Multi-reactive-power-resource space-time coordination control method and system under high-proportion optical storage access

Abstract

The invention discloses a multi-reactive power resource space-time coordination control method and system under high-proportion optical storage access, and the method comprises the steps: building a full-dimensional sensitivity matrix on the basis of a reactive power-voltage sensitivity matrix according to the coupling of a reactive power source control node and other load nodes; a g-dimensional reactive power source control space is constructed, and the Euclidean distance is adopted to represent the distance between the nodes; other load nodes refer to nodes except the reactive power source control node; performing reactive voltage control partitioning by using an improved hierarchical clustering algorithm to ensure reactive reserve margin charging of each partition, and selecting a dominant node based on a comprehensive sensitivity improvement index; on the basis of the second step, according to the effectiveness and economy of voltage regulation, cooperative control over different types of reactive power resources is achieved on the basis of the multi-reactive-power-source cooperative control principle of voltage-power sensitivity and voltage-cost sensitivity.

Description

Technical Field

[0001] The present application relates to the field of reactive voltage control, and in particular to a method and system for spatiotemporal coordinated control of multiple reactive resources under high-proportion photovoltaic storage access. Background Art

[0002] The proportion of renewable energy access represented by photovoltaic and wind power has increased significantly. As a typical high-proportion photovoltaic and storage access to the grid, its power electronics level is high, the grid structure is weak, the voltage stability problem is prominent, and the grid voltage reactive power control faces severe challenges.

[0003] In order to ensure the safe and economical operation of the power grid, the reactive voltage control of the power system should follow the principle of hierarchical zoning, among which the three-level voltage control mode of Electricité de France is more common. In the three-level voltage control mode, the secondary voltage control is the key link, which mainly includes three aspects: reactive voltage control zoning, selection of dominant nodes, and design of control laws.

[0004] In terms of reactive power and voltage control zoning, existing studies have mainly used clustering methods to achieve the division of power grid areas. Reference [1] (Li Yingliang, Wang Kang, Wang Deming, et al. Full-dimensional sensitivity matrix fast VCA method considering weak coupling relationship [J]. Electrical Measurement and Instrumentation, 2022, 59(01): 69-76.) constructs a reactive source control space, uses the control ability of reactive source nodes on load nodes to obtain the coordinates of load nodes, and then obtains the electrical distance between load nodes. Then, the condensed hierarchical clustering method is used for zoning research. However, the above literature does not consider the two boundary conditions of reactive reserve margin index and avoiding isolated nodes, which easily leads to the problem of insufficient reactive reserve in isolated nodes in the region.

[0005] In terms of the selection of dominant nodes, the literature [2] (Li Xianglong, Fu Xiao, Zhu Jie, et al. Research on the partitioning and dominant node selection method of distribution network containing distributed generation [J]. Power System Protection and Control, 2019, 47 (13): 24-29.) selects dominant nodes from the aspects of reactive / active controllability and voltage observability, which not only enables distributed generation to participate in the voltage regulation of the distribution network system more efficiently, but also makes the voltage level of the dominant node reflect the overall voltage level of the current area to a certain extent. However, the above literature does not consider the structural characteristics and location information of the nodes. Considering the large number of grid nodes, the results of sensitivity calculation may be too close, making it difficult to select the dominant node.

[0006] In terms of control law design, reference [3] (Zhang Bo, Wen Xiaojun, Wu Xuan. Data-driven voltage coordination control strategy for active distribution network based on voltage-power sensitivity [J / OL]. Journal of Electric Power Systems and Automation, 1-9 [2024-07-29].) realizes rapid regulation of distribution network node voltage based on the principle of voltage-power sensitivity descending control. However, the above references do not design control laws from the perspective of reactive power regulation cost. When two or more nodes have similar reactive power sensitivity, they should be regulated in descending order of voltage cost sensitivity.

[0007] Literature research shows that there are many deficiencies in existing research on secondary voltage control, and there are few studies on the coordinated control of multiple types of reactive resources. Therefore, how to formulate spatiotemporal coordinated control principles for multiple reactive sources such as SVG and phase-shifting devices in order to address the problems of insufficient coordination of multiple types of reactive resources and difficulty in static voltage regulation in the case of high-proportion photovoltaic storage access to weak power grids is an urgent problem to be solved. Summary of the invention

[0008] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a method and system for spatiotemporal coordinated control of multiple reactive resources under high-ratio photovoltaic storage access.

[0009] On the one hand, an embodiment of the present application provides a method for spatiotemporal coordinated control of multiple reactive resources under high-proportion photovoltaic storage access, characterized in that it includes the following steps:

[0010] Step 1: According to the coupling between the reactive source control node and other load nodes, a full-dimensional sensitivity matrix is ​​established on the basis of the reactive-voltage sensitivity matrix; then a g-dimensional reactive source control space is constructed, and the Euclidean distance is used to characterize the distance between nodes; other load nodes refer to nodes other than the reactive source control node;

[0011] Step 2: Use the improved hierarchical clustering algorithm to partition the reactive power and voltage control to ensure that the reactive power reserve margin of each partition is full, and select the leading node based on the comprehensive sensitivity improvement index;

[0012] Step 3. On the basis of step 2, according to the effectiveness and economy of voltage regulation, a multi-reactive source coordinated control principle based on voltage-power sensitivity and voltage-cost sensitivity is proposed to achieve coordinated control of different types of reactive resources.

[0013] In some embodiments, in step one, the coupling between the PV node and other load nodes is considered, and on the basis of the reactive-voltage sensitivity matrix obtained by inverting the power flow Jacobian matrix, each reactive source node is relaxed to a PQ node in a recursive manner, and the augmented sensitivity matrix is ​​recalculated, and then the full-dimensional sensitivity matrix is ​​constructed from each sub-matrix; then, the equivalent electrical distance is obtained according to the reactive voltage sensitivity, a g-dimensional reactive source control space is constructed, and the Euclidean distance is used to characterize the distance between the nodes.

