Power grid strength constraint based power transmission network and network construction device collaborative planning method and system

Abstract

The present application relates to the technical field of power system transmission network and network equipment collaborative planning, and particularly relates to a kind of transmission network and network equipment collaborative planning method and system under grid strength constraint, comprising: obtaining grid base topology and new energy access data, generating node admittance matrix;Build the minimum annual comprehensive configuration cost of network type energy storage, phase modifier and newly built line as target, the collaborative planning optimization model containing grid strength constraint;The node admittance matrix is dynamically corrected and is reduced by Kron, constructs source side and net side first-order sensitivity matrix, and converts grid strength constraint into linear inequality constraint;Solve the model, output network type energy storage configuration scheme, phase modifier configuration scheme and newly built line scheme.The present application linearizes the nonlinear grid strength constraint into the planning model, realizes the collaborative optimization of network equipment and transmission network, and improves the applicability of planning scheme in weak grid scenario.

Description

Technical Field

[0001] This invention relates to the field of collaborative planning technology for power system transmission networks and network construction equipment, and in particular to a method and system for collaborative planning of transmission networks and network construction equipment under power grid strength constraints. Background Technology

[0002] Against the backdrop of new power system construction, the Southwest Hydropower-Wind-Solar Integrated Base has become an important strategic direction for clean energy development and inter-regional transmission in my country. The region boasts abundant new energy and hydropower resources, but its local power grid structure is relatively weak, leading to insufficient grid strength after large-scale new energy grid integration. Grid expansion can strengthen the electrical coupling between new energy power plants and hydropower synchronous generators and strong grid support nodes, effectively shortening electrical distances and radiating the strong support capacity of hydropower to new energy aggregation areas. However, existing research mostly relies on grid-type equipment or synchronous condensers to improve grid strength under a fixed grid structure, with less consideration given to the impact of grid expansion on the grid strength of new energy sites.

[0003] Against this backdrop, designing an optimization method that integrates new transmission lines, grid-type energy storage, and synchronous condensers into a unified optimization model for comprehensive solution, while strictly satisfying the mSCR (modified Short Circuit Ratio) safety constraint, and ensuring the economic optimality of system planning costs, has become a core technical challenge in ensuring the safe operation of new power systems. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for collaborative planning of transmission networks and network construction equipment under grid strength constraints. This method determines the grid-type energy storage capacity, the number of synchronous condensers, and the proposed new transmission line schemes, given parameters such as the scale of new energy and hydropower integration, the foundation grid structure, candidate line pools, and equipment cost parameters. The goal is to ensure that the planning results meet grid strength constraints and minimize total investment costs. The technical solution is as follows:

[0005] A collaborative planning method for transmission network and network construction equipment under power grid strength constraints includes the following steps:

[0006] Step 1: Obtain the data on new energy access nodes and power output, hydropower access nodes and power output, and network topology data, and generate a network impedance matrix. Automatically invert the obtained network impedance matrix to obtain the node admittance matrix.

[0007] Step 2: Construct a collaborative planning and configuration model for the transmission network and network-building equipment under power grid strength constraints, including:

[0008] Step 2.1: The objective function is to minimize the annualized comprehensive configuration cost of grid-type energy storage, synchronous condensers, and newly built lines within the planning period;

[0009] Step 2.2: Establish constraints, including energy storage capacity constraints, synchronous condenser quantity constraints, upper limit constraints on the number of newly built lines, operation scenario constraints, and grid strength constraints;

[0010] Step 3: Linearize the power grid strength constraints in the collaborative planning configuration model, including:

[0011] Step 3.1: Dynamically correct the node admittance matrix by introducing the admittance increment of the newly built line and the admittance increment of the source-side equipment;

[0012] Step 3.2: Perform Kron reduction on the corrected node admittance matrix to eliminate non-new energy access nodes and extract the equivalent impedance matrix of new energy access nodes;

[0013] Step 3.3: Based on the equivalent impedance matrix, construct the source-side first-order sensitivity matrix and the network-side first-order sensitivity matrix;

[0014] Step 3.4: Transform the power grid strength constraint into a linear inequality constraint that includes the source-side first-order sensitivity matrix and the grid-side first-order sensitivity matrix;

[0015] Step 4: Solve the linearized optimization model and output the grid-type energy storage configuration scheme, synchronous condenser configuration scheme, and new line construction scheme.

[0016] A collaborative planning system for transmission network and network construction equipment under power grid strength constraints includes:

[0017] The data acquisition module is used to acquire new energy access node and output data, hydropower access node and output data, and grid topology data. Based on the new energy access node and output data, hydropower access node and output data, and grid topology data of the power grid, a network impedance matrix is ​​generated, and the obtained network impedance matrix is ​​automatically inverted to obtain the node admittance matrix.

[0018] The model building module is used to build a collaborative planning and configuration model of the transmission network and network construction equipment under the grid strength constraint. The objective function is to minimize the annualized comprehensive configuration cost of grid-type energy storage, synchronous condensers and new lines within the planning period. The module also establishes constraints including energy storage capacity constraints, synchronous condenser quantity constraints, upper limit constraints on the number of new lines, operation constraints and grid strength constraints.

[0019] The processing and solution module is used to linearize the power grid strength constraints in the collaborative planning configuration model, including:

[0020] The admittance correction unit is used to dynamically correct the node admittance matrix by introducing the admittance increment of the newly built line and the admittance increment of the source-side equipment.

