Voltage control method and system for clusters of power distribution network having high proportion of photovoltaics

Abstract

Disclosed in the present invention are a voltage control method and system for clusters of a power distribution network having a high proportion of photovoltaics. The method comprises: acquiring parameters of a power distribution network, and constructing a comprehensive electrical distance by means of adjustable active power and reactive power reserves of each node in the parameters of the power distribution network; forming an improved weight matrix by means of distributed photovoltaic reactive power and active power supporting capacities, a reactive power sensitivity matrix and an active power sensitivity matrix, and obtaining an optimal reactive power cluster and active power cluster division result by a community algorithm by means of a node coupling degree index in each cluster and the comprehensive electrical distance; and selecting, by means of a clustering algorithm on the basis of the division result, a key node in each cluster to act, to improve the cluster voltage regulation and control capability. Starting from the relationship between active power sensitivity and reactive power sensitivity, and considering the impact of different changes on other nodes, efficient utilization of the reactive power regulation capability of a grid-connected PV inverter can be achieved, the complexity of control strategy computation is greatly reduced, and the situation where there are too many adjustable distributed photovoltaics in clusters is avoided.

Description

A method and system for controlling voltage of a distribution network cluster containing a high proportion of photovoltaics Technical Field

[0001] The present invention relates to the technical field of distribution network control, and in particular to a cluster voltage control method and system for a distribution network containing a high proportion of photovoltaics. Background Art

[0002] my country's power system energy consumption is shifting from a focus on fossil fuels to a focus on clean energy. With the further implementation of national photovoltaic poverty alleviation policies, the number and capacity of household photovoltaic grid-connected systems in distribution networks have shown a rapid growth trend. However, the over-penetration of distributed photovoltaic systems in some areas has led to power backflow, transforming traditional passive distribution networks into complex multi-source networks. These networks are frequently subject to risks such as voltage overshoots and harmonic pollution. Voltage overshoots can impact the safe and stable operation of power lines and the integration of new energy sources within the distribution network. Traditional centralized control methods, which control voltage at every node in the distribution network, are computationally intensive and inefficient. Therefore, to effectively reduce computational complexity and improve the efficiency of system voltage observation and control, Chinese researchers have applied the concept of source-grid "clustering" to power system operation control. By clustering distributed photovoltaic generation, they effectively mitigate the volatility and uncertainty of individual distributed PV sources, improve the control efficiency of active distribution networks with a high proportion of distributed generation, and ensure safe and stable system operation.

[0003] Existing research has achieved cluster voltage regulation for distribution networks containing distributed generation (DGs) using dominant nodes from various technical perspectives. However, the following deficiencies exist in cluster division and dominant node selection: First, none fully consider the voltage / reactive power regulation capabilities of the grid-connected inverters when some PV nodes are connected; second, none consider the impact of the high volatility and uncertainty of PV output on system operation; and third, the impact of active power fluctuations on system voltage is ignored, considering only the impact of reactive power flow on system voltage. However, in medium and low voltage distribution networks, due to the similarity between resistance and reactance, the impact of active power changes on voltage cannot be ignored.

[0004] Summary of the Invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a distribution network cluster voltage control method and system with a high proportion of photovoltaics to solve the problems that the voltage / reactive power regulation capability of the grid-connected inverter itself when some PV nodes are connected is not fully considered in the current cluster division and dominant node selection; the impact of the strong volatility and uncertainty of PV output on the system operation state is not considered, and the impact of active power fluctuation on the system voltage is ignored.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power, comprising: obtaining distribution network parameters, combining the adjustable active and reactive power reserves of each node in the distribution network parameters, and constructing a comprehensive electrical distance;

[0009] An improved weight matrix is ​​formed by using the distributed photovoltaic reactive and active support capabilities and the reactive sensitivity matrix and active sensitivity matrix. Combined with the node coupling index within the cluster and the comprehensive electrical distance, the optimal reactive cluster and active cluster division results are obtained through the community algorithm.

[0010] According to the division results, key node actions in the cluster are selected through a clustering algorithm to improve the cluster voltage regulation capability.