[0014] In some embodiments, the step 1 specifically includes:

[0015] 1) For a power system network with n nodes, the number of PQ nodes is m-1, the number of reactive source control nodes is nm, and the number of balancing nodes is 1. The linearization of the system power flow equation yields:

[0016]

[0017] Where: △P is the change in active power injected into the node; △Q is the change in reactive power injected into the node; △θ is the change in node voltage phase angle; △V is the change in node voltage amplitude;

[0018] 2) Since the voltage amplitude is strongly coupled with the reactive power, the relationship between voltage and reactive power is mainly considered when analyzing reactive power and voltage control. Therefore, the injected active power is kept constant, and the voltage-reactive power sensitivity matrix can be expressed as:

[0019] △V / △Q=-(L (m-1)×(m-1) ) -1 =S (m-1)×(m-1) (2)

[0020] Where: L ij is the partial derivative of reactive power to voltage, S is the voltage-reactive sensitivity matrix;

[0021] 3) Select a reactive source control node and relax it to a PQ node, keep the other nodes unchanged, and recalculate the power flow to obtain the augmented sensitivity matrix, which can be expressed as:

[0022]

[0023] Where: S′ is the augmented sensitivity matrix, where the first m-1 elements of the last column of S′ are the sensitivity of the reactive source control node to the other m-1 load nodes, denoted as subvector e (m-1)×1 ; The first m-1 elements of the last row of S′ are the sensitivities of the other m-1 load nodes to the reactive source control node, denoted as subvector f 1×(m-1) ;s (m,m)is the sensitivity of the reactive source control node to itself, recorded as sub-vector g 1×1 ;

[0024] 4) Each reactive source node is relaxed to a PQ node in a recursive manner and the power flow is recalculated. Then all sub-vectors are merged to obtain a full-dimensional sensitivity matrix, which can be expressed as:

[0025]

[0026] Where: S″ is the full-dimensional sensitivity matrix; E (m-1)×(n-m) is composed of nm sub-vectors e (m-1)×1 The matrix composed of (n-m)×(m-1) is composed of nm sub-vectors f 1×(m-1) The matrix composed of (n-m)×(n-m) is composed of nm sub-vectors g 1×1 as a matrix consisting of diagonal elements;

[0027] 5) Construct a g-dimensional reactive source control space. For any load node i, its coordinate vector can be expressed as: (d i1 ,d i2 ,...,d ig ), the equivalent electrical distance between any load node i and reactive power source control node j can be expressed as: d ij =-lg|S″ ij S″ ji |, for any controlled load node m, n, the Euclidean distance can be used to characterize the electrical distance between the two, which can be expressed as:

[0028]

[0029] Where: g is the reactive power source control node; D mn is the electrical distance between the controlled load nodes m and n.

[0030] In some embodiments, the step 2 specifically includes:

[0031] The improved hierarchical clustering algorithm takes into account the reactive reserve margin index and the two boundary conditions of avoiding isolated nodes. In addition, it compares multiple inter-cluster distance merging curves and selects the optimal inter-cluster distance for partition merging, which is expressed as follows:

[0032] 1) Reactive power margin calculation formula:

[0033]

[0034] Where: is the reactive power margin of zone j; Q Lj is the sum of reactive loads in zone j; QQj is the sum of the maximum outputs of all reactive resources in zone j;

[0035] 2) Calculation formula for reactive unbalance:

[0036]

[0037] Where: η is the reactive unbalance degree of the partition; is the average value of reactive reserve in s partitions;

[0038] 3) Inter-cluster distance calculation formula:

[0039] Minimum distance:

[0040]

[0041] Where: C i and C j are two clusters; p and q are the elements of the two clusters respectively; dist min (C i ,C j ) represents the shortest distance between two clusters; dist(p,q) represents the distance between two cluster elements;

[0042] Maximum distance:

[0043]

[0044] Where: dist max (C i ,C j ) represents the maximum distance between two clusters;

[0045] Center of gravity distance:

[0046]

[0047] Where: dist bc (C i ,C j ) represents the centroid distance between two clusters; and Cluster C i and C j The center of gravity;

[0048] Average distance:

[0049]

[0050] Where: dist avg (C i ,C j ) represents the average distance between two clusters; and are the total number of elements in the two families respectively;

[0051] Ward distance (sum of squared deviations):

[0052]

[0053] Where: dist ward (C i ,C j ) represents the Ward distance between two clusters.

[0054] In some embodiments, the step 2 specifically includes:

[0055] The specific solution steps of the improved hierarchical clustering algorithm are as follows:

[0056] 1) According to the equivalent electrical distance formula derived in step 1, calculate the Euclidean distance D between two nodes in the power system network with n nodes. mn ;

[0057] 2) Construct n partitions, each containing only one node;

[0058] 3) Divide each reactive source control node according to the electrical distance and the principle of minimum connectivity;

[0059] 4) Merge the two closest partitions into a new partition based on the inter-cluster distance;

[0060] 5) Determine whether the newly merged partition contains a reactive power source control node, if so, execute step 7), if not, execute step 6);

[0061] 6) Split the merged partition, select the partition with the next closest merge distance, and return to step 5);

[0062] 7) Determine whether the reactive power margin of the newly merged partition is sufficient, the judgment condition is whether it is greater than or equal to 15%, if so, proceed to the next step, if not, return to step 6);

[0063] 8) Determine whether the number of partitions is equal to 1. If so, proceed to the next step. If not, recalculate the inter-cluster distances between the partitions and return to step 4);

[0064] 9) Draw the distance merging curve and output the partitioning results.

[0065] In some embodiments, the step 2 specifically includes:

[0066] The structural characteristics and location information of the nodes are introduced to improve the sensitivity index. The improved comprehensive sensitivity index considers three dimensions, namely, observability, controllability and the number of node edges, to select the dominant node. It is specifically expressed as follows:

[0067] 1) Observability sensitivity index of node k to other nodes:

[0068]

[0069] Where: OBS is the observability sensitivity index; m is the node in the partition; Ω all is the set of all nodes in the partition.

[0070] 2) The controllability sensitivity index of node k to other nodes:

[0071]

[0072] Where: CON is the controllability sensitivity index; k is the reactive source control node in the partition; Ω PV It is the collection of all reactive source control nodes in the partition.

