Photovoltaic installed capacity bearing determination method, device and equipment and readable storage medium

Abstract

The invention relates to a photovoltaic installed capacity bearing determination method, device and equipment and a readable storage medium. The method comprises the following steps: obtaining a plurality of topology networks corresponding to a target power grid and operation parameters, determining a constraint condition corresponding to each topology network according to each operation parameter for each topology network, and determining a photovoltaic installed capacity bearing range corresponding to the topology network according to the constraint condition, power grid branches formed by power grid nodes in different topological networks are different, the constraint conditions comprise a first constraint condition and a second constraint condition, and the first constraint condition is a constraint condition of the capacity of each power grid branch in the topological network on the photovoltaic installed capacity; the second constraint condition is the constraint condition of the voltage parameter of each power grid node in the topology network on the photovoltaic installed capacity. By adopting the method, the bearing range of the photovoltaic installed capacity of the target power grid under each topological network can be more efficiently determined.

Description

Technical Field

[0001] The present application relates to the field of power grid technology, and in particular to a method, device, equipment and readable storage medium for determining photovoltaic installed capacity. Background Art

[0002] Photovoltaic power generation, as a clean energy source, is widely used in power grids to supply electricity. Increasing the number of distributed photovoltaic devices connected to the grid can effectively increase the proportion of clean energy in the grid. However, when the number of devices involved is too large, it will also cause safety problems such as thermal overload or voltage crossing to the grid. In order to better determine the access strategy for photovoltaic devices to the grid, it is necessary to calculate the grid's carrying capacity for photovoltaic devices.

[0003] In related technologies, point-by-point simulation is usually performed. For example, the photovoltaic access strategy of the adjacent load-bearing range is first found based on the simulation technology, and the photovoltaic access strategies of other adjacent load-bearing ranges are determined point by point based on the photovoltaic access strategy, thereby determining the carrying range of the power grid's carrying capacity for the photovoltaic equipment.

[0004] However, the above method has the problem of low determination efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a photovoltaic installed capacity load determination method, device, equipment and readable storage medium that can improve the efficiency of photovoltaic installed capacity load determination in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for determining photovoltaic installed capacity load, comprising:

[0007] Acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes;

[0008] For each topological network, the constraint conditions corresponding to the topological network are determined according to the operating parameters. The constraint conditions include a first constraint condition and a second constraint condition. The first constraint condition is the constraint condition of each grid branch capacity on the photovoltaic installed capacity in the topological network. The second constraint condition is the constraint condition of each grid node voltage parameter on the photovoltaic installed capacity in the topological network.

[0009] The carrying range of the photovoltaic installed capacity corresponding to the topological network is determined according to the constraints.

[0010] In one embodiment, determining the constraint conditions corresponding to the topological network according to the operating parameters includes:

[0011] Determine a power supply path matrix corresponding to the topology network according to the topology network, wherein the elements in the power supply path matrix are used to represent closed branches in the topology network for supplying power to the grid nodes;

[0012] A matrix linear power flow model is established according to the operating parameters and the power supply path matrix, wherein the matrix linear power flow model includes a first linear relationship between the branch active power vector and the photovoltaic installed capacity, a second linear relationship between the branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between the node voltage vector and the photovoltaic installed capacity;

[0013] The constraints are determined based on the operating parameters and the matrix linear power flow model.

[0014] In one embodiment, determining the constraint condition according to the operating parameters and the matrix linear power flow model includes:

[0015] Determining a first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters;

[0016] The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0017] In one embodiment, a matrix linear power flow model is established according to the operating parameters and the power supply path matrix, including:

[0018] Determine an operation vector corresponding to the topological network according to the operation parameters, the operation vector including a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node;

[0019] Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain a first linear relationship;

[0020] Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain a second linear relationship;

[0021] Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain a third linear relationship;

[0022] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0023] In one embodiment, determining the carrying range of the photovoltaic installed capacity corresponding to the topological network according to the constraint conditions includes:

[0024] Linearly normalize the first constraint to obtain the first constraint in the target form;

[0025] Determine the branch capacity carrying range corresponding to the topology network according to the first constraint condition in the target form, and determine the node voltage carrying range corresponding to the topology network according to the second constraint condition;

[0026] The branch capacity carrying range and the node voltage carrying range are determined as the carrying range of the photovoltaic installed capacity.

[0027] In one embodiment, the method further comprises:

[0028] Obtaining a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate the node identification of the photovoltaic device connected to the target power grid and the reference photovoltaic installed capacity;

[0029] The security of the photovoltaic access strategy is determined according to the carrying range of the photovoltaic installed capacity corresponding to each topological network.

[0030] In a second aspect, the present application further provides a photovoltaic installed capacity load determination device, comprising:

[0031] An acquisition module is used to acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes;

[0032] A constraint module is used to determine the constraint conditions corresponding to each topological network according to various operating parameters for each topological network, wherein the constraint conditions include a first constraint condition and a second constraint condition, wherein the first constraint condition is the constraint condition of each power grid branch capacity on the photovoltaic installed capacity in the topological network, and the second constraint condition is the constraint condition of each power grid node voltage parameter on the photovoltaic installed capacity in the topological network;

[0033] The load range determination module is used to determine the load range of the photovoltaic installed capacity corresponding to the topological network according to the constraint conditions.

[0034] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method of the first aspect when executing the computer program.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method of the first aspect described above.

[0036] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method in the first aspect are implemented.