[0011] As a preferred solution of the voltage control method for a distribution network cluster with a high proportion of photovoltaic power described in the present invention, wherein: combining the adjustable active and reactive power reserves of each node in the distribution network parameters to construct a comprehensive electrical distance, including:

[0012] The electrical distance defined by voltage sensitivity information is used to set the closeness of the electrical connection between any two nodes in the system;

[0013] The distribution network flow calculation meets the following requirements:

[0014] Where: ΔP and ΔQ are the changes in active and reactive power injected into the node respectively; Δδ and ΔU are the changes in phase angle and amplitude of node voltage respectively; the Jacobian matrix J is given by Composition, used to express the relationship between node injection power fluctuation and node voltage change;

[0015] The inverse of the Jacobian matrix J can be obtained to obtain the voltage sensitivity of the distribution network:

[0016] Where: S PU 、S QU are the sensitivity matrices of node voltage amplitude changes when injecting unit active and reactive power respectively; S Pδ 、S Qδ are the sensitivity matrices of node voltage phase angle changes when unit active and reactive power are injected respectively;

[0017] The electrical distances between nodes are as follows:

[0018] Where, ΔU i,t , ΔU j,tare the voltage amplitude changes of nodes i and j at time t respectively; Reflects the voltage change of node i caused by the unit voltage change of node j at time t under the influence of active power or reactive power respectively; are the active voltage sensitivity factor and reactive voltage sensitivity factor of node i to node j at time t respectively;

[0019] Electrical distance l ij,t Defined as:

[0020] Expand the definition of the electrical distance between nodes i and j at time t:

[0021] Where, l iz,t 、l jz,t are the electrical distances between nodes i, j and node z at time t.

[0022] As a preferred solution of the method for controlling voltage of a distribution network cluster with a high proportion of photovoltaic power according to the present invention, wherein: the electrical distance defined by the power reserve is used to define the electrical distance in the entire system space, such that the node with less adjustable power moves closer to the node with greater adjustable power, including:

[0023] The electrical distance between any two nodes i and j at time t described by the reactive reserve is:

[0024] Where, is the reactive power that can be provided by the two-node PV inverter at time t; is the reactive power demand between the two nodes when the node power is regulated at time t; when both nodes have no PV power supply When the reactive power provided by the two nodes is greater than the reactive power demand,

[0025] The electrical distance between any two nodes i and j at time t described by the active reserve is:

[0026] Where, is the active power that can be provided by the two-node PV inverter at time t; is the active power demand between the two nodes when the power of node i is adjusted at time t; U it 、U jt are the voltage amplitudes of nodes i and j at time t; U pu Indicates the per-unit value of rated voltage;

[0027] The comprehensive electrical distance between any two nodes defined by reactive and active power reserves is defined as:

[0028] As a preferred solution of the voltage control method for a distribution network cluster with a high photovoltaic ratio according to the present invention, it further includes combining the electrical moment described by voltage sensitivity and power reserve to define the comprehensive electrical distance between any two nodes i and j at time t as:

[0029] d ij,t =λ1L ij,t +λ2γ ij,t

[0030] Set a certain electrical distance relative to the power reserve distance as an extremely important scale, and determine the weights of the two as λ1=0.9 and λ1=0.1 respectively.

[0031] As a preferred solution of the distribution network cluster voltage control method with a high proportion of photovoltaic power described in the present invention, the improved weight matrix is ​​formed by utilizing the distributed photovoltaic reactive power, active power support capacity, reactive power sensitivity matrix, and active power sensitivity matrix. The optimal reactive power cluster and active power cluster division results are obtained by combining the node coupling index within the cluster and the comprehensive electrical distance through the community algorithm, including:

[0032] Treat each node in the network as a cluster and calculate the network modularity value;

[0033] Initially, node i randomly selects node j to combine and form a new cluster, and calculates the modularity and network modularity increment. If the modularity increment is positive, nodes i and j are considered to be in the same cluster.

[0034] Treat the current cluster as a new cluster and continue to combine it with other clusters, repeating the previous step. After traversing all nodes in the entire distribution network, the first cluster division is completed;

[0035] Determine whether there is a cluster with 1 node in the entire system. If so, repeat the above two steps for this cluster. If not, the cluster division phase ends and the result of the current cluster division is output.

[0036] As a preferred solution of the voltage control method for a distribution network cluster with a high proportion of photovoltaic power generation according to the present invention, the following steps are used: based on the division results, a clustering algorithm is used to select key node actions within the cluster, including:

[0037] The self-importance, global importance and central influence of node i at time t are defined as follows:

[0038] GIN i,t =GIMi,t ×SIM i,t

[0039] Where, dg i,t It represents the degree of node i at time t, that is, the number of edges connected to the node in the network, expressed as dg i,t =degreet t (i); β1 and β2 are SIM i,t and GIM i,t The weight coefficient of GIN is β1=β2=1; i,t Represents the GIN centrality influence of node i at time t.

[0040] As a preferred solution of the distribution network cluster voltage control method with a high proportion of photovoltaics described in the present invention, the normalized GIN centrality of node i at time t and the reference degree p under the classical algorithm are calculated. i,t Numerical multiplication h i,t ,Right now:

[0041] Since the reference degree p i,t <0 and the larger the value is, the more suitable the node i is to become the cluster center. t Median h t mid Flip h for the axis t Determine the reference degree of the AP clustering algorithm after considering the optimization of node GIN centrality:

[0042] The entire distribution network is divided into multiple clusters according to the collected node voltage over-limit information.