[0073] 3) Improvement index of comprehensive sensitivity of node k to other nodes:

[0074]

[0075] Where: SYN is the comprehensive sensitivity improvement index; N k is the number of edges connecting nodes; λ1 is the weight coefficient of the observability sensitivity index; λ2 is the weight coefficient of the controllability sensitivity index.

[0076] In some embodiments, the step three specifically includes:

[0077] For reactive resources located at different nodes, the descending control principle based on voltage-power sensitivity is adopted, and the rapid regulation of grid node voltage is achieved through a two-stage voltage control mode combining reactive compensation and active power reduction.

[0078] In some embodiments, the step three specifically includes:

[0079] For nodes with voltage exceeding the limit, the output power and adjustment sequence of the reactive power source are controlled to indirectly achieve the regulation of the grid node voltage. The general steps are:

[0080] 1) First, sort the target nodes with voltage over-limit and select the node with the most over-limit as the target node; it can be expressed as:

[0081]

[0082] Where: △V iThe voltage of node i exceeds the limit;

[0083] 2) Based on the voltage-power sensitivity, the reactive power source with the largest value is regulated first, and the reactive power sources are arranged in descending order of voltage-reactive power sensitivity; this can be expressed as:

[0084]

[0085] Where: is the reactive voltage sensitivity of node i to node j;

[0086] 3) The theoretical output power is solved based on the voltage-power sensitivity and the voltage over-limit, and compared with the current reactive power margin to calculate the actual output power; it can be expressed as:

[0087]

[0088] Where: △Q j.rea is the reactive power actually output by node j; △Q j.the is the reactive power shortage; △Q j.mar is the maximum output reactive power of node j;

[0089] 4) Perform reactive power compensation and active power reduction of each over-limit node in turn, and iteratively adjust the node voltage until all node voltages return to normal. During the active power reduction process, set the power factor threshold, and select the target node and the controlled photovoltaic based on the voltage over-limit level and the voltage-active power sensitivity in descending order. The voltage-active power sensitivity in descending order can be expressed as:

[0090]

[0091] Where: is the active voltage sensitivity of node i to node l;

[0092] For the reactive resources at the same node, the voltage-cost sensitivity of each reactive source is calculated and sorted according to the numerical value. The reactive equipment corresponding to the larger one will participate in voltage regulation first when the voltage exceeds the limit. A descending control principle based on voltage-cost sensitivity is proposed. Based on the economic efficiency of the equipment participating in voltage regulation, the coordinated control between different equipment at the same location is assisted. The voltage cost sensitivity of different reactive resources can be expressed as:

[0093] PV inverter participates in voltage regulation at node j:

[0094]

[0095] Where: is the voltage cost sensitivity coefficient of the photovoltaic inverter; △V ij is the effect of power change at node j on the voltage at node i; C PV,jis the regulation cost of the PV inverter at node j; c PV is the unit reactive power regulation cost of the PV inverter;

[0096] Energy storage participates in voltage regulation at node j:

[0097]

[0098] Where: is the energy storage voltage cost sensitivity coefficient; is the voltage active sensitivity; C ESS,j is the regulation cost of energy storage at node j; c ESS Reactive power regulation cost for energy storage units;

[0099] SVG participates in voltage regulation of node j:

[0100]

[0101] Where: is the SVG voltage cost sensitivity coefficient; C SVG,j is the adjustment cost of SVG at node j; c SVG is the unit reactive power regulation cost of SVG;

[0102] Phase regulator participates in voltage regulation at node j:

[0103]

[0104] Where: C is the voltage cost sensitivity coefficient of the phase regulator; txj,j is the adjustment cost of the phase regulator at node j; c txj It is the unit reactive power regulation cost of the phase regulator.

[0105] In some embodiments, the step three specifically includes:

[0106] The principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity can be described as follows: when the voltage exceeds the limit in a sub-region, in the reactive power control stage, reactive sources at different nodes participate in voltage regulation in descending order of voltage-reactive power. If the voltage-reactive power sensitivity of two or more nodes is similar, the voltage regulation order can be further determined by the voltage-cost sensitivity descending principle; different types of reactive resources at the same node can be regulated in descending order according to the voltage-cost sensitivity; if the reactive resources in the region are exhausted and the voltage still exceeds the limit, the active power control stage can be entered, and the voltage regulation order can be determined according to the voltage-active power sensitivity and voltage-cost sensitivity descending principles.

[0107] On the other hand, this embodiment provides a spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic storage access, including:

[0108] A calculation module is used to establish a full-dimensional sensitivity matrix based on the reactive-voltage sensitivity matrix according to the coupling of the reactive source control node and other load nodes; construct a g-dimensional reactive source control space, and use Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than the reactive source control node;

[0109] The partitioning and selection module is used to partition the reactive power and voltage control using the improved hierarchical clustering algorithm to ensure that the reactive power reserve margin of each partition is full, and select the leading node based on the comprehensive sensitivity improvement index;

[0110] The control module is used to realize the coordinated control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, the effectiveness and economy of voltage regulation, and the principle of multi-reactive source coordinated control based on voltage-power sensitivity and voltage-cost sensitivity.

[0111] On the other hand, this embodiment provides a spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic storage access, characterized in that it includes:

[0112] Memory, used to store programs;

[0113] A processor is used to load the program to execute the method for spatiotemporal coordinated control of multiple reactive resources considering high-proportion photovoltaic storage access.

[0114] On the other hand, the embodiment of the present application provides a spatiotemporal coordination control system of multiple reactive resources under high-proportion photovoltaic storage access, including:

[0115] A space construction module is used to establish a full-dimensional sensitivity matrix based on the reactive-voltage sensitivity matrix according to the coupling between the reactive source control node and other load nodes; construct a g-dimensional reactive source control space, and use Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than the reactive source control node;

[0116] The node selection module is used to partition the reactive power and voltage control using an improved hierarchical clustering algorithm to ensure that the reactive power reserve margin of each partition is full, and to select the leading node based on the comprehensive sensitivity improvement index;

[0117] The collaborative control module is used to realize the collaborative control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, the effectiveness and economy of voltage regulation, and the principle of multi-reactive source coordinated control based on voltage-power sensitivity and voltage-cost sensitivity.

