the voltage.

[0069] However, in a modern power system where load-side power sources such as electric vehicles are widely involved, the change in active power has become an object that requires more attention. At the same time, the control effects of power source nodes (such as PV nodes, whose active power and voltage amplitude are given) on the voltage and frequency of the power system cannot be ignored. To solve the above problems, the present disclosure proposes to construct an augmented sensitivity matrix that includes the coupling relationships between all nodes and can simultaneously reflect the influence of active power on the voltage of the power system. This augmented sensitivity matrix not only considers the mutual influence between PQ nodes but also the influence of PV nodes and balance points on PQ nodes.

[0070] Specifically, referring to Figure 3 as shown, when determining the augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, PQ node information, and PV node information, the following steps S301 to S303 may be included:

[0071] S301, construct a PQ node voltage sensitivity matrix based on the Jacobian matrix and the PQ node information.

[0072] Here, the PQ node voltage sensitivity matrix represents the response relationship of the voltage amplitude of each node when the active power or reactive power injected by the PQ node changes; this matrix is constructed by using the original Jacobian matrix and PQ node information. The Jacobian matrix describes the linear relationship between the voltage and power of each node in the system. By extracting the part corresponding to the PQ node in the Jacobian matrix, the response relationship of the voltage amplitude of each node when the active power or reactive power injected by the PQ node changes can be calculated, that is, the PQ node voltage sensitivity matrix.

[0073] Among them, the PQ node voltage sensitivity matrix can be expressed as:

[0074]

[0075] It can be understood that due to the significant direct impact of reactive power on voltage amplitude, in the actual power grid, the sensitivity coefficients of the N matrix are generally much smaller than those of the L matrix. This means that in the voltage regulation process, reactive voltage control often plays a dominant role. When the system needs to adjust the voltage, it usually achieves this by regulating the reactive power because the change in reactive power can directly and effectively affect the voltage amplitude.

[0076] According to the above content, nodes can be divided into different types according to their characteristics and functions. Among them, PQ nodes (load nodes) are the most common type. The voltage amplitude and phase angle of PQ nodes need to be determined through power flow calculations because they are not given but are affected by other nodes and power injections in the system. When the power injection of a PQ node changes, this change directly affects the calculation of the sensitivity matrix because the sensitivity matrix reflects the response of the voltage of each node in the system to the change in power injection. Different from PQ nodes, the voltage amplitude of PV nodes (power source nodes) is fixed, and it is usually necessary to regulate the reactive power to maintain this fixed voltage amplitude. Therefore, in the sensitivity matrix, the sensitivity information of PV nodes is not included because their voltage amplitudes do not change with the change in power injection. In addition, the voltage amplitude and phase angle of the slack node in the power system are both fixed. It serves as a reference node in the system, providing a reference for voltage and phase angle for other nodes. Since the voltage and phase angle of the slack node are both given, it does not participate in the sensitivity analysis because in the sensitivity analysis, what needs to be concerned about is the response of the node voltage to the change in power injection, and the voltage and phase angle of the slack node do not change with the change in power injection.

[0077] In summary, the voltage sensitivity matrix only includes the information of PQ load nodes and does not contain the information of PV power source nodes and slack nodes. This is because the voltage amplitude and phase angle of PQ nodes need to be determined through power flow calculations, while the voltage amplitude or phase angle of PV nodes and slack nodes are given and do not change with the change in power injection.

[0078] S302, sequentially set the other nodes except the PQ nodes as PQ nodes, and after each round of node type change, reconstruct the Jacobian matrix based on the changed node type, and calculate the response relationship between the voltage amplitudes of each node when the active power or reactive power injection of the PQ node changes under the new node type configuration based on the newly constructed Jacobian matrix, the PV node information, and the slack point information, to obtain the initial sensitivity matrix.

[0079] Here, to comprehensively consider the influence of all nodes in the power system on the voltage of PQ nodes, the present disclosure sequentially sets other nodes (such as PV nodes) except PQ nodes as PQ nodes and conducts multiple rounds of simulations. After each round of node type change, it is necessary to reconstruct the Jacobian matrix according to the changed node type, because the change of node type will change the power flow distribution of the system, thereby affecting the elements of the Jacobian matrix. Then, based on the newly constructed Jacobian matrix, PV node information, and equilibrium point information, the response relationship between the voltage amplitudes of each node when the active power or reactive power injected into the PQ node changes under the new node type configuration can be calculated to obtain the initial sensitivity matrix. This process needs to be repeated until all non-PQ nodes have completed one simulation.

[0080] Specifically, when merging it with the nodes sequentially set as PQ nodes, n (total number of nodes in the system) - m (number of PQ nodes) initial sensitivity matrices can be obtained as follows:

[0081]

[0082] Among them, x can take an integer between 1 and n - m.

