Distributed photovoltaic aggregation equivalence method and system for low-voltage power distribution network

Abstract

The invention belongs to the technical field of smart power grids, and discloses a distributed photovoltaic aggregation equivalence method and system for a low-voltage power distribution network. Comprising the following steps: performing first clustering by taking an approximate electrical distance as a core, and positioning node electrical association by combining a K-means algorithm and an elbow method to avoid blindness of traditional regional division; multi-dimensional indexes such as area numbers and reactive current support coefficients are introduced in secondary clustering, and it is ensured that the characteristics of nodes of the same kind are consistent. The equivalence link follows the principle of summation, capacity weighting and voltage difference invariability, it is guaranteed that the model conforms to key electrical characteristics of an original system, photovoltaic is simplified into a limited equivalent unit, and calculation and data processing pressure is greatly reduced. Meanwhile, the method can accurately reflect the reactive power support capability of the sub-clusters, assists a dispatching system to quickly evaluate the influence of photovoltaic power on the power distribution network, provides reliable support for planning and monitoring of the power distribution network containing high-proportion photovoltaic power, and promotes distributed energy consumption and novel power system construction.

Description

Technical Field

[0001] This invention belongs to the field of smart grid technology and relates to an equivalent method and system for distributed photovoltaic aggregation in low-voltage distribution networks. Background Technology

[0002] In the context of the construction of new power systems, distributed photovoltaic power generation is an important form of new energy development. It is mainly distributed in low-voltage distribution networks and has the characteristics of "small single unit capacity" and "significant differences in the control design of inverters from different manufacturers". Massive deployment strengthens the interaction between the distribution network and the upper-level power grid, changes the power system stability mechanism and operating characteristics, and brings difficulties to power grid modeling and simulation. Therefore, the distributed photovoltaic aggregation equivalent modeling method applicable to low-voltage distribution networks is crucial.

[0003] Existing methods for equivalence aggregation of distributed photovoltaic (PV) systems, such as considering the electrical coupling degree of nodes in the region where the PV cluster is located, divide the region based on the node voltage sensitivity matrix and define a region cluster identification number, incorporating the region cluster identification number into the PV cluster division index, and selecting PV power plant irradiance and inverter control parameters as clustering indicators. The voltage sensitivity matrix requires calculating the impact of node power changes on bus voltage and phase angle within the region containing the PV cluster, i.e., detailed information about the nodes within the region is required. Current technologies rely on complete information about the grid structure and parameters. Therefore, when a large number of distributed PV systems are connected to the low-voltage distribution network, the complex topology of the low-voltage distribution network and the unknown nature of some grid structures and parameters make these methods unsuitable. Therefore, there is an urgent need for a method that can measure the steady-state voltage, power, and PV node load at PV nodes and grid connection points without requiring detailed grid information, thus solving the problems of cluster division and equivalence aggregation. Summary of the Invention

[0004] The purpose of this invention is to address the problem that when a large number of distributed photovoltaic (PV) systems are connected to a low-voltage distribution network, the network topology is complex, some network structures and parameters are unknown, and existing distributed PV aggregation equivalent methods are difficult to apply. This invention provides a distributed PV aggregation equivalent method and system for low-voltage distribution networks.

[0005] To achieve the above objectives, the present invention employs the following technical solution: An equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks includes: Obtain the steady-state electrical parameters of each photovoltaic node and grid connection point; The approximate electrical distance from each photovoltaic node to the grid connection point is calculated based on steady-state electrical parameters. Based on the K-means algorithm and the approximate electrical distance, and combined with the elbow method, the photovoltaic nodes are divided into regions to obtain several photovoltaic regions and assign region numbers. Using the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators, the photovoltaic nodes in each photovoltaic region are further clustered using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters. Based on the principles of capacity weighting and constant voltage difference, power, controller parameters, line parameters and load are equivalently evaluated for each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

[0006] A further improvement of the present invention is that: Furthermore, the steady-state electrical parameters include: the steady-state voltage of each photovoltaic node. Complex power is The load power connected to each photovoltaic node and the steady-state voltage at the grid connection point steady-state current Active power With reactive power The combined power of the grid connection point is .

[0007] Furthermore, before calculating the approximate electrical distance from each photovoltaic node to the grid connection point, the first step is to calculate the... Steady-state voltage difference between each photovoltaic node and the grid connection point Based on circuit theory, the steady-state voltage at the grid connection point is used as the basis for this calculation. Photovoltaic node complex power and current conjugate Based on this, calculate the first Equivalent impedance from a photovoltaic node to the grid connection point ; Among them, steady-state voltage difference for (i=1,2,...,n) No. Equivalent impedance of each photovoltaic node and grid connection point Specifically: in, The voltage at the grid connection point. It is the conjugate of the current; Calculate the first Photovoltaic nodes and PCC equivalent impedance for: in, The voltage angle at the grid connection point.