[0118] On the other hand, an embodiment of the present application provides a computer-readable storage medium storing a program, which, when loaded, implements a method for spatiotemporal coordinated control of multiple reactive resources under high-ratio solar-storage access.

[0119] The beneficial effects of this application are:

[0120] In step 1 of the present invention, the electrical distance between each reactive resource and each node of the power grid is calculated by considering the reactive voltage sensitivity of each node and the control capability of the reactive resources of each node; compared with the traditional scheme, this step considers the supporting capabilities of various new reactive equipment (SVG, energy storage, phase shifter, etc.), and is more adaptable to the needs of power grid analysis and control under the background of high-proportion photovoltaic storage access;

[0121] In step 2 of the present invention, based on the improved hierarchical clustering algorithm and the comprehensive sensitivity improvement index, multi-type reactive resource hierarchical partitioning is realized; wherein, the improved hierarchical clustering algorithm takes into account the reactive reserve margin index and the two boundary conditions of avoiding the occurrence of isolated nodes, and optimizes the reactive source merging principle, which can effectively avoid the occurrence of isolated nodes and insufficient reactive reserves in the partition; in addition, the comprehensive sensitivity improvement index considers the three dimensions of observability, controllability and the number of node edges to realize the selection of the dominant node, which can effectively solve the problem that the result of the sensitivity calculation may be too close due to the large number of power grid nodes, resulting in difficulty in selecting the dominant node;

[0122] In step three of the present invention, combined with the differences in the regulation capabilities of multiple types of reactive resources under different configuration modes and their impact after participating in grid regulation, a multi-reactive source coordinated control principle based on voltage-power sensitivity and voltage-cost sensitivity is proposed to achieve coordinated control of different types of reactive resources; this step can effectively solve the problem of lack of coordination among multiple types of resources in weak power grids under high proportion of photovoltaic energy storage access. BRIEF DESCRIPTION OF THE DRAWINGS

[0123] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0124] Figure 1 It is to establish a schematic diagram for a full-dimensional sensitivity matrix considering the coupling of reactive source control nodes and other load nodes;

[0125] Figure 2 To improve the hierarchical clustering algorithm flow chart;

[0126] Figure 3 It is a flow chart of the coordinated control principle of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity;

[0127] Figure 4 To improve the IEEE 39 node system block diagram;

[0128] Figure 5 The relative distance merging curve for partitioning using different inter-cluster distances;

[0129] Figure 6 It is the partition result under the traditional hierarchical clustering algorithm;

[0130] Figure 7 To improve the partitioning results under the hierarchical clustering algorithm;

[0131] Figure 8 Schematic diagram of voltage and power sensitivity of each partition and its reactive resource node. DETAILED DESCRIPTION

[0132] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described through the implementation method with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0133] In the description of the present invention, "several" means more than one, "many" means more than two, "greater than", "less than", "exceed", etc. are understood to exclude the number itself, and "above", "below", "within", etc. are understood to include the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0134] In the description of the present invention, unless otherwise clearly defined, words such as "setting" should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meaning of the above words in the present invention in combination with the specific content of the technical solution.

[0135] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0136] Combine the following Figure 1-Figure 8Describe the entire plan.

[0137] A spatiotemporal coordinated control method for multiple reactive resources considering high-proportion photovoltaic storage access, such as Figures 1 to 3 As shown, the following steps are included:

[0138] Step 1: Consider the coupling between the reactive source control node and other load nodes. On the basis of the reactive-voltage sensitivity matrix obtained by inverting the flow Jacobian matrix, each reactive source node is relaxed to a PQ node by a "successive recursion" method, and the augmented sensitivity matrix is ​​recalculated. The full-dimensional sensitivity matrix is ​​then constructed from each sub-matrix. Then, the equivalent electrical distance is obtained based on the reactive voltage sensitivity, a g-dimensional reactive source control space is constructed, and the Euclidean distance is used to characterize the distance between nodes. The specific expression is as follows:

[0139] 1) For a power system network with n nodes, the number of PQ nodes is m-1, the number of reactive source control nodes is nm, and the number of balancing nodes is 1. The linearization of the system power flow equation yields:

[0140]

[0141] Where: △P is the change in active power injected into the node; △Q is the change in reactive power injected into the node; △θ is the change in node voltage phase angle; △V is the change in node voltage amplitude.

[0142] 2) Since the voltage amplitude is strongly coupled with the reactive power, the relationship between voltage and reactive power is mainly considered when analyzing reactive power and voltage control. Therefore, the injected active power is kept constant, and the voltage-reactive power sensitivity matrix can be expressed as:

[0143] △V / △Q=-(L (m-1)×(m-1) ) -1 =S (m-1)×(m-1) (25)

[0144] Where: L ij is the partial derivative of reactive power to voltage, S is the voltage-reactive power sensitivity matrix.

[0145] 3) Select a reactive source control node and relax it to a PQ node, keep the other nodes unchanged, and recalculate the power flow to obtain the augmented sensitivity matrix, which can be expressed as:

[0146]

[0147] Where: S′ is the augmented sensitivity matrix, where the first m-1 elements of the last column of S′ are the sensitivity of the reactive source control node to the other m-1 load nodes, denoted as subvector e (m-1)×1; The first m-1 elements of the last row of S′ are the sensitivities of the other m-1 load nodes to the reactive source control node, denoted as subvector f 1×(m-1) ;s (m,m) is the sensitivity of the reactive source control node to itself, recorded as sub-vector g 1×1 .

[0148] 4) Use the “successive recursion” method to relax each reactive source node into a PQ node and recalculate the power flow. Then merge all sub-vectors to obtain a full-dimensional sensitivity matrix, which can be expressed as:

[0149]

[0150] Where: S″ is the full-dimensional sensitivity matrix; E (m-1)×(n-m) is composed of nm sub-vectors e (m-1)×1 The matrix composed of (n-m)×(m-1) is composed of nm sub-vectors f 1×(m-1) The matrix composed of (n-m)×(n-m) is composed of nm sub-vectors g 1×1 as a matrix consisting of diagonal elements.