[0037] The above-mentioned photovoltaic installed capacity carrying determination method, device, equipment and readable storage medium obtain multiple topological networks and operating parameters corresponding to the target power grid, and then determine the constraints corresponding to the topological network according to the operating parameters for each topological network, so as to determine the carrying range of the photovoltaic installed capacity corresponding to the topological network according to the constraints, wherein different topological networks include different grid branches formed by various grid nodes, and the constraints include a first constraint and a second constraint, the first constraint is the constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint is the constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity. In this way, for different topological networks, the constraints of each grid branch capacity on the photovoltaic installed capacity corresponding to the target grid in each topological network and the constraints of each grid node voltage parameter on the photovoltaic installed capacity are directly determined according to the operating parameters, thereby determining the carrying range of the photovoltaic installed capacity, avoiding the problem of low determination efficiency caused by the need to perform simulation calculations on multiple data in point-by-point simulation. The technical solution provided in the present application can more efficiently determine the carrying range of the photovoltaic installed capacity of the target grid in each topological network. In addition, the carrying range of the photovoltaic installed capacity determined according to the constraints is continuous data, which is more accurate than the carrying range determined by point-by-point simulation in traditional technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0039] FIG1 is a diagram showing an application environment of a method for determining photovoltaic installed capacity load in one embodiment;

[0040] Figure 2 It is a schematic diagram of a flow chart of a method for determining photovoltaic installed capacity load in one embodiment;

[0041] Figure 3 is a flow chart of step 202 in another embodiment;

[0042] Figure 4 A schematic diagram of a flow chart of an exemplary method for determining photovoltaic installed capacity load in an embodiment;

[0043] Figure 5 is an exemplary topological network structure in an embodiment;

[0044] Figure 6 is an exemplary load range calculation result in one embodiment;

[0045] Figure 7 An exemplary calculation time result in an embodiment;

[0046] Figure 8 It is a structural block diagram of a photovoltaic installed capacity load determination device in one embodiment;

[0047] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with 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.

[0049] Photovoltaic power generation, as a clean energy source, is widely used in power grids to supply electricity. Increasing the number of distributed photovoltaic devices connected to the grid can effectively increase the proportion of clean energy in the grid. However, when the number of devices involved is too large, it will also cause safety problems such as thermal overload or voltage crossing the line in the operation of the grid. In order to better determine the access strategy for photovoltaic devices to the grid and avoid affecting the safe operation of the grid when photovoltaic devices are connected to the grid, it is necessary to calculate the carrying capacity of the grid for photovoltaic devices, so as to conduct a safety assessment of the access strategy based on the calculated carrying capacity.

[0050] In related technologies, when calculating the carrying capacity of a power grid for photovoltaic equipment, a point-by-point simulation is usually performed. For example, a photovoltaic access strategy adjacent to the carrying range is found based on simulation technology, and based on the photovoltaic access strategy, photovoltaic access strategies for other adjacent carrying ranges are determined point by point, thereby determining the carrying range of the power grid's carrying capacity for photovoltaic equipment.

[0051] However, the amount of data that needs to be simulated when determining the carrying capacity range of the power grid for photovoltaic equipment is extremely large. The above method has the problem of low determination efficiency. In addition, point-by-point simulation will cause some data to be missing, resulting in a low accuracy in the carrying capacity range of the photovoltaic equipment that is ultimately determined.

[0052] In view of this, the present application provides a method, device, equipment and readable storage medium for determining the carrying capacity of photovoltaic installed capacity. By obtaining multiple topological networks and operating parameters corresponding to the target power grid, the constraints corresponding to the topological network are determined for each topological network according to the operating parameters, and the carrying range of the photovoltaic installed capacity corresponding to the topological network can be determined according to the constraints. Among them, different topological networks include different grid branches formed by various grid nodes, and the constraints include a first constraint and a second constraint. The first constraint is the constraint of the capacity of each grid branch in the topological network on the photovoltaic installed capacity, and the second constraint is the constraint of the voltage parameter of each grid node in the topological network on the photovoltaic installed capacity. In this way, for different topological networks, the constraints of each grid branch capacity on the photovoltaic installed capacity corresponding to the target grid in each topological network and the constraints of each grid node voltage parameter on the photovoltaic installed capacity are directly determined according to the operating parameters, thereby determining the carrying range of the photovoltaic installed capacity, avoiding the problem of low determination efficiency caused by the need to perform simulation calculations on multiple data in point-by-point simulation. The technical solution provided in the present application can more efficiently determine the carrying range of the photovoltaic installed capacity of the target grid in each topological network. In addition, the carrying range of the photovoltaic installed capacity determined according to the constraints is continuous data, which is more accurate than the carrying range determined by point-by-point simulation in traditional technology.

[0053] The photovoltaic installed capacity load determination method provided in the embodiment of the present application can be applied to the application environment shown in FIG1. ​​Among them, the data storage system can store the data that the server 101 needs to process. The data storage system can be integrated on the server 101, or it can be placed on the cloud or other network servers. The server 101 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0054] In an exemplary embodiment, Figure 2 As shown, a method for determining photovoltaic installed capacity load is provided, which is described by taking the method applied to the server 101 in FIG. 1 as an example, and includes the following steps 201 to 203. Among them:

[0055] Step 201: Acquire multiple topological networks and operating parameters corresponding to the target power grid.

[0056] The target power grid may be a power supply grid with a corresponding carrying range of the photovoltaic installed capacity to be determined, and the server may obtain multiple topological networks and operating parameters corresponding to the target power grid.