[0043] In a second aspect, the present invention provides a system for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power, comprising: a construction module for obtaining distribution network parameters, combining the adjustable active and reactive power reserves of each node in the distribution network parameters, and constructing a comprehensive electrical distance;

[0044] A partitioning module is used to use the distributed photovoltaic reactive and active support capabilities and the reactive sensitivity matrix and active sensitivity matrix to form an improved weight matrix, and combine the node coupling index within the cluster and the comprehensive electrical distance to obtain the optimal reactive cluster and active cluster partitioning results through a community algorithm;

[0045] The key point selection module is used to select key node actions in the cluster through a clustering algorithm based on the division results to improve the cluster voltage regulation capability.

[0046] In a third aspect, the present invention provides a computing device, comprising:

[0047] memory and processor;

[0048] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaics are implemented.

[0049] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaics.

[0050] Compared with the existing technology, the present invention has the following beneficial effects: the present invention defines the VS-PR comprehensive electrical distance by considering the node power reserve, and uses a comprehensive and improved community algorithm to perform cluster division of high-penetration distributed photovoltaic access distribution network; starting from the relationship between active and reactive sensitivity, taking into account the influence of different changes in the active / reactive power of the current node on other nodes, and combining the node coupling index within the cluster, the community algorithm is used to obtain the optimal reactive cluster and active set division results; combined with the improved GIN-AP clustering algorithm to select key nodes of the active distribution network dynamic cluster, it can achieve efficient utilization of the reactive regulation capability of the PV grid-connected inverter. The present invention can effectively reduce the total amount of abandoned light in the system and greatly reduce the complexity of the control strategy operation. The present invention combines the photovoltaic support capability with the sensitivity matrix to avoid the situation where there are too many adjustable distributed photovoltaics in the cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0052] FIG1 is a schematic diagram of the overall flow of a method for controlling voltage in a distribution network cluster containing a high proportion of photovoltaic power generation according to an embodiment of the present invention;

[0053] FIG2 is a schematic diagram of a specific flow chart of a method for controlling voltage in a distribution network cluster containing a high proportion of photovoltaic power generation according to an embodiment of the present invention;

[0054] FIG3 is a simplified schematic diagram of cluster voltage coordinated control in a method for controlling cluster voltage in a distribution network with a high photovoltaic ratio according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0056] Example 1

[0057] 1-2 , an embodiment of the present invention provides a method for controlling voltage of a distribution network cluster with a high proportion of photovoltaic power generation, including:

[0058] S1: Obtain distribution network parameters, and construct a comprehensive electrical distance based on the adjustable active and reactive power reserves of each node in the distribution network parameters;

[0059] Furthermore, the integrated electrical distance is constructed by combining the adjustable active and reactive power reserves of each node in the distribution network parameters, including:

[0060] The electrical distance defined by voltage sensitivity information is used to set the closeness of the electrical connection between any two nodes in the system;

[0061] It should be noted that in order to facilitate voltage control within the cluster, it is necessary to ensure that there is a strong electrical connection between the nodes within the cluster. First, the traditional electrical distance defined by voltage sensitivity information is used to describe the closeness of the electrical connection between any two nodes in the system. The distribution network flow calculation should meet the following requirements:

[0062] Where: ΔP and ΔQ are the changes in active and reactive power injected into the node respectively; Δδ and ΔU are the changes in phase angle and amplitude of node voltage respectively; the Jacobian matrix J is given by Composition, used to express the relationship between node injection power fluctuation and node voltage change;

[0063] Compared with the large power grid, the R / X of the distribution network is larger, and the output fluctuation of the distributed power generation will affect other nodes. Therefore, considering the impact of power changes on node voltage and phase angle, the inverse of the Jacobian matrix J in formula (8) can be obtained to obtain the distribution network voltage sensitivity:

[0064] Where: S PU 、S QU are the sensitivity matrices of node voltage amplitude changes when injecting unit active and reactive power respectively; S Pδ 、S Qδ are the sensitivity matrices of node voltage phase angle changes when unit active and reactive power are injected respectively;

[0065] The electrical distances between nodes are as follows:

[0066] Where, ΔU i,t , ΔU j,t are the voltage amplitude changes of nodes i and j at time t respectively; Reflects the voltage change of node i caused by the unit voltage change of node j at time t under the influence of active power or reactive power respectively; are the active voltage sensitivity factor and reactive voltage sensitivity factor of node i to node j at time t respectively;

[0067] It should be noted that It is positively correlated with the influence of node j on node i. The larger its value is, the closer the electrical connection between the two is. The weights are the same, then:

[0068] Electrical distance l ij,t Defined as:

[0069] At the same time, considering the mutual influence between all nodes in the system, then:

[0070] Expand the definition of the electrical distance between nodes i and j at time t:

[0071] Where, l iz,t 、l jz,t are the electrical distances between nodes i, j and node z at time t.