[0151] 5) Construct a g-dimensional reactive source control space. For any load node i, its coordinate vector can be expressed as: (d i1 ,d i2 ,...,d ig ), the equivalent electrical distance between any load node i and reactive power source control node j can be expressed as: d ij =-lg|S″ ij S″ ji |, for any controlled load node m, n, the Euclidean distance can be used to characterize the electrical distance between the two, which can be expressed as:

[0152]

[0153] Where: g is the reactive power source control node; D mn is the electrical distance between the controlled load nodes m and n.

[0154] Step 2: Use the improved hierarchical clustering algorithm to partition the reactive power and voltage control to ensure that the reactive power reserve margin of each partition is sufficient, and select the dominant node based on the comprehensive sensitivity improvement index.

[0155] The improved hierarchical clustering algorithm takes into account the reactive reserve margin index and the two boundary conditions of avoiding isolated nodes. In addition, it compares multiple inter-cluster distance merging curves and selects the optimal inter-cluster distance for partition merging, which is expressed as follows:

[0156] 1) Reactive power margin calculation formula:

[0157]

[0158] Where: is the reactive power margin of zone j; Q Lj is the sum of reactive loads in zone j; Q Qj It is the sum of the maximum output of all reactive resources in zone j.

[0159] 2) Calculation formula for reactive unbalance:

[0160]

[0161] Where: η is the reactive unbalance degree of the partition; is the average value of reactive reserve in s partitions.

[0162] 3) Inter-cluster distance calculation formula:

[0163] Minimum distance:

[0164]

[0165] Where: C i and C j are two clusters; p and q are the elements of the two clusters respectively; dist min (C i ,C j ) represents the shortest distance between two clusters; dist(p,q) represents the distance between two cluster elements.

[0166] Maximum distance:

[0167]

[0168] Where: dist max (C i ,C j ) represents the maximum distance between two clusters.

[0169] Center of gravity distance:

[0170]

[0171] Where: dist bc (C i ,C j ) represents the centroid distance between two clusters; and Cluster C i and C j center of gravity.

[0172] Average distance:

[0173]

[0174] Where: dist avg (C i ,C j ) represents the average distance between two clusters; and are the total number of elements in the two families respectively.

[0175] Ward distance (sum of squared deviations):

[0176]

[0177] Where: dist ward (C i ,C j ) represents the Ward distance between two clusters.

[0178] The specific solution steps of the improved hierarchical clustering algorithm are as follows:

[0179] 1) According to the equivalent electrical distance formula derived in step 1, calculate the Euclidean distance D between two nodes in the power system network with n nodes. mn ;

[0180] 2) Construct n partitions, each containing only one node;

[0181] 3) Divide each reactive source control node according to the electrical distance and the principle of minimum connectivity;

[0182] 4) Merge the two closest partitions into a new partition based on the inter-cluster distance;

[0183] 5) Determine whether the newly merged partition contains a reactive power source control node, if so, execute step 7), if not, execute step 6);

[0184] 6) Split the merged partition, select the partition with the next closest merge distance, and return to step 5);

[0185] 7) Determine whether the reactive power margin of the newly merged partition is sufficient (greater than or equal to 15%), if so, proceed to the next step, if not, return to step 6);

[0186] 8) Determine whether the number of partitions is equal to 1. If so, proceed to the next step. If not, recalculate the inter-cluster distances between the partitions and return to step 4);

[0187] 9) Draw the distance merging curve and output the partitioning results.

[0188] In order to solve the problem that the results of sensitivity calculation may be too close and it is difficult to select the dominant node, it is necessary to introduce the structural characteristics and location information of the node to improve the sensitivity index. The improved comprehensive sensitivity index considers the three dimensions of observability, controllability and the number of node edges to select the dominant node, which is specifically expressed as follows:

[0189] 1) Observability sensitivity index of node k to other nodes:

[0190]

[0191] Where: OBS is the observability sensitivity index; m is the node in the partition; Ω all is the set of all nodes in the partition.

[0192] 2) The controllability sensitivity index of node k to other nodes:

[0193]

[0194] Where: CON is the controllability sensitivity index; k is the reactive source control node in the partition; Ω PV It is the collection of all reactive source control nodes in the partition.

[0195] 3) Improvement index of comprehensive sensitivity of node k to other nodes:

[0196]

[0197] Where: SYN is the comprehensive sensitivity improvement index; N k is the number of nodes connected to each other; λ1 is the weight coefficient of the observability sensitivity index; λ2 is the weight coefficient of the controllability sensitivity index;

[0198] Step 3: Considering the effectiveness and economy of voltage regulation, a multi-reactive source coordinated control principle based on voltage-power sensitivity and voltage-cost sensitivity is proposed to achieve coordinated control of different types of reactive resources.

[0199] For reactive resources located at different nodes, the descending control principle based on voltage-power sensitivity is adopted, and the rapid control of grid node voltage is achieved through a two-stage voltage control mode combining reactive compensation and active reduction. For nodes with voltage exceeding the limit, the output power and adjustment sequence of reactive sources are reasonably controlled, which can indirectly realize the control of grid node voltage. The general steps are:

[0200] 1) First, sort the target nodes with voltage over-limit and select the node with the most over-limit as the target node; it can be expressed as:

[0201]

[0202] Where: △V i The voltage at node i exceeds the limit.

[0203] 2) Based on the voltage-power sensitivity, the reactive power source with the largest value is regulated first, and the reactive power sources are arranged in descending order of voltage-reactive power sensitivity; this can be expressed as:

[0204]

[0205] Where: is the reactive voltage sensitivity of node i to node j.

