Maximum accessible capacity determination method and device, equipment, medium and program product

Abstract

The invention relates to a maximum accessible capacity determination method and device, equipment, a medium and a program product. The method comprises the steps of determining electrical distances of to-be-selected nodes according to impedance and lengths of lines corresponding to the to-be-selected nodes for the to-be-selected nodes in the power distribution network, then determining target nodes from the to-be-selected nodes according to the electrical distances of the to-be-selected nodes and preset conditions, and sending the target nodes to the power distribution network. And finally, based on the second-order cone programming model, the current amplitude of the line corresponding to the target node and the first voltage of the target node, determining the maximum accessible capacity of the target node. According to the embodiment of the invention, the to-be-selected nodes are screened based on the electrical distance, so that the calculation amount and the calculation complexity are reduced, and the calculation efficiency of the maximum accessible capacity can be improved. Moreover, the maximum accessible capacity of the target node is calculated based on the second-order cone programming model, so that the accuracy of calculating the maximum accessible capacity is improved.

Description

Technical Field

[0001] The present application relates to the technical field of critical capacity calculation, and particularly to a method, device, equipment, medium, and program product for determining the maximum accessible capacity. Background Art

[0002] Distributed power sources such as photovoltaic and wind power, as an efficient and environmentally friendly energy form, are gradually becoming an important part of the distribution network. However, with the large-scale access of distributed power sources to the distribution network, it also brings a series of challenges to the operation of the distribution network. For example, the volatility of photovoltaic power generation may cause severe local voltage changes, even leading to voltage over-limit. The access of a large number of distributed power sources may also cause the line current to exceed the safety limit, resulting in risks of equipment overload or short circuit, thus directly affecting the reliability of the power grid and the power quality of users. Therefore, how to evaluate the maximum accessible capacity of distributed power sources that the power grid can withstand has become a key issue in power planning.

[0003] However, there is currently a lack of a method that can quickly and accurately evaluate the maximum accessible capacity of distributed power sources that the power grid can withstand. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, equipment, medium, and program product for determining the maximum accessible capacity that can improve the accuracy and efficiency of determining the maximum accessible capacity.

[0005] In a first aspect, the present application provides a method for determining the maximum accessible capacity. The method includes:

[0006] For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node;

[0007] Determine a target node from each of the candidate nodes according to the electrical distance of each candidate node and a preset condition;

[0008] Based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

[0009] In one embodiment, the step of determining a target node from each of the candidate nodes according to the electrical distance of each candidate node and a preset condition includes:

[0010] Determine the nodes that meet the first preset condition among each of the candidate nodes as the first intermediate nodes; the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance;

[0011] Determine the nodes in each of the first intermediate nodes that meet the second preset condition as the second intermediate nodes; the second preset condition includes: the voltage deviation of the first intermediate node is not greater than a preset voltage threshold;

[0012] Determine the nodes in each of the second intermediate nodes that meet the third preset condition as the target nodes; the third preset condition includes: the short - circuit current of the second intermediate node is not greater than a preset current threshold.

[0013] In one embodiment, the method further includes:

[0014] Construct the objective function of the second - order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source at the target node, the reference voltage of the target node, and the first voltage;

[0015] Based on the objective function and the constraint conditions, determine the second - order cone programming model; the constraint conditions include power flow balance constraint conditions, second - order cone voltage drop constraint conditions, and operation safety constraint conditions;

[0016] Among them, the power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive injection power of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence;

[0017] The second - order cone voltage drop constraint condition is determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node;

[0018] The operation safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, the reactive injection power of the distributed power source is equal to the product of the active injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine of the power factor angle of the target node.

[0019] In one embodiment, the determining the maximum accessible capacity of the target node based on the second - order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node includes:

[0020] Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model. With the goal of minimizing the value of the objective function, under the constraints of the constraint conditions, solve the active injection power of the distributed power source at the target node to obtain the maximum accessible capacity of the target node.

[0021] In one embodiment, determining the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node includes:

[0022] For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line;

[0023] Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each section of the intermediate line and the lengths of each section of the intermediate line.

[0024] In one embodiment, the method further includes:

[0025] Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

[0026] In a second aspect, the present application also provides a maximum accessible capacity determination device. The device includes:

[0027] A first determination module, configured to determine the electrical distance of each candidate node in the distribution network according to the impedance and length of the line corresponding to the candidate node;

[0028] A second determination module, configured to determine a target node from each candidate node according to the electrical distance of each candidate node and a preset condition;

[0029] A third determination module, configured to determine the maximum accessible capacity of the target node based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node.