[0008] Furthermore, the process of dividing the region based on the K-means algorithm and the elbow method to obtain several photovoltaic regions and assigning region numbers is as follows: Randomly select k initial cluster centers and calculate the approximate electrical distance between the characteristic parameters of each photovoltaic node and the characteristic parameters of each initial cluster center; Each photovoltaic node is assigned to the cluster corresponding to the cluster center with the smallest approximate electrical distance. The average value of the characteristic parameters of all photovoltaic nodes in each cluster is calculated, and the cluster center is updated. Repeat the photovoltaic node allocation and cluster center update operations until the cluster centers no longer change or the preset maximum number of iterations is reached; Calculate the sum of squared errors (SSE) for different k values ​​and observe its changing trend. When the rate of decrease of SSE suddenly slows down and forms an "elbow" inflection point, the k value corresponding to this inflection point is the number of photovoltaic regions. Finally, k photovoltaic regions are obtained and assigned region numbers from 1 to k.

[0009] Furthermore, the calculation of the approximate electrical distance between the characteristic parameters of each photovoltaic node and the characteristic parameters of each initial cluster center specifically involves: in, Indicates the first Steady-state voltage difference and equivalent impedance from each photovoltaic node to the PCC Indicates the first Steady-state voltage difference and equivalent impedance from photovoltaic nodes to PCC in each regional cluster center. Represented as the first The photovoltaic node to the first The approximate electrical distance between each region cluster center is used to obtain the approximate electrical distance from each photovoltaic node to each cluster center. The process of assigning each photovoltaic node to the cluster corresponding to the cluster center with the smallest approximate electrical distance, and calculating the average value of the characteristic parameters of all photovoltaic nodes in each cluster, specifically involves: Each data point is assigned to the cluster corresponding to the nearest cluster center, specifically: in, Representing data points The index of the cluster to which it was assigned; For each cluster, its cluster center is recalculated. The new cluster center is the average of all data points in that cluster. Specifically: in, Belongs to the The number of data points in each cluster; The sum of squared errors within a cluster (SSE) is calculated as follows: Furthermore, the clustering index set is as follows: ,in, For area code, This represents the reactive power compensation coefficient for a photovoltaic power station. This is the equivalent impedance from the photovoltaic node to the grid connection point. This refers to the rated capacity of the photovoltaic power station. Among them, the reactive power compensation coefficient of photovoltaic power station The method for obtaining it is as follows: During voltage drop periods, photovoltaic (PV) power plants provide reactive power by injecting reactive current into the grid. When the PV system is operating at low voltage (i.e., the interconnection point voltage is less than 90% of the grid's rated voltage), the PV system injects reactive current into the grid to provide reactive power support. The PV system prioritizes reactive power output, and the active current output reference depends on the reactive current output reference. The active current reference and the reactive current reference are respectively: in, This is the reactive current reference value, which is the target reactive current value that the inverter needs to output. This represents the reactive power compensation coefficient for a photovoltaic power station. This is the per-unit value of the grid voltage. This is the inverter's rated current; This is the active current coefficient; This is the active current reference value, i.e., the target value of the active current output by the inverter; This is the maximum short-time output current allowed by the inverter; This is the maximum current coefficient of the inverter; The photovoltaic nodes within each photovoltaic region are then subjected to a second clustering using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters, specifically: By region number The photovoltaic nodes are grouped, with each group corresponding to a photovoltaic region; for each group of photovoltaic nodes, a clustering index set is used. Feature parameters, combined with the K-means algorithm and elbow method, are used to determine the optimal number of sub-clusters within each photovoltaic region, ultimately dividing all photovoltaic nodes into... A photovoltaic sub-cluster.

[0010] Furthermore, the specific process of power equivalence is as follows: For the There are 1 photovoltaic sub-clusters, and the number of photovoltaic power stations within each sub-cluster is counted. Calculate the equivalent active power of this sub-cluster. , Equal to all within the sub-cluster Active power of a photovoltaic power station the sum of Calculate the equivalent reactive power of this sub-cluster. , Equal to all within the sub-cluster Reactive power of a photovoltaic power station sum, The specific process for equivalence of the controller parameters is as follows: Equivalent unit modeling is used to replace the distributed photovoltaic sub-cluster after cluster division. The controller parameter is the reactive current support coefficient. For the first... For each photovoltaic sub-cluster, calculate the weighting factor for each photovoltaic power station within that sub-cluster. and the equivalent reactive current support coefficient of the sub-cluster Specifically: in, The weighting factor for photovoltaic power plants; For the first Equivalent reactive current compensation coefficient for each distributed photovoltaic sub-cluster; For the first In a distributed photovoltaic sub-cluster One reactive current compensation coefficient, It is the first In the first distributed photovoltaic sub-cluster Rated capacity of distributed photovoltaic power.