[0057] A topological network can be the connection structure of each grid node in the target power grid. Different topological networks include different grid branches formed by each grid node, which will lead to different characteristics such as power flow distribution and voltage level of the power grid. Therefore, it is necessary to obtain multiple topological networks corresponding to the target power grid in order to determine the photovoltaic installed capacity of the target power grid from multiple angles, and the results obtained will be more accurate.

[0058] The operating parameters may be various data that describe the operating status of the target power grid. In the embodiment of the present application, the operating parameters may include the impedance parameters of each power grid branch, the disconnection status of the power grid branch, the real-time power of each power grid node, the safe operating range of the voltage parameters of each power grid node, the capacity limit of the power grid branch, the maximum reverse load rate allowed for the power grid branch, etc. under different topology networks.

[0059] Regarding the process of the server acquiring the topology network, optionally, the server can directly acquire it from a database; optionally, the server can acquire it through an external input device.

[0060] Regarding the process of the server obtaining operating parameters, optionally, the operating parameters of the target power grid will be archived in real time to the database, and the server can read the operating parameters through the database; optionally, the server can directly communicate with the monitoring device that monitors the operating parameters of the target power grid, so the server can directly obtain the operating parameters through the monitoring device.

[0061] Step 202: for each topological network, determine the constraint condition corresponding to the topological network according to each operating parameter.

[0062] The constraint conditions include a first constraint condition and a second constraint condition.

[0063] In the embodiment of the present application, the first constraint condition is the constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is the constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity.

[0064] It is understandable that when photovoltaic equipment is connected to the target power grid, its photovoltaic installed capacity changes, which will cause changes in the electric power transmitted by each grid branch. However, each grid branch has a certain capacity limitation. If the photovoltaic installed capacity is increased without restriction, the electric power transmitted by each grid branch will exceed the branch capacity limit, reducing the safety of the target power grid operation. That is, there is a relationship between the photovoltaic installed capacity carrying capacity of the target power grid and the restrictions of each grid branch capacity on the photovoltaic installed capacity. Therefore, the server needs to obtain the first constraint condition to determine the photovoltaic installed capacity carrying capacity of the target power grid.

[0065] In addition, after the photovoltaic equipment is connected to the target power grid, it will also affect the voltage of each grid node in the target power grid. If the photovoltaic installed capacity is too large, it may cause the operating voltage of some grid nodes to exceed the safe operating range, affecting the normal operation of the power grid. That is, there is a relationship between the photovoltaic installed capacity carrying capacity of the target power grid and the restrictions of the grid node voltage parameters on the photovoltaic installed capacity. Therefore, the server needs to obtain the second constraint condition to determine the photovoltaic installed capacity carrying capacity of the target power grid.

[0066] Regarding the process of the server obtaining constraint conditions, optionally, the server can input operating parameters into a pre-trained constraint determination model to obtain the constraint conditions output by the constraint determination model; optionally, the server can substitute the operating parameters into a pre-built mathematical model to determine the constraint conditions. In an embodiment of the present application, the mathematical model can be established based on a linear power flow model.

[0067] Step 203: determine the carrying range of the photovoltaic installed capacity corresponding to the topological network according to the constraint conditions.

[0068] In a possible implementation, the server may directly use the branch capacity carrying range corresponding to the first constraint condition and the node voltage carrying range corresponding to the second constraint condition as the carrying range of the photovoltaic installed capacity.

[0069] In another possible implementation, the server may set a standardized range format, and perform standardized processing on the first constraint condition and / or the second constraint condition according to the standardized range format, and use the range corresponding to the standardized first constraint condition and / or the second constraint condition as the carrying range of the photovoltaic installed capacity, wherein the standardized range format may be linear standardization,

[0070] After obtaining the carrying range of the photovoltaic installed capacity corresponding to each topological network, the server can evaluate the security of different photovoltaic access strategies. In an embodiment of the present application, the server can obtain the photovoltaic access strategy, and then determine the security of the photovoltaic access strategy based on the carrying range of the photovoltaic installed capacity corresponding to each topological network.

[0071] The photovoltaic access strategy is used to indicate the node identification of the photovoltaic equipment connected to the target power grid and the reference photovoltaic installed capacity.

[0072] In one possible implementation, for each photovoltaic access strategy, the server can substitute the node identifier and reference photovoltaic installed capacity included in the photovoltaic access strategy into the branch capacity carrying range corresponding to the first constraint condition and the node voltage carrying range corresponding to the second constraint condition to determine whether the photovoltaic access strategy belongs to the carrying range of the photovoltaic installed capacity corresponding to each topological network. If so, it means that the security of the current photovoltaic access strategy meets the requirements. In an embodiment of the present application, the server can use the number of photovoltaic installed capacity carrying capacities that the photovoltaic access strategy complies with as a measure of safety. The more compliance there is, the higher the security of the photovoltaic access strategy.

[0073] In the above embodiments, for different topological networks, the constraints of the capacity of each grid branch corresponding to the target grid in each topological network on the photovoltaic installed capacity and the constraints of the voltage parameters of each grid node on the photovoltaic installed capacity are directly determined according to the operating parameters, so as to determine the carrying range of the photovoltaic installed capacity, thereby avoiding the problem of low determination efficiency caused by the need to perform simulation calculations on multiple data in point-by-point simulation. The technical solution provided in the present application can more efficiently determine the carrying range of the photovoltaic installed capacity of the target grid in each topological network. In addition, the carrying range of the photovoltaic installed capacity determined according to the constraints is continuous data, which is more accurate than the carrying range determined by point-by-point simulation in traditional technologies.