[0030] In a third aspect, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of any of the above methods are implemented.

[0031] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0032] In a fifth aspect, the present application further provides a computer program product, including a computer program which, when executed by a processor, implements the steps of any of the above methods.

[0033] In the above method, apparatus, device, medium, and program product for determining the maximum accessible capacity, for each candidate node in the distribution network, the electrical distance of the candidate node is determined according to the impedance and length of the line corresponding to the candidate node, and then, according to the electrical distances of the candidate nodes and preset conditions, target nodes are determined from the candidate nodes. Finally, based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, the maximum accessible capacity of the target node is determined. In the embodiments of the present application, since the candidate nodes are first screened based on the electrical distance, the amount of calculation and the complexity of the calculation are reduced, so the calculation efficiency of the maximum accessible capacity can be improved. Moreover, in the embodiments of the present application, the maximum accessible capacity of the target node is calculated based on the second-order cone programming model, which improves the accuracy of calculating the maximum accessible capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is an internal structure diagram of a computer device provided by an embodiment of the present application;

[0035] Figure 2 is a flowchart of a method for determining the maximum accessible capacity provided by an embodiment of the present application;

[0036] Figure 3 is a flowchart of a method for determining a target node provided by an embodiment of the present application;

[0037] Figure 4 is a flowchart of a method for determining a second-order cone programming model provided by an embodiment of the present application;

[0038] Figure 5 is a flowchart of a method for determining the electrical distance provided by an embodiment of the present application;

[0039] Figure 6 is a flowchart of a method for evaluating the critical access capacity of distributed power sources in a distribution network provided by an embodiment of the present application;

[0040] Figure 7 is a structural block diagram of a device for determining the maximum accessible capacity provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] In order to make the objectives, technical solutions, and advantages of the present application more clearly understood, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] As an efficient and environmentally friendly form of energy, distributed power sources such as photovoltaic and wind power are gradually becoming an important part of the distribution network. However, with the large-scale access of distributed power sources to the distribution network, it also brings a series of challenges to the operation of the distribution network. For example, the volatility of photovoltaic power generation may cause drastic changes in local voltage, even leading to voltage over-limit. The access of a large number of distributed power sources may also cause the line current to exceed the safety limit, resulting in the risk of equipment overload or short circuit, thus directly affecting the reliability of the power grid and the power quality of users. Therefore, how to evaluate the maximum accessible capacity of distributed power sources that the power grid can withstand has become a key issue in power planning.

[0043] Currently, the evaluation of the maximum accessible capacity of the distribution network is either accurately calculated by the "trial and error method" that simulates the operation state of the power grid, or the calculation is accelerated by improving the method through simplifying the power grid model. The complexity of the accurate calculation method increases exponentially with the number of nodes. For a distribution network with multiple nodes, it takes up to several hours, which cannot meet the requirements of real-time planning and rapid response. The simplified calculation method will lead to a large error in the results. Therefore, there is a lack of a method that is both fast and accurate to evaluate the maximum accessible capacity of distributed power sources that the power grid can withstand.

[0044] The maximum accessible capacity determination method provided by the embodiments of this application can be applied to Figure 1 the application environment as shown. Figure 1 It is the internal structure diagram of a computer device provided by the embodiments of this application. This computer device can be a server, and its internal structure diagram can be as Figure 1 shown. This computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of this computer device is used to provide computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of this computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it realizes a maximum accessible capacity determination method.

[0045] Those skilled in the art can understand that Figure 1 the structure shown in

[0046] is only the block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0046] In one embodiment, as Figure 2 shown, Figure 2It is a schematic flowchart of a method for determining the maximum accessible capacity provided by an embodiment of the present application. This method can be applied to Figure 1 a computer device, and the method includes the following steps:

[0047] S201. For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node.

[0048] In one embodiment, the topological structure of the distribution network can be obtained, and several candidate nodes can be determined according to the topological structure of the distribution network. Then, for each candidate node, determine the equivalent impedance (i.e., electrical distance) from the candidate node to the bus.

[0049] Exemplarily, in the path from the candidate node to the bus, there may be multiple segments of lines. Therefore, the electrical distances of each segment of the line can be calculated separately, and then the electrical distances of each segment of the line can be summed to obtain the electrical distance of the candidate node.

[0050] Exemplarily, the impedance of the line corresponding to the candidate node may include, for example, the resistance per unit length and reactance of each segment of the line in the path from the candidate node to the bus, and the length of the line corresponding to the candidate node may include, for example, the lengths of each segment of the line in the path from the candidate node to the bus.

[0051] S202. Determine the target node from each candidate node according to the electrical distance of each candidate node and the preset condition.