[0011] Furthermore, the specific process for equivalence of the line parameters includes: For the For each photovoltaic sub-cluster, calculate all [data / values] within that sub-cluster. The weighted average voltage difference between each photovoltaic node and the grid connection point is as follows: After being equalized, the first Each equivalent generator unit access point and grid connection point The voltage difference is: Based on the principle of constant voltage difference, all sub-clusters The weighted average voltage difference between the photovoltaic node and the grid connection point and the first Each equivalent generator unit access point and grid connection point Since the voltage difference is equal, the following holds: The formula for calculating the equivalent impedance of the line from the equivalent unit to the grid connection point is: The specific process of load equivalence is as follows: For the Calculate the equivalent load of each photovoltaic sub-cluster. , Equal to all within the sub-cluster The load power connected to each photovoltaic node the sum of Statistics on the total load of unconnected photovoltaic nodes in the low-voltage distribution network Specifically: in, Equal to the total load of the grid connection point With all The difference between the sum of the equivalent loads of each photovoltaic sub-cluster.

[0012] A distributed photovoltaic aggregation equivalent system for low-voltage distribution networks, comprising: The acquisition module acquires the steady-state electrical parameters of each photovoltaic node and grid connection point; The region division module calculates the approximate electrical distance from each photovoltaic node to the grid connection point based on steady-state electrical parameters, and divides the photovoltaic nodes into regions based on the K-means algorithm and the approximate electrical distance, combined with the elbow method, to obtain several photovoltaic regions and assign region numbers. The clustering module uses the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators. It then uses the K-means algorithm combined with the elbow method to perform secondary clustering on the photovoltaic nodes in each photovoltaic region to obtain several photovoltaic sub-clusters. The equivalent module, based on the principle of capacity weighting and constant voltage difference, performs power equivalence, controller parameter equivalence, line parameter equivalence, and load equivalence on each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

[0013] Compared with the prior art, the present invention has the following beneficial effects: This invention employs a novel clustering method, using approximate electrical distance as the core, combining the K-means algorithm with the elbow method to locate the electrical associations of nodes, thus avoiding the blind spots of traditional regional divisions. Secondary clustering introduces multi-dimensional indicators such as region numbering and reactive current support coefficients to ensure consistent characteristics of nodes within the same category. The equivalence step follows the principles of summation, capacity weighting, and constant voltage difference, ensuring that the model matches the key electrical characteristics of the original system while simplifying photovoltaics into finite equivalent units, significantly reducing computational and data processing pressure. Simultaneously, this invention accurately reflects the reactive power support capacity of sub-clusters, assisting dispatch systems in quickly assessing the impact of photovoltaics on the distribution network, providing reliable support for the planning and monitoring of distribution networks with a high proportion of photovoltaics, and promoting the consumption of distributed energy and the construction of new power systems. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart illustrating the low-voltage distribution network distributed photovoltaic aggregation equivalent method of the present invention. Figure 2 A schematic diagram illustrating the division of a large-scale distributed photovoltaic cluster into several distributed photovoltaic sub-clusters according to the present invention; Figure 3 This is a schematic diagram illustrating the aggregated equivalent results of a distributed photovoltaic cluster. Figure 4 This is a schematic diagram of the structure of the low-voltage distribution network distributed photovoltaic aggregation equivalent system of the present invention; Figure 5 This is a schematic diagram of an IEEE-14 node computation example according to an embodiment of the present invention; Figure 6 This is a schematic diagram showing the variation of the total sum of squared errors within a cluster corresponding to the number of photovoltaic regions in this invention. Figure 7 This is a schematic diagram illustrating the division of a large-scale distributed photovoltaic cluster according to an embodiment of the present invention. Figure 8 This is a schematic diagram of the final partitioning result of distributed photovoltaic power generation according to an embodiment of the present invention; Figure 9 This is a schematic diagram of a distributed photovoltaic equivalent unit according to an embodiment of the present invention; Figure 10 This is a schematic diagram comparing the active and reactive power at the grid connection point when the voltage drops to 0.8 pu in an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0017] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0018] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0019] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0020] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0021] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0022] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 1This invention discloses an equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks, comprising: S101, obtain the steady-state electrical parameters of each photovoltaic node and grid connection point; The steady-state electrical parameters include: the steady-state voltage of each photovoltaic node. Complex power is The load power connected to each photovoltaic node and the steady-state voltage at the grid connection point steady-state current Active power With reactive power The combined power of the grid connection point is .