[0074] In one embodiment, based on the above Figure 2 The embodiment shown, see Figure 3 This embodiment involves a process of determining the constraint conditions corresponding to the topology network according to various operating parameters. Figure 3 As shown, step 202 may include steps 301 to 303 .

[0075] Step 301: determine a power supply path matrix corresponding to the topology network according to the topology network.

[0076] The elements in the power supply path matrix are used to represent closed branches in the topology network for supplying power to the grid nodes.

[0077] In an embodiment of the present application, the server may determine a power supply path matrix corresponding to the topological network according to a connection relationship between each power grid node in the topological network.

[0078] Optionally, the server may generate an original node-branch association matrix based on the grid nodes and grid branches in the target grid. , the dimension of the matrix is ​​N×(M+N), where the rows of the matrix represent nodes and the columns represent branches. The matrix contains only four elements: With branch When not connected, the matrix OK Column Elements =0; when the node It is a branch road At the starting point, the matrix OK Column Elements =1; when the node It is a branch road At the end point of the matrix OK Column Elements =-1; when the branch When disconnected, the branch With Node If connected, = , where Is an imaginary unit.

[0079] Then, the server can determine the disconnection status between each grid node according to the topological network, and generate a branch disconnection state vector based on this. The branch disconnection state vector can be expressed by referring to the following formula:

[0080] (1)

[0081] in, is the branch disconnection state vector, each element in the vector represents the disconnection state of the i-th power grid branch. If the disconnection state is 0, it means that the power grid branch is disconnected. If the disconnection state is 1, it means that the power grid branch is closed. M represents the number of disconnected power grid branches, and N represents the number of closed power grid branches.

[0082] After obtaining the branch disconnection state vector, the server can calculate the branch disconnection state vector based on the original node branch association matrix. , determine the branch association matrix corresponding to the current topology network , the specific determination process can refer to the following formula:

[0083] (2)

[0084] The operator " "To select all rows of the matrix, the formula means Extract The column with median value 1, that is, according to Determine the closed power grid branches and extract the original node-branch correlation matrix from the closed power grid branches Extract the corresponding columns to form the branch association matrix corresponding to the current topology network .

[0085] For the power supply path matrix, the server can be based on the branch association matrix corresponding to the current topology network Determine, the determination process can refer to the following formula:

[0086] (3)

[0087] in, is the power supply path matrix corresponding to the current topology network, ” means to invert the matrix.

[0088] Step 302: Establish a matrix linear power flow model according to the operating parameters and the power supply path matrix.

[0089] Among them, the matrix linear power flow model includes a first linear relationship between the branch active power vector and the photovoltaic installed capacity, a second linear relationship between the branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between the node voltage vector and the photovoltaic installed capacity.

[0090] In an embodiment of the present application, the elements in the branch active power vector can represent the active power of each power grid branch under the current topology network, the elements in the branch reactive power vector can represent the reactive power of each power grid branch under the current topology network, and the elements in the node voltage vector can represent the voltage amplitude of each power grid node under the current topology network.

[0091] In an embodiment of the present application, the server can construct these three vectors according to the operating parameters and the power supply path matrix, and then determine the corresponding linear relationship according to the three vectors.

[0092] In a possible implementation, the server may input the operating parameters and the power supply path matrix into a pre-trained neural network model, thereby obtaining a matrixed linear power flow model output by the network model.

[0093] In another possible implementation, the server may determine the operating vector corresponding to the topological network based on the operating parameters, wherein the operating vector includes the resistance vector corresponding to each closed branch in the topological network, the reactance vector corresponding to each closed branch, the active vector corresponding to each grid node, and the reactive vector corresponding to each grid node. Then, the active vector, the power supply path matrix, and the preset photovoltaic active output coefficient are substituted into the first preset formula to obtain a first linear relationship, the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient are substituted into the second preset formula to obtain a second linear relationship, and the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balancing node voltage parameters included in the operating parameters are substituted into the third preset formula to obtain a third linear relationship.

[0094] In the embodiment of the present application, the active vector Each element in can represent the active injection power of each grid node in the operating parameters, and the expression can refer to the following formula:

[0095] (4)

[0096] The first preset formula can refer to the following formula:

[0097] = (5)

[0098] in, is the branch active power vector, P is the active injection power vector of the grid node, and the calculation process of P can refer to the following formula:

[0099] = (6)

[0100] in, is the photovoltaic active output coefficient, and its value range can be [0,1]. The operator symbol is " ” is the Hadamard product. is the unknown photovoltaic installed capacity vector, the expression can be , the elements included in the matrix can represent the photovoltaic installed capacity corresponding to each grid node.

[0101] Substituting the active power vector and the photovoltaic active output coefficient into formula (6) can obtain the active power injection vector of the grid node. Substituting the active power injection vector of the grid node and the power supply path matrix into formula (6) can obtain the first linear relationship between the branch active power vector and the photovoltaic installed capacity.

[0102] In the embodiment of the present application, the active vector Each element in can represent the reactive injection power of each grid node in the operating parameters, and the expression can refer to the following formula:

[0103] (7)

[0104] The second preset formula can refer to the following formula:

[0105] = (8)

[0106] in, is the branch reactive power vector, Q is the reactive injection power vector of the grid node, and the calculation process of Q can refer to the following formula:

[0107] = (9)

[0108] in, is the photovoltaic reactive output coefficient, and its value range can be [0,1]. In the embodiment of the present application, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy the preset numerical relationship, that is, + =1.