[0052] In the embodiment of the present application, the preset condition can be set according to actual needs, and then each candidate node can be screened based on the preset condition and the electrical distance. The candidate nodes whose electrical distances do not meet the preset condition are excluded, and the candidate nodes whose electrical distances meet the preset condition are determined as the target nodes.

[0053] Optionally, the preset condition may include, for example, at least one of the electrical distance not being greater than the upper limit of the preset electrical distance, the voltage deviation not being greater than the preset voltage threshold, and the short-circuit current not being greater than the preset current threshold.

[0054] In a possible implementation, the candidate nodes can be screened based on the electrical distances of the candidate nodes, and the candidate nodes with electrical distances greater than the upper limit of the preset electrical distance are excluded from the candidate nodes, and the candidate nodes with electrical distances not greater than the upper limit of the preset electrical distance are determined as the first intermediate nodes. Then, a second-round screening is performed based on the voltage deviation of each first intermediate node, the first intermediate nodes with voltage deviations greater than the preset voltage threshold are excluded from the first intermediate nodes, and the first intermediate nodes with voltage deviations not greater than the preset voltage threshold are determined as the second intermediate nodes. Finally, a final-round screening is performed based on the short-circuit current of each second intermediate node, the second intermediate nodes with short-circuit currents greater than the preset current threshold are excluded from the second intermediate nodes, and the second intermediate nodes with short-circuit currents not greater than the preset current threshold are determined as the target nodes.

[0055] S203. Based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

[0056] In one embodiment, an objective function of the second-order cone programming model can be constructed based on the correlation between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source at the target node, the reference voltage of the target node, and the first voltage. And the constraint conditions of the second-order cone programming model are preset based on the objective function of the second-order cone programming model.

[0057] Optionally, the objective function of the second-order cone programming model can be solved under the constraints of the constraint conditions based on the current amplitude of the line corresponding to the target node, the reference voltage of the target node, and the first voltage, so as to obtain the maximum accessible capacity of the target node.

[0058] Exemplarily, the current amplitude of the line corresponding to the target node and the first voltage of the target node can be substituted into the objective function of the second-order cone programming model, and with the goal of minimizing the value of the objective function, the objective function of the second-order cone programming model is solved under the constraints of the constraint conditions to obtain the maximum active injection power of the distributed power source at the target node, and the maximum active injection power of the distributed power source at the target node is the maximum accessible capacity of the above-mentioned target node.

[0059] In the embodiments of the present application, for each candidate node in the distribution network, the electrical distance of the candidate node is determined according to the impedance and length of the line corresponding to the candidate node. Then, according to the electrical distances and preset conditions of the candidate nodes, the target node is determined from the candidate nodes. Finally, based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, the maximum accessible capacity of the target node is determined. Since in the embodiments of the present application, the candidate nodes are screened based on the electrical distance first, the amount of calculation and the complexity of the calculation are reduced, so the calculation efficiency of the maximum accessible capacity can be improved. Moreover, in the embodiments of the present application, the maximum accessible capacity of the target node is calculated based on the second-order cone programming model, which improves the accuracy of calculating the maximum accessible capacity.

[0060] Referring to Figure 3 , Figure 3 FIG. is a schematic flowchart of a method for determining a target node provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to determine the target node from each candidate node according to the electrical distance and preset conditions of each candidate node. On the basis of the above embodiment, S202 described above includes the following steps:

[0061] S301, determine the nodes that meet the first preset condition among the candidate nodes as the first intermediate nodes.

[0062] Among them, the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance.

[0063] In one embodiment, the candidate nodes can be screened based on the electrical distances of the candidate nodes, the candidate nodes with electrical distances greater than the upper limit of the preset electrical distance among the candidate nodes are excluded, and the candidate nodes with electrical distances not greater than the upper limit of the preset electrical distance among the candidate nodes are determined as the first intermediate nodes.

[0064] Exemplarily, the electrical distance of candidate node i can be compared with the upper limit of the preset electrical distance . If , then candidate node i is directly excluded; otherwise, candidate node i is determined as the first intermediate node.

[0065] Optionally, if it is a rural distribution network, the upper limit of the preset electrical distance can be set to 5.0 Ω; if it is an urban distribution network, the upper limit of the preset electrical distance can be set to 3.0 Ω.

[0066] S302, determine the nodes that meet the second preset condition among the first intermediate nodes as the second intermediate nodes.

[0067] Among them, the second preset condition includes: the voltage deviation of the first intermediate node is not greater than the preset voltage threshold.