[0072] Furthermore, the electrical distance defined by the power reserve is used to define the electrical distance in the entire system space, which is represented by nodes with less adjustable power moving closer to nodes with greater adjustable power;

[0073] It should be noted that cluster voltage control in active power distribution networks primarily relies on the master node to flexibly regulate the active and reactive power outputs of each cluster's PV grid-connected inverters. This requires each cluster's master node to have a large regulation capacity, meaning it should have a larger reactive and active power reserve relative to other nodes. Therefore, this invention defines a power reserve degree. The smaller its value, the greater the power reserve between nodes. This describes the electrical distance within the entire system space, resulting in nodes with less adjustable power moving closer to nodes with greater adjustable power. Specifically, the reactive and active power reserve degrees are defined as follows:

[0074] include,

[0075] The electrical distance between any two nodes i and j at time t described by the reactive reserve is:

[0076] Where, is the reactive power that can be provided by the two-node PV inverter at time t; is the reactive power demand between the two nodes when the node power is regulated at time t; when both nodes have no PV power supply When the reactive power provided by the two nodes is greater than the reactive power demand,

[0077] The smaller it is, the more distributed PV access node i is, and the higher the reactive power reserve between nodes i and j at time t, the greater the adjustable reactive power that can be provided.

[0078] The electrical distance between any two nodes i and j at time t described by the active reserve is:

[0079] Where, is the active power that can be provided by the two-node PV inverter at time t; is the active power demand between the two nodes when the power of node i is adjusted at time t; U it 、U jt are the voltage amplitudes of nodes i and j at time t; U pu Indicates the per-unit value of rated voltage;

[0080] The comprehensive electrical distance between any two nodes defined by reactive and active power reserves is defined as:

[0081] Furthermore, the electrical distance between any two nodes i and j at time t is defined as follows:

[0082] d ij，t =λ1L ij，t +λ2γ ij，t (12)

[0083] Set a certain electrical distance relative to the power reserve distance as an extremely important scale, and determine the weights of the two as λ1=0.9 and λ1=0.1 respectively.

[0084] It should be noted that in order to comply with the system topology principle, a judgment matrix was established using the 1-9 score scaling method according to the hierarchical analysis method, thereby setting a certain electrical distance relative to the power reserve distance as an extremely important scale.

[0085] It should also be noted that the above definition of comprehensive electrical distance combines the electrical distance described by voltage sensitivity and power reserve to define the VS-PR comprehensive electrical distance between any two nodes i and j at time t, laying the foundation for subsequent related cluster division and key node selection.

[0086] S2: Using the distributed photovoltaic reactive and active support capabilities and the reactive sensitivity matrix and active sensitivity matrix, an improved weight matrix is ​​formed. Combined with the node coupling index within the cluster and the comprehensive electrical distance, the optimal reactive cluster and active cluster division results are obtained through the community algorithm;

[0087] Furthermore, including

[0088] Treat each node in the network as a cluster and calculate the network modularity value;

[0089] Initially, node i randomly selects node j to combine and form a new cluster, and calculates the modularity and network modularity increment. If the modularity increment is positive, nodes i and j are considered to be in the same cluster.

[0090] Treat the current cluster as a new cluster and continue to combine it with other clusters, repeating the previous step. After traversing all nodes in the entire distribution network, the first cluster division is completed;

[0091] Determine whether there is a cluster with 1 node in the entire system. If so, repeat the above two steps for this cluster. If not, the cluster division phase ends and the result of the current cluster division is output.

[0092] Specifically, the specific steps and formulas for the above division are as follows:

[0093] ① Perform decoupling control:

[0094] The Jacobian matrix of the power system load flow can be rewritten as:

[0095] Where ΔP and ΔQ are the changes in the injected active power and reactive power of the node respectively; Δθ and ΔU are the changes in the phase angle and voltage of the node respectively; S PU and S QU The degree of change in node voltage amplitude when a unit amount of active and reactive power is injected into the node; S Pθ and S Qθ The degree of change in the node phase angle when a unit amount of active and reactive power is injected into the node.