[0023] S102: Calculate the approximate electrical distance from each photovoltaic node to the grid connection point based on steady-state electrical parameters. Based on the K-means algorithm and the approximate electrical distance, and combined with the elbow method, divide the photovoltaic nodes into regions to obtain several photovoltaic regions and assign region numbers.

[0024] Before calculating the approximate electrical distance from each photovoltaic node to the grid connection point, first calculate the first... Steady-state voltage difference between each photovoltaic node and the grid connection point Based on circuit theory, the steady-state voltage at the grid connection point is used as the basis for this calculation. Photovoltaic node complex power and current conjugate Based on this, calculate the first Equivalent impedance from a photovoltaic node to the grid connection point ; Among them, steady-state voltage difference for (i=1,2,...,n) No. Equivalent impedance of each photovoltaic node and grid connection point Specifically: in, The voltage at the grid connection point. It is the conjugate of the current; Calculate the first Photovoltaic nodes and PCC equivalent impedance for: in, The voltage angle at the grid connection point.

[0025] The process of dividing the region based on the K-means algorithm and the elbow method results in several photovoltaic regions, which are then assigned region numbers. Specifically: Randomly select k initial cluster centers and calculate the approximate electrical distance between the characteristic parameters of each photovoltaic node and the characteristic parameters of each initial cluster center; Each photovoltaic node is assigned to the cluster corresponding to the cluster center with the smallest approximate electrical distance. The average value of the characteristic parameters of all photovoltaic nodes in each cluster is calculated, and the cluster center is updated. Repeat the photovoltaic node allocation and cluster center update operations until the cluster centers no longer change or the preset maximum number of iterations is reached; Calculate the sum of squared errors (SSE) for different k values ​​and observe its changing trend. When the rate of decrease of SSE suddenly slows down and forms an "elbow" inflection point, the k value corresponding to this inflection point is the number of photovoltaic regions. Finally, k photovoltaic regions are obtained and assigned region numbers from 1 to k.

[0026] The calculation of the approximate electrical distance between the feature parameters of each photovoltaic node and the feature parameters of each initial cluster center is specifically as follows: in, Indicates the first Steady-state voltage difference and equivalent impedance from each photovoltaic node to the PCC Indicates the first Steady-state voltage difference and equivalent impedance from photovoltaic nodes to PCC in each regional cluster center. Represented as the first The photovoltaic node to the first The approximate electrical distance between each region cluster center is obtained by calculating the approximate electrical distance from each photovoltaic node to each cluster center.

[0027] The process of assigning each photovoltaic node to the cluster corresponding to the cluster center with the smallest approximate electrical distance, and calculating the average value of the characteristic parameters of all photovoltaic nodes in each cluster, specifically involves: Each data point is assigned to the cluster corresponding to the nearest cluster center, specifically: in, Representing data points The index of the cluster to which it was assigned; For each cluster, its cluster center is recalculated. The new cluster center is the average of all data points in that cluster. Specifically: in, Belongs to the The number of data points in each cluster; The sum of squared errors within a cluster (SSE) is calculated as follows: S103 uses the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators. The photovoltaic nodes in each photovoltaic region are then clustered again using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters. The clustering index set is as follows: ,in, For area code, This represents the reactive power compensation coefficient for a photovoltaic power station. This is the equivalent impedance from the photovoltaic node to the grid connection point. This refers to the rated capacity of the photovoltaic power station. Among them, the reactive power compensation coefficient of photovoltaic power station The method for obtaining it is as follows: During voltage drop periods, photovoltaic (PV) power plants provide reactive power by injecting reactive current into the grid. When the PV system is operating at low voltage (i.e., the interconnection point voltage is less than 90% of the grid's rated voltage), the PV system injects reactive current into the grid to provide reactive power support. The PV system prioritizes reactive power output, and the active current output reference depends on the reactive current output reference. The active current reference and the reactive current reference are respectively: in, This is the reactive current reference value, which is the target reactive current value that the inverter needs to output. This represents the reactive power compensation coefficient for a photovoltaic power station. This is the per-unit value of the grid voltage. This is the inverter's rated current; This is the active current coefficient; This is the active current reference value, i.e., the target value of the active current output by the inverter; This is the maximum short-time output current allowed by the inverter; This is the maximum current coefficient of the inverter; The photovoltaic nodes within each photovoltaic region are then subjected to a second clustering using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters, specifically: By region number The photovoltaic nodes are grouped, with each group corresponding to a photovoltaic region; for each group of photovoltaic nodes, a clustering index set is used. Feature parameters, combined with the K-means algorithm and elbow method, are used to determine the optimal number of sub-clusters within each photovoltaic region, ultimately dividing all photovoltaic nodes into... A large-scale distributed photovoltaic (PV) cluster is divided into several distributed PV sub-clusters, such as... Figure 2As shown.