[0021] Kron reduction unit is used to perform Kron reduction on the corrected node admittance matrix, eliminate non-new energy access nodes, and extract the equivalent impedance matrix of new energy access nodes.

[0022] A sensitivity construction unit is used to construct a source-side first-order sensitivity matrix and a network-side first-order sensitivity matrix based on the equivalent impedance matrix.

[0023] The constraint transformation unit is used to transform the power grid strength constraint into a linear inequality constraint that includes the source-side first-order sensitivity matrix and the grid-side first-order sensitivity matrix.

[0024] The model solving unit is used to solve the optimized model after linearization and outputs the grid-type energy storage configuration scheme, the synchronous condenser configuration scheme, and the new line scheme.

[0025] The beneficial effects of this invention are as follows:

[0026] 1. This invention incorporates grid strength constraints into the planning model, avoiding post-planning reinforcement. By using a short-circuit ratio of each renewable energy node not lower than a preset target value as a hard constraint during the planning stage, and employing admittance dynamic correction, Kron order reduction, and sensitivity matrix construction to transform it into a linear inequality constraint, the planning scheme meets the grid strength requirements from the outset, avoiding the iterative process of planning first, verifying later, and then reinforcing if the verification fails, as is common in traditional methods.

[0027] 2. This invention achieves coordinated optimization of grid-building equipment and transmission lines, reducing overall configuration costs. It places grid-building energy storage, synchronous condensers, and new transmission lines into the same optimization model for joint decision-making—grid-building equipment provides short-circuit capacity support, and new transmission lines change the grid topology—these three methods are automatically coordinated under unified grid strength constraints, avoiding redundant investment caused by the disconnect between equipment configuration and line selection in phased planning.

[0028] 3. The linearization process of this invention allows the model to directly call the mixed-integer linear programming solver, significantly improving computational efficiency. The original power grid strength constraints were nonlinear (containing matrix inversion and coupling terms), but after linearization based on first-order sensitivity, they are transformed into explicit linear inequalities. The overall model remains in the form of mixed-integer linear programming, without relying on nonlinear solvers or heuristic algorithms, thus significantly improving solution efficiency and convergence reliability. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating a method for collaborative planning and configuration of transmission networks and network construction equipment under power grid strength constraints, as provided in an embodiment of the present invention.

[0030] Figure 2 This is a schematic diagram of a newly created line when the maximum number of newly created lines is 1, as provided in an embodiment of the present invention.

[0031] Figure 3 This is a schematic diagram of a newly created line when the maximum number of newly created lines is 2, as provided in an embodiment of the present invention.

[0032] Figure 4 This is a schematic diagram of a newly created line when the maximum number of newly created lines is 3, as provided in an embodiment of the present invention.

[0033] Figure 5 This is a schematic diagram of a collaborative planning and configuration system for transmission networks and network construction equipment under power grid strength constraints, provided in an embodiment of the present invention. Detailed Implementation

[0034] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings of the embodiments of the present invention, so that those skilled in the art can better understand the present invention. It should be noted that these embodiments do not constitute a limitation of the present invention, but are merely examples.

[0035] This invention proposes a collaborative planning method and system for transmission networks and network construction equipment under power grid strength constraints, which can effectively improve power grid strength and ensure optimal economic efficiency.

[0036] The system acquires the power grid base topology, node coordinates, new energy access nodes and scale, hydropower access nodes and scale, synchronous condenser parameters, grid-type energy storage parameters, new line parameters, and planning economic parameters to form a unified collaborative planning dataset for the transmission network and grid-building equipment.

[0037] Based on the existing grid admittance matrix, candidate line admittance increments, equivalent support admittance of grid-type energy storage, and equivalent support admittance of synchronous condensers, a mixed integer programming master problem is constructed, which includes continuous capacity variables, integer equipment variables, and binary line variables.

[0038] The non-convex terms in the power grid strength constraints are accurately evaluated, and a non-convex external approximation cut plane is generated at the current candidate solution. After the candidate solution of the main problem satisfies the short-circuit ratio target, the DC power flow sub-problem is invoked for N-0 ground state security verification; if the verification fails, an integer exclusion cut or fault line disabling constraint is generated and the process returns to the main problem to continue iteration.

[0039] Once a strictly feasible candidate solution is obtained, the global optimal upper bound is updated, and the number of allowed new lines is traversed until the iteration limit, stagnation criterion, or exhaustive feasible topology is reached. Finally, the source-side configuration, network-side construction scheme, and short-circuit ratio improvement effect are output.

[0040] The grid new energy access points and output data, hydropower access points and output data, and grid topology data are input into the established collaborative planning and configuration model of the transmission network and network construction equipment under grid strength constraints. The non-convex part in the optimization model is linearized to obtain a linearized collaborative planning and configuration model of the transmission network and network construction equipment under grid strength constraints. A commercial solver is called to solve the linearized collaborative planning and configuration model of the transmission network and network construction equipment under grid strength constraints to obtain the optimal configuration scheme of the grid-type energy storage, synchronous condenser, and new line. The optimal configuration scheme of the grid-type energy storage, synchronous condenser, and new line includes the configuration location and capacity of the grid-type energy storage, the configuration location and capacity of the synchronous condenser, the branch of the new line, and the distance of the new line.