[0109] Substituting the reactive power vector and the PV reactive output coefficient into formula (9) can obtain the reactive injection power vector of the grid node. Substituting the reactive injection power vector of the grid node and the power supply path matrix into formula (8) can obtain the second linear relationship between the branch reactive power vector and the PV installed capacity.

[0110] In the embodiment of the present application, the elements in the resistance vector can represent the resistance of each closed branch, and the expression can refer to the following formula:

[0111] (10)

[0112] in, is the number of closed branches in the distribution network, the vector The element is a branch resistance.

[0113] The elements in the reactance vector can represent the reactance of each closed branch, and the expression can refer to the following formula:

[0114] (11)

[0115] Among them, The element is a branch reactance.

[0116] The third preset formula can refer to the following formula:

[0117] (12)

[0118] in, is the voltage amplitude parameter of the grid node, and U0 is the balanced node voltage.

[0119] The server may substitute the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into the third preset formula (12) to obtain a third linear relationship.

[0120] Step 303: determine constraint conditions according to the operating parameters and the matrix linear power flow model.

[0121] In an embodiment of the present application, the server can determine the constraint conditions based on the operating parameters and the matrixed linear power flow model, specifically including: the server determines the first constraint condition based on the maximum reverse load rate, the first linear relationship and the second linear relationship included in the operating parameters, and the server can also determine the second constraint condition based on the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0122] In the embodiment of the present application, the server may determine the first constraint condition based on the first constraint formula according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters. The first constraint formula may refer to the following formula:

[0123] (13)

[0124] in, is the maximum reverse load rate, represents the branch capacity upper limit vector, which can be expressed as , where the i-th element represents the capacity upper limit of the grid branch i, which can be determined based on the operating parameters.

[0125] In the embodiment of the present application, the server may determine the second constraint formula according to the third linear relationship:

[0126] (14)

[0127] in, is the voltage amplitude upper limit vector. The server can determine the voltage amplitude upper limit value according to the current topology network. , and bring it into the second constraint formula to get the second constraint condition.

[0128] Based on the above embodiments, in a possible implementation, the process of determining the carrying range of the photovoltaic installed capacity corresponding to the topological network according to the constraint condition may include: the server linearly normalizes the first constraint condition to obtain the first constraint condition in the target form, so that the server can determine the branch capacity carrying range corresponding to the topological network according to the first constraint condition in the target form, and determine the node voltage carrying range corresponding to the topological network according to the second constraint condition, and then, the server can determine the branch capacity carrying range and the node voltage carrying range as the carrying range of the photovoltaic installed capacity.

[0129] In the embodiment of the present application, it can be seen from the first constraint condition that there is a square term in the left-hand form of the constraint condition. In order to eliminate the square term, the first constraint condition is converted into a target form. The server can perform linear normalization on the first constraint condition. The normalized formula can refer to the following formula:

[0130] (15)

[0131] in, , is the coefficient of the linearization constraint of the dodecagon inscribed in a circle, which can be set according to the actual application scenario.

[0132] Based on the first constraint condition of the target form, the server can determine the expression of the branch capacity carrying range as:

[0133] (16)

[0134] Based on the second constraint, the server can determine the node voltage carrying range as:

[0135] (17)

[0136] In a possible implementation, when the server evaluates any photovoltaic access strategy based on the branch capacity carrying range and the node voltage carrying range, the server can determine the corresponding photovoltaic installed capacity matrix according to the photovoltaic intervention strategy. Then, the photovoltaic installed capacity matrix By bringing in the above branch capacity carrying range and node voltage carrying range, the corresponding photovoltaic installed capacity matrix can be determined based on the current photovoltaic intervention strategy. Whether the above-mentioned carrying range is met, if so, the server determines that the current photovoltaic intervention strategy can be safely operated under the current topology network, otherwise, the current photovoltaic intervention strategy cannot be safely operated under the current topology network.

[0137] In one embodiment, an exemplary photovoltaic installed capacity load determination method is provided. The method is used for a server and can be applied in the implementation environment shown in FIG. 1 .

[0138] Step 401, obtaining multiple topological networks and operating parameters corresponding to the target power grid.

[0139] Among them, different topological networks include different power grid branches formed by various power grid nodes.

[0140] Step 402: for each topology network, determine a power supply path matrix corresponding to the topology network according to the topology network.

[0141] The elements in the power supply path matrix are used to represent closed branches in the topology network for supplying power to the grid nodes.

[0142] Step 403: Determine an operation vector corresponding to the topology network according to the operation parameters.

[0143] The operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node.

[0144] Step 404: Substitute the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain a first linear relationship.

[0145] Step 405: Substitute the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain a second linear relationship.

[0146] Step 406 , substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain a third linear relationship.

[0147] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0148] Among them, the matrix linear power flow model includes a first linear relationship between the branch active power vector and the photovoltaic installed capacity, a second linear relationship between the branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between the node voltage vector and the photovoltaic installed capacity.

[0149] Step 407: determining a first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters.

[0150] Step 408: Determine a second constraint condition according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0151] Among them, the constraints include a first constraint and a second constraint. The first constraint is the constraint of the capacity of each grid branch in the topological network on the photovoltaic installed capacity, and the second constraint is the constraint of the voltage parameters of each grid node in the topological network on the photovoltaic installed capacity.

[0152] Step 409: linearly normalize the first constraint condition to obtain the first constraint condition in a target form.