[0096] From formula (13), we can see that in a distribution network with n nodes, the change in voltage amplitude ΔU and the changes in active and reactive power ΔP and ΔQ at node i can be expressed as:

[0097] ΔU=S PU ΔP+S QU ΔQ (14)

[0098] In the distribution network, m nodes are connected to photovoltaic power plants with different capacities. The impact on the voltage of node i can be expressed as:

[0099] Where U i0 is the initial voltage of node i, S PUij is the active voltage sensitivity factor of node i to node j; S QUij is the reactive voltage sensitivity factor of node i to node j. From Equations (14) and (15), we can see that when the reactive power of a node is changed without changing the active power, the degree of change in the voltage amplitude is only related to the reactive sensitivity matrix; similarly, when the active power of the node is changed without changing the reactive power, the degree of change in the voltage amplitude is only related to the active sensitivity matrix, so decoupling control of reactive and active power can be achieved.

[0100] ② Improved clustering method based on Louvain algorithm

[0101] The Louvain algorithm is a modularity function clustering algorithm proposed by Newman. This algorithm can quickly generate the optimal clustering results and greatly reduce human intervention. The modularity function can be expressed as:

[0102] Where A ij is the edge weight between node i and node j. When nodes i and j are directly connected, A ij =1, when not directly connected A ij =0,k i is the sum of the edge weights connected to node i, k j is the sum of the edge weights connected to node j, m = (∑i∑jA ij ) / 2 is the sum of the weights of all edges in the network. If nodes i and j are in the same cluster, δ(i, j) = 1, otherwise δ(i, j) = 0.

[0103] 1) Reactive cluster division:

[0104] The original edge weight matrix is ​​replaced by the mean of different node sensitivities. The improved edge weight can be expressed as:

[0105] The supporting capacity of node j by adjusting the reactive power of node i can be expressed as:

[0106] α QUij =S QUij / S QUij ×Q QUi(18)

[0107] Where Q QUi The reactive capacity of the photovoltaic inverter at node i can be adjusted.

[0108] The final improved weight matrix can be expressed as:

[0109] A QUij =α QUij +η QUij (19)

[0110] The improved modularity can be expressed as:

[0111] Considering the internal structural characteristics of the cluster, the aggregation index can be expressed as:

[0112] Where c is the number of the current cluster, m is the total number of clusters, and the comprehensive evaluation index can be expressed as:

[0113] ρ QU =ρ QUa +ρ QUb (twenty two)

[0114] 2) Active power cluster division:

[0115] The active sensitivity matrix can accurately reflect the active coupling degree of different nodes. Therefore, the mean of the active sensitivity matrix is ​​used to replace the original edge weight matrix. The improved edge weight can be expressed as:

[0116] The support capability of node i’s active power adjustment to node j can be expressed as:

[0117] α PUij =S PUij / S PUjj ×P PUi (twenty four)

[0118] The final improved edge weight matrix can be expressed as:

[0119] A PUij =α PUij +S PU (25)

[0120] Modularity can be expressed as:

[0121] Aggregation index of active cluster:

[0122] The comprehensive modularity evaluation index can be expressed as:

[0123] ρPU =ρ PUa +ρ PUb (28)

[0124] It should be noted that this step uses the distributed photovoltaic reactive / active support capacity and reactive sensitivity matrix / active sensitivity matrix to form an improved weight matrix. Combined with the node coupling index within the cluster, the community algorithm is used to obtain the optimal division results of reactive clusters and active clusters, and the various nodes of the power grid are divided into active clusters and reactive clusters.

[0125] S3: Based on the division results, a clustering algorithm is used to select key node actions within the cluster to improve the voltage regulation capability of the cluster.

[0126] It should be noted that the GIN algorithm is introduced to evaluate the suitability of nodes as cluster centers. By increasing the reference degree of nodes with distributed PV power sources and large capacity in the AP algorithm and reducing the reference degree of nodes without distributed PV power sources, the optimal distribution of node reference degrees is achieved to obtain a more suitable cluster center, which is set as the dominant node, thereby improving the system's cluster voltage regulation capability to a certain extent.

[0127] Furthermore, the self-importance, global importance, and central influence of node i at time t are defined as follows:

[0128] GIN i，t =GIM i，t ×SIM i，t (31)

[0129] Where, dg i,t It represents the degree of node i at time t, that is, the number of edges connected to the node in the network, expressed as dg i,t =degreet t (i); β1 and β2 are SIM i,t and GIM i,t The weight coefficient of GIN is β1=β2=1; i,t represents the GIN centrality influence of node i at time t;

[0130] It should be noted that SIM i,t The total number of network nodes n is used as the balance coefficient through the natural logarithm e, which is positively correlated with the degree of the node itself. In addition, the importance of node i is also related to the importance of its interconnected nodes. The more important the connected nodes are, the higher the importance of node i is. The comprehensive electrical distance dg between nodes is i,t Cannot be ignored, node GIM i,tAt the same time, the present invention considers the importance of the node itself and the global importance to be equally important, so β1=β2=1 is taken.