[0083] S303. After all other nodes except the PQ nodes have completed the node change task, based on the initial sensitivity matrix obtained after each round of node type change and the PQ node voltage sensitivity matrix, the augmented sensitivity matrix is determined.

[0084] Specifically, after completing all rounds of node type changes and calculations of the initial sensitivity matrix, these initial sensitivity matrices and the original PQ node voltage sensitivity matrix can be synthesized. This synthesis process needs to consider the influence of node type changes on the system voltage in each round of simulation, as well as the direct influence of PQ node power changes on the system voltage. Through mathematical operations and weight allocation, an augmented sensitivity matrix containing the coupling relationships between all nodes in the system and the influence of active power on voltage can be obtained. This matrix not only reflects the mutual influence between PQ nodes but also considers the influence of PV nodes and equilibrium points on PQ nodes.

[0085] Here, the augmented sensitivity matrix can be expressed as:

[0086]

[0087] It can be understood that the augmented sensitivity matrix comprehensively reflects the coupling relationships between nodes in the power system, especially considering the influence of PQ nodes and other node types after simulation conversion on the system voltage, including the sensitivity of voltage to changes in active power and reactive power. Therefore, after obtaining the augmented sensitivity matrix, the spatial electrical distance matrix can be further determined based on this matrix.

[0088] Here, the spatial electrical distance matrix is a matrix used to quantify the degree of electrical coupling between nodes in a power system. It is different from the geographical distance and is defined based on the mutual influence of voltage and power between nodes. The elements of the spatial electrical distance matrix represent the spatial electrical distance between any two nodes in the system, that is, the tightness of the voltage response or power transmission between them. The closer the spatial electrical distance, the greater the mutual influence of voltage or power changes between the two nodes; conversely, the farther the electrical distance, the smaller the mutual influence.

[0089] Specifically, when determining the spatial electrical distance matrix according to the augmented sensitivity matrix, it can be solved based on the spatial electrical distance calculation formula. During the solution process, for the lower right corner area of the augmented sensitivity matrix, since it contains a large number of zero elements, taking the logarithm will result in infinity, leading to data inundation. Therefore, when calculating it, the first m data are used, that is:

[0090]

[0091] where, D ij represents the spatial electrical distance between the i-th node and the j-th node; m represents the dimension of the augmented sensitivity matrix; S ij represents the element in the i-th row and j-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage amplitude of the i-th node when the injection power of the j-th node changes; S ji represents the element in the j-th row and i-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage amplitude of the j-th node when the injection power of the i-th node changes; S imax represents the maximum value among all elements in the i-th row of the augmented sensitivity matrix; S jmax represents the maximum value among all elements in the j-th row of the augmented sensitivity matrix.

[0092] Here, the present disclosure maps each node to a linear space, which not only reflects the electrical coupling relationship between two nodes but also comprehensively considers the influence of other nodes on the two nodes.

[0093] S103. Determine an initial partitioning result of the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve amounts of each power partition in the initial partitioning result all meet a preset threshold.

[0094] Here, the agglomerative hierarchical clustering method is a bottom-up clustering method that forms larger clusters by continuously merging the most similar clusters. After obtaining the spatial electrical distance matrix, the agglomerative hierarchical clustering method and the spatial electrical distance matrix can be used to determine the initial partitioning result of the power system. The initial partitioning result divides the power system into several power partitions, and each partition contains a group of nodes with relatively close electrical distances.

[0095] Exemplarily, as shown in Figure 4 when determining the initial partitioning result of the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix, the following steps S401 to S404 may be included:

[0096] S401, determine each node in the power system as an independent cluster, and determine the similarity between each node based on the spatial electrical distance matrix to obtain an initial similarity matrix.

[0097] It can be understood that the spatial electrical distance matrix reflects the electrical coupling degree and mutual influence between nodes in the power system. Based on this matrix, the similarity between each node (i.e., between each independent cluster), that is, the proximity of the electrical distance, can be determined, thereby obtaining an initial similarity matrix.

[0098] S402, select the two clusters with the highest similarity for merging to form a new cluster, and update the initial similarity matrix based on the new cluster to reflect the similarity relationship between the new cluster and other clusters.

[0099] Here, according to the result of the initial similarity matrix, select the two clusters with the highest similarity for merging to form a new cluster. After merging, the new cluster will be recalculated with other clusters to update the similarity matrix to ensure that it can reflect the similarity relationship between the new cluster and other clusters. In this way, by continuously merging similar clusters, the number of clusters is gradually reduced, so that the clustering result is more accurate and reflects the actual electrical connection between nodes inside the power system.

[0100] S403, repeatedly execute step S402 until the total number of clusters reaches the preset number of clusters and / or all nodes are merged into one cluster, and then execute step S404.