[0068] In one embodiment, a second round of screening can be performed based on the voltage deviation of each first intermediate node, and the first intermediate nodes with voltage deviation greater than the preset voltage threshold among the first intermediate nodes are excluded, and the first intermediate nodes with voltage deviation not greater than the preset voltage threshold among the first intermediate nodes are determined as the second intermediate nodes.

[0069] Exemplarily, the voltage deviation can be calculated based on the following formula (1) :

[0070] (1)

[0071] In formula (1), is the active power output of the distributed power source, is the reactive power output of the distributed power source, with the unit of MVar, , are the real and imaginary parts of the electrical distance in sequence, is the rated voltage.

[0072] In a possible implementation manner, the preset voltage threshold can be set to 7%. If the voltage deviation of the first intermediate node , then this first intermediate node is directly excluded; otherwise, this first intermediate node is determined as the second intermediate node.

[0073] S303. Determine the nodes that meet the third preset condition among the second intermediate nodes as the target nodes.

[0074] Among them, the third preset condition includes: the short-circuit current of the second intermediate node is not greater than the preset current threshold.

[0075] In one embodiment, a final round of screening can be performed based on the short-circuit current of each second intermediate node, and the second intermediate nodes with short-circuit current greater than the preset current threshold among the second intermediate nodes are excluded, and the second intermediate nodes with short-circuit current not greater than the preset current threshold among the second intermediate nodes are determined as the target nodes.

[0076] Optionally, the short-circuit current of the second intermediate node can be determined based on the following formula (2):

[0077] (2)

[0078] In formula (2), is the equivalent impedance modulus value, with the unit of Ω.

[0079] Exemplarily, the preset current threshold can be determined according to the circuit breaker breaking capacity , for example, the preset current threshold can be set to . If the short-circuit current of the second intermediate node , the second intermediate node is directly eliminated; otherwise, the second intermediate node is determined as the target node.

[0080] In the embodiments of the present application, nodes with an electrical distance not greater than a preset upper limit of the electrical distance among the candidate nodes are determined as the first intermediate nodes, nodes with a voltage deviation not greater than a preset voltage threshold among the first intermediate nodes are determined as the second intermediate nodes, and finally nodes with a short-circuit current not greater than a preset current threshold among the second intermediate nodes are determined as the target nodes, so as to realize the screening of the candidate nodes, reduce the calculation amount and the calculation complexity, and improve the efficiency of calculating the maximum accessible capacity of the target node in the subsequent calculation. Moreover, the implementation threshold is reduced. Since the calculation amount and the calculation complexity are relatively low, large-scale distribution network analysis can be completed on hardware with relatively low performance resources without relying on a high-performance computing cluster, thereby reducing the hardware cost.

[0081] Referring to Figure 4 , Figure 4 is a schematic flowchart of a method for determining a second-order cone programming model provided by the embodiments of the present application. On the basis of the above embodiments, the method further includes the following steps:

[0082] S401, construct the objective function of the second-order cone programming model.

[0083] Among them, the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source of the target node, the reference voltage of the target node, and the first voltage.

[0084] Exemplarily, the objective function of the second-order cone programming model can be expressed as the following formula (3):

[0085] (3)

[0086] In formula (3), , , are preset weight coefficients, is the per-unit value of the current amplitude of the line between the target node i and the node j, is the per-unit value of the voltage of the target node i, is the reference voltage, usually 1.0 p.u., is the active injection power of the distributed power source of the target node i. Among them, the line between the target node i and the node j is the line corresponding to the above target node.

[0087] Exemplarily, if it is a rural distribution network, then , , ; if it is an urban distribution network, then , , .

[0088] S402. Determine the second-order cone programming model based on the objective function and constraint conditions.

[0089] Among them, the constraint conditions include power flow balance constraint conditions, second-order cone voltage drop constraint conditions, and operation safety constraint conditions.

[0090] The power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active power injection of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive power injection of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence.

[0091] Exemplarily, the power flow balance constraint conditions can be expressed as the following formula (4):

[0092] (4)

[0093] In formula (4), , are the first active power and the first reactive power flowing from node j to target node i, , are the second active power and the second reactive power flowing from target node i to node k, , are the third active power and the third reactive power of load i, , are the active power injection and reactive power injection of the distributed power source at target node i.

[0094] Optionally, the active power injection and reactive power injection of the distributed power source can be determined based on the predicted output curve of the distributed power source.

[0095] The second-order cone voltage drop constraint conditions are determined based on the relationship between the first voltage, current amplitude, second voltage of the upstream node of the target node, and impedance of the line corresponding to the target node.