[0041] This invention also provides a collaborative planning system for transmission networks and network construction equipment under power grid strength constraints, comprising:

[0042] The data acquisition module is used to acquire new energy access node and output data, hydropower access node and output data, and grid topology data. Based on the new energy access node and output data, hydropower access node and output data, and grid topology data of the power grid, a network impedance matrix is ​​generated, and the obtained network impedance matrix is ​​automatically inverted to obtain the node admittance matrix.

[0043] The model building module is used to establish a collaborative planning and configuration model of the transmission network and network construction equipment under grid strength constraints. The collaborative planning and configuration model of the transmission network and network construction equipment under grid strength constraints includes an optimization objective function and constraints. The optimization objective is to minimize the annualized cost of network-type energy storage, synchronous condensers, and newly built lines. The constraints include planning constraints for network-type energy storage, planning constraints for synchronous condensers, planning constraints for newly built lines, and operational constraints for baseline scenarios.

[0044] The processing and solving module is used to input the grid new energy access node and output data, hydropower access node and output data, and grid topology data into the grid strength constraint-based collaborative planning and configuration model of transmission network and grid-building equipment, and solve the linearized grid strength constraint-based collaborative planning and configuration model of transmission network and grid-building equipment to obtain the optimal configuration scheme of grid-based energy storage, synchronous condensers, and new lines.

[0045] In a collaborative planning system for transmission networks and network construction equipment under power grid strength constraints provided in a second aspect of the present invention, the processing and solving module includes a model processing unit and a model solving unit, wherein:

[0046] The model processing unit is used to linearize the non-convex part of the collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint, so as to obtain a linearized collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint.

[0047] The model solving unit is used to call a commercial solver to solve the linearized grid strength constraint collaborative planning and configuration model of the transmission network and grid-building equipment, and obtain the optimal configuration scheme of the grid-type energy storage, synchronous condenser and new line.

[0048] The model processing unit is used to linearize the non-convex part of the collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint.

[0049] Please refer to Figure 1 This invention provides a method for collaborative planning of transmission networks and network construction equipment under power grid strength constraints. The method includes steps S1 to S4, each of which is detailed below:

[0050] Step S1: Obtain the new energy access node and output data, hydropower access node and output data, and grid topology data. Based on the new energy access node and output data, hydropower access node and output data, and grid topology data of the power grid, generate a network impedance matrix. Then, automatically invert the obtained network impedance matrix to obtain the node admittance matrix.

[0051] Step S2: Establish a collaborative planning and configuration model for the transmission network and network construction equipment under grid strength constraints. The collaborative planning and configuration model for the transmission network and network construction equipment under grid strength constraints includes an optimization objective function and constraints. The optimization objective is to minimize the annualized total investment cost of grid energy storage, synchronous condensers, and new grid structures within the planning time period. The constraints include the energy storage capacity constraint, the number of synchronous condensers constraint, the upper limit constraint of the number of new lines, and the basic DC power flow constraint.

[0052] Step S21: Establish the optimization objective function of the collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint. The optimization objective function is to minimize the annualized total investment cost of network construction energy storage, synchronous condensers and new grid structures within a set planning time period.

[0053] In the collaborative planning method for power transmission networks and network construction equipment provided in the first aspect of this invention, the optimization objective function of the collaborative planning configuration model for power transmission networks and network construction equipment under power grid strength constraints is to minimize the annualized total investment cost of network energy storage, synchronous condensers, and newly built grid structures within the planning time period. Specifically:

[0054] (1);

[0055] (2);

[0056] (3);

[0057] (4);

[0058] (5);

[0059] in, The annualized comprehensive configuration cost for grid-connected energy storage; The annualized comprehensive configuration cost of a centralized synchronous condenser; The annualized comprehensive configuration cost for newly built lines; The unit capacity investment cost coefficient for grid-type energy storage; The capital recovery factor for energy storage equipment; The annual operating cost coefficient per unit capacity of grid-connected energy storage; The duration of continuous support configured for energy storage; Configure capacity for energy storage; Configure the number of centralized synchronous condensers; Capacity of a single synchronous condenser; The unit capacity investment cost coefficient for the camera; The capital recovery factor for adjusting the camera; The annual operating cost coefficient per unit capacity of the camera; This refers to the unit investment cost coefficient for newly constructed lines. The capital recovery factor for newly built lines; This refers to the unit annual operating cost coefficient for newly constructed lines. This represents the total length of the newly constructed lines; AP As a capital recovery factor, r The discount rate is... N life The economic service life of the equipment.

[0060] Step S22: Construct the constraints of the collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint, including: energy storage capacity constraint, synchronous condenser quantity constraint, upper limit constraint of the number of newly built lines (step S221), benchmark scenario operation constraint (step S222), and power grid strength constraint (step S223).

[0061] Step S221: Establish constraints on energy storage capacity, number of synchronous condensers, and upper limit of the number of new lines.

[0062] In the first aspect of this invention, a method for collaborative planning of transmission networks and network construction equipment under power grid strength constraints is provided; the constraints for collaborative planning of transmission networks and network construction equipment include energy storage capacity constraints, synchronous condenser quantity constraints, and upper limit constraints on the number of newly built lines. Its specific expression is:

[0063] (6);

[0064] (7);

[0065] (8);

[0066] in, Configure the energy storage capacity for the new energy node i in the grid construction; The installed capacity of new energy node i; The upper limit for the proportion of energy storage configuration in a single-site grid-connected system; Configure the number of synchronous condensers for new energy node i; Configure an upper limit on the number of synchronous condensers per station; These are 0 / 1 variables for newly created lines; This represents the maximum number of newly constructed lines. This is a set of candidate new routes.