[0101] Specifically, repeatedly execute step S402. Each iteration will merge the two clusters with the highest similarity and update the similarity matrix until the preset stop condition is met. Here, the stop condition can be that the total number of clusters reaches the preset value, or all nodes are finally merged into one cluster. At this stage, the partitioning of the system gradually converges, and the final number of clusters can be set according to the actual needs of the power system to ensure the rationality and effectiveness of the partitioning.

[0102] S404. Construct a dendrogram based on the process of each iterative merger, and determine the initial partitioning result of the power system based on the dendrogram.

[0103] It can be understood that based on the process of each iterative merger, a dendrogram, also known as a clustering tree, is constructed. The formation of the dendrogram can intuitively display the hierarchical structure and merger path of the clustering process. By analyzing the dendrogram, the initial partitioning result (including multiple power partitions) of the power system can be clearly determined. These partitions divide the nodes in the power system into several power partitions, and each power partition contains a group of nodes with relatively close electrical distances and greater mutual influence, forming a relatively stable area.

[0104] In some possible embodiments, in order to further optimize the partitioning effect of the power system and ensure the rationality and connectivity of the partitioning, after obtaining the initial partitioning result of the power system, the following (a) - (b) may further be included:

[0105] (a) Determine whether there are isolated nodes in the initial partitioning result;

[0106] (b) If there are, incorporate the isolated nodes into the power partition with the smallest spatial electrical distance from the isolated nodes, and determine the partitioning result after incorporating the isolated nodes as the initial partitioning result; wherein, the initial partitioning result includes multiple power partitions.

[0107] Specifically, isolated nodes refer to nodes that, due to various reasons (such as weak electrical connections, equipment failures, etc.), are not assigned to any power partition during the initial partitioning process. Their existence may affect the overall operating efficiency and stability of the power system.

[0108] Here, if the judgment result shows that there are isolated nodes, then step (b) is executed, that is, the isolated nodes are incorporated into the power partition with the smallest spatial electrical distance from the isolated nodes. At this time, the power partition that is most closely electrically connected and closest in spatial position to the isolated nodes is determined and incorporated into it. In this way, not only can the connectivity of the power system be maintained, but also the operating risks that may be brought about by the existence of isolated nodes can be minimized. Finally, the partitioning result after incorporating the isolated nodes is determined as the new initial partitioning result, and the partitioning result after processing the isolated nodes will be more perfect and reasonable.

[0109] Exemplarily, in a power system, the active power and reactive power reserves in each sub-region have important impacts on the stability of the power system. The node voltages in the power system have a strong coupling relationship with reactive power. Abundant dynamic reactive power reserves help the power grid cope with voltage fluctuations caused by various disturbances and maintain the stability of the system voltage. Active power is closely related to the power system frequency, and the system requires a certain amount of active power reserve to cope with the fluctuations of the power system load and various special situations. Therefore, after obtaining the initial sub-region results, it is necessary to judge the reserve amounts of each power sub-region and check whether the reserve amounts of each power sub-region in the initial sub-region results meet the preset thresholds. Among them, the reserve amount refers to the additional capacity reserved in the power system to cope with possible load fluctuations, equipment failures or other emergencies, and can include active power reserve and reactive power reserve. The active power reserve refers to the additional active power reserved (i.e., the actual power that can be provided) to cope with situations such as load fluctuations or generator outages; the reactive power reserve refers to the reactive power reserved to ensure the stability of the system voltage (i.e., the power required to maintain the voltage level in the power system).

[0110] Specifically, referring to Figure 5 as shown, when judging whether the reserve amounts of each power sub-region meet the preset thresholds, the following steps S501 to S503 can be included:

[0111] S501, obtain the sub-region information of each power sub-region.

[0112] Among them, the sub-region information includes the total maximum reactive power generation, the total reactive power required by the load, the total maximum active power generation, and the total active power required by the load. These data are the basis for evaluating the reserve amount of the power sub-region.

[0113] S502, for each power sub-region, determine the reactive power reserve based on the reactive power reserve calculation formula, the total maximum reactive power generation corresponding to the power sub-region, and the total reactive power required by the load; and determine the active power reserve based on the active power reserve calculation formula, the total maximum active power generation corresponding to the power sub-region, and the total active power required by the load.

[0114] After obtaining the sub-region information, next, it is necessary to calculate the reactive power reserve and active power reserve of each power sub-region according to the reactive power reserve calculation formula and the active power reserve calculation formula respectively.