[0153] Step 410, determining a branch capacity carrying range corresponding to the topology network according to a first constraint condition in a target form, and determining a node voltage carrying range corresponding to the topology network according to a second constraint condition.

[0154] Step 411, determining the branch capacity carrying range and the node voltage carrying range as the photovoltaic installed capacity carrying range.

[0155] Step 412: Acquire a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in a target power grid and a reference photovoltaic installed capacity.

[0156] Step 413: Determine the security of the photovoltaic access strategy according to the carrying range of the photovoltaic installed capacity corresponding to each topological network.

[0157] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0158] Based on the above embodiment, an exemplary introduction is given. The topology network that the server can obtain can refer to Figure 5 , the photovoltaic access strategy obtained by the server indicates that photovoltaic equipment needs to be connected at nodes 11, 18 and 33. For example, the voltage safety operating range of the grid node is [0.93, 1.07], and the maximum current carrying capacity allowed by the grid branch is 500A. The access locations of each grid node and their corresponding power parameters can be referred to Table 1:

[0159]

[0160] Table 1

[0161] The corresponding branch parameters of each power grid branch (including resistance, reactance, identification of the head node, identification of the terminal node) can be referred to Table 2:

[0162]

[0163] Table 2

[0164] Based on the above operating parameters, the server calculates the carrying range of the photovoltaic installed capacity corresponding to the four topological networks through the steps in the above embodiment. The calculation results can be referred to Figure 6 .

[0165] In the embodiment of the present application, the server can verify the efficiency and accuracy of determining the carrying range of the photovoltaic installed capacity in the above steps through the following four schemes:

[0166] Solution 1: Marked as M1, it is the technical solution proposed in this application; Solution 2: Adopting a point-by-point simulation method based on linear tidal flow (M2); Solution 3: Adopting a multi-objective optimization method based on improved particle swarm (M3); Solution 4: Adopting a point-by-point simulation method based on precise tidal flow (M4).

[0167] The implementation environment for verifying the four solutions can be Intel (R) Core (TM) i9-11900, with a main frequency of 2.50GHz, a memory of 16GB, and a software environment of Windows 11 operating system.

[0168] First, scheme M4 is compared with the technical scheme provided in this application. Assuming that the locations where the photovoltaic equipment is connected are nodes 5, 22 and 25, when a single node is connected to the photovoltaic equipment, the calculation error of the photovoltaic carrying capacity is shown in Table 3. The corresponding calculation errors are 2.976%, 0.745% and 3.153% respectively:

[0169]

[0170] Table 3

[0171] It can be seen that the calculation accuracy corresponding to the technical solution provided in this application is relatively high.

[0172] Then, the calculation speeds corresponding to each solution are compared. The comparison results can be found in Table 4:

[0173]

[0174] Table 4

[0175] As can be seen from the table, the M1 method takes the least time in terms of analytical formula establishment time and boundary characterization time. Figure 7 The calculation time is explained intuitively. The calculation time of methods M3 and M4 is in seconds, while the calculation time of methods M1 and M2 is in milliseconds. The bearer domain establishment time of M2 is 0.38s, while the bearer domain establishment time of M4 is 446.49s, which illustrates the advantage of the calculation speed of the technical solution of this application. The bearer domain establishment time of M1 is 0.013276s, which is further reduced compared to M2, which illustrates the advantage of the application in calculation time.

[0176] Based on the same inventive concept, the embodiment of the present application also provides a photovoltaic installed capacity load determination device for implementing the photovoltaic installed capacity load determination method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more photovoltaic installed capacity load determination device embodiments provided below can refer to the limitations of the photovoltaic installed capacity load determination method above, and will not be repeated here.

[0177] In an exemplary embodiment, Figure 8 As shown, a photovoltaic installed capacity load determination device is provided, comprising: an acquisition module 801, a constraint module 802 and a load range determination module 803, wherein:

[0178] The acquisition module 801 is used to acquire multiple topological networks and operation parameters corresponding to the target power grid, and different topological networks include different power grid branches formed by various power grid nodes;

[0179] A constraint module 802 is used to determine, for each of the topological networks, the constraint conditions corresponding to the topological network according to the operating parameters, wherein the constraint conditions include a first constraint condition and a second constraint condition, wherein the first constraint condition is the constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is the constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity;

[0180] The load range determination module 803 is used to determine the load range of the photovoltaic installed capacity corresponding to the topological network according to the constraint condition.

[0181] In one embodiment, the constraint module 802 includes:

[0182] A power supply path matrix determination unit, used to determine a power supply path matrix corresponding to the topology network according to the topology network, wherein the elements in the power supply path matrix are used to characterize a closed branch in the topology network for supplying power to the grid node;

[0183] A model building unit, used to build a matrix linear power flow model according to the operating parameters and the power supply path matrix, wherein the matrix linear power flow model includes a first linear relationship between a branch active power vector and the photovoltaic installed capacity, a second linear relationship between a branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between a node voltage vector and the photovoltaic installed capacity;

[0184] A constraint determination unit is used to determine the constraint condition according to the operating parameters and the matrixed linear power flow model.