[0067] Step S222: Construct the constraints of the benchmark operating scenario, including DC power flow constraints and voltage phase angle magnitude constraints.

[0068] In the method for collaborative planning of transmission networks and network-building equipment under power grid strength constraints provided in the first aspect of this invention, the operational scenario constraints include DC power flow constraints and voltage phase angle magnitude constraints. The specific expressions are as follows:

[0069] (9);

[0070] (10);

[0071] (11);

[0072] in, It is a Big-M constant; For the construction status variables of the new line; The ground state power flow of candidate line l; Let l be the DC equivalent admittance of candidate line l; The ground state phase angle of the first node of the candidate line; The ground state phase angle of the last node of the candidate line; The active power transmission limit after candidate line l is completed; The phase angle of the balancing node.

[0073] Step S223: Construct the power grid strength constraint.

[0074] In the collaborative planning method for transmission networks and network construction equipment under power grid strength constraints provided by this invention, the specific expression of the power grid strength constraint is as follows:

[0075] (12);

[0076] (13);

[0077] in, The grid strength of new energy node i; Let be the mutual impedance between new energy nodes i and j in the network impedance matrix. The installed capacity of new energy node j; denoted as the target value for grid strength, and n as the number of new energy nodes.

[0078] Step S3: Input the grid new energy access node and output data, hydropower access node and output data, and grid topology data into the grid strength constraint-based collaborative planning and configuration model of transmission network and network construction equipment. Perform linear processing on the grid strength constraint-based collaborative planning and configuration model of transmission network and network construction equipment to obtain a linearized grid strength constraint-based collaborative planning and configuration model of transmission network and network construction equipment. Solve for the optimal configuration scheme of the linearized grid strength constraint-based collaborative planning of transmission network and network construction equipment.

[0079] Step S31: Based on the grid new energy access node and output data, hydropower access node and output data, and grid topology data, construct the optimization objective function and the constraint conditions of the collaborative planning and configuration model of the transmission network and network construction equipment under the grid strength constraint;

[0080] Step S32: Linearize the non-convex part in the optimization model to obtain a linearized collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint;

[0081] Step S33: Call a commercial solver to solve the linearized power grid strength constraint collaborative planning configuration model of the transmission network and network construction equipment to obtain the optimal configuration scheme of the collaborative planning of the transmission network and network construction equipment.

[0082] The optimal configuration scheme for the collaborative planning of the power transmission network and network construction equipment includes the configuration location and capacity of the network-type energy storage, the configuration location and capacity of the synchronous condenser, the newly built line branches, and the distance of the newly built lines.

[0083] The specific steps are as follows:

[0084] The dynamic correction of the entire network admittance matrix is ​​necessary during the optimization process of the main problem. Whenever a new network-type energy storage, synchronous condenser, or a new 500kV AC line is added, the entire network admittance matrix must be dynamically corrected.

[0085] (14);

[0086] in, This is the corrected nodal admittance matrix; Let be the initial admittance matrix of the system base; The increase in inter-node mutual admittance and self-admittance brought about by the construction of new lines; The incremental self-admittance injected into the source-side device. Among them, The specific expression is as follows:

[0087] (15);

[0088] in, This indicates the construction status of a new line, with 0 indicating no construction and 1 indicating construction. Let e ​​be the per-unit equivalent admittance of the newly constructed line e; Let be the topology association matrix corresponding to the newly created route e, and

[0089] (16);

[0090] (17);

[0091] in, Let i be the standard basis vector of the new energy node i; Let j be the standard basis vector of the new energy node. This refers to the positive sequence reactance per unit length of a 500kV line. This refers to the distance of the newly constructed line.

[0092] The specific expression is as follows:

[0093] (18);

[0094] in, The per-unit value of the equivalent admittance of the grid-connected energy storage or synchronous condenser at the new energy node i; Let i be the self-admittance mapping matrix corresponding to the new energy node i; and

[0095] (19);

[0096] (20);

[0097] in, For grid-connected energy storage, the overcurrent multiple is required. Configure per-unit capacity values ​​for energy storage in new energy nodes and network structures; Configure the number of synchronous condensers for new energy node i; To adjust the per-unit value of the camera's subtransient reactance.

[0098] Kron reduction and equivalent impedance extraction: To calculate mSCR, Kron elimination is used to eliminate non-new energy grid-connected nodes (denoted as set) in the entire network matrix. Only core nodes for grid connection of new energy sources (denoted as the set) are retained. ).

[0099] Kron reduction is a network simplification method that eliminates internal nodes (i.e., intermediate nodes without new energy access or network infrastructure) from the node admittance matrix, retaining only the new energy grid-connected nodes, to obtain a reduced-order admittance matrix. The reduced-order admittance matrix is ​​electrically equivalent to the original network—the electrical coupling relationships of the eliminated internal nodes are "folded" into the equivalent admittances between the retained nodes, thereby reducing the matrix dimension without sacrificing electrical accuracy and providing a simplified basis for subsequent sensitivity matrix calculations.

[0100] First, divide the entire network admittance matrix into blocks:

[0101] (twenty one);

[0102] in, , , and These are the admittance submatrices between retained nodes, between retained and eliminated nodes, between eliminated and retained nodes, and between eliminated nodes, respectively.