[0115] Here, the reactive power reserve calculation formula can be expressed as:

[0116]

[0117] where β i represents the reactive power reserve of the i-th power sub-region; Q LiDenoted as the total reactive power required by the load in the \(i\)-th power sub-region; \(Q\) Gi Denoted as the maximum total reactive power generation corresponding to the \(i\)-th power sub-region;

[0118] Here, the calculation formula for the active reserve can be expressed as:

[0119]

[0120] where, \(\alpha\) i Denoted as the active reserve of the \(i\)-th power sub-region; \(P\) Li Denoted as the total active power required by the load in the \(i\)-th power sub-region; \(P\) Gi Denoted as the maximum total active power generation corresponding to the \(i\)-th power sub-region.

[0121] S503, respectively determine whether the reactive power reserve and the active power reserve of each power sub-region in the initial sub-region result both meet the preset threshold.

[0122] It can be understood that after calculating the reactive power reserve and the active power reserve of each power sub-region, it is necessary to judge these reserves. By comparing with the preset reserve threshold, it is confirmed whether the reactive power and active power reserves of each power sub-region meet the requirements. If the reactive power reserve or the active power reserve of a certain power sub-region is lower than the preset threshold, it may mean that the coping ability of this sub-region in the case of load fluctuations or faults is insufficient, thus affecting the stability and security of the power system. Here, the preset threshold can be set to values such as 20% and 25%, and no specific limitation is made here.

[0123] S104, if satisfied, then determine the initial sub-region result as the target sub-region result.

[0124] Here, if the reserves of each power sub-region in the initial sub-region result all meet the preset threshold, it means that this sub-region scheme is effective in aspects such as power distribution and reserve capacity, and is applicable to subsequent actual application scenarios such as power dispatching and load balancing. Then, the initial sub-region result can be directly determined as the target sub-region result. The target sub-region result is a sub-region scheme that has been preliminarily verified and meets certain reserve requirements, and has high reliability, and can be used as a basis for specific power system optimization, load management, emergency dispatching and other tasks to ensure stable power supply and efficient system operation.

[0125] S105, if not satisfied, then correct the initial sub-region result, and re-determine whether the reserves of each power sub-region in the corrected sub-region result meet the preset threshold until the reserves of each power sub-region in the corrected sub-region result all meet the preset threshold, and obtain the target sub-region result.

[0126] Here, if the reserve of some power partitions in the initial partition result fails to meet the preset threshold, then the initial partition result needs to be corrected. This situation usually means that in the initial partition scheme, there may be problems of uneven power distribution and insufficient reserves in some areas, which may cause the partition to be unable to effectively cope with power fluctuations or sudden load changes. To ensure the reliability and stability of the power system, the non-compliant power partitions must be adjusted. These adjustments can be carried out in various ways, such as readjusting the boundaries of the partitions, reasonably increasing or decreasing the power nodes within the partitions, or balancing the reserves of each power partition by optimizing resource allocation. After the correction, the corrected partition result will be judged again to check whether the reserves of each power partition meet the preset threshold.

[0127] This process will be continuously iterated until the reserves of all power partitions meet the preset standards. Each correction and judgment will further optimize the partition scheme to ensure that the final target partition result can fully meet the requirements of the power system and has good reserve capacity and stability. Through this optimization and adjustment process, the problem of insufficient reserves that may occur in power partitions can be effectively solved, ensuring the reliability of the power system under different operating conditions, and finally obtaining a scientific, reasonable and practical target partition scheme.

[0128] In some possible embodiments, to optimize the operating efficiency of the power system and ensure the stability and reliability of power distribution, referring to Figure 6 as shown, after obtaining the target partition result, the following steps S601 to S603 may further be included:

[0129] S601, according to a preset time period, judge whether the reserves of each power partition in the target partition result meet the preset value and whether the voltage of each node in each power partition is stable.

[0130] It can be understood that during the operation of the power system with a large number of electric vehicles participating, the power is constantly changing in real time. Therefore, the present disclosure proposes to perform real-time dynamic inspection and correction on the partition of the power system with a preset time period as the time granularity. Specifically, according to the preset time period (for example, 5 minutes, 10 minutes), each power partition in the target partition result is inspected to judge whether the reserve of each power partition meets the preset value, and at the same time, it is also necessary to confirm whether the voltage of each node in each power partition is in a stable state. In this way, it can be ensured whether the power partition has sufficient reserves to cope with possible load fluctuations, and whether the voltage of each node in the power grid is maintained within a safe and stable range.

[0131] S602. When the reserve of each power sub - region in the target sub - region result meets the preset value and the voltage of each node in each power sub - region is stable, the target sub - region result is adopted in the next preset time period.

[0132] If the reserve of each power sub - region in the target sub - region result has met the preset value and the voltage in each power sub - region remains stable, the system will continue to use the current target sub - region result in the next preset time period. At this time, since both the reserve of the power sub - region and the voltage condition meet the requirements, there is no need to adjust the sub - region result, and the power grid can continue to operate in a relatively stable state, avoiding unnecessary adjustments and operations, thereby improving the operating efficiency of the system.