[0185] In one embodiment, the constraint determination unit is specifically configured to perform:

[0186] determining the first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters;

[0187] The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0188] In one embodiment, the model building unit is specifically configured to perform:

[0189] Determine an operation vector corresponding to the topological network according to the operation parameters, wherein the operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node;

[0190] Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain the first linear relationship;

[0191] Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain the second linear relationship;

[0192] Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain the third linear relationship;

[0193] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0194] In one embodiment, the bearer range determination module 803 includes:

[0195] A linear unit, used for linearly normalizing the first constraint condition to obtain the first constraint condition in a target form;

[0196] A range determination unit, configured to determine a branch capacity carrying range corresponding to the topology network according to the first constraint condition of the target form, and to determine a node voltage carrying range corresponding to the topology network according to the second constraint condition;

[0197] The photovoltaic installed capacity carrying determination unit is used to determine the branch capacity carrying range and the node voltage carrying range as the photovoltaic installed capacity carrying range.

[0198] In one embodiment, the apparatus comprises:

[0199] A strategy acquisition module, used to acquire a photovoltaic access strategy, wherein the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in the target power grid and a reference photovoltaic installed capacity;

[0200] An evaluation module is used to determine the security of the photovoltaic access strategy according to the carrying range of the photovoltaic installed capacity corresponding to each of the topological networks.

[0201] Each module in the above photovoltaic installed capacity load determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0202] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the 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 database of the computer device is used to store photovoltaic installed capacity carrying determination data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining photovoltaic installed capacity carrying is implemented.

[0203] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0204] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0205] Acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes;

[0206] For each of the topological networks, a constraint condition corresponding to the topological network is determined according to each of the operating parameters, wherein the constraint condition includes a first constraint condition and a second constraint condition, wherein the first constraint condition is a constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is a constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity;

[0207] The carrying range of the photovoltaic installed capacity corresponding to the topological network is determined according to the constraint conditions.

[0208] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0209] Determine a power supply path matrix corresponding to the topology network according to the topology network, wherein the elements in the power supply path matrix are used to characterize a closed branch in the topology network for supplying power to the grid node;

[0210] Establishing a matrix linear power flow model according to the operating parameters and the power supply path matrix, the matrix linear power flow model includes a first linear relationship between a branch active power vector and the photovoltaic installed capacity, a second linear relationship between a branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between a node voltage vector and the photovoltaic installed capacity;

[0211] The constraint condition is determined according to the operating parameters and the matrixed linear power flow model.

[0212] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0213] determining the first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters;

[0214] The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0215] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0216] Determine an operation vector corresponding to the topological network according to the operation parameters, wherein the operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node;

[0217] Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain the first linear relationship;

[0218] Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain the second linear relationship;

[0219] Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain the third linear relationship;

[0220] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0221] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0222] Linearly normalizing the first constraint condition to obtain the first constraint condition in target form;

[0223] Determine the branch capacity carrying range corresponding to the topology network according to the first constraint condition of the target form, and determine the node voltage carrying range corresponding to the topology network according to the second constraint condition;

[0224] The branch capacity carrying range and the node voltage carrying range are determined as the carrying range of the photovoltaic installed capacity.

[0225] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0226] Acquire a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in the target power grid and a reference photovoltaic installed capacity;

[0227] The security of the photovoltaic access strategy is determined according to the carrying range of the photovoltaic installed capacity corresponding to each of the topological networks.

[0228] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0229] Acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes;

[0230] For each of the topological networks, a constraint condition corresponding to the topological network is determined according to each of the operating parameters, wherein the constraint condition includes a first constraint condition and a second constraint condition, wherein the first constraint condition is a constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is a constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity;

[0231] The carrying range of the photovoltaic installed capacity corresponding to the topological network is determined according to the constraint conditions.

[0232] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0233] Determine a power supply path matrix corresponding to the topology network according to the topology network, wherein the elements in the power supply path matrix are used to characterize a closed branch in the topology network for supplying power to the grid node;

[0234] Establishing a matrix linear power flow model according to the operating parameters and the power supply path matrix, the matrix linear power flow model includes a first linear relationship between a branch active power vector and the photovoltaic installed capacity, a second linear relationship between a branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between a node voltage vector and the photovoltaic installed capacity;

[0235] The constraint condition is determined according to the operating parameters and the matrixed linear power flow model.

[0236] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0237] determining the first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters;

[0238] The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0239] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0240] Determine an operation vector corresponding to the topological network according to the operation parameters, wherein the operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node;

[0241] Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain the first linear relationship;

[0242] Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain the second linear relationship;

[0243] Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain the third linear relationship;

[0244] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0245] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0246] Linearly normalizing the first constraint condition to obtain the first constraint condition in target form;

[0247] Determine the branch capacity carrying range corresponding to the topology network according to the first constraint condition of the target form, and determine the node voltage carrying range corresponding to the topology network according to the second constraint condition;

[0248] The branch capacity carrying range and the node voltage carrying range are determined as the carrying range of the photovoltaic installed capacity.

[0249] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0250] Acquire a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in the target power grid and a reference photovoltaic installed capacity;

[0251] The security of the photovoltaic access strategy is determined according to the carrying range of the photovoltaic installed capacity corresponding to each of the topological networks.

[0252] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0253] Acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes;

[0254] For each of the topological networks, a constraint condition corresponding to the topological network is determined according to each of the operating parameters, wherein the constraint condition includes a first constraint condition and a second constraint condition, wherein the first constraint condition is a constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is a constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity;

[0255] The carrying range of the photovoltaic installed capacity corresponding to the topological network is determined according to the constraint conditions.