[0206] 3) The theoretical output power is solved based on the voltage-power sensitivity and the voltage over-limit, and compared with the current reactive power margin to calculate the actual output power; it can be expressed as:

[0207]

[0208] Where: △Q j.rea is the reactive power actually output by node j; △Q j.the is the reactive power shortage; △Q j.mar is the maximum output reactive power of node j

[0209] 4) Perform reactive power compensation and active power reduction of each over-limit node in turn, and iteratively adjust the node voltage until all node voltages return to normal. During the active power reduction process, the power factor threshold is set, and the target node and the controlled photovoltaic are selected based on the voltage over-limit level and the voltage-active power sensitivity in descending order; among them, the voltage-active power sensitivity in descending order can be expressed as:

[0210]

[0211] Where: is the active voltage sensitivity of node i to node l.

[0212] For the reactive resources at the same node, the voltage-cost sensitivity of each reactive source is calculated and sorted according to the numerical value. The reactive equipment corresponding to the larger one will participate in voltage regulation first when the voltage exceeds the limit. A descending control principle based on voltage-cost sensitivity is proposed. Based on the economic efficiency of the equipment participating in voltage regulation, the coordinated control between different equipment at the same location is assisted. The voltage cost sensitivity of different reactive resources can be expressed as:

[0213] PV inverter participates in voltage regulation at node j:

[0214]

[0215] Where: is the voltage cost sensitivity coefficient of the photovoltaic inverter; △V ijis the effect of power change at node j on the voltage at node i; C PV,j is the regulation cost of the PV inverter at node j; c PV is the unit reactive power regulation cost of the PV inverter.

[0216] Energy storage participates in voltage regulation at node j:

[0217]

[0218] Where: is the energy storage voltage cost sensitivity coefficient; is the voltage active sensitivity; C ESS,j is the regulation cost of energy storage at node j; c ESS is the reactive power regulation cost per energy storage unit.

[0219] SVG participates in voltage regulation of node j:

[0220]

[0221] Where: is the SVG voltage cost sensitivity coefficient; C SVG,j is the adjustment cost of SVG at node j; c SVG is the reactive power regulation cost per unit of SVG.

[0222] Phase regulator participates in voltage regulation at node j:

[0223]

[0224] Where: C is the voltage cost sensitivity coefficient of the phase regulator; txj,j is the adjustment cost of the phase regulator at node j; c txj It is the unit reactive power regulation cost of the phase regulator.

[0225] The principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity can be described as follows: when the voltage exceeds the limit in a sub-region, in the reactive power control stage, reactive sources at different nodes participate in voltage regulation in descending order of voltage-reactive power. If the voltage-reactive power sensitivity of two or more nodes is similar, the voltage regulation order can be further determined by the voltage-cost sensitivity descending principle; different types of reactive resources at the same node can be regulated in descending order according to the voltage-cost sensitivity; if the reactive resources in the region are exhausted and the voltage still exceeds the limit, the active power control stage can be entered, and the voltage regulation order can be determined according to the voltage-active power sensitivity and voltage-cost sensitivity descending principles.

[0226] In order to verify the effectiveness of the method proposed in this patent in the scenario of high-proportion solar-storage access, a simulation analysis is carried out using the improved IEEE 39-node system as an example, and compared with the existing optimization scheme. Figure 4 shown. Figure 4 In the photovoltaic power station, the wind turbines operate in MPPT mode with rated capacities of 200MW and 100MW respectively; the power of SVG and phase-shifting converters are both 50Mvar; and the maximum charging and discharging power of energy storage is 50kWh / 100kWh.

[0227] Based on the improved hierarchical clustering algorithm, five commonly used inter-class distances are used for comparative analysis. Considering that the numerical comparison of different inter-class distances is poorly comparable, this patent uses relative merge distance for comparison, that is, the distance of each merge is divided by the maximum merge distance in this clustering process, so as to ensure that the relative merge distances of different inter-class distances are within the range of

[01] . Figure 5 It can be seen that when the Ward distance is selected, its relative distance is smaller than other inter-class distances, that is, the higher the correctness of the merger, the better. Therefore, this patent selects the Ward distance as the inter-class distance for reactive power voltage control partitioning.

[0228] from Figure 5 From the relative distance merging curve of the Ward distance, it can be seen that when merging from 5 partitions to 4 partitions, there is an obvious inflection point, and a long plateau period occurs when the number of partitions is less than 5, indicating that each merger requires a large cost to complete when the number of partitions is less than 5. Therefore, it is more appropriate to divide the improved IEEE 39-node system into 5 areas.

[0229] Table 1 Partition results and partition quality indicators under traditional hierarchical clustering algorithm

[0230]

[0231] Table 2 The partition results and partition quality indicators under the improved hierarchical clustering algorithm

[0232]

[0233] Figure 6 , Figure 7 They are the partitioning results under the traditional hierarchical clustering algorithm and the improved hierarchical clustering algorithm respectively; Table 1 and Table 2 show the partitioning results and partitioning quality indicators under the two algorithms. From the perspective of regional reactive power margin, after the traditional hierarchical clustering algorithm is partitioned, the reactive power reserve of region 3 is less than 15%, that is, the reactive power reserve of this region is insufficient; while the reactive power reserve of each region of the clustering partitioning method proposed in this patent meets the requirement of more than 15%, and the reactive power imbalance of the method proposed in this patent is smaller, so it can make more reasonable use of reactive power compensation resources.

[0234] Table 3 Dominant nodes and index values ​​of each sub-region before and after index improvement

[0235]

[0236] Table 3 shows the dominant node selection indicators before and after the improvement. Comparative analysis shows that when the node structure characteristics and location information are not considered, the comprehensive sensitivity of node 1 in partition 1 is the highest. Although node 1 has high sensitivity, its location is at the edge of the partition, so it cannot effectively reflect the voltage fluctuation of the entire partition; however, after introducing the number of node edges to quantitatively evaluate the connection density of nodes from the perspective of network structure, node 39 has the highest comprehensive sensitivity in partition 1; at the same time, node 39 is located in the center of partition 1, so it can better reflect the voltage level in the control area.