[0133] S603. When the reserve of each power sub - region in the target sub - region result does not meet the preset value and / or the voltage of each node in each power sub - region is unstable, the target sub - region result is corrected, and it is re - judged whether the corrected target sub - region result meets the conditions until the corrected target sub - region result meets the conditions, and the target sub - region result for the next preset time period is obtained.

[0134] Here, if it is found in step S601 that the reserve of some power sub - regions in the target sub - region result does not meet the preset value, or the node voltage in some power sub - regions is unstable, then step S603 is executed. At this time, the current target sub - region result will be corrected. The correction may involve adjusting the boundary of the power sub - region, re - allocating reserve resources or taking other measures to ensure the stability of the system. The corrected target sub - region result will be verified again to determine whether it meets the conditions of reserve and voltage stability. If the corrected result still does not meet the conditions, the adjustment will continue until a target sub - region result that meets all requirements is obtained, and finally the target sub - region result for the next preset time period is determined. In this way, the sub - region adaptive dynamic adjustment mechanism proposed in the present disclosure ensures that the power system can operate efficiently and stably in different time periods, and effectively evaluates the rationality of the dynamic sub - region situation of the power grid regulation.

[0135] The dynamic sub - region determination method and device provided in the embodiments of the present disclosure, considering the regulation resource capacity of the power grid load side, effectively improve the stability and flexibility of the power system, optimize the resource allocation, and ensure the efficient utilization of the regulation resources on the load side of the power grid.

[0136] Those skilled in the art can understand that in the above - mentioned method of the specific implementation manner, the writing order of each step does not mean a strict execution order that constitutes any limitation to the implementation process. The specific execution order of each step should be determined according to its function and possible internal logic.

[0137] Based on the same inventive concept, embodiments of the present disclosure also provide a dynamic partition determination device considering the capacity of grid load-side regulation resources corresponding to the dynamic partition determination method considering the capacity of grid load-side regulation resources. Since the principle of problem-solving of the device in the embodiments of the present disclosure is similar to that of the above-mentioned dynamic partition determination method considering the capacity of grid load-side regulation resources in the embodiments of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be elaborated.

[0138] Referring Figure 7 As shown, it is a schematic diagram of a dynamic partition determination device 700 considering the capacity of grid load-side regulation resources provided by an embodiment of the present disclosure. The device includes:

[0139] A matrix construction module 701, configured to obtain basic data of the power system and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data; wherein, the basic data includes PQ node information and PV node information;

[0140] A matrix determination module 702, configured to determine an augmented sensitivity matrix regarding PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix;

[0141] A system partition module 703, configured to determine an initial partition result regarding the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve amounts of each power partition in the initial partition result all meet a preset threshold;

[0142] A partition determination module 704, configured to, if satisfied, determine the initial partition result as the target partition result;

[0143] A partition correction module 705, configured to, if not satisfied, correct the initial partition result and re-determine whether the reserve amounts of each power partition in the corrected partition result meet the preset threshold until the reserve amounts of each power partition in the corrected partition result all meet the preset threshold to obtain the target partition result.

[0144] In some possible embodiments, the PQ node information includes the voltage amplitude, active power information, and reactive power information corresponding to each PQ node, and the PV node information includes the voltage amplitude and active power information corresponding to each PV node; specifically, the matrix construction module 701 is configured to:

[0145] For PQ nodes, establish a PQ active power error equation based on the voltage amplitude and active power information corresponding to the PQ node, and establish a PQ reactive power error equation based on the voltage amplitude and reactive power information corresponding to the PQ node;

[0146] For the PV node, establish a PV active power error equation based on the voltage amplitude and active power information corresponding to the PV node;

[0147] Determine the system error equation based on the PQ active power error equation, the PQ reactive power error equation, and the PV active power error equation; and expand the system error equation according to the Taylor series to obtain a correction equation; and, determine the Jacobian matrix based on the correction equation;

[0148] The basic data further includes swing node information; the matrix determination module 702 is specifically configured to:

[0149] Construct a PQ node voltage sensitivity matrix based on the Jacobian matrix and the PQ node information; wherein, the PQ node voltage sensitivity matrix represents the response relationship of the voltage amplitudes of each node when the active power or reactive power injection of the PQ node changes;

[0150] Successively set the other nodes except the PQ nodes as PQ nodes, and after each round of node type change, reconstruct the Jacobian matrix based on the changed node type, and, based on the newly constructed Jacobian matrix, the PV node information, and the swing point information, calculate the response relationship of the voltage amplitudes of each node when the active power or reactive power injection of the PQ node changes under the new node type configuration to obtain an initial sensitivity matrix;

[0151] After all the other nodes except the PQ nodes have completed the node change task, determine the augmented sensitivity matrix based on the initial sensitivity matrix obtained after each round of node type change and the PQ node voltage sensitivity matrix.