[0096] Exemplarily, the second-order cone voltage drop constraint conditions can be expressed as the following formula (5):

[0097] (5)

[0098] In formula (5), is the per-unit value of the voltage of node j, , is the resistance and reactance of the line between the target node i and node j, , are the active power and reactive power flowing from the target node i to node j.

[0099] The operating safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, the reactive power injection power of the distributed power source is equal to the product of the active power injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine value of the power factor angle of the target node.

[0100] Exemplarily, the operating safety constraint conditions can be expressed by the following formula (6):

[0101] (6)

[0102] In formula (6), and are the preset voltage upper and lower limits. Usually, , , is the maximum current-carrying capacity of the line between the target node i and node j, is the power factor angle of the target node i.

[0103] In the embodiments of the present application, an objective function of a second-order cone programming model for characterizing the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active power injection power of the distributed power source of the target node, the reference voltage of the target node, and the first voltage is constructed. Based on the objective function, the power flow balance constraint conditions, the second-order cone voltage drop constraint conditions, and the operating safety constraint conditions, the second-order cone programming model is determined. Among them, the power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active power injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive power injection power of the distributed power source. The second-order cone voltage drop constraint conditions are determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node. The operating safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, the reactive power injection power of the distributed power source is equal to the product of the active power injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine value of the power factor angle of the target node. Thus, the accuracy of calculating the maximum accessible capacity of the target node in the subsequent calculation is improved based on the second-order cone programming model.

[0104] Based on the above embodiments, the above S203 includes the following steps:

[0105] Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model. With the goal of minimizing the value of the objective function, solve for the active power injection of the distributed power source at the target node under the constraints of the constraint conditions, so as to obtain the maximum accessible capacity of the target node.

[0106] In one embodiment, the current amplitude of the line corresponding to the target node and the first voltage of the target node can be substituted into the above formula (3), and then under the constraints of formulas (4)-(6), solve for the active power injection of the distributed power source at the target node and then the obtained active power injection is determined as the maximum accessible capacity of the target node.

[0107] In the embodiment of the present application, the current amplitude of the line corresponding to the target node and the first voltage of the target node are substituted into the objective function of the second-order cone programming model. With the goal of minimizing the value of the objective function, solve for the active power injection of the distributed power source at the target node under the constraints of the constraint conditions, so as to obtain the maximum accessible capacity of the target node, thereby improving the accuracy of subsequent calculation of the maximum accessible capacity of the target node based on the second-order cone programming model.

[0108] Refer to Figure 5 Figure 5 is a schematic flowchart of a method for determining electrical distance provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to determine the electrical distance of a candidate node according to the impedance and length of the line corresponding to the candidate node. On the basis of the above embodiment, the above S201 includes the following steps:

[0109] S501. For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line.

[0110] Exemplarily, for each intermediate line in the path from the candidate node to the bus, the intermediate electrical distance corresponding to the kth intermediate line can be determined according to the resistance per unit length and reactance of the kth intermediate line, so as to determine the intermediate electrical distance corresponding to the kth intermediate line

[0111] S502. Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line.

[0112] Exemplarily, the electrical distance of candidate node i can be determined based on the following formula (7):

[0113] (7)

[0114] In formula (7), is the equivalent impedance from the candidate node i to the bus, with the unit of Ω; is the length of the k-th intermediate line; n is the total number of intermediate lines in the path from the candidate node i to the bus.

[0115] In the embodiment of the present application, for each intermediate line in the path from the candidate node to the bus, according to the impedance per unit length of the intermediate line, the corresponding intermediate electrical distance of the intermediate line is determined. According to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line, the electrical distance of the candidate node is determined, so that the candidate node can be screened based on the electrical distance, thereby reducing the calculation amount of calculating the maximum accessible capacity in the subsequent calculation and improving the calculation efficiency.

[0116] Based on the above embodiment, the method further includes the following steps:

[0117] According to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load, the bearing capacity level corresponding to the target node is determined.

[0118] In one embodiment, the bearing capacity level division standard can be formulated based on the load and the preset proportional coefficient of the load. For example, the preset proportional coefficients of the load can be set to 80% and 50%. Then, the bearing capacity level of the target node with the maximum accessible capacity greater than can be determined as the first level, and the bearing capacity level of the target node with the maximum accessible capacity between and can be determined as the second level, and the bearing capacity level of the target node with the maximum accessible capacity less than can be determined as the third level. Among them, the target node at the first level has a greater maximum accessible capacity. Therefore, when accessing distributed power sources, the safety of the target node at the first level is better. While the target node at the third level has a smaller maximum accessible capacity. Therefore, when accessing distributed power sources, careful selection should be made to prevent problems such as voltage over-limit.