[0131] It should be noted that this step introduces the GIN algorithm to evaluate the suitability of nodes as cluster centers. By increasing the reference degree of nodes with distributed PV power sources and large capacity in the AP algorithm and reducing the reference degree of nodes without distributed PV power sources, the optimal distribution of node reference degrees is achieved to obtain more suitable cluster centers, which are set as key nodes, improving the voltage control effect, increasing the efficiency of voltage control, and to a certain extent, enhancing the system's cluster voltage regulation capability.

[0132] Furthermore, the normalized GIN centrality of node i at time t and the reference degree P under the classic algorithm are calculated. i,t (Take the negative mean of the comprehensive electrical distance )Numerical multiplication value h i,t ,Right now:

[0133] Since the reference degree P i,t <0 and the larger the value is, the more suitable the node i is to become the cluster center. t median Flip h for the axis t Determine the reference degree of the AP clustering algorithm after considering the optimization of node GIN centrality:

[0134] The entire distribution network is divided into multiple clusters according to the collected node voltage over-limit information.

[0135] It should be noted that the present invention adopts a strategy for voltage regulation that combines active and reactive power. First, reactive power compensation is performed on key nodes within the cluster, followed by reactive power compensation on other nodes within the cluster. Finally, a coordinated control strategy is implemented across clusters. If the voltage still exceeds the limit after compensation, active power is reduced accordingly. The sequence of steps is similar to that for reactive power compensation. This cluster control strategy facilitates local power balancing and effectively resolves voltage over-limit issues.

[0136] The above is a schematic diagram of a method for controlling voltage in a distribution network cluster with a high photovoltaic ratio according to this embodiment. It should be noted that the technical solution of the system for controlling voltage in a distribution network cluster with a high photovoltaic ratio and the technical solution of the method for controlling voltage in a distribution network cluster with a high photovoltaic ratio described above are based on the same concept. For details not described in detail in the technical solution of the voltage control system for a distribution network cluster with a high photovoltaic ratio in this embodiment, please refer to the description of the technical solution of the method for controlling voltage in a distribution network cluster with a high photovoltaic ratio described above.

[0137] In this embodiment, the voltage control system for a distribution network cluster with a high proportion of photovoltaic power generation includes:

[0138] A construction module is used to obtain distribution network parameters, and construct a comprehensive electrical distance based on the adjustable active and reactive power reserves of each node in the distribution network parameters;

[0139] A partitioning module is used to use the distributed photovoltaic reactive and active support capabilities and the reactive sensitivity matrix and active sensitivity matrix to form an improved weight matrix, and combine the node coupling index within the cluster and the comprehensive electrical distance to obtain the optimal reactive cluster and active cluster partitioning results through a community algorithm;

[0140] The key point selection module is used to select key node actions in the cluster through a clustering algorithm based on the division results to improve the cluster voltage regulation capability.

[0141] This embodiment further provides a computing device applicable to voltage control of a distribution network cluster with a high proportion of photovoltaic power generation, including:

[0142] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the voltage control method for a distribution network cluster with a high proportion of photovoltaic power generation as proposed in the above embodiment.

[0143] This embodiment further provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the method for controlling the voltage of a distribution network cluster containing a high proportion of photovoltaic power generation is implemented as proposed in the above embodiment.

[0144] The storage medium proposed in this embodiment and the method for realizing voltage control of a distribution network cluster containing a high proportion of photovoltaic power proposed in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0145] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer's floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0146] Example 2

[0147] 3 , which shows an embodiment of the present invention, provides a method for controlling voltage of a distribution network cluster with a high proportion of photovoltaic power generation. In order to verify its feasibility and beneficial effects, an application comparison is provided to illustrate the method.

[0148] Several typical clusters are selected to elaborate on the control strategy proposed in this invention. The cluster voltage coordination control strategy is shown in Figure 1. When voltage fluctuation occurs, the clusters in the system can be divided into three categories:

[0149] Cluster I: Node voltage is normal and coordination capability is sufficient;

[0150] Cluster II: The voltage of some nodes exceeds the limit and the cluster coordination capability is sufficient;

[0151] Cluster III: Most node voltages exceed the limit and the cluster coordination capability is insufficient.

[0152] When the PV output of cluster I fluctuates, the voltage remains at a normal level and the distributed PV continues to operate in normal mode.

[0153] When the photovoltaic output of cluster II fluctuates, the voltage of some nodes exceeds the limit. The information processing center sends an action signal to cluster II. After compensation at key nodes, the overall voltage level of the cluster returns to normal.

[0154] When the photovoltaic output of cluster III fluctuates, the voltage of some nodes seriously exceeds the limit. The information processing center sends an action signal to cluster III. After reactive power compensation within cluster III, the voltage is still in an over-limit state. The information processing center sends an action signal to cluster I, which is more sensitive to the voltage changes of cluster III. After cluster I takes action, cluster III is still in a voltage over-limit state. The information processing center sends an action signal to cluster II. The compensation steps are the same as the internal coordinated control of cluster I.