[0103] By eliminating irrelevant internal nodes, the reduced admittance matrix is ​​obtained. :

[0104] (twenty two);

[0105] (Note: To prevent the matrix from becoming singular in extreme isolated states, a...) Minimal tolerance array (Numerical regularization protection is performed). Subsequently, the short-circuit reference capacity matrix of the new energy power station itself is taken into account. Find the equivalent impedance matrix of the entire network. :

[0106] (twenty three);

[0107] Quantification of mSCR physical indicators: For any new energy node i, its grid strength The expression is as follows:

[0108] (twenty four);

[0109] in, Let be the mutual impedance between new energy node i and node j in the network impedance matrix. Let j be the installed capacity of the new energy node.

[0110] Grid strength involves matrix inversion, which results in highly nonlinear characteristics that cannot be directly solved using the commercial solver Guroib. To transform this problem into an easily solvable mixed-integer linear programming (MILP) model, a linearized calculation method for grid strength based on the first-order sensitivity matrix is ​​proposed.

[0111] A method for linearizing grid strength calculation based on the first-order sensitivity matrix of the source side: defining the elements in the first-order sensitivity matrix. , used to characterize the increase in grid strength at node i when node k increases by one unit self-admittance. Under engineering approximation conditions (considering that reactance in a high-voltage grid is much greater than resistance, i.e., X >> R, the elements of the impedance matrix can be approximated as purely imaginary numbers), The analytical expression can be derived as follows:

[0112] (25);

[0113] (26);

[0114] (27);

[0115] (28);

[0116] (29);

[0117] (30);

[0118] (31);

[0119] (32);

[0120] In formula (32), The grid strength of new energy node i under the current operating state; This represents the mutual impedance between new energy nodes i and k in the system node impedance matrix; This represents the equivalent admittance increment at the new energy node k. The capacity-weighted equivalent impedance sum of node i, a new energy node. The source-side first-order sensitivity matrix elements. This sensitivity matrix characterizes the increase in grid strength at new energy node i when the self-admittance of new energy node k increases by one unit. It accurately depicts the spatial support effect on the strength of all new energy nodes in the system after any node is equipped with grid-connecting equipment.

[0121] A method for linearizing grid strength calculation based on the first-order sensitivity matrix of the grid side: First-order sensitivity matrix This characterizes the improvement in the short-circuit ratio of renewable energy node i caused by adding a unit self-admittance line between candidate line endpoints p and q. It also represents the grid strength improvement for renewable energy node i. Regarding the admission of a new candidate line between candidate line endpoints p and q By taking partial derivatives and simplifying under the engineering approximation condition that the reactance is much greater than the resistance, we obtain the analytical expression for the elements of the first-order sensitivity matrix on the grid side. The analytical expression can be derived as follows:

[0122] (33);

[0123] (34);

[0124] (35);

[0125] (36);

[0126] (37);

[0127] (38);

[0128] (39);

[0129] (40);

[0130] in, , , , These are the mutual reactance between new energy node i and candidate line endpoint p, the mutual reactance between new energy node i and candidate line endpoint q, the mutual reactance between candidate line endpoint p and new energy node j, and the mutual reactance between candidate line endpoint q and new energy node j, respectively.

[0131] A linearized calculation method for grid strength based on the first-order sensitivity matrix: The incremental form of the short-circuit ratio constraint expression is as follows:

[0132] (41);

[0133] (42);

[0134] (43);

[0135] (44);

[0136] in, Let i be the amount of grid strength improvement at node i. The target power grid strength threshold; Configure the per-unit capacity of the grid-connected energy storage for new energy node k; Configure the number of synchronous condensers for new energy node k; To adjust the per-unit value of the camera's subtransient reactance; This refers to the positive sequence reactance per unit length of a 500kV line. The distance for the newly constructed transmission line. Therefore, the original nonlinear power grid strength constraint can be transformed into the following linear constraint:

[0137] (45);

[0138] In this linear inequality and , All calculations use known constants, thus completely avoiding matrix inversion operations during the optimization process, allowing direct use of the commercial solver Gurobi for solving.

[0139] Finally, the linearized optimization model is solved to output the grid-type energy storage configuration scheme, the synchronous condenser configuration scheme, and the new line construction scheme.

[0140] The linearized optimization model is solved by calling a mixed-integer linear programming solver; the grid-type energy storage configuration scheme includes the configuration location and configuration capacity of the grid-type energy storage, the synchronous condenser configuration scheme includes the configuration location and number of synchronous condensers, and the new line scheme includes the new line branches and the new line distance.

[0141] To verify the effectiveness and engineering practicality of the collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint, this section selects a simplified equivalent system of the power grid of a new energy base in a certain region of my country as a case study for analysis. Among them, nodes 1, 7, 8, 9, 13, 20, 26, and 28 are hydropower nodes; nodes 4, 5, 6, 15, 17, and 18 are new energy nodes.

[0142] 1) When the maximum number of newly built lines is 0, the configuration optimization results are shown in Table 1.

[0143] Table 1. Configuration optimization results when the maximum number of newly built lines is 0.

[0144]

[0145] 2) When the maximum number of newly built lines is 1, the configuration optimization results are shown in Table 2.

[0146] Table 2 shows the configuration optimization results (mSCR) when the maximum number of newly built lines is 1. (Chinese explanation needed for mSCR)

[0147]

[0148] New Line Status: L04-L20

[0149] 3) When the maximum number of newly built lines is 2, the configuration optimization results are shown in Table 3.