[0256] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0257] Determine a power supply path matrix corresponding to the topology network according to the topology network, wherein the elements in the power supply path matrix are used to characterize a closed branch in the topology network for supplying power to the grid node;

[0258] Establishing a matrix linear power flow model according to the operating parameters and the power supply path matrix, the matrix linear power flow model includes a first linear relationship between a branch active power vector and the photovoltaic installed capacity, a second linear relationship between a branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between a node voltage vector and the photovoltaic installed capacity;

[0259] The constraint condition is determined according to the operating parameters and the matrixed linear power flow model.

[0260] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0261] determining the first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters;

[0262] The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

[0263] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0264] Determine an operation vector corresponding to the topological network according to the operation parameters, wherein the operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node;

[0265] Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain the first linear relationship;

[0266] Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain the second linear relationship;

[0267] Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain the third linear relationship;

[0268] Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

[0269] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0270] Linearly normalizing the first constraint condition to obtain the first constraint condition in target form;

[0271] Determine the branch capacity carrying range corresponding to the topology network according to the first constraint condition of the target form, and determine the node voltage carrying range corresponding to the topology network according to the second constraint condition;

[0272] The branch capacity carrying range and the node voltage carrying range are determined as the carrying range of the photovoltaic installed capacity.

[0273] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0274] Acquire a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in the target power grid and a reference photovoltaic installed capacity;

[0275] The security of the photovoltaic access strategy is determined according to the carrying range of the photovoltaic installed capacity corresponding to each of the topological networks.

[0276] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0277] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0278] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this application.

[0279] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining photovoltaic installed capacity load, characterized in that: The method comprises Acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes; For each of the topological networks, a constraint condition corresponding to the topological network is determined according to each of the operating parameters, wherein the constraint condition includes a first constraint condition and a second constraint condition, wherein the first constraint condition is a constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition is a constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity; The carrying range of the photovoltaic installed capacity corresponding to the topological network is determined according to the constraint conditions.

2. The method according to claim 1, characterized in that: The determining of the constraint conditions corresponding to the topological network according to the operating parameters includes: Determine a power supply path matrix corresponding to the topology network according to the topology network, wherein elements in the power supply path matrix are used to characterize closed branches in the topology network for supplying power to the grid node; Establishing a matrix linear power flow model according to the operating parameters and the power supply path matrix, the matrix linear power flow model includes a first linear relationship between a branch active power vector and the photovoltaic installed capacity, a second linear relationship between a branch reactive power vector and the photovoltaic installed capacity, and a third linear relationship between a node voltage vector and the photovoltaic installed capacity; The constraint condition is determined according to the operating parameters and the matrixed linear power flow model.

3. The method according to claim 2, characterized in that The determining the constraint condition according to the operating parameters and the matrixed linear power flow model includes: determining the first constraint condition according to the maximum reverse load rate, the first linear relationship, and the second linear relationship included in the operating parameters; The second constraint condition is determined according to the voltage amplitude upper limit value corresponding to the current topology network included in the operating parameters and the third linear relationship.

4. The method according to claim 2, characterized in that: The step of establishing a matrix linear power flow model according to the operating parameters and the power supply path matrix includes: Determine an operation vector corresponding to the topological network according to the operation parameters, wherein the operation vector includes a resistance vector corresponding to each closed branch in the topological network, a reactance vector corresponding to each closed branch, an active vector corresponding to each grid node, and a reactive vector corresponding to each grid node; Substituting the active power vector, the power supply path matrix, and the preset photovoltaic active power output coefficient into a first preset formula to obtain the first linear relationship; Substituting the reactive vector, the power supply path matrix, and the preset photovoltaic reactive output coefficient into a second preset formula to obtain the second linear relationship; Substituting the resistance vector, the reactance vector, the first linear relationship, the second linear relationship, the power supply path matrix, and the balance node voltage parameter included in the operating parameters into a third preset formula to obtain the third linear relationship; Among them, the preset photovoltaic active output coefficient and the preset photovoltaic reactive output coefficient satisfy a preset numerical relationship.

5. The method according to claim 1, characterized in that The determining, according to the constraint condition, the carrying range of the photovoltaic installed capacity corresponding to the topological network includes: Linearly normalizing the first constraint condition to obtain the first constraint condition in target form; Determine the branch capacity carrying range corresponding to the topology network according to the first constraint condition of the target form, and determine the node voltage carrying range corresponding to the topology network according to the second constraint condition; The branch capacity carrying range and the node voltage carrying range are determined as the carrying range of the photovoltaic installed capacity.

6. The method according to claim 1, characterized in that The method further comprises: Acquire a photovoltaic access strategy, where the photovoltaic access strategy is used to indicate a node identifier of a photovoltaic device accessed in the target power grid and a reference photovoltaic installed capacity; The security of the photovoltaic access strategy is determined according to the carrying range of the photovoltaic installed capacity corresponding to each of the topological networks.

7. A photovoltaic installed capacity load determination device, characterized in that: The device comprises: An acquisition module is used to acquire multiple topological networks and operating parameters corresponding to the target power grid, where different topological networks include different power grid branches formed by various power grid nodes; A constraint module, for determining, for each of the topological networks, the constraint conditions corresponding to the topological network according to the operating parameters, the constraint conditions including a first constraint condition and a second constraint condition, the first constraint condition being the constraint condition of each grid branch capacity in the topological network on the photovoltaic installed capacity, and the second constraint condition being the constraint condition of each grid node voltage parameter in the topological network on the photovoltaic installed capacity; The load range determination module is used to determine the load range of the photovoltaic installed capacity corresponding to the topological network according to the constraint conditions.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: 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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