[0155] When all clusters do not have adjustable reactive power, the active cluster coordination stage begins. The active cluster coordination control is basically the same as the reactive cluster coordination control. Cluster voltage coordination control can not only fully utilize the system regulation capability, but also reduce the number of control nodes, improve voltage control efficiency, and reduce system network losses.

[0156] For the out-of-limit clusters I and II shown in Figure 3, the key nodes of each cluster take action first and record the difference ΔV1 between the voltage of the out-of-limit node b and the voltage limit c. The reactive power adjustment required to restore the voltage of the out-of-limit node to normal can be expressed as:

[0157] Q c =ΔU1 / S QUab (34)

[0158] Let Q ais the maximum reactive power adjustment that can be adjusted at the key node. If Q c <Q a , provided by the key node Q c The voltage returns to normal if Q a <Q c Q is provided by the key node a , perform a power flow calculation, record the difference ΔU2 between the voltage of the over-limit node and c and the network loss compensated by the key node, and repeat the reactive power coordination control according to the selected key nodes. When there is no reactive power adjustment in the cluster, enter the inter-cluster reactive power coordination stage.

[0159] Different PV access points within other clusters have varying degrees of influence on the voltage of the cluster's over-limit node. The node with the greatest support capacity is selected first to calculate the reactive power adjustment required to restore the voltage to normal. If the required reactive power is less than the current node can provide, reactive power compensation is performed on that node, and the voltage at the over-limit node returns to normal. If the required reactive power is greater than the current node can provide, that node provides the full reactive power, performs a power flow calculation, and records the difference between the current and normal voltages. Compensation is then applied sequentially based on the impact. When the adjustable reactive power of all clusters is insufficient, active cluster control begins. The active cluster control method is identical to the reactive cluster control steps and will not be repeated here.

[0160] In summary, by defining the VS-PR integrated electrical distance based on node power reserve, an improved community algorithm was used to cluster distributed photovoltaic systems with high penetration rates. Starting from the relationship between active and reactive power sensitivities, considering the impact of varying the active and reactive power of a node on other nodes, and incorporating the node coupling index within the cluster, the community algorithm was used to determine the optimal reactive cluster and active set partitioning results, achieving improvements of 12.3% and 18.8% in reactive modularity and active modularity compared to the unmodified results.

[0161] Selecting key nodes in a cluster can improve control efficiency. This invention combines an improved GIN-AP clustering algorithm with dynamic key node selection for active distribution network clusters, enabling efficient utilization of the reactive power regulation capabilities of PV grid-connected inverters. This cluster selection reduces the number of control nodes, improving voltage control effectiveness and efficiency when insufficient measurement devices are available.

[0162] A comparison of the voltage regulation effects of different control methods demonstrates that the present invention comprehensively considers the impact of high PV output volatility and uncertainty on system operating conditions. The proposed method can effectively address highly volatile distributed PV access, significantly reducing system voltage fluctuations. Compared with centralized control, the present invention can effectively reduce the total amount of curtailed solar power in the system and significantly reduce the complexity of control strategy calculations. By combining PV support capacity with a sensitivity matrix, the present invention avoids the situation where there are too many adjustable distributed PV systems within the cluster.

[0163] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power, characterized in that: include: Obtaining distribution network parameters, and constructing a comprehensive electrical distance in combination with the adjustable active and reactive power reserves of each node in the distribution network parameters; The distributed photovoltaic reactive power and active power support capabilities, reactive power sensitivity matrix, and active power sensitivity matrix are used to form an improved weight matrix. The optimal reactive power cluster and active power cluster division results are obtained through the community algorithm by combining the node coupling index within the cluster and the comprehensive electrical distance. According to the division result, key node actions in the cluster are selected through a clustering algorithm to improve the voltage regulation capability of the cluster.

2. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 1, characterized in that: Combined with the adjustable active and reactive power reserve of each node in the distribution network parameters, a comprehensive electrical distance is constructed, including: The electrical distance defined by the voltage sensitivity information is used to set the closeness of the electrical connection between any two nodes in the system; The distribution network flow calculation meets the following requirements: Where: ΔP and ΔQ are the changes in active and reactive power injected into the node respectively; Δδ and ΔU are the changes in the phase angle and amplitude of the node voltage respectively; the Jacobian matrix J is given by Composition, used to express the relationship between node injection power fluctuation and node voltage change; The inversion of the Jacobian matrix J can obtain the voltage sensitivity of the distribution network as: Where: S PU , S QU are the sensitivity matrices of node voltage amplitude changes when unit active and reactive power are injected respectively; S Pδ , S Qδ are the sensitivity matrices of node voltage phase angle changes when unit active and reactive power are injected respectively; The electrical distances between nodes are as follows: In the formula, ΔU i,t , ΔU j,t are the voltage amplitude changes of nodes i and j at time t respectively; Respectively reflects the voltage change of node i caused by the unit voltage change of node j at time t under the influence of active power or reactive power; are the active voltage sensitivity factor and reactive voltage sensitivity factor of node i to node j at time t respectively; Electrical distance l ij,t Defined as: The electrical distance between nodes i and j at time t is extended to: In the formula, l iz,t , l jz,t are the electrical distances between nodes i, j and node z at time t respectively.

3. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 1 or 2, characterized in that: The electrical distance defined by the power reserve is used to define the electrical distance in the entire system space, which is manifested as nodes with less adjustable power moving closer to nodes with greater adjustable power. include, The electrical distance between any two nodes i and j at time t described by the reactive reserve is: In the formula, is the reactive power that can be provided by the two-node PV inverter at time t; is the reactive power demand between the two nodes when the node power is adjusted at time t; when both nodes have no PV power supply When the reactive power that can be provided by the two nodes is greater than the reactive power demand, The electrical distance between any two nodes i and j at time t described by the active reserve is: In the formula, is the active power that can be provided by the two-node PV inverter at time t; is the active power demand between two nodes when the power of node i is adjusted at time t; U it , U jt are the voltage amplitudes of nodes i and j at time t; U pu Indicates the rated voltage per unit value; The comprehensive electrical distance between any two nodes defined by reactive and active power reserves is defined as:

4. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 3, characterized in that: It also includes combining the electrical moment described by voltage sensitivity and power reserve to define the comprehensive electrical distance between any two nodes i and j at time t as: ij，t =λ1L ij，t +λ2γ ij，t Set a certain electrical distance relative to the power reserve distance as an extremely important scale, and determine the weights of the two respectively λ1=0.9 and λ1=0.

1.

5. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 4, characterized in that: The distributed photovoltaic reactive and active support capabilities, reactive sensitivity matrix, and active sensitivity matrix are used to form an improved weight matrix. The optimal reactive cluster and active cluster division results are obtained through the community algorithm by combining the node coupling index within the cluster and the comprehensive electrical distance, including: Treat each node in the network as a cluster and calculate the network modularity value; Initially, node i randomly selects node j to combine to obtain a new cluster, and calculates the modularity and network modularity increment. If the modularity increment is positive, nodes i and j are considered to be the same cluster. Treat the current cluster as a new cluster and continue to combine it with other clusters, repeat the previous step, and after traversing all nodes in the entire distribution network, the first cluster division is completed; Determine whether there is a cluster with 1 node in the entire system. If so, repeat the above two steps for this cluster. If not, the cluster division phase ends and the result of the current cluster division is output.

6. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 4 or 5, characterized in that: According to the division results, the key node actions in the cluster are selected through the clustering algorithm, including: The self-importance, global importance and central influence of node i at time t are defined as follows: GIN i，t =GIM i，t ×SIM i，t In the formula, dg i,t It represents the degree of node i at time t, that is, the number of edges connected to the node in the network, expressed as dg i,t =degreet t (i); β1 and β2 are SIM i,t and GIM i,t The weight coefficient of GIN is β1=β2=1; i,t Represents the GIN centrality influence of node i at time t.

7. The method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power generation according to claim 6, characterized in that: Calculate the normalized GIN centrality of node i at time t and the reference degree p under the classic algorithm i,t Numerical multiplication h i,t ,Right now: Since the reference degree p i,t <0 and the larger the value, the higher the suitability of node i to become the cluster center. t Median h t mid Flip h for the axis t Determine the reference degree of the AP clustering algorithm after considering the optimization of the node GIN centrality: The entire distribution network is divided into multiple clusters according to the collected node voltage over-limit information.

8. A system for controlling voltage of a distribution network cluster with a high proportion of photovoltaic power generation, characterized in that: include, A construction module, used to obtain distribution network parameters, and construct a comprehensive electrical distance in combination with the adjustable active and reactive power reserves of each node in the distribution network parameters; A partitioning module is used to use the distributed photovoltaic reactive and active support capabilities and the reactive sensitivity matrix and the active sensitivity matrix to form an improved weight matrix, and to obtain the optimal partitioning results of reactive clusters and active clusters through a community algorithm by combining the node coupling index within the cluster and the comprehensive electrical distance; The key point selection module is used to select key node actions in the cluster through a clustering algorithm according to the division result to improve the voltage regulation capability of the cluster.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaics as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for controlling voltage of a distribution network cluster containing a high proportion of photovoltaic power as claimed in any one of claims 1 to 7.

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