[0150] Table 3 Configuration optimization results when the maximum number of newly built lines is 2

[0151]

[0152] Newly constructed lines: L04-L20, L09-L17

[0153] 4) When the maximum number of newly built lines is 3, the configuration optimization results are shown in Table 4.

[0154] Table 4. Configuration optimization results when the maximum number of newly built lines is 3.

[0155]

[0156] Newly constructed lines: L04-L20, L09-L17, L04-L05

[0157] When the maximum number of newly created lines is greater than 3, the configuration optimization result is consistent with the result when the maximum number of newly created lines is 3. Table 5 shows a comparison of the configuration optimization results when the maximum number of newly created lines is different.

[0158] Table 5. Configuration optimization results when the upper limit for the number of newly built lines is different.

[0159]

[0160] Table 5 shows the optimization results when the upper limit of the number of new lines is different. It can be seen that in the scenario where no new lines are built, the configuration capacity of grid-connected energy storage and synchronous condenser is the largest, and the total planning cost is also the largest. When the upper limit of the number of new lines increases from 1 to 3, the configuration capacity of grid-connected energy storage gradually decreases, and the configuration capacity of synchronous condenser is 0, which greatly reduces the total planning cost.

[0161] Figures 2 to 4 The diagram illustrates the situation where the upper limit for the number of newly built lines is not the same. It can be seen that compared with the simple source-side configuration, the grid-source coordinated planning, by building new key lines (L04-020 and L09-17 are located on the strong coupling path between the new energy power station and the nearby hydropower unit, and L04-05 is located on the strong coupling path between new energy power stations), enables the strong support capacity of hydropower to radiate to the new energy gathering area, thereby significantly improving the local power grid strength.

[0162] Please refer to Figure 5The figure shows a schematic diagram of a collaborative planning and configuration system for transmission networks and network-building equipment under power grid strength constraints, provided by an embodiment of the present invention. As shown, this collaborative planning and configuration system 10 for transmission networks and network-building equipment under power grid strength constraints includes a data acquisition module 101, a model building module 102, and a processing and solution module 103. The specific units of each module are as follows:

[0163] The data acquisition module 101 is used to acquire new energy access node and output data, hydropower access node and output data, and grid topology data. Based on the new energy access node and output data, hydropower access node and output data, and grid topology data of the power grid, a network impedance matrix is ​​generated, and the obtained network impedance matrix is ​​automatically inverted to obtain the node admittance matrix.

[0164] The model building module 102 is used to establish a collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint. The collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint includes an optimization objective function and constraints. The optimization objective is to minimize the annualized cost of network-type energy storage, synchronous condensers, and newly built lines. The constraints include planning constraints for network-type energy storage, planning constraints for synchronous condensers, planning constraints for newly built lines, and operational constraints for the baseline scenario.

[0165] The processing and solving module 103 is used to input the grid new energy access node and output data, hydropower access node and output data, and grid topology data into the grid strength constraint-based transmission network and grid construction equipment collaborative planning and configuration model, and solve the linearized grid strength constraint-based transmission network and grid construction equipment collaborative planning and configuration model to obtain the optimal configuration scheme of grid-type energy storage, synchronous condenser and new line.

[0166] Optionally, the processing and solving module 103 includes a model processing unit 1031 and a model solving unit 1032, wherein:

[0167] The model processing unit 1031 is used to linearize the non-convex part of the collaborative planning and configuration model of the transmission network and network-building equipment under the power grid strength constraint, thereby obtaining a linearized collaborative planning and configuration model of the transmission network and network-building equipment under the power grid strength constraint. The model processing unit 1031 specifically includes:

[0168] The admittance correction unit is used to dynamically correct the node admittance matrix by introducing the admittance increment of the newly built line and the admittance increment of the source-side equipment.

[0169] Kron reduction unit is used to perform Kron reduction on the corrected node admittance matrix, eliminate non-new energy access nodes, and extract the equivalent impedance matrix of new energy access nodes.

[0170] A sensitivity construction unit is used to construct a source-side first-order sensitivity matrix and a network-side first-order sensitivity matrix based on the equivalent impedance matrix.

[0171] The constraint transformation unit is used to transform the power grid strength constraint into a linear inequality constraint that includes the source-side first-order sensitivity matrix and the grid-side first-order sensitivity matrix.

[0172] The model solving unit 1032 is used to call the commercial solver Gurobi to solve the linearized grid strength constraint collaborative planning and configuration model of transmission network and grid-building equipment, and obtain the optimal configuration scheme of grid-type energy storage, synchronous condenser and new line.