[0119] Exemplarily, if , then the bearing capacity level of the target node i is the first level; if , then the bearing capacity level of the target node i is the second level; if , then the bearing capacity level of the target node i is the third level.

[0120] In one embodiment, the bearing capacity level of the target node can be output through signals of different colors to more intuitively remind relevant personnel of the bearing capacity level of the target node, further improving the safety of distributed power source access. For example, the first level can output a green signal, the second level can output a yellow signal, and the third level can output a red signal.

[0121] In the embodiments of the present application, according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load, the bearing capacity level corresponding to the target node is determined, so that the size of the maximum accessible capacity of the target node can be more intuitively reflected by different bearing capacity levels, with higher convenience, and further the safety of distributed power access can be improved.

[0122] Referring to Figure 6 , Figure 6 is a schematic flow chart of a method for evaluating the critical access capacity of distributed power sources in a distribution network provided by an embodiment of the present application. The method includes the following steps:

[0123] S601. For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node.

[0124] S602. Determine the target node from each candidate node according to the electrical distance of each candidate node and the preset conditions.

[0125] S603. Construct a second-order cone programming model.

[0126] S604. Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model, and with the aim of minimizing the value of the objective function, solve the active injection power of the distributed power source of the target node under the constraints of the constraint conditions to obtain the maximum accessible capacity of the target node.

[0127] S605. Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

[0128] It should be understood that although the steps in the flow charts involved in the above-described embodiments are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flow charts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these steps or stages does not necessarily have to be sequential, but can be executed alternately or alternately with at least a part of other steps or steps in other steps.

[0129] Based on the same inventive concept, an embodiment of the present application further provides a maximum accessible capacity determination device for implementing the maximum accessible capacity determination method involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the maximum accessible capacity determination device provided below can refer to the limitations on the maximum accessible capacity determination method in the foregoing, and will not be elaborated herein.

[0130] In one embodiment, as Figure 7 shown, Figure 7 is a structural block diagram of a maximum accessible capacity determination device provided by an embodiment of the present application. The device 700 includes:

[0131] A first determination module 701, configured to determine the electrical distance of each candidate node in the distribution network according to the impedance and length of the line corresponding to the candidate node.

[0132] A second determination module 702, configured to determine a target node from each candidate node according to the electrical distance of each candidate node and a preset condition.

[0133] A third determination module 703, configured to determine the maximum accessible capacity of the target node based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node.

[0134] In one of the embodiments, the second determination module 702 includes:

[0135] A first determination unit, configured to determine a first intermediate node from the candidate nodes that meet a first preset condition; the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance.

[0136] A second determination unit, configured to determine a second intermediate node from the first intermediate nodes that meet a second preset condition; the second preset condition includes: the voltage deviation of the first intermediate node is not greater than the preset voltage threshold.

[0137] A third determination unit, configured to determine a target node from the second intermediate nodes that meet a third preset condition; the third preset condition includes: the short-circuit current of the second intermediate node is not greater than the preset current threshold.

[0138] In one of the embodiments, the device 700 further includes:

[0139] A construction module, configured to construct an objective function of the second-order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source of the target node, the reference voltage of the target node, and the first voltage.

[0140] A fourth determination module, configured to determine a second-order cone programming model based on an objective function and constraint conditions; the constraint conditions include a power flow balance constraint condition, a second-order cone voltage drop constraint condition, and an operation safety constraint condition.

[0141] Among them, the power flow balance constraint condition includes that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active power injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive power injection power of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence.

[0142] The second-order cone voltage drop constraint condition is determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node.

[0143] The operation safety constraint condition includes that the first voltage is between the preset upper and lower voltage limits, the current amplitude is less than the preset current amplitude upper limit, and the reactive power injection power of the distributed power source is equal to the product of the active power injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine value of the power factor angle of the target node.

[0144] In one embodiment, the third determination module 703 includes:

[0145] A solving unit, configured to substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model, and taking the minimum value of the objective function as the goal, solve the active power injection power of the distributed power source of the target node under the constraints of the constraint conditions to obtain the maximum accessible capacity of the target node.

[0146] In one embodiment, the first determination module 701 includes:

[0147] A fourth determination unit, configured to determine the intermediate electrical distance corresponding to each intermediate line in the path from the candidate node to the bus according to the impedance per unit length of the intermediate line.

[0148] A fifth determination unit, configured to determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line.