[0028] S104, based on the principle of capacity weighting and constant voltage difference, performs power equivalence, controller parameter equivalence, line parameter equivalence and load equivalence on each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, forming a distributed photovoltaic aggregation equivalent model.

[0029] Based on the principles of "capacity weighting" and "constant voltage difference," parameter aggregation and equivalence are performed. A single photovoltaic unit represents several units within the same photovoltaic sub-cluster, ensuring that the external characteristics of the distributed photovoltaic cluster remain consistent at the grid connection point before and after equivalence. The unknown quantities for the network equivalent parameters include the equivalent impedance of the lines. Equivalent photovoltaic power station grid connection voltage and equivalent load ,like Figure 3 As shown, each photovoltaic sub-cluster is eventually aggregated into an equivalent unit.

[0030] The specific process of power equivalence is as follows: For the There are 1 photovoltaic sub-clusters, and the number of photovoltaic power stations within each sub-cluster is counted. Calculate the equivalent active power of this sub-cluster. , Equal to all within the sub-cluster Active power of a photovoltaic power station the sum of Calculate the equivalent reactive power of this sub-cluster. , Equal to all within the sub-cluster Reactive power of a photovoltaic power station sum, The specific process for equivalence of the controller parameters is as follows: Equivalent unit modeling is used to replace the distributed photovoltaic sub-cluster after cluster division. The controller parameter is the reactive current support coefficient. For the first... For each photovoltaic sub-cluster, calculate the weighting factor for each photovoltaic power station within that sub-cluster. and the equivalent reactive current support coefficient of the sub-cluster Specifically: in, The weighting factor for photovoltaic power plants; For the first Equivalent reactive current compensation coefficient for each distributed photovoltaic sub-cluster; For the first In a distributed photovoltaic sub-cluster One reactive current compensation coefficient, It is the first In the first distributed photovoltaic sub-cluster Rated capacity of distributed photovoltaic power.

[0031] The specific process for equivalence of the line parameters includes: For the For each photovoltaic sub-cluster, calculate all [data / values] within that sub-cluster. The weighted average voltage difference between each photovoltaic node and the grid connection point is as follows: After being equalized, the first Each equivalent generator unit access point and grid connection point The voltage difference is: Based on the principle of constant voltage difference, all sub-clusters The weighted average voltage difference between the photovoltaic node and the grid connection point and the first Each equivalent generator unit access point and grid connection point Since the voltage difference is equal, the following holds: The formula for calculating the equivalent impedance of the line from the equivalent unit to the grid connection point is: The specific process of load equivalence is as follows: For the Calculate the equivalent load of each photovoltaic sub-cluster. , Equal to all within the sub-cluster The load power connected to each photovoltaic node the sum of Statistics on the total load of unconnected photovoltaic nodes in the low-voltage distribution network Specifically: in, Equal to the total load of the grid connection point With all The difference between the sum of the equivalent loads of each photovoltaic sub-cluster.

[0032] See Figure 4 This invention discloses a distributed photovoltaic aggregation equivalent system for low-voltage distribution networks, comprising: The acquisition module acquires the steady-state electrical parameters of each photovoltaic node and grid connection point; The region division module calculates the approximate electrical distance from each photovoltaic node to the grid connection point based on steady-state electrical parameters, and divides the photovoltaic nodes into regions based on the K-means algorithm and the approximate electrical distance, combined with the elbow method, to obtain several photovoltaic regions and assign region numbers. The clustering module uses the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators. It then uses the K-means algorithm combined with the elbow method to perform secondary clustering on the photovoltaic nodes in each photovoltaic region to obtain several photovoltaic sub-clusters. The equivalent module, based on the principle of capacity weighting and constant voltage difference, performs power equivalence, controller parameter equivalence, line parameter equivalence, and load equivalence on each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

[0033] Example: This invention discloses an equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks, considering, for example... Figure 5 The IEEE-14 node system shown has a total of 10 distributed photovoltaic systems connected.

[0034] Measure the voltage at 10 photovoltaic nodes Complex power Loads connected to photovoltaic nodes and grid connection point voltage Grid connection point power This provides information for subsequent grouping.

[0035] Calculate the first The steady-state voltage difference between each photovoltaic node and the PCC is: (i=1,2,...,10) Calculate the first Photovoltaic nodes and PCC equivalent impedance for: The steady-state voltage difference and equivalent impedance between each photovoltaic node and the PCC point are obtained.