[0237] Table 4 Multiple reactive sources are arranged in descending order based on voltage-power sensitivity and voltage-cost sensitivity

[0238]

[0239]

[0240] Figure 8 The voltage-power sensitivity of each partition and its reactive resource node is shown. Table 4 shows the descending order of multiple reactive sources in each partition based on voltage-power sensitivity and voltage-cost sensitivity. Figure 8 It can be concluded from Table 4 that when the voltage exceeds the limit in a sub-area, the reactive sources of different nodes are preferentially arranged in descending order of voltage-reactive power to participate in voltage regulation. If the voltage-reactive sensitivity of two or more nodes is similar, for example, nodes 21 and 24 in partition 4, the voltage-cost sensitivity descending principle can be further used to determine the voltage regulation order, that is, the reactive source regulation order of partition 4 is 34, 36, 33, 35, 24, and 21.

[0241] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0242] This embodiment provides a spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic and energy storage access, which is characterized by comprising:

[0243] A calculation module is used to establish a full-dimensional sensitivity matrix based on the reactive-voltage sensitivity matrix according to the coupling of the reactive source control node and other load nodes; construct a g-dimensional reactive source control space, and use Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than the reactive source control node;

[0244] The partitioning and selection module is used to partition the reactive power and voltage control using the improved hierarchical clustering algorithm to ensure that the reactive power reserve margin of each partition is full, and select the leading node based on the comprehensive sensitivity improvement index;

[0245] The control module is used to realize the coordinated control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, the effectiveness and economy of voltage regulation, and the principle of multi-reactive source coordinated control based on voltage-power sensitivity and voltage-cost sensitivity.

[0246] A spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic and energy storage access, comprising:

[0247] Memory, used to store programs;

[0248] A processor is used to load the program to execute the method for spatiotemporal coordinated control of multiple reactive resources considering high-proportion photovoltaic storage access.

[0249] The embodiment of the present application provides a spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic storage access, including:

[0250] A space construction module is used to establish a full-dimensional sensitivity matrix based on the reactive-voltage sensitivity matrix according to the coupling between the reactive source control node and other load nodes; construct a g-dimensional reactive source control space, and use Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than the reactive source control node;

[0251] The node selection module is used to partition the reactive power and voltage control using an improved hierarchical clustering algorithm to ensure that the reactive power reserve margin of each partition is full, and to select the leading node based on the comprehensive sensitivity improvement index;

[0252] The collaborative control module is used to realize the collaborative control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, the effectiveness and economy of voltage regulation, and the principle of multi-reactive source coordinated control based on voltage-power sensitivity and voltage-cost sensitivity.

[0253] An embodiment of the present application provides a computer-readable storage medium storing a program, which, when loaded, implements a method for spatiotemporal coordinated control of multiple reactive resources under high-ratio solar-storage access.

[0254] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0255] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0256] The step numbers in the above method embodiment are only provided for the convenience of explanation and description, and no limitation is imposed on the order of the steps. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0257] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for spatiotemporal coordination control of multiple reactive resources under high-proportion photovoltaic storage access, characterized in that: include: According to the coupling between the reactive source control node and other load nodes, a full-dimensional sensitivity matrix is ​​established on the basis of the reactive-voltage sensitivity matrix; Constructing a g-dimensional reactive source control space, and using Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than reactive source control nodes; The improved hierarchical clustering algorithm is used to partition the reactive power and voltage control to ensure the reactive power reserve margin of each partition, and the leading node is selected based on the comprehensive sensitivity improvement index; Based on the results of reactive voltage control partitioning and dominant node selection, according to the effectiveness and economy of voltage regulation, the coordinated control principle of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity is adopted to realize the coordinated control of different types of reactive resources.

2. According to the method of spatiotemporal coordination control of multiple reactive resources under high-ratio photovoltaic storage access according to claim 1, it is characterized in that: According to the coupling between the reactive source control node and other load nodes, a full-dimensional sensitivity matrix is ​​established on the basis of the reactive-voltage sensitivity matrix; in the step of constructing a g-dimensional reactive source control space and using Euclidean distance to characterize the distance between nodes, based on the coupling between the PV node and other load nodes, on the basis of the reactive-voltage sensitivity matrix obtained by inverting the power flow Jacobian matrix, each reactive source node is relaxed to a PQ node in a recursive manner, and an augmented sensitivity matrix is ​​recalculated, and then a full-dimensional sensitivity matrix is ​​constructed from each sub-matrix; then, the equivalent electrical distance is obtained according to the reactive voltage sensitivity, a g-dimensional reactive source control space is constructed, and the Euclidean distance is used to characterize the distance between the nodes.

3. According to the method of spatiotemporal coordination control of multiple reactive resources under high-ratio photovoltaic storage access according to claim 1, it is characterized in that: According to the coupling between the reactive source control node and other load nodes, a full-dimensional sensitivity matrix is ​​established on the basis of the reactive-voltage sensitivity matrix; a g-dimensional reactive source control space is constructed, and the Euclidean distance is used to characterize the distance between nodes; The step in which the other load nodes refer to nodes other than the reactive source control node specifically includes: 1) For a power system network with n nodes, the number of PQ nodes is m-1, the number of reactive source control nodes is nm, and the number of balancing nodes is 1, and the system power flow equation is set to be linear; 2) Keep the injected active power constant and obtain the voltage-reactive power sensitivity matrix; 3) Select a reactive source control node to relax as a PQ node, keep the unselected nodes unchanged, and recalculate the power flow to obtain the augmented sensitivity matrix; 4) Each reactive source node is relaxed to a PQ node in a recursive manner and the power flow is recalculated. Then all sub-vectors are merged to obtain a full-dimensional sensitivity matrix. 5) Construct a g-dimensional reactive source control space, and use the Euclidean distance to represent the electrical distance between two nodes.

4. According to the method of spatiotemporal coordination control of multiple reactive resources under high-ratio photovoltaic-storage access according to claim 1, it is characterized in that: The steps of using the improved hierarchical clustering algorithm to partition reactive voltage control to ensure reactive reserve margin of each partition, and selecting the leading node based on the comprehensive sensitivity improvement index specifically include: The improved hierarchical clustering algorithm takes into account the two boundary conditions of reactive power reserve margin index and avoiding isolated nodes, compares multiple inter-cluster distance merging curves, and selects the optimal inter-cluster distance for partition merging.