[0173] It should be noted that the above embodiments of the transmission network and network-building equipment collaborative planning and configuration model system under grid strength constraints, when executing the collaborative planning and configuration method for transmission networks and network-building equipment under grid strength constraints, are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the collaborative planning and configuration model system for transmission networks and network-building equipment under grid strength constraints can be divided into different functional modules to complete all or part of the functions described above. In addition, the collaborative planning and configuration system for transmission networks and network-building equipment under grid strength constraints and the collaborative planning and configuration method embodiments under grid strength constraints provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0174] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for collaborative planning of transmission networks and network construction equipment under power grid strength constraints, characterized in that, Includes the following steps: Step 1: Obtain the data on new energy access nodes and power output, hydropower access nodes and power output, and network topology data, and generate a network impedance matrix. Automatically invert the obtained network impedance matrix to obtain the node admittance matrix. Step 2: Construct a collaborative planning and configuration model for the transmission network and network-building equipment under power grid strength constraints, including: Step 2.1: The objective function is to minimize the annualized comprehensive configuration cost of grid-type energy storage, synchronous condensers, and newly built lines within the planning period; Step 2.2: Establish constraints, including energy storage capacity constraints, synchronous condenser quantity constraints, upper limit constraints on the number of newly built lines, operation scenario constraints, and grid strength constraints; Step 3: Linearize the power grid strength constraints in the collaborative planning configuration model, including: Step 3.1: Dynamically correct the node admittance matrix by introducing the admittance increment of the newly built line and the admittance increment of the source-side equipment; Step 3.2: Perform Kron reduction on the corrected node admittance matrix to eliminate non-new energy access nodes and extract the equivalent impedance matrix of new energy access nodes; Step 3.3: Based on the equivalent impedance matrix, construct the source-side first-order sensitivity matrix and the network-side first-order sensitivity matrix; Step 3.4: Transform the power grid strength constraint into a linear inequality constraint that includes the source-side first-order sensitivity matrix and the grid-side first-order sensitivity matrix; Step 4: Solve the linearized optimization model and output the grid-type energy storage configuration scheme, synchronous condenser configuration scheme, and new line construction scheme.

2. The method for coordinated planning of transmission network and network construction equipment under power grid strength constraints according to claim 1, characterized in that, In step 2.1, the objective function is the sum of the annualized comprehensive configuration costs of grid-type energy storage, synchronous condensers, and newly built power lines within the planning period. The minimum is shown in the following formula: （1）； （2）； （3）； （4）； in, The annualized comprehensive configuration cost for grid-connected energy storage; The annualized comprehensive configuration cost of a centralized synchronous condenser; The annualized comprehensive configuration cost for newly built lines; The unit capacity investment cost coefficient for grid-type energy storage; The capital recovery factor for energy storage equipment; The annual operating cost coefficient per unit capacity of grid-connected energy storage; The duration of continuous support configured for energy storage; Configure capacity for energy storage; Configure the number of centralized synchronous condensers; Capacity of a single synchronous condenser; The unit capacity investment cost coefficient for the camera; The capital recovery factor for adjusting the camera; The annual operating cost coefficient per unit capacity of the camera; This refers to the unit investment cost coefficient for newly constructed lines. The capital recovery factor for newly built lines; This refers to the unit annual operating cost coefficient for newly constructed lines. This refers to the distance of the newly constructed line.

3. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 1, characterized in that, In step 2.2, the constraints on energy storage capacity, the number of synchronous condensers, and the upper limit of the number of newly built power lines are respectively shown in the following formulas: （5）； （6）； （7）； in, Configure the energy storage capacity for the new energy node i in the grid construction; The installed capacity of new energy node i; The upper limit for the proportion of energy storage configuration in a single-site grid-connected system; Configure the number of synchronous condensers for new energy node i; Configure an upper limit on the number of synchronous condensers per station; These are 0 / 1 variables for newly created lines; This represents the maximum number of newly constructed lines. This is a set of candidate new routes.

4. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 1, characterized in that, In step 2.2, the operational scenario constraints include DC power flow constraints and voltage phase angle magnitude constraints; the specific expressions are as follows: （8）； （9）； （10）； in, It is a Big-M constant; For the construction status variables of the new line; The ground state power flow of candidate line l; Let l be the DC equivalent admittance of candidate line l; The ground state phase angle of the first node of the candidate line; The ground state phase angle of the last node of the candidate line; The active power transmission limit after candidate line l is completed; The phase angle of the balancing node.

5. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 1, characterized in that, In step 2.2, the grid strength constraint is constructed in the form that the short-circuit ratio of each new energy node is not lower than a preset target value, as shown in the following formula: （11）； （12）； in, The grid strength of new energy node i; Let be the mutual impedance between new energy nodes i and j in the network impedance matrix. The installed capacity of new energy node j; denoted as the target value for grid strength; n represents the number of new energy nodes.

6. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 1, characterized in that, In step 3.1, the dynamic correction of the nodal admittance matrix is ​​as shown in the following equation: （13）； in, This is the corrected nodal admittance matrix; Let be the initial admittance matrix of the system base; The increase in inter-node mutual admittance and self-admittance brought about by the construction of new lines; The self-admittance increment injected into the source-side device; Inter-node mutual admittance and self-admittance increment The specific expression is as follows: （14）； in, This indicates the construction status of a new line, with 0 indicating no construction and 1 indicating construction. Let e ​​be the per-unit equivalent admittance of the newly constructed line e; Let e ​​be the topology correlation matrix corresponding to the newly created route e; and （15）； （16）； in, Let i be the standard basis vector of the new energy node i; Let j be the standard basis vector of the new energy node. This refers to the positive sequence reactance per unit length of a 500kV line. For the distance of the newly built line; Self-admittance increment injected by source-side device The specific expression is as follows: （17）； in, The per-unit value of the equivalent admittance of the grid-connected energy storage or synchronous condenser at the new energy node i; Let i be the self-admittance mapping matrix corresponding to the new energy node i; and （18）； （19）； in, For grid-connected energy storage, the overcurrent multiple is required. Configure per-unit capacity values ​​for energy storage in new energy nodes and network structures; Configure the number of synchronous condensers for new energy node i; To adjust the per-unit value of the camera's subtransient reactance.

7. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 6, characterized in that, Step 3.2, the Krone reduction and extraction of the equivalent impedance matrix, includes: The corrected node admittance matrix The sub-matrix is ​​divided into a new energy access node sub-matrix and an internal node sub-matrix, as shown in the following formula: （20）； in, , , and These are the admittance submatrices between retained nodes, between retained nodes and eliminated nodes, between eliminated nodes and retained nodes, and between eliminated nodes; Eliminating internal nodes yields the reduced-order admittance matrix. As shown in the following formula: （21）； in, It is a matrix with extremely small tolerance; Taking into account the short-circuit baseline capacity matrix of new energy power stations Find the equivalent impedance matrix As shown in the following formula: （22）。 8. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 7, characterized in that, In step 3.3, constructing the source-side first-order sensitivity matrix includes: The grid strength of node i The relationship between the elements of the equivalent impedance matrix and the nodal injected power is expressed as follows: （23）； （24）； （25）； in, Let be the mutual impedance between new energy nodes i and j in the network impedance matrix. The installed capacity of new energy node j; This represents the equivalent admittance increment at the new energy node k. The capacity-weighted equivalent impedance sum of node i, a new energy node; Grid strength of new energy node i Regarding the equivalent admittance increment at new energy node k By taking the partial derivatives and simplifying under the engineering approximation that the reactance is much greater than the resistance, we obtain the elements of the first-order sensitivity matrix on the source side. The parsing expression is shown below: （26）； in, This represents the mutual impedance between new energy nodes i and k in the system node impedance matrix; The grid strength of the new energy node k; the source-side first-order sensitivity matrix element This is used to characterize the increase in grid strength of new energy node i when the self-admittance of new energy node k is increased by one unit; Using the first-order sensitivity matrix of the network side Characterizes the improvement in the short-circuit ratio of renewable energy node i by adding a unit self-admittance line between the candidate line endpoints p and q; and the improvement in the grid strength of renewable energy node i. Regarding the admission of a new candidate line between candidate line endpoints p and q Taking the partial derivatives and simplifying under the engineering approximation that the reactance is much greater than the resistance, we obtain the analytical expression for the elements of the first-order sensitivity matrix on the grid side, as shown in the following equation: （27）； in, , , , These are the mutual reactance between new energy node i and candidate line endpoint p, the mutual reactance between new energy node i and candidate line endpoint q, the mutual reactance between candidate line endpoint p and new energy node j, and the mutual reactance between candidate line endpoint q and new energy node j, respectively.

9. The method for collaborative planning of transmission network and network construction equipment under power grid strength constraints according to claim 8, characterized in that, In step 3.4, the linear inequality constraints are constructed as follows: Using the grid strength of each new energy node under the current operating state as the base value, the product of the admittance increment of each grid-connecting equipment node and the element of the first-order sensitivity matrix of the source side, as well as the product of the admittance increment of each candidate line and the element of the first-order sensitivity matrix of the grid side, is superimposed to transform the grid strength constraint into an incremental form, as shown in the following formula: （28）； （29）； in, Let i be the amount of grid strength improvement at node i. The target power grid strength threshold, This represents the admittance increment for each network device node; Increment of admittance of each network device node Configure grid-type energy storage capacity, number of synchronous condensers, and corresponding parameters. The expression is as follows: （30）； Increment of admittance for each candidate circuit Expressed using the positive sequence reactance per unit length of the line and the line distance, as shown in the following formula: （31）； in, Configure the per-unit capacity of the grid-connected energy storage for node k; Configure the number of camera converters for node k; To adjust the per-unit value of the camera's subtransient reactance; This refers to the positive sequence reactance per unit length of a 500kV line. For the distance of the newly built line; The nonlinear power grid strength constraint is transformed into the following linear constraint: （32）。 10. A collaborative planning system for transmission networks and network construction equipment under power grid strength constraints, characterized in that, include: The data acquisition module (101) is used to acquire new energy access node and output data, hydropower access node and output data, and grid topology data. Based on the new energy access node and output data, hydropower access node and output data, and grid topology data of the power grid, a network impedance matrix is ​​generated, and the obtained network impedance matrix is ​​automatically inverted to obtain the node admittance matrix. The model building module (102) is used to build a collaborative planning and configuration model of the transmission network and network construction equipment under the power grid strength constraint. The objective function is to minimize the annualized comprehensive configuration cost of network-type energy storage, synchronous condensers and new lines within the planning period. The module also establishes constraints including energy storage capacity constraints, synchronous condenser quantity constraints, upper limit constraints on the number of new lines, operation constraints and power grid strength constraints. The processing and solving module (103) is used to linearize the power grid strength constraints in the collaborative planning configuration model, including: The admittance correction unit is used to dynamically correct the node admittance matrix by introducing the admittance increment of the newly built line and the admittance increment of the source-side equipment. Kron reduction unit is used to perform Kron reduction on the corrected node admittance matrix, eliminate non-new energy access nodes, and extract the equivalent impedance matrix of new energy access nodes. A sensitivity construction unit is used to construct a source-side first-order sensitivity matrix and a network-side first-order sensitivity matrix based on the equivalent impedance matrix. The constraint transformation unit is used to transform the power grid strength constraint into a linear inequality constraint that includes the source-side first-order sensitivity matrix and the grid-side first-order sensitivity matrix. The model solving unit is used to solve the optimized model after linearization and outputs the grid-type energy storage configuration scheme, the synchronous condenser configuration scheme, and the new line scheme.

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