[0036] Using the K-means algorithm, k cluster centers are randomly selected, and the distances between the data from the 10 photovoltaic nodes and the randomly selected cluster centers are calculated. The expression is: at this time, Indicates the first Steady-state voltage difference and equivalent impedance from each photovoltaic node to the PCC Indicates the first Calculate the steady-state voltage difference and equivalent impedance from the photovoltaic nodes to the PCC in each regional cluster center. The photovoltaic node to the first Approximate electrical distance between the cluster centers of each region , as a clustering indicator for regional division.

[0037] Each data point is assigned to the cluster corresponding to the nearest cluster center, using the following formula: In the formula, Representing data points The index of the cluster to which it was assigned.

[0038] For each cluster, its cluster center is recalculated; the new cluster center is the average of all data points in that cluster.

[0039] In the formula, Belongs to the The number of data points in each cluster.

[0040] Repeated data distribution and cluster center updates continue until the cluster centers no longer change significantly or the preset maximum number of iterations is reached.

[0041] The formula that minimizes the sum of squared errors within the final cluster is: The sum of squared total intra-cluster errors corresponding to the number of photovoltaic regions obtained by combining the K-means algorithm with the elbow method is as follows: Figure 6 As shown, when k changes from 3 to 4, the rate of decrease in the sum of squared errors within the cluster suddenly slows down. Therefore, the large-scale distributed photovoltaic cluster is divided into 3 regions, as follows: Figure 7 As shown. The area number is given. Its value ranges from 1 to 3, and it serves as one of the clustering indicators for the next step.

[0042] The parameters of the 10 distributed photovoltaic systems are shown in Table 1: Table 1 Parameters of Distributed Photovoltaics Again, K-means combined with the elbow method was used to cluster photovoltaic nodes within different region numbers based on clustering indices. Perform secondary clustering, at this time, Indicates the first Each node Value. Among them, The value is used as a reference, that is, in different regions. Perform a secondary partition within the value range.

[0043] The photovoltaic clusters are divided into three regions, and the sum of squared total errors within each cluster corresponding to the number of photovoltaic areas in each region is calculated. For example, region 1 is ultimately divided into two distributed photovoltaic sub-clusters, resulting in the following: Figure 8 The six photovoltaic sub-clusters shown are illustrated.

[0044] Based on the principles of capacity weighting and constant voltage difference, power, controller parameters, line parameters and load are equivalently evaluated for each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

[0045] The specific process of power equivalence is as follows: The parameters of the photovoltaic power stations within each photovoltaic sub-cluster are aggregated. When h=1, that is, the power of all photovoltaic power stations within the first photovoltaic sub-cluster is added together to obtain the equivalent unit. , The formula is: The specific process for equivalence of the controller parameters is as follows: The rated capacity and reactive current support factor of all photovoltaic units within the first photovoltaic sub-cluster are obtained. Based on the capacity support coefficient for reactive current By applying weighted averages, the reactive current support coefficient of the equivalent unit is obtained. .

[0046] (d=2, h=1) The specific process for equivalence of the line parameters includes: Depend on Find the two photovoltaic power stations in the first group and The weighted average voltage difference between points is shown in the following formula: (d=2, h=1) After equivalence, the first equivalence unit access point and The voltage difference at the points is: (h=1) Based on the principle that the voltage difference remains constant (h=1) The equivalent impedance of the line from the first equivalent unit to the grid connection point can be calculated as follows: (d=2, h=1) The equivalent load for the first group is: (d=2) The remaining five photovoltaic sub-clusters were aggregated and valued using this method, resulting in the following: Figure 9 The six equivalent photovoltaic units shown are illustrated.

[0047] The equivalent load of the system without connected photovoltaic nodes is: (r=6) A three-phase voltage drop occurs at 0.5s. The external characteristics of the detailed models before and after the equivalent voltage drop, and the proposed aggregate model, are compared at the grid connection point. When the three-phase voltage drops to 0.8 pu, the active and reactive power at the grid connection point of the detailed models before and after the equivalent voltage drop, and the proposed model, are as follows: Figure 10 As shown.

[0048] The accuracy of the model is verified by calculating the relative error between the measured data before and after the equivalent measurement. A smaller relative error F indicates that the model's calculation results are closer to the actual measured values, and therefore, higher accuracy. The relative error formula includes the voltage at the grid connection point. Current Active power reactive power The formula used is as follows: In the formula, The value after the equivalent. This is the data before it was equalized. F is the relative error. The data after being equated The termination and start points of the calculation. and The data before equivalence. The termination and start points of the calculation.