[0152] In some possible embodiments, the matrix determination module 702 is specifically configured to:

[0153] Determine the spatial electrical distance matrix based on the augmented sensitivity matrix and the spatial electrical distance calculation formula;

[0154] The spatial electrical distance calculation formula is expressed as:

[0155]

[0156] where D ij represents the spatial electrical distance between the i-th node and the j-th node; m represents the dimension of the augmented sensitivity matrix; S ij represents the element in the i-th row and j-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage amplitude of the i-th node when the injection power of the j-th node changes; S jiIt is the element in the \(j\)-th row and \(i\)-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage magnitude of the \(j\)-th node when the injection power of the \(i\)-th node changes; \(S\) imax It is the maximum value among all elements in the \(i\)-th row of the augmented sensitivity matrix; \(S\) jmax It is the maximum value among all elements in the \(j\)-th row of the augmented sensitivity matrix.

[0157] In some possible embodiments, the system partitioning module 703 is specifically configured to perform:

[0158] Step 1: Determine each node in the power system as an independent cluster, and determine the similarity between each node based on the spatial electrical distance matrix to obtain an initial similarity matrix;

[0159] Step 2: Select two clusters with the highest similarity for merging to form a new cluster, and update the initial similarity matrix based on the new cluster to reflect the similarity relationship between the new cluster and other clusters;

[0160] Step 3: Repeat Step 2 until the total number of clusters reaches the preset number of clusters and / or all nodes are merged into one cluster, and then perform Step 4;

[0161] Step 4: Construct a dendrogram based on the merging process of each iteration, and determine the initial partitioning result of the power system based on the dendrogram.

[0162] In some possible embodiments, the system partitioning module 703 is further configured to:

[0163] Determine whether there are isolated nodes in the initial partitioning result;

[0164] If there are isolated nodes, incorporate the isolated nodes into the power partition with the smallest spatial electrical distance from the isolated nodes, and determine the partitioning result after incorporating the isolated nodes as the initial partitioning result; wherein, the initial partitioning result includes multiple power partitions.

[0165] In some possible embodiments, the reserve includes active reserve and reactive reserve; the system partitioning module 703 is specifically configured to:

[0166] Obtain the partitioning information of each power partition; wherein, the partitioning information includes the total maximum reactive power generation, the total reactive power required by the load, the total maximum active power generation, and the total active power required by the load;

[0167] For each power sub-region, determine the reactive power reserve based on the reactive power reserve calculation formula, the total maximum reactive power generation corresponding to the power sub-region, and the total reactive power required by the load; and determine the active power reserve based on the active power reserve calculation formula, the total maximum active power generation corresponding to the power sub-region, and the total active power required by the load;

[0168] Respectively determine whether the reactive power reserve and the active power reserve of each power sub-region in the initial sub-region result both meet the preset threshold;

[0169] The reactive power reserve calculation formula includes:

[0170]

[0171] where β i represents the reactive power reserve of the i-th power sub-region; Q Li represents the total reactive power required by the load in the i-th power sub-region; Q Gi represents the total maximum reactive power generation corresponding to the i-th power sub-region;

[0172] The active power reserve calculation formula includes:

[0173]

[0174] where α i represents the active power reserve of the i-th power sub-region; P Li represents the total active power required by the load in the i-th power sub-region; P Gi represents the total maximum active power generation corresponding to the i-th power sub-region.

[0175] In some possible embodiments, the sub-region correction module 705 is further configured to:

[0176] According to a preset time period, determine whether the reserves of each power sub-region in the target sub-region result all meet the preset value and whether the voltages of each node in each power sub-region are stable;

[0177] When the reserves of each power sub-region in the target sub-region result all meet the preset value and the voltages of each node in each power sub-region are stable, continue to use the target sub-region result in the next preset time period;

[0178] When the reserves of each power sub-region in the target sub-region result do not meet the preset value and / or the voltages of each node in each power sub-region are unstable, correct the target sub-region result, and re-determine whether the corrected target sub-region result meets the conditions until the corrected target sub-region result meets the conditions to obtain the target sub-region result for the next preset time period.

[0179] Based on the same inventive concept, embodiments of the present disclosure also provide a computer device. Referring to Figure 8 As shown in Figure 8 , it is a schematic structural diagram of a computer device 800 provided by an embodiment of the present disclosure, including a processor 801, a memory 802, and a bus 803. Among them, the memory 802 is used to store execution instructions, including an internal memory 8021 and an external memory 8022; the internal memory 8021 here is also called the main memory, which is used to temporarily store the operation data in the processor 801 and the data exchanged with the external memory 8022 such as a hard disk. The processor 801 exchanges data with the external memory 8022 through the internal memory 8021.