5. According to the method of spatiotemporal coordination control of multiple reactive resources under high-ratio photovoltaic storage access according to claim 1, it is characterized in that: The steps of using the improved hierarchical clustering algorithm to partition reactive voltage control to ensure reactive reserve margin of each partition, and selecting the leading node based on the comprehensive sensitivity improvement index specifically include: The specific solution steps of the improved hierarchical clustering algorithm are as follows: 1) According to the equivalent electrical distance formula, calculate the Euclidean distance D between two nodes in the power system network with n nodes. mn ; 2) Construct n partitions, each containing only one node; 3) Divide each reactive source control node according to the electrical distance and the principle of minimum connectivity; 4) Merge the two closest partitions into a new partition based on the inter-cluster distance; 5) Determine whether the newly merged partition contains a reactive power source control node, if so, execute step 7), if not, execute step 6); 6) Split the merged partition, select the partition with the next closest merge distance, and return to step 5); 7) Determine whether the reactive power margin of the newly merged partition is greater than or equal to 15%, if so, proceed to the next step, if not, return to step 6); 8) Determine whether the number of partitions is equal to 1. If so, proceed to the next step. If not, recalculate the inter-cluster distances between the partitions and return to step 4); 9) Draw the distance merging curve and output the partitioning results.

6. The method for spatiotemporal coordinated control of multiple reactive resources under high-ratio photovoltaic-storage access according to claim 1 is characterized in that: The steps of using the improved hierarchical clustering algorithm to partition reactive voltage control to ensure reactive reserve margin of each partition, and selecting the leading node based on the comprehensive sensitivity improvement index specifically include: The structural characteristics and location information of the nodes are introduced to improve the sensitivity index. The improved comprehensive sensitivity index considers three dimensions, namely observability, controllability and the number of node edges, to select the dominant node.

7. The method for spatiotemporal coordinated control of multiple reactive resources under high-ratio photovoltaic-storage access according to claim 1 is characterized in that: The steps of realizing coordinated control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, according to the effectiveness and economy of voltage regulation, and the principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity, specifically include: For reactive resources located at different nodes, the descending control principle based on voltage-power sensitivity is adopted, and the rapid regulation of grid node voltage is achieved through a two-stage voltage control mode combining reactive compensation and active power reduction.

8. The method for spatiotemporal coordinated control of multiple reactive resources under high-ratio photovoltaic-storage access according to claim 1 is characterized in that: The steps of realizing coordinated control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, according to the effectiveness and economy of voltage regulation, and the principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity, specifically include: For nodes with voltage exceeding the limit, the output power and adjustment sequence of the reactive power source are controlled to indirectly control the voltage of the grid nodes. The specific steps are as follows: 1) Sort the target nodes with voltage over-limit and select the node with the most over-limit as the target node; 2) Based on the voltage-power sensitivity, the reactive power source with the largest value is regulated first, and the reactive power sources are arranged in descending order of voltage-reactive power sensitivity; 3) Calculate the theoretical output power based on the voltage-power sensitivity and voltage over-limit, and compare it with the current reactive power source power margin to calculate the actual output power; 4) Perform reactive power compensation and active power reduction of each over-limit node in turn, and iteratively adjust the node voltage until all node voltages return to normal; during the active power reduction process, set the power factor threshold, and select the target node and the controlled photovoltaic based on the voltage over-limit level and the voltage-active power sensitivity in descending order; For the reactive resources at the same node, the voltage-cost sensitivity of each reactive source is calculated and sorted according to the numerical value. The reactive equipment corresponding to the larger one will be given priority in voltage regulation when the voltage exceeds the limit.

9. The method for spatiotemporal coordinated control of multiple reactive resources under high-ratio photovoltaic-storage access according to claim 1 is characterized in that: The steps of realizing coordinated control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, according to the effectiveness and economy of voltage regulation, and the principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity, specifically include: The principle of coordinated control of multiple reactive sources based on voltage-power sensitivity and voltage-cost sensitivity can be described as follows: when the voltage exceeds the limit in a sub-region, in the reactive power control stage, reactive sources at different nodes participate in voltage regulation in descending order of voltage-reactive power. If the difference in voltage-reactive power sensitivity between two or more nodes is less than the threshold, the voltage regulation order can be further determined by the voltage-cost sensitivity descending principle; different types of reactive resources at the same node can be regulated in descending order according to the voltage-cost sensitivity; if the reactive resources in the region are exhausted and the voltage still exceeds the limit, the active power control stage can be entered, and the voltage regulation order can be determined according to the voltage-active power sensitivity and voltage-cost sensitivity descending principles.

10. A spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic storage access, characterized in that: include: Memory, used to store programs; A processor is used to load the program to execute the spatiotemporal coordinated control method of multiple reactive resources considering high-proportion photovoltaic storage access as described in any one of claims 1-9.

11. A spatiotemporal coordination control system for multiple reactive resources under high-proportion photovoltaic storage access, characterized in that: include: A space construction module is used to establish a full-dimensional sensitivity matrix based on the reactive-voltage sensitivity matrix according to the coupling between the reactive source control node and other load nodes; construct a g-dimensional reactive source control space, and use Euclidean distance to characterize the distance between nodes; wherein the other load nodes refer to nodes other than the reactive source control node; The node selection module is used to partition the reactive power and voltage control using an improved hierarchical clustering algorithm to ensure that the reactive power reserve margin of each partition is full, and to select the leading node based on the comprehensive sensitivity improvement index; The collaborative control module is used to realize the collaborative control of different types of reactive resources based on the results of reactive voltage control partitioning and dominant node selection, the effectiveness and economy of voltage regulation, and the principle of multi-reactive source coordinated control based on voltage-power sensitivity and voltage-cost sensitivity.

12. A computer-readable storage medium, characterized in that: It stores a program, which, when loaded, implements the spatiotemporal coordinated control method of multiple reactive resources under high-ratio photovoltaic storage access as described in any one of claims 1-9.

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