[0049] Eight data points were taken from each of the four measurement data points in the steady-state interval (0.1s-0.45s) and the transient interval (0.6s-0.95s), and the relative errors are shown in Table 2. Table 2. Relative errors of different intervals for each measurement data. Combination Figure 10 As can be seen from the simulation curves and the relative error levels shown in Table 2, the proposed aggregate equivalent model has higher equivalent accuracy compared with the detailed model when voltage drops. This invention only requires measuring the steady-state voltage and power of photovoltaic nodes and grid connection points, without needing to know the detailed information of the grid structure and other nodes. The influence of the unknown structure and parameters of the low-voltage distribution network on its transient analysis in voltage drop systems can be ignored.

[0050] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for equivalent value aggregation of distributed photovoltaic power in low-voltage distribution networks, characterized in that, include: Obtain the steady-state electrical parameters of each photovoltaic node and grid connection point; The approximate electrical distance from each photovoltaic node to the grid connection point is calculated based on steady-state electrical parameters. Based on the K-means algorithm and the approximate electrical distance, and combined with the elbow method, the photovoltaic nodes are divided into regions to obtain several photovoltaic regions and assign region numbers. Using the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators, the photovoltaic nodes in each photovoltaic region are further clustered using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters. Based on the principles of capacity weighting and constant voltage difference, power, controller parameters, line parameters and load are equivalently evaluated for each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

2. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 1, characterized in that, The steady-state electrical parameters include: the steady-state voltage of each photovoltaic node. Complex power is The load power connected to each photovoltaic node and the steady-state voltage at the grid connection point steady-state current Active power With reactive power The combined power of the grid connection point is .

3. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 2, characterized in that, Before calculating the approximate electrical distance from each photovoltaic node to the grid connection point, first calculate the first... Steady-state voltage difference between each photovoltaic node and the grid connection point Based on circuit theory, the steady-state voltage at the grid connection point is used as the basis for this calculation. Photovoltaic node complex power and current conjugate Based on this, calculate the first Equivalent impedance from a photovoltaic node to the grid connection point ; Among them, steady-state voltage difference for (i=1,2,...,n) No. Equivalent impedance of each photovoltaic node and grid connection point Specifically: in, The voltage at the grid connection point. It is the conjugate of the current; Calculate the first Photovoltaic nodes and PCC equivalent impedance for: in, The voltage angle at the grid connection point.

4. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 3, characterized in that, The process of dividing the region based on the K-means algorithm and the elbow method results in several photovoltaic regions, which are then assigned region numbers. Specifically: Randomly select k initial cluster centers and calculate the approximate electrical distance between the characteristic parameters of each photovoltaic node and the characteristic parameters of each initial cluster center; Each photovoltaic node is assigned to the cluster corresponding to the cluster center with the smallest approximate electrical distance. The average value of the characteristic parameters of all photovoltaic nodes in each cluster is calculated, and the cluster center is updated. Repeat the photovoltaic node allocation and cluster center update operations until the cluster centers no longer change or the preset maximum number of iterations is reached; Calculate the sum of squared errors (SSE) for different k values ​​and observe its changing trend. When the rate of decrease of SSE suddenly slows down and forms an "elbow" inflection point, the k value corresponding to this inflection point is the number of photovoltaic regions. Finally, k photovoltaic regions are obtained and assigned region numbers from 1 to k.

5. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 4, characterized in that, The calculation of the approximate electrical distance between the feature parameters of each photovoltaic node and the feature parameters of each initial cluster center is specifically as follows: in, Indicates the first Steady-state voltage difference and equivalent impedance from each photovoltaic node to the PCC Indicates the first Steady-state voltage difference and equivalent impedance from photovoltaic nodes to PCC in each regional cluster center. Represented as the first The photovoltaic node to the first The approximate electrical distance between each region cluster center is used to obtain the approximate electrical distance from each photovoltaic node to each cluster center. The process of assigning each photovoltaic node to the cluster corresponding to the cluster center with the smallest approximate electrical distance, and calculating the average value of the characteristic parameters of all photovoltaic nodes in each cluster, specifically involves: Each data point is assigned to the cluster corresponding to the nearest cluster center, specifically: in, Representing data points The index of the cluster to which it was assigned; For each cluster, its cluster center is recalculated. The new cluster center is the average of all data points in that cluster. Specifically: in, Belongs to the The number of data points in each cluster; The sum of squared errors within a cluster (SSE) is calculated as follows: 。 6. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 5, characterized in that, The clustering index set is as follows: ,in, For area code, This represents the reactive power compensation coefficient for a photovoltaic power station. This is the equivalent impedance from the photovoltaic node to the grid connection point. This refers to the rated capacity of the photovoltaic power station. Among them, the reactive power compensation coefficient of photovoltaic power station The method for obtaining it is as follows: During voltage drop periods, photovoltaic (PV) power plants provide reactive power by injecting reactive current into the grid. When the PV system is operating at low voltage (i.e., the interconnection point voltage is less than 90% of the grid's rated voltage), the PV system injects reactive current into the grid to provide reactive power support. The PV system prioritizes reactive power output, and the active current output reference depends on the reactive current output reference. The active current reference and the reactive current reference are respectively: in, This is the reactive current reference value, which is the target reactive current value that the inverter needs to output. This represents the reactive power compensation coefficient for a photovoltaic power station. This is the per-unit value of the grid voltage. This is the inverter's rated current; This is the active current coefficient; This is the active current reference value, i.e., the target value of the active current output by the inverter; This is the maximum short-time output current allowed by the inverter; This is the maximum current coefficient of the inverter; The photovoltaic nodes within each photovoltaic region are then subjected to a second clustering using the K-means algorithm combined with the elbow method to obtain several photovoltaic sub-clusters, specifically: By region number The photovoltaic nodes are grouped, with each group corresponding to a photovoltaic region; for each group of photovoltaic nodes, a clustering index set is used. Feature parameters, combined with the K-means algorithm and elbow method, are used to determine the optimal number of sub-clusters within each photovoltaic region, ultimately dividing all photovoltaic nodes into... A photovoltaic sub-cluster.

7. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 6, characterized in that, The specific process of power equivalence is as follows: For the There are 1 photovoltaic sub-clusters, and the number of photovoltaic power stations within each sub-cluster is counted. Calculate the equivalent active power of this sub-cluster. , Equal to all within the sub-cluster Active power of a photovoltaic power station The sum of Calculate the equivalent reactive power of this sub-cluster. , Equal to all within the sub-cluster Reactive power of a photovoltaic power station sum; 。 8. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 7, characterized in that, The specific process for equivalence of the controller parameters is as follows: Equivalent unit modeling is used to replace the distributed photovoltaic sub-cluster after cluster division. The controller parameter is the reactive current support coefficient. For the first... For each photovoltaic sub-cluster, calculate the weighting factor for each photovoltaic power station within that sub-cluster. and the equivalent reactive current support coefficient of the sub-cluster Specifically: in, The weighting factor for photovoltaic power plants; For the first Equivalent reactive current compensation coefficient for each distributed photovoltaic sub-cluster; For the first In a distributed photovoltaic sub-cluster One reactive current compensation coefficient, It is the first In the first distributed photovoltaic sub-cluster Rated capacity of distributed photovoltaic power.

9. The equivalent method for distributed photovoltaic aggregation in low-voltage distribution networks according to claim 8, characterized in that, The specific process for equivalence of the line parameters includes: For the For each photovoltaic sub-cluster, calculate all [data / values] within that sub-cluster. The weighted average voltage difference between each photovoltaic node and the grid connection point is as follows: After being equalized, the first Each equivalent generator unit access point and grid connection point The voltage difference is: Based on the principle of constant voltage difference, all sub-clusters The weighted average voltage difference between the photovoltaic node and the grid connection point and the first Each equivalent generator unit access point and grid connection point Since the voltage difference is equal, the following holds: The formula for calculating the equivalent impedance of the line from the equivalent unit to the grid connection point is: The specific process of load equivalence is as follows: For the Calculate the equivalent load of each photovoltaic sub-cluster. , Equal to all within the sub-cluster The load power connected to each photovoltaic node The sum of Statistics on the total load of unconnected photovoltaic nodes in the low-voltage distribution network Specifically: in, Equal to the total load of the grid connection point With all The difference between the sum of the equivalent loads of each photovoltaic sub-cluster.

10. A distributed photovoltaic aggregation equivalent system for low-voltage distribution networks, characterized in that, include: The acquisition module acquires the steady-state electrical parameters of each photovoltaic node and grid connection point; The region division module calculates the approximate electrical distance from each photovoltaic node to the grid connection point based on steady-state electrical parameters, and divides the photovoltaic nodes into regions based on the K-means algorithm and the approximate electrical distance, combined with the elbow method, to obtain several photovoltaic regions and assign region numbers. The clustering module uses the region number, reactive current support coefficient of the photovoltaic power station, rated capacity, and equivalent impedance from the photovoltaic node to the grid connection point as clustering indicators. It then uses the K-means algorithm combined with the elbow method to perform secondary clustering on the photovoltaic nodes in each photovoltaic region to obtain several photovoltaic sub-clusters. The equivalent module, based on the principle of capacity weighting and constant voltage difference, performs power equivalence, controller parameter equivalence, line parameter equivalence, and load equivalence on each photovoltaic sub-cluster to obtain the equivalent unit representing each photovoltaic sub-cluster, thus forming a distributed photovoltaic aggregation equivalent model.

Images