[0180] In an embodiment of the present application, the memory 802 is specifically used to store the application program code for implementing the solution of the present application, and is controlled by the processor 801 to execute. That is, when the computer device 800 runs, the processor 801 communicates with the memory 802 through the bus 803, so that the processor 801 executes the application program code stored in the memory 802, and then executes the method described in any of the foregoing embodiments.

[0181] Among them, the memory 802 may be, but is not limited to, a random access memory, a read-only memory, a programmable read-only memory, an erasable read-only memory, an electrically erasable read-only memory, etc. The processor 801 may be an integrated circuit chip with signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit, a network processor, etc.; it may also be a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0182] It can be understood that the structure schematically shown in the embodiments of the present application does not constitute a specific limitation on the computer device 800. In other embodiments of the present application, the computer device 800 may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange different components. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0183] Embodiments of the present disclosure also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the steps of the method for dynamically partitioning and determining considering the grid load-side regulation resource capacity described in the foregoing method embodiments. Among them, the storage medium may be a volatile or non-volatile computer-readable storage medium.

[0184] Embodiments of the present disclosure also provide a computer program product. The computer program product carries program codes, and the instructions included in the program codes can be used to execute the steps of the dynamic partition determination method considering the regulation resource capacity on the grid load side described in the above method embodiments. For details, reference can be made to the above method embodiments and will not be elaborated herein. Among them, the above computer program product can be specifically implemented in the form of hardware, software, or a combination thereof. In an alternative embodiment, the computer program product is specifically embodied as a computer storage medium. In another alternative embodiment, the computer program product is specifically embodied as a software product, such as a software development kit, etc.

[0185] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems and devices described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein. In several embodiments provided by the present disclosure, it should be understood that the disclosed systems and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0186] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, the functional units in various embodiments of the present disclosure can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such an understanding, the technical solution of the present disclosure, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, or optical discs that can store program codes.

[0187] Finally, it should be noted that the above-described embodiments are only specific embodiments of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present disclosure can still modify the technical solutions recorded in the foregoing embodiments or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A method for determining dynamic partition considering the regulation resource capacity on the grid load side, characterized in that Including: Obtain the basic data of the power system, and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data; wherein, the basic data includes PQ node information and PV node information; Determine an augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix; Determine an initial partitioning result for the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve amounts of each power partition in the initial partitioning result all meet a preset threshold; If it is satisfied, determine the initial partitioning result as the target partitioning result; If it is not satisfied, correct the initial partitioning result, and re-determine whether the reserve amounts of each power partition in the corrected partitioning result meet the preset threshold until the reserve amounts of each power partition in the corrected partitioning result all meet the preset threshold to obtain the target partitioning result.

2. The method according to claim 1, wherein The PQ node information includes the voltage amplitude, active power information, and reactive power information corresponding to each PQ node, and the PV node information includes the voltage amplitude and active power information corresponding to each PV node; The constructing the Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data includes: For PQ nodes, establish a PQ active power error equation based on the voltage amplitude and active power information corresponding to the PQ node, and establish a PQ reactive power error equation based on the voltage amplitude and reactive power information corresponding to the PQ node; For PV nodes, establish a PV active power error equation based on the voltage amplitude and active power information corresponding to the PV node; Determine a system error equation based on the PQ active power error equation, the PQ reactive power error equation, and the PV active power error equation; expand the system error equation according to the Taylor series to obtain a correction equation; and determine the Jacobian matrix based on the correction equation; The basic data further includes balance node information; the determining the augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information includes: Construct a PQ node voltage sensitivity matrix based on the Jacobian matrix and the PQ node information; wherein, the PQ node voltage sensitivity matrix represents the response relationship of the voltage amplitudes of each node when the active power or reactive power injection of the PQ node changes; Successively set other nodes except the PQ nodes as PQ nodes, and after each change of the node type, reconstruct the Jacobian matrix based on the changed node type, and calculate the response relationship of the voltage amplitudes of each node when the active power or reactive power injection of the PQ node changes under the new node type configuration based on the newly constructed Jacobian matrix, the PV node information, and the balance point information to obtain an initial sensitivity matrix; After the node change tasks are completed for all nodes except the PQ nodes, the augmented sensitivity matrix is determined based on the initial sensitivity matrix and the PQ node voltage sensitivity matrix obtained after each round of node type change.