[0149] In one embodiment, the apparatus 700 further includes:

[0150] A fifth determination module, configured to determine a bearing capacity level corresponding to a target node according to a load, a maximum accessible capacity of the target node, and a preset proportionality coefficient of the load.

[0151] Each module in the above maximum accessible capacity determination device can be implemented in whole or in part by software, hardware, and a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0152] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0153] For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node.

[0154] Determine a target node from each candidate node according to the electrical distance of each candidate node and a preset condition.

[0155] Based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

[0156] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0157] Determine the nodes that meet the first preset condition among each candidate node as the first intermediate nodes; the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance.

[0158] Determine the nodes that meet the second preset condition among each first intermediate node as the second intermediate nodes; the second preset condition includes: the voltage deviation of the first intermediate node is not greater than the preset voltage threshold.

[0159] Determine the nodes that meet the third preset condition among each second intermediate node as the target nodes; the third preset condition includes: the short-circuit current of the second intermediate node is not greater than the preset current threshold.

[0160] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0161] Construct an objective function of the second-order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source of the target node, the reference voltage of the target node, and the first voltage.

[0162] Based on the objective function and constraint conditions, a second-order cone programming model is determined; the constraint conditions include power flow balance constraint conditions, second-order cone voltage drop constraint conditions, and operation safety constraint conditions;

[0163] Among them, the power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active power injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive power injection power of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence;

[0164] The second-order cone voltage drop constraint conditions are determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node;

[0165] The operation safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, and the reactive power injection power of the distributed power source is equal to the product of the active power injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine value of the power factor angle of the target node.

[0166] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0167] Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model, and with the goal of minimizing the value of the objective function, solve the active power injection power of the distributed power source of the target node under the constraints of the constraint conditions to obtain the maximum accessible capacity of the target node.

[0168] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0169] For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line;

[0170] Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line.

[0171] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0172] Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

[0173] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0174] For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node;

[0175] Determine the target node from each candidate node according to the electrical distance of each candidate node and the preset conditions;

[0176] Based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

[0177] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0178] Determine the nodes that meet the first preset condition among each candidate node as the first intermediate nodes; the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance;

[0179] Determine the nodes that meet the second preset condition among each first intermediate node as the second intermediate nodes; the second preset condition includes: the voltage deviation of the first intermediate node is not greater than the preset voltage threshold;

[0180] Determine the nodes that meet the third preset condition among each second intermediate node as the target nodes; the third preset condition includes: the short-circuit current of the second intermediate node is not greater than the preset current threshold.

[0181] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

[0182] Construct the objective function of the second-order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source of the target node, the reference voltage of the target node, and the first voltage;

[0183] Based on the objective function and the constraint conditions, determine the second-order cone programming model; the constraint conditions include power flow balance constraint conditions, second-order cone voltage drop constraint conditions, and operation safety constraint conditions;

[0184] Among them, the power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active power injection of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive power injection of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence;

[0185] The second-order cone voltage drop constraint condition is determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node;

[0186] The operation safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, and the reactive power injection of the distributed power source is equal to the product of the active power injection of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine of the power factor angle of the target node.

[0187] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0188] Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model, and with the minimum value of the objective function as the goal, solve the active power injection of the distributed power source of the target node under the constraints of the constraint conditions to obtain the maximum accessible capacity of the target node.

[0189] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0190] For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line;

[0191] Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line.

[0192] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0193] Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

[0194] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by the processor, the following steps are implemented:

[0195] For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node;

[0196] Determine the target node from each candidate node according to the electrical distance of each candidate node and the preset conditions;

[0197] Based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

[0198] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0199] Determine the nodes that meet the first preset condition among each candidate node as the first intermediate nodes; the first preset condition includes: the electrical distance of the candidate node is not greater than the upper limit of the preset electrical distance;

[0200] Determine the nodes that meet the second preset condition among each first intermediate node as the second intermediate nodes; the second preset condition includes: the voltage deviation of the first intermediate node is not greater than the preset voltage threshold;

[0201] Determine the nodes that meet the third preset condition among each second intermediate node as the target nodes; the third preset condition includes: the short-circuit current of the second intermediate node is not greater than the preset current threshold.

[0202] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0203] Construct the objective function of the second-order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source at the target node, the reference voltage of the target node, and the first voltage;

[0204] Based on the objective function and the constraint conditions, determine the second-order cone programming model; the constraint conditions include the power flow balance constraint conditions, the second-order cone voltage drop constraint conditions, and the operation safety constraint conditions;

[0205] Among them, the power flow balance constraint conditions include that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive injection power of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence;

[0206] The second-order cone voltage drop constraint condition is determined based on the relationship among the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node;

[0207] The operating safety constraint conditions include that the first voltage is between the preset voltage upper and lower limits, the current amplitude is less than the preset current amplitude upper limit, the reactive injection power of the distributed power source is equal to the product of the active injection power of the distributed power source and the target parameter, and the target parameter is equal to the tangent value of the arccosine value of the power factor angle of the target node.