3. The method according to claim 1, characterized in that The determining of the spatial electrical distance matrix based on the augmented sensitivity matrix includes: Determining the spatial electrical distance matrix based on the augmented sensitivity matrix and the spatial electrical distance calculation formula; The spatial electrical distance calculation formula is expressed as: Among them, D ij represents the spatial electrical distance between the i-th node and the j-th node; m represents the dimension of the augmented sensitivity matrix; S ij represents the element in the i-th row and j-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage amplitude of the i-th node when the injection power of the j-th node changes; S ji represents the element in the j-th row and i-th column of the augmented sensitivity matrix, reflecting the response degree of the voltage amplitude of the j-th node when the injection power of the i-th node changes; S imax represents the maximum value among all elements in the i-th row of the augmented sensitivity matrix; S jmax represents the maximum value among all elements in the j-th row of the augmented sensitivity matrix.

4. The method according to claim 1, characterized in that The determining of the initial partitioning result of the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix includes: Step 1: Determine each node in the power system as an independent cluster, and determine the similarity between each node based on the spatial electrical distance matrix to obtain the initial similarity matrix; Step 2: Select the two clusters with the highest similarity for merging to form a new cluster, and update the initial similarity matrix based on the new cluster to reflect the similarity relationship between the new cluster and other clusters; Step 3: Repeat Step 2 until the total number of clusters reaches the preset number of clusters and / or all nodes are merged into one cluster, and then execute Step 4; Step 4: Construct a dendrogram based on the process of each iterative merge, and determine the initial partitioning result of the power system based on the dendrogram.

5. The method according to claim 4, characterized in that, After determining the initial partitioning result of the power system based on the dendrogram, it includes: Judging whether there are isolated nodes in the initial partitioning result; If there are, incorporate the isolated nodes into the power partition with the smallest spatial electrical distance from the isolated nodes, and determine the partitioning result after incorporating the isolated nodes as the initial partitioning result; where the initial partitioning result includes multiple power partitions.

6. The method according to claim 5, characterized in that, The reserve includes active reserve and reactive reserve; the respective judgments on whether the reserves of each power partition in the initial partitioning result meet the preset thresholds include: Obtain the partitioning information of each power partition; where the partitioning information includes the total maximum reactive power generation, the total reactive power required by the load, the total maximum active power generation, and the total active power required by the load; For each power partition, determine the reactive reserve based on the reactive reserve calculation formula, the total maximum reactive power generation corresponding to the power partition, and the total reactive power required by the load; and determine the active reserve based on the active reserve calculation formula, the total maximum active power generation corresponding to the power partition, and the total active power required by the load; Respectively judge whether the reactive reserve and the active reserve of each power partition in the initial partitioning result meet the preset thresholds; The reactive reserve calculation formula includes: Among them, β i represents the reactive power reserve of the i-th power sub-region; Q Li represents the total reactive power required by the load in the i-th power sub-region; Q Gi represents the maximum total reactive power generation corresponding to the i-th power sub-region; The active reserve calculation formula includes: Among them, α i represents the active reserve of the i-th power sub-region; P Li represents the total active power required by the load in the i-th power sub-region; P Gi represents the maximum total active power generation corresponding to the i-th power sub-region.

7. The method according to any one of claims 1 to 6, characterized in that The method further includes: After obtaining the target partitioning result, according to the preset time period, judge whether the reserves of each power partition in the target partitioning result meet the preset values and whether the voltages of each node in each power partition are stable; When the reserves of each power partition in the target partitioning result meet the preset values and the voltages of each node in each power partition are stable, use the target partitioning result in the next preset time period. When the reserve of each power sub-region in the target sub-region result does not meet the preset value and / or the voltage of each node in each power sub-region is unstable, the target sub-region result is corrected, and it is re-determined whether the corrected target sub-region result meets the conditions until the corrected target sub-region result meets the conditions, and the target sub-region result for the next preset time period is obtained.

8. A dynamic partition determination device considering the regulation resource capacity on the grid load side, characterized in that, Including: A matrix construction module, configured to obtain basic data of a power system and construct a Jacobian matrix based on the Newton-Raphson method in polar coordinates and the basic data; wherein, the basic data includes PQ node information and PV node information; A matrix determination module, configured to determine an augmented sensitivity matrix for PQ nodes based on the Jacobian matrix, the PQ node information, and the PV node information; and determine a spatial electrical distance matrix based on the augmented sensitivity matrix; A system partitioning module, configured to determine an initial partitioning result for the power system based on the agglomerative hierarchical clustering method and the spatial electrical distance matrix; and respectively determine whether the reserve of each power sub-region in the initial partitioning result meets a preset threshold; A partitioning determination module, configured to, if it is satisfied, determine the initial partitioning result as the target partitioning result; A partitioning correction module, configured to, if it is not satisfied, correct the initial partitioning result, and re-determine whether the reserve of each power sub-region in the corrected partitioning result meets the preset threshold until the reserve of each power sub-region in the corrected partitioning result meets the preset threshold, and obtain the target partitioning result.

9. A storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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