[0208] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0209] Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model. With the aim of minimizing the value of the objective function, under the constraints of the constraint conditions, solve the active injection power of the distributed power source of the target node to obtain the maximum accessible capacity of the target node.

[0210] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0211] For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line;

[0212] Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each intermediate line and the lengths of each intermediate line.

[0213] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0214] Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

[0215] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0216] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0217] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for determining the maximum accessible capacity, characterized in that, The method includes: For each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node; Determine the target node from each of the candidate nodes according to the electrical distances of the candidate nodes and a preset condition; Based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node, determine the maximum accessible capacity of the target node.

2. The method according to claim 1, characterized in that, The determining the target node from each of the candidate nodes according to the electrical distances of the candidate nodes and a preset condition includes: Determine the first intermediate nodes as the nodes among the candidate nodes that satisfy a first preset condition; the first preset condition includes that the electrical distance of the candidate node is not greater than a preset upper limit of the electrical distance; Determine the second intermediate nodes as the nodes among the first intermediate nodes that satisfy a second preset condition; the second preset condition includes that the voltage deviation of the first intermediate node is not greater than a preset voltage threshold; Determine the target node as the nodes among the second intermediate nodes that satisfy a third preset condition; the third preset condition includes that the short-circuit current of the second intermediate node is not greater than a preset current threshold.

3. The method according to claim 1, characterized in that, The method further includes: Construct an objective function of the second-order cone programming model; the objective function is used to characterize the relationship between the current amplitude of the line corresponding to the target node in the distribution network, the active injection power of the distributed power source at the target node, the reference voltage of the target node, and the first voltage; Determine the second-order cone programming model based on the objective function and constraint conditions; the constraint conditions include a power flow balance constraint condition, a second-order cone voltage drop constraint condition, and an operation safety constraint condition; Among them, the power flow balance constraint condition includes that the difference between the first active power and the second active power is equal to the difference between the third active power of the load and the active injection power of the distributed power source, and the difference between the first reactive power and the second reactive power is equal to the difference between the third reactive power of the load and the reactive injection power of the distributed power source; the first active power and the first reactive power are the active power and reactive power flowing from the upstream node of the target node to the target node in sequence, and the second active power and the second reactive power are the active power and reactive power flowing from the target node to the downstream node of the target node in sequence; The second-order cone voltage drop constraint condition is determined based on the relationship between the first voltage, the current amplitude, the second voltage of the upstream node of the target node, and the impedance of the line corresponding to the target node; The operation safety constraint condition includes that the first voltage is between a preset upper and lower voltage limit, the current amplitude is less than a preset upper limit of the current amplitude, the reactive injection power of the distributed power source is equal to the product of the active injection power of the distributed power source and a target parameter, and the target parameter is equal to the tangent value of the arccosine of the power factor angle of the target node.

4. The method according to claim 3, wherein The determining the maximum accessible capacity of the target node based on the second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node includes: Substitute the current amplitude of the line corresponding to the target node and the first voltage of the target node into the objective function of the second-order cone programming model. With the goal of minimizing the value of the objective function, solve the active injection power of the distributed power source at the target node under the constraints of the constraint conditions to obtain the maximum accessible capacity of the target node.

5. The method according to any one of claims 1-4, characterized in that, The determining the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node includes: For each intermediate line in the path from the candidate node to the bus, determine the intermediate electrical distance corresponding to the intermediate line according to the impedance per unit length of the intermediate line; Determine the electrical distance of the candidate node according to the summation result of the intermediate electrical distances corresponding to each section of the intermediate line and the lengths of each section of the intermediate line.

6. The method according to claim 3, characterized in that, The method further includes: Determine the bearing capacity level corresponding to the target node according to the load, the maximum accessible capacity of the target node, and the preset proportional coefficient of the load.

7. A maximum accessible capacity determination device, characterized in that The device includes: A first determination module, configured to, for each candidate node in the distribution network, determine the electrical distance of the candidate node according to the impedance and length of the line corresponding to the candidate node; A second determination module, configured to determine a target node from each of the candidate nodes according to the electrical distances of each of the candidate nodes and a preset condition; A third determination module, configured to determine the maximum accessible capacity of the target node based on a second-order cone programming model, the current amplitude of the line corresponding to the target node, and the first voltage of the target node.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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